Quality Assurance 

Handbook for Air 

Pollution Measurement 

Systems 

Volume II 

Ambient Air Quality 

Monitoring Program 

 
 Page Intentionally Left Blank 
EPA-454/B-08-003 

December, 2008 

QA Handbook for Air Pollution Measurement Systems 

Volume II 

Ambient Air Quality Monitoring Program 

U.S. Environmental Protection Agency 

Office of Air Quality Planning and Standards 

Air Quality Assessment Division 

RTP, NC 27711
QA Handbook Volume II December, 2008 

iv 

Contents

Section Page Revision Date

Contents iv 1 12/08

Figures vi 1 12/08

Tables vii 1 

Acknowledgments viii 1 12/08

Acronyms and Abbreviations ix 1 12/08

0. Introduction 

 0.1 Intent of the Handbook 

 0.2 Use of Terms Shall, Must, Should, May 

 0.3 Use of Footnotes 

 0.4 Handbook Review and Distribution 

1/2 

2/2 

2/2 

2/2 

1 12/08

PROJECT MANAGEMENT

1. Program Background 

1.1 Ambient Air Quality Monitoring Network 

1.2 The EPA Quality System Requirements 

1.3 The Ambient Air Monitoring Program Quality System 

1/10 

5/10 

7/10 

1 12/08

2. Program Organization 

 2.1 Organization Responsibilities 

 2.2 Lines of Communication 

 2.3 Quality Assurance Workgroups 

1/7 

5/7 

7/7 

1 12/08

3. Data Quality Objectives 

 3.1 The DQO Process 

 3.2 Ambient Air Quality DQOs 

 3.2 Measurement Quality Objectives 

4/7 

5/7 

5/7 

1 12/08

4. Personnel Qualification and Training 

 4.1 Personnel Qualifications 

 4.2 Training 

1/3 

2/3 

1 12/08

5. Documentation and Records 

 5.1 Management and Organization 

 5.2 Site Information 

 5.3 Environmental Data Operations 

 5.4 Raw Data 

 5.5 Data Reporting 

 5.6 Data Management 

 5.7 Quality Assurance 

2/8 

2/8 

3/8 

7/8 

7/8 

8/8 

8/8 

1 12/08

MEASUREMENT ACQUISITION

6. Monitoring Network Design 

 6.1 Monitoring Objectives and Spatial Scales 

 6.2 Monitoring Site Location 

 6.3 Monitor Placement 

 6.4 Minimum Network Requirements 

 6.5 Operating Schedules 

4/14 

7/14 

11/14 

11/14 

12/14 

1 12/08

7. Sampling Methods 

 7.1 Environmental Control 

 7.2 Sampling Probes and Manifolds 

 7.3 Reference/Equivalent and Approved Regional Methods 

1/14 

4/14 

10/14 

1 12/8

8. Sample Handling and Custody 

 8.1 Sample Handling 

 8.2 Chain of Custody 

2/6 

4/6 

1 12/08

9. Analytical Methods 

 9.1 Good Laboratory Practices 

 9.2 Laboratory Activities 

2/2 

2/2 

1 12/08
QA Handbook Volume II December, 2008 

v 

Section Page Revision Date

10. Quality Control 

 10.1 QC Activity Areas 

 10.2 Internal vs. External Quality Control 

 10.3 CFR Related Quality Control Samples 

 10.4 Use of Computers for Quality Control 

3/8 

4/8 

7/8 

8/8 

1 12/08

11. Instrument/Equipment Testing, Inspection, and Maintenance 

 11.1 Instrumentation 

 11.2 Preventative Maintenance 

1/6 

4/6 

1 12/08

12. Calibration 

 12.1 Calibration Standards and Reagents 

 12.2 Multi-point Verifications/Calibrations 

 12.3 Frequency of Calibration and Analyzer Adjustment 

 12.4 Adjustment to Analyzers 

 12.5 Data Reduction using Calibration Information 

 12.6 Validation of Ambient Data 

2/11 

7/11 

8/11 

9/11 

10/11 

11/11 

1 12/08

13 Inspection/Acceptance for Supplies and Consumables 

 13.1 Supplies Management 

 13.2 Standards and Reagents 

 13.3 Volumetric Glassware 

 13.4 Sample Containers 

 13.5 Particulate Sampling Filters 

 13.6 Field Supplies 

1/4 

2/4 

2/4 

3/4 

3/4 

4/4 

1 12/08

14. Data Acquisition and Management 

 14.1 Data Acquisition 

 14.2 Data Transfer-Public Reporting 

 14.3 Data Transfer-Reporting to External Data Bases 

 14.4 Data Management 

2/14 

9/14 

11/14 

13/14 

1 12/08

ASSESSMENT/OVERSIGHT

15. Assessment and Corrective Action 

 15.1 Network Reviews 

 15.2 Performance Evaluations 

 15.3 Technical Systems Audits 

 15.4 Data Quality Assessments 

1/14 

4/14 

8/14 

14/14 

1 12/08

16. Reports to Management 

16.1 Guidelines for Preparation of Reports to Management 2/4 

1 12/08

DATA VALIDATION AND USABILITY

17. Data Review, Verification, Validation

 17.1 Data Review Methods 

 17.2 Data Verification Methods 

 17.3 Data Validation Methods 

3/7 

3/7 

4/7 

1 12/08

18. Reconciliation with Data Quality Objectives 

 18.1 Five Steps of the DQA Process 1/9 

1 12/08

APPENDICES 

A. National Monitoring Program Fact Sheets 

B: Ambient Air Monitoring QA Information and Web Addresses 

C: Using the Graded Approach for the Development of QMPs and 

QAPPs 

D: Measurement Quality Objectives and Validation Templates 

E: Characteristics of Spatial Scales Related to Each Pollutant 

F: Sample Manifold Design for Precursor Gas Monitoring 

G: Example Procedure for Calibrating Data Acquisition System 

H: Audit Information 

I: Example of Reports to Management 

11 

4 

6 

25 

7 

13 

3 

46 

25 

1 12/08

 
QA Handbook Volume II December, 2008 

vi 

Figures

Number Title Section/Page

1.1 Ambient air quality monitoring process 1/1 

1.2 Hierarchy of quality system development 1/5 

1.3 Ambient Air Quality Monitoring QA Program 1/7 

2.1 Program organization and lines of communication 2/1 

2.2 Relationship of monitored pollutants to site, monitoring organizations and 

primary quality assurance organizations 

2/4 

3.1 Effect of positive bias on the annual average estimate resulting in a false 

rejection error 

3/1 

3.2 Effect of negative bias on the annual average estimate resulting in a false 

acceptance error 

3/1 

6.1 Wind rose pattern 6/8 

6.2 Sampling schedule based on ratio to the 24-hour PM10 NAAQS 6/13 

7.1 Example design for shelter 7/2 

7.2 Position of calibration line in sampling manifold 7/5 

7.3 Acceptable areas for PM10 and PM2.5 micro, middle, neighborhood, and 

urban samplers except for microscale canyon sites 

7/7 

7.4 Optical mounting platform 7/8 

8.1 Example sample label 8/3 

8.2 Example field COC form 8/6 

8.3 Example laboratory COC form 8/6 

10.1 QC samples for PM2.5 placed at various stages of measurement process 10/2 

10.2 Example control chart 10/8 

12.1 Suggested zero/span drift limits 12/8 

14.1 DAS data flow 14/4 

14.2 Flow of data from gas analyzers to final reporting 14/4 

15.1 Definition of independent assessment 15/7 

15.2 Pre-Audit activities 15/8 

15.3 On-Site audit activities 15/10 

15.4 Audit finding form 15/11 

15.5 Post-audit activities 15/12 

15.6 Audit response form 15/13 

18.1 DQA in the context of data life cycle 18/2 
QA Handbook Volume II December, 2008 

vii 

Tables

Number Title Section/Page

3-1 Measurement Quality Objectives Developed into a Validation Template 3/7 

4-1 Monitoring Functions the Need Some Level of Staffing or Expertise 4/1 

4-2 Suggested Sequence of Core QA Related Ambient Air Training Courses ... 4/3 

5-1 Types of Information the Should be Retained Through Document Control 5/1 

6-1 Relationship Among Monitoring Objectives and Scale of Representativeness 6/5 

6-2 Summary of Spatial Scales for SLAMS, NCore, PAMS, and Open Path Sites 6/6 

6-3 Relationships of Topography, Air Flow, and Monitoring Site Selection 6/9 

6-4 Site Descriptions of PAMS Monitoring Sites 6/10 

6-5 Monitoring Station Categories Related to Monitoring Site Placement 6/11 

6-6 Completeness Goals for Ambient Monitoring Data 6/14 

7-1 Environment Control Parameters 7/3 

7-2 Summary of Probe and Monitoring Path Siting Criteria 7/6 

7-3 Minimum Separation Distance between Road and Sampling Probes... 7/7 

7-4 Techniques for Quality Control for Support Services 7/10 

7-5 Performance Specifications for Automated Methods 7/12 

9-1 Acceptable Analytical Methods 9/1 

10-1 QC Samples Used in Various Ambient Air Monitoring Programs 10/5 

10-2 PM2.5 Field and Lab QC Checks 10/6 

10-3 Ambient Air Monitoring Measurement Quality Samples 10/7 

11-1 Routine Operation Checks 11/5 

12-1 Certification Periods for Compressed Gas Calibration Standards... 12/4 

12-2 Instrumentation and Devices Requiring Calibration and Certifications 12/6 

14-1 AQS Data Reporting Requirements 14/12 

14-2 NCore Information Technology Performance Needs 14/13 

15-1 National Performance Evaluation Activities Performed by EPA 15/5 

15-2 NPAP Acceptance Criteria 15/7 

15-3 Suggested Elements of an Audit Plan 15/9 

16-1 Types of QA Reports to Management 16/2 

16-2 Sources of Information for Preparing Reports to Management 16/2 

16-3 Presentation Methods for Use in Reports to Management 16/3 

18-1 Summary of Violations of DQO Assumptions 18/5 

18-2 Weights for Estimating Three-Year Bias and Precision 18/6 

18-3 Summary of Bias and Precision 18/8 

 
QA Handbook Volume II December, 2008 

viii 

Acknowledgments

This QA Hand Book is the product of the combined efforts of the EPA Office of Air Quality Planning and 

Standards, the EPA Regional Offices, and the State, Tribal and Local monitoring organizations. The 

development and review of the material found in this document was accomplished through the activities 

of the QA Strategy Workgroup. The following individuals are acknowledged for their contributions. 

State, Tribal and Local Organizations

Andy Clifton, Andy Johnson, Anna Kelley, Arun Roychowdhury, Barb Regynski, Ben Davis, Charles 

Pearson, Ceresa.Stewart, Cindy Wike, Dick Duker, Dennis Fenlon, Don Gourley, Donovan Rafferty, 

Edward Huck, Erick Saganic, Glenn Gehring, Hugh Tom, Jim Conner, Joseph Ugorowski , Jackie 

Waynick , James Jordan, Jeff Wasson ,Jeremy Hardin, Jason Low, Keith Duncan, Ken Cowen, Kent 

Curtis, Kevin Watts, Leonard Marine, Larry Taylor, Leroy Williams, Merrin Wright, Mary Kay Clark, 

Melinda Ronca-Battista, Melvin Schuchardt, Mickey Palmer, Mike Draper, Mike Hamdan, Nydia 

Burdick, Patti DeLaCruz, Paul Sanborn, Robert Franicevich, Rachael Townsend, Randy Dillard, Rayna 

Broadway, Richard Heffern, Ritchie Scott , Robert Olson, Ryan Callison, Scott Reynolds, Stephanie 

McCarthy, Susan Kilmer, Susan Selby, Tyler Muxworthy ,Terry Rowles, Thomas Mcgrath , Sandra 

Wardwell, Yousaf Hameed 

EPA Regions

 

 Region 

 1 Mary Jane Cuzzupe, Peter Kahn, Chris St.Germane, Karen Way 

 2 Mustafa Mustafa, Avraham Teitz, Mark Winter 

 3 Victor Guide, Andrew Hass 

 4 Greg Noah, Danny France, Jerry Burge, Doug Jager 

 5 Gordon Jones, Scott Hamilton, Basim Dihu 

 6 Kuenja Chung, John Lay 

 7 Thien Bui, James Regehr, Leland Grooms, Michael Davis 

 8 Michael Copeland, Gordan MacRae, Joe Delwiche 

 9 Mathew Plate, Catherine Brown, Bob Pallarino, Roseanne Sakamoto 

 10 Chris Hall, Bill Puckett 

Office of Radiation and Indoor Air 

Montgomery, AL - Eric Boswell, Jewell Smiley, Steve Taylor 

Las Vegas, NV - David Musick, Emilio Braganza, Jeff Lantz 

Office of Air Quality Planning and Standards

Dennis Mikel, Dennis Crumpler, Mark Shanis, Louise Camalier, Jonathan Miller, Lewis Weinstock, Tim 

Hanley, Joseph Elkins 
QA Handbook Volume II December, 2008 

ix 

Acronyms and Abbreviations 

AAMG Ambient Air Monitoring Group 

APTI Air Pollution Training Institute 

ADQ audit of data quality 

AMTIC Ambient Monitoring Technical Information Center 

ANSI American National Standards Institute 

AQAD Air Quality Assessment Division 

AQI Air Quality Index 

AQS Air Quality System 

ARM approved regional method 

ASTM American Society for Testing and Materials 

ASQ American Society for Quality 

AWMA Air and Waste Management Association 

CAA Clean Air Act 

CFR Code of Federal Regulations

CL confidence limit 

CBSA core-based statistical area 

CMSA combined metropolitan statistical area 

CMZ community monitoring zone 

COC chain of custody 

CPU central processing unit 

CSA combined statistical area 

CSN PM2.5 Chemical Speciation Network 

CRM certified reference material 

CV coefficient of variation 

DAS data acquisition system 

DASC Data Assessment Statistical Calculator 

DC direct current 

DQA data quality assessment 

DOP digital aerosol photometer 

DQI data quality indicators 

DQOs data quality objectives 

EDO environmental data operation 

EDERF energy dispersive x-ray flouresence 

EPA Environmental Protection Agency 

FEM federal equivalent method 

FR flow rate 

FRM federal reference method 

FTIR fourier transform infrared (spectroscopy) 

GC/MS gas chromatography mass spectrometry 

GIS geographical information systems 

GLP good laboratory practice 

GMIS gas manufactures internal standards 

HAP hazardous air pollutants 

HC hydrocarbon 

HPLC high performance liquid chromatography 

HVAC heating, ventilating and air conditioning 

ICP inductively coupled plasma 

IMPROVE Interagency Monitoring of Protected Visual Environments 

IT information technology 

LDL lower detectable limit 

LIMS` laboratory information management systems 

MDL method detection limit 

MFC mass flow control 
QA Handbook Volume II December, 2008 

x 

Acronyms and Abbreviations (Continued) 

MPA monitoring planning area 

MQAG Monitoring and Quality Assurance Group 

MQOs measurement quality objectives 

MSA Metropolitan Statistical Area 

NAAQS National Ambient Air Quality Standards 

NACAA National Association of Clean Air Agencies 

NATTS National Air Toxics Trends Sites 

NECTA New England city and town area 

NEIC National Enforcement Investigations Center 

NTAA National Tribal Air Association 

NTEC National Tribal Environmental Council 

NCore National Core Network 

NERL National Environmental Research Laboratory 

NIST National Institute of Standards and Technology 

NF National Formulary 

NPS National Park Service 

NPAP National Performance Audit Program 

NPEP National Performance Evaluation Program 

NOAA National Oceanic Atmospheric Administration 

NTRM NIST traceable reference material 

OAQPS Office of Air Quality Planning and Standards 

OMB Office of Management and Budget 

ORD Office of Research and Development 

ORIA Office of Radiation and Indoor Air 

P&A precision and accuracy 

PAMS Photochemical Assessment Monitoring Stations 

PDFID Cryogenic Preconcentration and Direct Flame Ionization Detection 

PC personal computer 

PE performance evaluation 

PEP PM2.5 Performance Evaluation Program 

PBMS performance based measurement system 

ppb part per billion 

ppm part per million 

PSD Prevention of Significant Deterioration 

PQAO primary quality assurance organization 

PT proficiency test 

PWD primary wind direction 

QA quality assurance 

QA/QC quality assurance/quality control 

QAARWP quality assurance annual report and work plan 

QAD EPA Quality Assurance Division 

QAM quality assurance manager 

QAO quality assurance officer 

QAPP quality assurance project plan 

QMP quality management plan 

RPO regional planning organization 

RSD relative standard deviation 

SD standard deviation 

SIPS State Implementation Plans 

SLAMS state and local monitoring stations 

SOP standard operating procedure 

SPMS special purpose monitoring stations 

SRM standard reference material 

SRP standard reference photometer 

STN PM2.5 Speciation Trends Network (a subset of Chemical Speciation Network) 
QA Handbook Volume II December, 2008 

xi 

Acronyms and Abbreviations (Continued) 

TAD technical assistance document 

TEOM tapered element oscillating microbalance 

TIP tribal implementation plan 

TSA technical system audit 

TSP total suspended particulate 

TTL transistor-transistor logic 

USB universal serial bus 

USGS U.S. Geological Survey 

UTM universal transverse Mercator 

USP US Pharmacopeial 

VAC volts of alternating current 

VOC volatile organic carbon 
QA Handbook Vol II, Introduction 

Revision No: 1 

Date: 12/08 

Page 1 of 2 

0. Introduction

0.1 Intent of the Handbook

This document is Volume II of a five-volume quality assurance (QA) handbook series dedicated to air 

pollution measurement systems. Volume II is dedicated to the Ambient Air Quality Surveillance 

Program and the data collection activities inherent to that program. This guidance is part of a quality 

management system designed to ensure that the Ambient Air Quality Surveillance Program: (1) provides 

data of sufficient quality to meet the program’s objectives and (2) is implemented consistently across the 

Nation. 

The purpose of the Handbook is twofold. First, the document is intended to assist technical personnel at 

tribal, state and local monitoring organizations1

 develop and implement a quality system for the Ambient 

Air Quality Monitoring Program. A quality system, as defined by The American National StandardSpecifications and Guidelines for Quality Systems for Environmental Data Collection and 

Environmental Technology Programs(ANSI/ASQ E4), 2 is “a structured and documented management 

system describing the policies, objectives, principles, organizational authority, responsibilities, 

accountability, and implementation plan of an organization for ensuring the quality in its work processes, 

products, and services. The quality system provides the framework for planning, implementing, and 

assessing the work performed by the organization and for carrying out required quality assurance (QA) 

and quality control (QC) activities”. A monitoring organization’s quality system for the Ambient Air 

Quality Surveillance Program is described in its quality assurance project plan (QAPP). Second, the 

Handbook provides additional information and guidance on the material covered in the Code of Federal 

Regulations (CFR) pertaining to the Ambient Air Quality Surveillance Program. 

The Handbook has been written in a style similar to a QA project plan as specified in the document EPA 

Requirements for Quality Assurance Project Plans for Environmental Data Operations (EPA QA/R5) 3

. 

Environmental data operations (EDO) refer to the work performed to obtain, use, or report information 

pertaining to natural surroundings and conditions. The information in this Handbook can be used as 

guidance in the development of detailed monitoring organization QAPPS. 

Earlier versions of the Handbook focused on the six criteria pollutants monitored at the State and Local 

Ambient Monitoring Stations (SLAMS) and National Ambient Monitoring Stations (NAMS). In 2006, 

the term NAMS was discontinued and a new national monitoring concept-the National Ambient Air 

Monitoring Strategy- was adopted. Although the focus will remain on the criteria pollutants, this edition 

is expanded to cover quality assurance guidance for: 

• Photochemical Assessment Monitoring Stations (PAMS); 

http://www.epa.gov/ttn/amtic/pamsmain.html; 

• Open path monitoring ( http://www.epa.gov/ttn/amtic/longpath.html ); 

• PM2.5 Chemical Speciation Network (http://www.epa.gov/ttn/amtic/speciepg.html); 

 

1

 Monitoring organization will be used throughout the handbook to identify any tribal, state or local organization 

that is implementing an ambient air monitoring program, especially if they are using the data for comparison to the 

National Ambient Air Quality Standards (NAAQS). 

2 http://webstore.ansi.org/RecordDetail.aspx?sku=ANSI%2fASQ+E4-2004 3 http://www.epa.gov/quality1/qa_docs.html 
QA Handbook Vol II, Introduction 

Revision No: 1 

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Page 2 of 2 

• National Air Toxics Trends Network (NATTS) http://www.epa.gov/ttn/amtic/airtoxpg.html; and 

• NCore Network (http://www.epa.gov/ttn/amtic/ncore/index.html) 

This Handbook is not intending to supplant the detailed guidance provided by the programs listed above 

but to provide general information and pointers, in the form of hyperlinks, where one can go for more 

detailed information. Extensive use of hyperlinks will be used throughout the document. 

0.2 Use of the Terms Shall, Must, Should and May 

The intent of this handbook is to provide additional guidance on the ambient air monitoring requirements 

found in the Clean Air Act and 40 CFR Parts 50, 53 and 58. In order to distinguish requirements from 

guidance, the following terms will be used with consistency. 

< shall, must- when the element is a requirement in 40 CFR and the Clean Air Act

< should- when the element is recommended. This term is used when extensive experience in 

monitoring provides a recommended procedure that would help establish or improve 

the quality of data or a procedure. The process that includes the term is not required 

but identifies something that is considered important to data quality that may have 

alterative methods that can be implemented to achieve the same quality results.

< may- when the element is optional or discretionary. The term also indicates that what is 

suggested may improve data quality, that it is important to consider, but it is not as 

important as those that have been suggested using the term “should”.

 

0.3 Use of Footnotes 

This document will make extensive use of internet links that will provide the user with access to more 

detailed information on a particular subject. Due to the limitations of Adobe, full URL addresses must be 

provided in order for the links to work. Rather than clutter the body of the document with long URL 

addresses, footnotes will be used to direct the interested reader to the correct link. 

0.4 Handbook Review and Distribution

The information in this Handbook was revised and/or developed by many of the organizations 

responsible for implementing the Ambient Air Quality Surveillance Program (see Acknowledgments). It 

has been peer-reviewed and accepted by these organizations and serves to promote consistency among 

the organizations collecting and reporting ambient air data. 

This Handbook is accessible as a PDF file on the Internet under the AMTIC Homepage: 

[http://www.epa.gov/ttn/amtic/qabook.html]

Recommendations for modifications or revisions are always welcome. Comments should be sent to the 

appropriate Regional Office Ambient Air Monitoring contact or posted on AMTIC forum4

. The 

Handbook Steering Committee will meet quarterly to discuss any pertinent issues and proposed changes.

 

4 http://yosemite.epa.gov/oar/Forums.nsf/Forum%5CAMTICByTopic?OpenView&CollapseView 
QA Handbook Vol II, Section 1.0 

Revision No: 1 

Date: 12/08 

Page 1 of 10 

1.0 Program Background

1.1 Ambient Air Quality Monitoring Network 

The purpose of this section 

is to describe the general 

concepts for establishing the 

Ambient Air Quality 

Monitoring Network. The 

majority of this material, as 

well as additional details, 

can be found in the Clean 

Air Act (CAA)1

, 40 CFR 

Parts 50, 53 and 582

, and 

their references.

Between the years 1900 and 

1970, the emission of six 

principal pollutants 

increased significantly. The 

principal pollutants, also 

called criteria pollutants are: 

particulate matter (PM10 and 

PM2.5), sulfur dioxide, 

carbon monoxide, nitrogen 

dioxide, ozone, and lead. In 

1970 the CAA was signed 

into law. The CAA and its 

amendments provide the 

framework for all pertinent 

organizations to protect air 

quality. 

40 CFR Part 58, Appendix D requires that monitoring networks be designed for three basic monitoring 

objectives: 

• to provide air pollution data to the general public in a timely manner 

• to support compliance with ambient air quality standards and emission strategy development 

• to support air pollution research studies 

In addition, these monitoring networks can also be developed: 

• to activate emergency control procedures that prevent or alleviate air pollution episodes 

• to observe pollution trends throughout the region, including non-urban areas 

 

1 http://epa.gov/air/caa/ 2 http://www.access.gpo.gov/nara/cfr/cfr-table-search.html 
QA Handbook Vol II, Section 1.0 

Revision No: 1 

Date: 12/08 

Page 2 of 10 

To meet these basic needs, networks are designed with a variety of types of monitoring sites located to: 

• Determine the highest concentration expected to occur in the area covered by the network. 

• Measure typical concentrations in areas of high population density. 

• Determine the impact of significant sources or source categories on air quality. 

• Determine background concentration levels. 

• Determine the extent of regional pollutant transport among populated areas; and in support of 

secondary standards. 

• Measure air pollution impacts on visibility, vegetation damage, or welfare-based impacts. 

These six objectives will be used during the development of data quality objectives (Section 3). As one 

reviews the objectives, it becomes apparent that it will be rare that individual sites can be located to meet 

more than two or three objectives. Therefore, monitoring organizations need to choose the sites that are 

most representative of its priority objective(s). 

Through the process of implementing the CAA, six major categories of monitoring stations or networks 

that measure the air pollutants have been developed. These networks are described below. In addition, a 

fact sheet on each network (with the exception of SPMs) can be found in Appendix A.

State and Local Air Monitoring Stations (SLAMS) including Tribal Monitoring Stations

The SLAMS consist of a network of monitoring stations whose size and distribution is largely determined 

by the monitoring requirements for NAAQS comparison and the needs of monitoring organizations to 

meet their respective tribal/state implementation plan (TIP/SIP) requirements. The TIP/SIPs provide for 

the implementation, maintenance, and enforcement of the national ambient air quality standards 

(NAAQS) in each air quality control region within a tribe/state. The Handbook is largely devoted to 

guidance related to the SLAMS network. SLAMS exclude special purpose monitor (SPM) stations and 

include NCore, PAMS, and all other State or locally operated stations that have not been designated as 

SPM stations. 

Special Purpose Monitoring Stations (SPMs)

An SPM station means a monitor included in a monitoring organizations network has been designated as 

a special purpose monitor station in its monitoring network plan and in the Air Quality System (AQS), 

and which the agency does not count when showing compliance with the minimum monitoring 

requirements for the number and siting of monitors of various types. SPMs provide for special studies 

needed by the monitoring organizations to support TIPs/SIPs and other air program activities. These 

monitors are not counted towards the monitoring organization’s minimum requirements established in 

CFR for monitoring certain pollutants. The SPMs are not permanently established and can be adjusted to 

accommodate changing needs and priorities. The SPMs are used to supplement the fixed monitoring 

network as circumstances require and resources permit. If the data from SPMs are used for SIP purposes, 

they must meet all QA, siting and methodology requirements for SLAMS monitoring. Any SPM data 

collected by an air monitoring agency using a Federal reference method (FRM), Federal equivalent 

method (FEM), or approved regional method (ARM) must meet the requirements of 40 CFR Part 58.11, 

58.12, and the QA requirements in 40 CFR Part 58, Appendix A or an approved alternative to Appendix 

A to this part. Compliance with the probe and monitoring path siting criteria in 40 CFR Part 58, Appendix 

E is optional but encouraged except when the monitoring organization’s data objectives are inconsistent 

with those requirements. Data collected at an SPM using a FRM, FEM, or ARM meeting the 

requirements of Appendix A must be submitted to AQS according to the requirements of 40 CFR Part 
QA Handbook Vol II, Section 1.0 

Revision No: 1 

Date: 12/08 

Page 3 of 10 

58.16. Data collected by other SPMs may be submitted. The monitoring agency must also submit to AQS 

an indication of whether each SPM reporting data to AQS meets the requirements of Appendices A and E.

PM2.5 Chemical Speciation Network (CSN)3

As part of the effort to monitor particulate matter, EPA monitors and gathers data on the chemical 

makeup of these particles. EPA established a chemical speciation network consisting of approximately 

300 monitoring sites. These sites are placed at various SLAMS across the Nation. Fifty-four of these 

CSN sites, the Speciation Trends Network (STN), will be used to determine, over a period of several 

years, trends in concentration levels of selected ions, metals, carbon species, and organic compounds in 

PM2.5. Further breakdown on the location or placement of the trends sites requires that approximately 20 

of the monitoring sites be placed at existing Photochemical Assessment Monitoring Stations (PAMS). 

The placement of the remaining trends sites will be coordinated by EPA, the regional offices, and the 

monitoring organizations. Locations will be primarily in or near larger Metropolitan Statistical Areas 

(MSAs). The remaining chemical speciation sites will be used to enhance the required trends network 

and to provide information for developing effective TIPs/SIPs. 

The STN is a component of the National PM2.5 SLAMS. Although the STN is intended to complement 

the SLAMS activities, STN data will not be used for attainment or nonattainment decisions. The 

programmatic objectives of the STN network are: 

• annual and seasonal spatial characterization of aerosols; 

• air quality trends analysis and tracking the progress of control programs; 

• comparing, aggregating and evaluating the chemical speciation data set to the data collected from 

the IMPROVE network; and 

• development of emission control strategies. 

Photochemical Assessment Monitoring Stations (PAMS)4

Section 182(c)(1) of the 1990 CAA required the Administrator to promulgate rules for the enhanced 

monitoring of ozone, oxides of nitrogen (NOx), and volatile organic compounds (VOC) to obtain more 

comprehensive and representative data on ozone air pollution. Immediately following the promulgation of 

such rules, the affected states/tribes were to commence such actions as were necessary to adopt and 

implement a program to improve ambient monitoring activities and the monitoring of emissions of NOx 

and VOC. Each TIP/SIP for the affected areas must contain measures to implement the ambient 

monitoring of such air pollutants. The subsequent revisions to 40 CFR 58 required states to establish 

Photochemical Assessment Monitoring Stations (PAMS) as part of their SIP monitoring networks in 

ozone nonattainment areas classified as serious, severe, or extreme. 

The chief objective of the enhanced ozone monitoring revisions is to provide an air quality database that 

will assist air pollution control agencies in evaluating, tracking the progress of, and, if necessary, refining 

control strategies for attaining the ozone NAAQS. Ambient concentrations of ozone and ozone precursors 

will be used to make attainment/nonattainment decisions, aid in tracking VOC and NOx emission 

inventory reductions, better characterize the nature and extent of the ozone problem, and to evaluate air 

quality trends. In addition, data from the PAMS will provide an improved database for evaluating 

photochemical model performance, especially for future control strategy mid-course corrections as part of 

 

3 http://www.epa.gov/ttn/amtic/speciepg.html 4

 http://www.epa.gov/ttn/amtic/pamsmain.html 
QA Handbook Vol II, Section 1.0 

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Page 4 of 10 

the continuing air quality management process. The data will help to ensure the implementation of the 

most cost-effective regulatory controls. 

National Air Toxic Trends Stations (NATTS)5

There are currently 188 hazardous air pollutants (HAPs) or Air Toxics (AT) regulated under the 

CAA. These pollutants have been associated with a wide variety of adverse health and ecosystem effects. 

In 1999, EPA finalized the Urban Air Toxics Strategy (UATS). The UATS states that emissions data are 

needed to quantify the sources of air toxics impacts and aid in the development of control strategies, while 

ambient monitoring data are needed to understand the behavior of air toxics in the atmosphere after they 

are emitted. Part of this strategy included the development of the National Air Toxics Trends Stations 

(NATTS). Specifically, it is anticipated that the NATTS data will be used for: 

• tracking trends in ambient levels to evaluate progress toward emission and risk reduction goals; 

• directly evaluating public exposure & environmental impacts in the vicinity of monitors; 

• providing quality assured data for risk characterization; 

• assessing the effectiveness of specific emission reduction activities; and 

• evaluating and subsequently improving air toxics emission inventories and model performance. 

Currently the NATTS program is made up of 22 monitoring sites; 15 representing urban communities and 

7 representing rural communities. 

National Core Monitoring Network (NCore)6

The NCore multi-pollutant stations are part of an overall strategy to integrate multiple monitoring 

networks and measurements. Each state (i.e., the fifty states, District of Columbia, Puerto Rico, and the 

Virgin Islands) is required to operate at least one NCore site. Monitors at NCore multi-pollutant sites will 

measure particles (PM2.5, speciated PM2.5, PM10-2.5, speciated PM10-2.5), O3, SO2, CO, nitrogen oxides 

(NO/NO2/NOy), and basic meteorology. In addition a number of NCore sites will be selected to measure 

lead (Pb). 

The objective is to locate sites in broadly representative urban (about 55 sites) and rural (about 20 sites) 

locations throughout the country to help characterize regional and urban patterns of air pollution. The 

NCore network should be fully operational by 2011. 

In many cases, monitoring organizations will collocate these new stations with STN sites measuring 

speciated PM2.5 components, PAMS sites already measuring O3 precursors, and/or NATTS sites 

measuring air toxics. By combining these monitoring programs at a single location, EPA and its partners 

will maximize the multi-pollutant information available. This greatly enhances the foundation for future 

health studies, NAAQS revisions, validation of air quality models, assessment of emission reduction 

programs, and studies of ecosystem impacts of air pollution. 

 

5

 http://www.epa.gov/ttn/amtic/airtoxpg.html 

6

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1.2 The EPA Quality System Requirements

A quality system is the “blueprint” or 

framework by which an organization 

applies sufficient quality control (QC) 

and quality assurance (QA) practices to 

ensure that the results of its 

environmental programs meet or exceed 

expectations. It is based upon the model 

of planning the work, implementing 

what is planned, assessing the results 

against the performance criteria, 

reporting on data quality and making 

improvements if necessary. Figure 1.2 

provides an illustration of the pertinent 

regulations and policy that drive the 

development of a quality system. Some 

important aspects of this figure are 

explained below. 

1.2.1 Policy and Regulations 

At the highest level, standards and 

regulations determine what QA is 

required for the monitoring program 

and, therefore, set the stage for program 

and project specific guidance. The 

standards and regulations pertinent to 

the Ambient Air Quality Monitoring 

Program include: 

• ANSI/ASQ E4 – EPA’s quality system is based on the document: American National StandardQuality Systems for Environmental Data and Technology Programs-Requirements with Guidance 

for use (ANSI/ASQ E4-2004)7

. This document describes a basic set of mandatory specifications 

and non-mandatory guidelines by which a quality system for programs involving environmental 

data collection can be planned, implemented, and assessed. 

• Internal Policies- EPA Order 5360.18 expresses the EPA policy in regards to the quality system 

development for all EPA organizations and by non-EPA organizations performing work on behalf 

of EPA through extramural agreements. The EPA QA Orders adhere to E4 under the authority of 

the Office of Management and Budget. Section 1.2.5 below provides more specifics on this 

Order. 

 

7 http://webstore.ansi.org/default.aspx 8 http://www.epa.gov/quality1/. 

Figure 1.2. Hierarchy of quality system development 
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NOTE: During development of this document EPA Order 5360.1 was under revision and its new 

reference may be changed to CIO 2105.0. This Handbook will continue to use 5360.1 as the 

current reference. 

• External Policies - Refers to the Code of Federal Regulation (CFR). The references to the 

external regulations are those that apply to the quality system requirements for external funding. 

Those most important to the monitoring community are 40 CFR Parts 30, 31 and 35 but are not 

specific to ambient air monitoring. 

• Ambient Air -The consensus standards (E4) and internal and external requirements then funnel 

to the Headquarters and Regional programs (yellow circle) where additional QA requirements, 

specific to a particular monitoring program, are included. Ambient air requirements include 

documents like the Clean Air Act (CAA) and 40 CFR Parts 50, 53 and 58 which are specific to 

ambient air monitoring. 

1.2.2 Organization/Program 

This area in Figure 1.2 refers to the monitoring organization and is used to describe its overall quality 

system, usually in the form of a quality management plan (QMP)9

. Many monitoring organizations 

perform a multitude of data collection activities for different media (e.g., air, water, solid waste) where 

ambient air monitoring might be only one branch in a large organization. It is the responsibility of each 

organization to have a QMP that demonstrates an acceptable quality system. QMPs are approved by the 

EPA Regions. 

1.2.3 Project 

The term “project” refers to the specific environmental data operation (EDO) that occurs at the 

monitoring organization. An environmental data operation refers to the work performed to obtain, use, or 

report information pertaining to environmental processes and conditions. This handbook provides the 

majority of the guidance necessary for the monitoring organizations to develop QA project plans specific 

to its data collection needs. Other guidance has been developed specific to a part of the measurement 

system (i.e., calibration techniques) or to specific methods. A listing of this guidance is included in 

Appendix B. It is anticipated that the majority of these documents will be available on the AMTIC 

bulletin board. 

1.2.4 Quality System Requirements for EPA Funded Programs 

EPA’s national quality system requirements can be found in EPA QA Policy 5360.110. Any organization 

using EPA funds for the collection of environmental data are covered under 5360.1 and must develop, 

implement, and maintain a quality system that demonstrates conformance to the minimum specifications 

of ANSI/ASQC E4-1994 and that additionally provides for the following (excerpt from 5360.1): 

1. A quality assurance manager (QAM), or person/persons assigned to an equivalent position, who 

functions independently of direct environmental data generation, model development, or 

technology development responsibility; who reports on quality issues to the senior manager 

 

9 http://www.epa.gov/quality1/qs-docs/r2-final.pdf 10 http://www.epa.gov/irmpoli8/ciopolicy/2105-0.pdf 
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having executive leadership authority for the organization; and who has sufficient technical and 

management expertise and authority to conduct independent oversight of and assure the 

implementation of the organization’s quality system in the environmental programs of the 

organization. 

2. A Quality Management Plan (QMP), which documents the organization’s quality policy, 

describes its quality system, identifies the environmental programs to which the quality system 

applies, and which is implemented following approval by the organization’s executive leadership. 

3. Sufficient resources to implement the quality system defined in the approved QMP. 

4. Assessments of the effectiveness of the quality system at least annually. 

5. Submittal to the Office of Environmental Information (OEI) of the Quality Assurance Annual 

Report and Work Plan (QAARWP) for the organization that summarizes the previous years QA 

and QC activities and outlines the work proposed for the current year (not applicable to air 

monitoring organizations) 

6. Use of a systematic planning approach to develop acceptance or performance criteria for all work 

covered by this Order. 

7. Approved Quality Assurance Project Plans (QAPPs), or equivalent documents defined by the 

QMP, for all applicable projects and tasks involving environmental data with review and approval 

having been made by the EPA QAM (or authorized representative defined in the QMP). QAPPs 

must be approved prior to any data gathering work or use, except under circumstances requiring 

immediate action to protect human health and the environment or operations conducted under 

police powers. 

8. Assessment of existing data, when used to support Agency decisions or other secondary purposes, 

to verify that they are of sufficient quantity and adequate quality for their intended use. 

9. Implementation of Agency-wide Quality System requirements in all applicable EPA-funded 

extramural agreements 

10. Implementation of corrective actions based on assessment results. 

11. Appropriate training, for all levels of management and staff, to assure that QA and QC 

responsibilities and requirements are understood at every stage of project implementation. 

1.3 The Ambient Air Monitoring 

Program Quality System 

Figure 1.3 represents the stages of the 

Ambient Air Quality Monitoring QA 

Program. OAQPS modified EPA 5360.1 as 

appropriate in order to provide data of the 

quality needed to meet the Ambient Air 

Monitoring Program objectives. The planning, 

implementation, assessment and reporting 

tools will be briefly discussed below. 

1.3.1 Planning 

Planning activities include: 

Data Quality Objectives (DQOs) - DQOs are 

qualitative and quantitative statements derived 

from the outputs of the DQO Process that: (1) clarify the study objective; (2) define the most appropriate 
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type of data to collect; (3) determine the most appropriate conditions from which to collect the data; and 

(4) specify tolerable limits on decision errors which will be used as the basis for establishing the quantity 

and quality of data needed to support the decision. Section 3 will provide more information on the DQO 

Process. 

Methods- Reference methods and measurement principles have been written for each criteria pollutant. 

For monitoring for comparison to the NAAQS, monitoring organizations must use methods that are 

designated as Federal Reference (FRM) Federal Equivalent (FEM)11 or approved regional monitor 

(ARM)12 for PM2.5. ORD NERL implements the FRM/FEM designation program and provides technical 

assistance in the PM2.5 ARM process. Approved FRM/FEM methods refer to individual monitoring 

instruments that either provide a pollutant concentration or provide a sample for further laboratory 

analysis and must be operated minimally as required in 40 CFR Part 50. Since these methods cannot be 

applied to the actual instruments acquired by each monitoring organization, they should be considered as 

guidance for detailed standard operating procedures that would be developed by monitoring organizations 

as part of an acceptable QAPP. 

Training - Training is an essential part of any good monitoring program. Training activities are 

discussed in Section 4. 

Guidance - This QA Handbook as well as many other guidance documents have been developed for the 

Ambient Air Quality Monitoring Program. Many of the monitoring networks listed above have 

developed technical assistance documents and generic QAPPs to help guide personnel in the important 

aspects of these programs. A list of these documents is included in Appendix B. 

1.3.2 Implementation 

Implementation activities include: 

QMP/QAPP Development - Each state, local, and tribal organization must develop a QMP and QAPP. 

• QMP - describes the quality system in terms of the organizational structure, functional 

responsibilities of management and staff, lines of authority, and required interfaces for those 

planning, implementing, and assessing activities involving environmental data collection. The 

QMP is not specific to any particular project, but related to how the monitoring organization 

implements its quality system. 

• QAPP- is a formal document describing, in comprehensive detail, the necessary QA/QC and 

other technical activities that must be implemented to ensure that the results of work performed 

will satisfy the stated performance criteria, which may be in the form of a data quality objective 

(DQO). The QAPP is specific to a particular monitoring project. Standard operating procedures 

(SOPs) are part of the QAPP development process and are vital to the quality of any monitoring 

program. The QAPP should be detailed enough to provide a clear description of every aspect of 

the project and include information for every member of the project staff, including samplers, lab 

staff, and data reviewers. The QAPP facilitates communication among clients, data users, project 

staff, management, and external reviewers. 

 

11 http://www.epa.gov/ttn/amtic/criteria.html 12 40 CFR Part 58 Appendix C Section 2.4 
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Guidance for the development of both QMPs and QAPPs can be found on the EPA Quality Staff’s 

website13. In addition, EPA has provided flexibility on how EPA organizations implement this policy, 

allowing for use of a graded approach. Since EPA funds the collection and use of data for a number of 

monitoring objectives and for organizations with a broad range of capabilities, flexibility in the QMP and 

QAPP requirements is necessary. For example, data collection for the purpose of comparison to the 

National Ambient Air Quality Standards (NAAQS) will require more stringent requirements, while 

monitoring programs for special purposes may not require the same level of quality assurance. The level 

of detail of QMPs and QAPPs, as explained by the EPA Quality Staff in the EPA Quality Manual, 

“should be based on a common sense, graded approach that establishes the QA and QC requirements 

commensurate with the importance of the work, available resources, and the unique needs of the 

organization.” The ambient air program has developed a graded approach that will help tribes and 

smaller monitoring organizations develop both a QMP and QAPPs. Appendix C provides information on 

this approach. 

Internal QC Activities - The quality control (QC) system is used to fulfill requirements for quality. It is 

the overall system of technical activities that measure the attributes and performance of a process, item, or 

service against defined standards to verify that they meet the stated requirements established by the 

customer. In the case of the Ambient Air Quality Monitoring Network, QC activities are used to ensure 

that measurement uncertainty is maintained within established acceptance criteria for the attainment of 

the DQOs. 

Federal regulation provides for the implementation of a number of qualitative and quantitative checks to 

ensure that the data will meet the DQOs. Each of the checks attempt to evaluate phases of measurement 

uncertainty. Some of these checks are discussed below and in Section 10. 

• Precision and Bias (P & B) Checks - These checks are described in the 40 CFR Part 58, 

Appendix A. These checks can be used to provide an overall assessment of measurement 

uncertainty. 

• Zero/Span Checks - These checks provide an internal quality control check of proper operation 

of the measurement system. 

• Annual Certifications - A certification is the process which ensures the traceability and viability 

of various QC standards. Standard traceability is the process of transferring the accuracy or 

authority of a primary standard to a field-usable standard. Traceability protocols are available for 

certifying a working standard by direct comparison to a NIST-SRM14, 15. 

• Calibrations - Calibrations should be carried out at the field monitoring site by allowing the 

analyzer to sample test atmospheres containing known pollutant concentrations. Calibrations are 

discussed in Section 12. 

1.3.3 Assessments

Assessments, as defined in ANSI/ASQC-E4 and EPA’s document, Guidance on Technical Audits and 

Related Assessments for Environmental Data Operations (QA/G-7)16, are evaluation processes used to 

measure the performance or effectiveness of a system and its elements. It is an all inclusive term used to 

denote any of the following: audit, performance evaluation, management systems review, peer review, 

 

13 (http://www.epa.gov/quality1/ ) 14 http://www.epa.gov/ttn/amtic/files/ambient/criteria/reldocs/4-79-056.pdf 15 http://www.epa.gov/appcdwww/pubs/600r97121/600r97121.htm 16 http://www.epa.gov/quality1/qs-docs/g7-final.pdf 
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inspection, or surveillance. Assessments for the Ambient Air Quality Monitoring Program, as discussed 

in Section 15, include: 

Technical Systems Audits (TSA) -A TSA is an on-site review and inspection of a State or local agency's 

ambient air monitoring program to assess its compliance with established regulations governing the 

collection, analysis, validation, and reporting of ambient air quality data. Both EPA and State 

organizations perform TSAs. Procedures for this audit are discussed in general terms in Section 15. 

Network Reviews - The network review is used to determine how well a particular air monitoring 

network is achieving its required air monitoring objective(s) and how it should be modified to continue to 

meet its objective(s). Network reviews are discussed in Section 15. 

Performance Evaluations- Performance evaluations are a type of audit in which the quantitative data 

generated in a measurement system are obtained independently and compared with routinely obtained 

data to evaluate the proficiency of an analyst, laboratory, or measurement system. The following 

performance evaluations, discussed in further detail in Section 15, are included in the Ambient Air 

Quality Monitoring Program: 

• Monitoring Organization Performance Evaluations (Audits) - These performance evaluation 

audits are used to provide an independent assessment of the measurement operations of each 

instrument being audited. This is accomplished by comparing performance samples or devices 

of “known” concentrations or values to the values measured by the instruments being audited. 

• National Performance Evaluation Program (NPEP) – These performance evaluation audits 

are implemented at the federal level although some programs may be implemented by the 

monitoring organizations if certain requirements are met. 

1.3.4 Reports 

All concentration data should be assessed in order to evaluate the attainment of the DQOs or the 

monitoring objectives. These assessments can be documented using the following types of reports: 

• Data quality assessment (DQA) is the scientific and statistical evaluation to determine if data 

are of the right type, quality, and quantity to support their intended use (DQOs). QA/QC data can 

be statistically assessed at various levels of aggregation to determine whether the DQOs have 

been attained. Data quality assessments of precision, bias, and accuracy can be aggregated at the 

following three levels. 

o Monitor- monitor/method designation

o PQAO - monitors in a method designation, all monitors

o National - monitors in a method designation, all monitors

• P & B reports are generated annually and evaluate the precision and bias of data against the 

acceptance criteria discussed in Section 3. 

• QA reports provide an evaluation of QA/QC data for a given time period to determine whether 

the data quality objectives were met. Discussions of QA reports can be found in Sections 16 and 

18. 

• Meetings and Calls at various national meetings and conference calls can be used as assessment 

tools for improving the network. It is important that information derived from the avenues of 

communication is appropriately documented.
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2.0 Program Organization 

Federal, state, tribal, and local 

agencies all have important roles 

in developing and implementing 

air monitoring programs. Figure 

2.1 identifies the major entities 

involved in the Ambient Air 

Quality Monitoring Program, the 

organizational structure, and the 

lines of communication. The 

responsibilities of each 

organization follow. 

2.1 Organization Responsibilities 

2.1.1 EPA Office of Air Quality Planning and Standards (OAQPS)

EPA’s responsibility, under the Clean Air Act (CAA) as amended in 1990, includes: setting National 

Ambient Air Quality Standards (NAAQS) for pollutants considered harmful to the public health and 

environment; ensuring that these air quality standards are met or attained through national standards and 

strategies to control air emissions from sources; and ensuring that sources of toxic air pollutants are well 

controlled. 

OAQPS1

 is the organization charged under the authority of the CAA to protect and enhance the quality of 

the nation’s air resources. OAQPS evaluates the need to regulate potential air pollutants and develops 

national standards; works with state, tribes and local agencies to develop plans for meeting these 

standards; monitors national air quality trends and maintains a database of information on air pollution 

and controls; provides technical guidance and training on air pollution control strategies; and monitors 

compliance with air pollution standards. 

Within the OAQPS Air Quality Assessment Division, the Ambient Air Monitoring Group (AAMG)2

 is 

responsible for the oversight of the Ambient Air Quality Monitoring Network and its quality assurance 

program. AAMG, relative to quality assurance, has the responsibility to: 

• develop a satisfactory quality system for the Ambient Air Quality Monitoring Network; 

• ensure that the methods and procedures used in making air pollution measurements are adequate 

to meet the programs objectives and that the resulting data are of appropriate quality; 

• manage the National Performance Evaluation Program (NPEP); 

 

1 http://www.epa.gov/air/oarofcs.html 2 http://www.epa.gov/air/oaqps/organization/aqad/aamg.html 
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• perform data quality assessments of organizations making air pollution measurements of 

importance to the regulatory process; 

• ensure that guidance pertaining to the quality assurance aspects of the Ambient Air Program are 

written and revised as necessary; and 

• render technical assistance to the EPA Regional Offices and the air pollution monitoring 

community. 

In particular to this Handbook, OAQPS will be responsible for: 

• coordinating the Handbook Revision Workgroup responsible for continued improvement of the 

Handbook; 

• seeking resolution on Handbook issues; 

• incorporating agreed upon revisions into the Handbook; and 

• reviewing and revising the Handbook (Vol II) as necessary. 

Specific AAMG leads for the various QA activities (e.g., precision and bias, training, etc.) can be found 

within the QA Section3

 of the Ambient Monitoring Technical Information Center (AMTIC). 

2.1.2 EPA Regional Offices

EPA Regional Offices4

 play a critical role in addressing environmental issues related to the monitoring 

organizations within their jurisdiction and to administering and overseeing regulatory and congressionally 

mandated programs. 

The major quality assurance responsibilities of EPA’s Regional Offices in regards to the Ambient Air 

Quality Program are the coordination of quality assurance matters between the various EPA offices and 

the monitoring organizations. This role requires that the Regional Offices: 

• distribute and explain technical and quality assurance information to the monitoring 

organizations; 

• identify quality assurance needs of the monitoring organization to EPA Headquarters that are 

“national” in scope; 

• provide personnel and the infrastructure to implement NPEP programs; 

• provide the personnel with knowledge of QA regulations and with adequate technical expertise to 

address ambient air monitoring and QA issues; 

• ensure monitoring organization have approved quality management plans (QMPs) and quality 

assurance project plans (QAPPs) prior to routine monitoring; 

• evaluate the capabilities of monitoring organizations to measure the criteria air pollutants by 

implementing network reviews and technical systems audits; 

• assess data quality of monitoring organizations within its Regions; and 

• assist SLT agencies in defining primary quality assurance organizations within their jurisdiction 

and in assigning sites to a primary quality assurance organization. 

Specific responsibilities as they relates to the Handbook include: 

• serving as a liaison to the monitoring organizations for their particular Region; 

 

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• serving on the Handbook Revision Workgroup; 

• fielding questions related to the Handbook and ambient air monitoring programs; 

• reporting issues that would require Handbook Revision Workgroup attention; and 

• serving as a reviewer of the Handbook and participating in its revision. 

2.1.3 Monitoring Organizations

40 CFR Part 585

 defines a monitoring organization as a “state, local or other monitoring organization 

(such as tribes) responsible for operating a monitoring site for which quality assurance regulations apply.” 

Federally recognized Indian Tribes are Sovereign Nations. However, Section 301(d) of the CAA gives the 

Administrator the authority to treat an Indian Tribe as a State Agency with some exceptions. Additionally, 

Section 302 of the CAA states an air pollution control agency can be an agency of an Indian Tribe. 

The major responsibility of the monitoring organization6

 is the implementation of a satisfactory 

monitoring program, which would naturally include the implementation of an appropriate quality 

assurance program. Implementation of an appropriate quality assurance program includes the 

development and implementation of a QMP and QAPPs for the Ambient Air Quality Monitoring 

Program. It is the responsibility of monitoring organizations to implement quality assurance programs in 

all phases of the data collection process, including the field, its own laboratories, and in any consulting 

and contractor laboratories which it may use to obtain data. 

Monitoring organizations may be identified for reasons such as: 

• distinguishing geographic regions (e.g. CA Districts) 

• distinguishing different entities or sources of funds (e.g., tribal funds versus state/local funds) 

• identifying organizations receiving funds directly from EPA 

• identifying organizations that have different methods or objectives for monitoring 

Therefore, if the monitoring organization accepts federal funds for monitoring, it will be identified as a 

monitoring organization that will be required to submit a requisite QMP and QAPPs to cover its 

monitoring activities. This does not eliminate it from consolidating to a PQAO with other organizations 

that it shares common factors, as described in the next section. 

Specific responsibilities of monitoring organizations as they relates to the Handbook include: 

• serving as a representative for the monitoring organization on the Handbook Revision 

Workgroup; 

• assisting in the development of QA guidance for various sections; and 

• reporting issues and comments to Regional Contacts or on the AMTIC Bulletin Board. 

2.1.4 Primary Quality Assurance Organizations (PQAOs) 

A PQAO is a monitoring organization or a group of monitoring organizations that share a number of 

common “QA Factors”. Below is an excerpt on PQAOs from 40 CFR Part 58, Appendix A: 

 

5 http://www.access.gpo.gov/nara/cfr/cfr-table-search.html 6 http://www.4cleanair.org/contactUsaLevel.asp 
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3.1.1 Each primary quality assurance organization shall be defined such that measurement uncertainty 

among all stations in the organization can be expected to be reasonably homogeneous, as a result of 

common factors. Common factors that should be considered by monitoring organizations in defining 

primary quality assurance organizations include: 

 

 (a) Operation by a common team of field operators according to a common set of procedures; 

 (b) Use of a common QAPP or standard operating procedures; 

 (c) Common calibration facilities and standards; 

 (d) Oversight by a common quality assurance organization; and 

(e) Support by a common management, laboratory or headquarters. 

PQAO has very important implications to quality assurance activities. For each pollutant, the number of 

monitoring sites in a PQAO is used to determine the number and frequency of quality control checks, 

including the number of collocated monitors and the NPAP/PEP audit frequencies. PQAO is also used to 

aggregate data for assessments of completeness, precision and bias. EPA will base many of its data 

quality assessments at the PQAO level. The 5 common factors listed are the key criteria to be used when 

an agency decides the sites to be considered for aggregation to a PQAO. There are cases where state, 

local and tribal monitoring organizations have consolidated to one PQAO. The requirement does not 

intend that all 5 factors have to be fulfilled but that these factors are considered. However, common 

procedures and a common QAPP should be strongly considered as key to making decisions to consolidate 

sites into a PQAO. However, the QAPP(s) of the monitoring organizations must refer to the PQAO that 

the monitoring organization is affiliated with. EPA Regions will need to be aware of monitoring 

organizations consolidating to a PQAO and have documentation on file to this effect. Figure 2.2 shows 

the relationship of pollutants monitored at unique sites and how these unique sites are then related to 

monitoring organizations and primary quality assurance organizations. In the case of PQAO #1, a tribal 

monitoring organization and local monitoring organization have common factors that allow for 

consolidation. 
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PQAO is identified at the pollutant (monitor) level so two monitoring organizations may consolidate to a 

single PQAO for one pollutant due to similar methods and QA procedure, but not consolidate for another 

pollutant where they may have different quality requirements. 

2.1.5 EPA Office of Research and Development (ORD) National Exposure Research 

Laboratory (NERL)7

NERL conducts research and development that leads to improved methods, measurements and models to 

assess and predict exposures of humans and ecosystems to harmful pollutants and other conditions in air, 

water, soil, and food. The NERL provides the following activities relative to the Ambient Air Quality 

Monitoring networks: 

• develops, improves, and validates methods and instruments for measuring gaseous, semi-volatile, 

and non-volatile pollutants in source emissions and in ambient air; 

• supports multi-media approaches to assessing human exposure to toxic contaminated media 

through development and evaluation of analytical methods and reference materials, and provides 

analytical and method support for special monitoring projects for trace elements and other 

inorganic and organic constituents and pollutants; 

• develops standards and systems needed for assuring and controlling data quality; 

• assesses whether candidate sampling methods conform to accepted reference method 

specifications and are capable of providing data of acceptable quality and completeness for 

determining compliance with applicable National Ambient Air Quality Standards; 

• assesses whether emerging methods for monitoring criteria pollutants are “equivalent” to 

accepted Federal Reference Methods and are capable of addressing the Agency’s research and 

regulatory objectives; and 

• provides an independent audit and review function on data collected by NERL or other 

appropriate clients. 

NERL will continue to assist in the Handbook by: 

• providing overall guidance; 

• participating in the Handbook review process; 

• developing new methods including the appropriate QA/QC; and 

• conducting laboratory and field evaluations of sampling and analysis methods to resolve ad hoc 

technical issues. 

2.2 Lines of Communication

In order to maintain a successful Ambient Air Quality Monitoring Program, effective communication is 

essential. Lines of communication will ensure that decisions can be made at the most appropriate levels 

in a more time-efficient manner. It also means that each organization in this structure must be aware of 

the regulations governing the Ambient Air Quality Monitoring Program. In most circumstances, the 

monitoring organizations first line of contact is the EPA Region. Any issues that require a decision, 

especially in relation to the quality of data, or the quality system, should be addressed to the EPA Region. 

A monitoring organization should, in only rare circumstances, contact OAQPS with an issue if it has not 

initially contacted the EPA Region. If this does occur, OAQPS normally tries to include the pertinent 

EPA Region in the conversation, or at a minimum, briefs the EPA Region about the issue(s) discussed. 

 

7 http://www.epa.gov/nerl/ 
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This is appropriate as long as decisions are not made during these information-seeking communications. 

If important decisions are made at various locations along the line, it is important that the information is 

disseminated in all directions in order that improvements to the quality system can reach all organizations 

in the Program. Nationwide communication will be accomplished through AMTIC and the subsequent 

revisions to this Handbook. 

There are many other routes of communication available in the monitoring community. Three that occur 

with some frequency and should be used to identify important monitoring and QA issues are: 

National Association of Clean Air Agencies (NACAA)8

- represents air pollution control agencies in 53 

states and territories and over 165 major metropolitan areas across the United States. It formed in the 

1970’s to improve their effectiveness as managers of air quality programs. The association serves to 

encourage the exchange of information among air pollution control officials, to enhance communication 

and cooperation among federal, state, and local regulatory agencies, and to promote good management of 

our air resources. Specifically for the Ambient Air Monitoring Program, it facilitates a monthly 

conference call and has organized a Steering Committee, made up of monitoring organization 

representatives and EPA, that meet twice a year to discuss issues related to ambient air monitoring. 

National Tribal Air Association (NTAA)9

- is an autonomous organization affiliated with the National 

Tribal Environmental Council (NTEC). The NTAA’s mission is to advance air quality management 

policies and programs, consistent with the needs, interests, and unique legal status of American Indian 

Tribes, Alaska Natives, and Native Hawaiians. This organization has many similarities to NACCA. It 

also facilitates a monthly conference call with EPA and holds a national annual meeting. 

EPA Headquarters and Regional Monitoring and QA Calls- These calls occur monthly and are 

devoted to relevant monitoring and QA topics where EPA tries to develop consistent approaches to 

relevant monitoring issues. 

Besides the three communication mechanisms described above, there are many others, such as the 

Regional Planning Organization (RPOs)10 conference calls/meetings, EPA Regional conference 

calls/meetings that also serve to communicate the needs and issues of the ambient air monitoring 

community. 

 

8 http://www.4cleanair.org/about.asp 9 http://www.ntaatribalair.org/ 10 http://epa.gov/visibility/regional.html 
QA Handbook Vol II, Section 2.0 

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2.3 Quality Assurance (QA) Workgroups 

Two workgroups have been formed to provide information for improving the Ambient Air Monitoring 

Program Quality System 

• QA Strategy Workgroup 

• Handbook Revision Workgroup 

2.3.1 QA Strategy Workgroup

Organized and chaired by the QA Team Lead of OAQPS/AQAD, the Workgroup consists of Ambient Air 

Quality Assurance personnel from OAQPS, EPA Regions, and monitoring organizations. The Workgroup 

members were solicited through NACAA in 2001 in conjunction with OAQPS vision of a new 

monitoring strategy for the ambient air monitoring community. The goal, established by the Workgroup, 

was to define the elements of a Quality System. To achieve this goal, the Workgroup scheduled 

conference calls and meetings. Additionally, the work group meets on an annual basis at the National QA 

Meeting to discuss issues relevant to quality assurance work in the ambient air monitoring field. For 

information on the workgroup’s activities please refer to: www.epa.gov/ttn/amtic/qaqcrein.html. 

2.3.2 The Handbook Revision Workgroup

The Handbook Revision Workgroup is made up of representatives from the following four entities in 

order to provide representation at the Federal, State and local level: 

• OAQPS - OAQPS is represented by the coordinator for the Handbook and other 

representatives of the Ambient Air Quality Monitoring QA Team. 

• Regions - A minimum of 1 representative from each EPA Regional Office. 

• NERL -A minimum of one representative. NERL represents historical knowledge of the 

Handbook series as well as the expertise in the reference and equivalent methods program 

and QA activities. 

• Monitoring Organizations- A minimum of 10 representatives of the monitoring 

organizations. 

The mission of the workgroup is the continued clarification and addition of quality assurance procedures 

as related to ambient air monitoring and the networks. The workgroup provides experiences and insights 

in the ambient air monitoring field that will assist OAQPS with the task of the continuous improvement of 

the quality system. This ensures data integrity and provides valid quality indicators for decision makers 

faced with attainment/nonattainment issues as well as providing quality data to health professionals, 

academia and environmental professionals using the data. 

The Handbook Revision Workgroup will be formed every five years for the purpose of reviewing and 

revising the Handbook or sections as needed. Issues may surface from comments made by monitoring 

organizations liaisons, AMTIC bulletin board comments, or the development/revision of regulations. 
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3.0 Data Quality Objectives 

Data collected for the Ambient Air Quality Monitoring Program are used to make very specific decisions 

that can have an economic impact on the area represented by the data. Data quality objectives (DQOs)

are qualitative and quantitative statements derived from the DQO Planning Process that clarify the 

purpose of the study, define the most appropriate type of information to collect, determine the most 

appropriate conditions from which to collect that information, and specify tolerable levels of potential 

decision errors. Throughout this document, the 

term decision maker is used. This term represents 

individuals that are the ultimate users of ambient 

air data and therefore may be responsible for 

setting the NAAQS (or other objective), 

developing a quality system, or evaluating the data 

(e.g., NAAQS comparison). The DQO will be 

based on the data requirements of the decision 

maker who needs to feel confident that the data 

used to make environmental decisions are of 

adequate quality. The data used in these decisions 

are never error free and always contain some level 

of uncertainty. Because of these uncertainties or 

errors, there is a possibility that decision makers 

may declare an area “nonattainment” when the area 

is actually in “attainment” (Fig. 3.1 a false 

rejection of the baseline condition) or “attainment” 

when actually the area is in “nonattainment” (Fig. 

3.2 false acceptance of the baseline condition)1

. 

Figures 3.1 and 3.2 illustrate how false rejection 

and acceptance errors can affect a NAAQS 

decision based on an annual mean concentration 

value of 15 and the baseline condition that the area 

is in attainment. There are serious political, 

economic and health consequences of making such 

decision errors. Therefore, decision makers need to 

understand and set limits on the probabilities of 

making incorrect decisions with these data. 

In order to set probability limits on decision 

errors, one needs to understand and control 

uncertainty. Uncertainty is used as a generic term 

to describe the sum of all sources of error associated with an EDO and can be illustrated as follows: 

 2 2 2

o p m S = S + S Equation 3-1

where: 

So= overall uncertainty 

Sp= population uncertainty (spatial and temporal) 

Sm= measurement uncertainty (data collection). 

 

1

 “Guidance on Systematic Planning Using the Data Quality Objectives Process,” EPA QA/G-4 U.S. Environmental 

Protection Agency, QAD, February 2006. http://www.epa.gov/quality1/qs-docs/g4-final.pdf 

Figure 3.2 Effect of negative bias on the annual average 

resulting in a false acceptance error.

Figure 3.1 Effect of positive bias on the annual average 

estimate, resulting in a false rejection error.
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The estimate of overall uncertainty is an important component in the DQO process. Both population and 

measurement uncertainties must be understood. 

Population uncertainties - The most important data quality indicator of any ambient air monitoring 

network is representativeness2

. This term refers to the degree to which data accurately and precisely 

represent a characteristic of a population, a parameter variation at a sampling point, a process condition, 

or a condition. Population uncertainty, the spatial and temporal components of error, can affect 

representativeness. These uncertainties can be controlled through the selection of appropriate boundary 

conditions (the monitoring area and the sampling time period/frequency of sampling) to which the 

decision will apply, and the development of a proper statistical sampling design (see Section 6). 

Appendix B of the Quality Staff’s document titled Guidance for Quality Assurance Project Plans 

(EPA/G5)3 provides a very good dissertation on representativeness. It does not matter how precise or 

unbiased the measurement values are if a site is unrepresentative of the population it is presumed to 

represent. Assuring the collection of a representative air quality sample depends on the following factors: 

• selecting a network size that is consistent with the monitoring objectives and locating 

representative sampling sites; 

• identifying the constraints on the sampling sites that are imposed by meteorology, local 

topography, emission sources, land access and the physical constraints and documenting these; 

and 

• selecting sampling schedules and frequencies that are consistent with the monitoring objectives.

Measurement uncertainties are the errors associated with the EDO, including errors associated with the 

field, preparation and laboratory measurement phases. At each measurement phase, errors can occur, that 

in most cases, are additive. The goal of a QA program is to control measurement uncertainty to an 

acceptable level through the use of various quality control and evaluation techniques. In a resource 

constrained environment, it is most important to be able to calculate and evaluate the total measurement 

system uncertainty (Sm) and compare this to the DQO. If resources are available, it may be possible to 

evaluate various phases (e.g., field, laboratory) of the measurement system. 

Three data quality indicators are most important in determining total measurement uncertainty: 

• Precision - a measure of agreement among repeated measurements of the same property under 

identical, or substantially similar, conditions. This is the random component of error. Precision 

is estimated by various statistical techniques typically using some derivation of the standard 

deviation. 

• Bias - the systematic or persistent distortion of a measurement process which causes error in one 

direction. Bias will be determined by estimating the positive and negative deviation from the true 

value as a percentage of the true value. 

• Detection Limit - The lowest concentration or amount of the target analyte that can be 

determined to be different from zero by a single measurement at a stated level of probability. Due 

to the fact the NCore sites will require instruments to quantify at lower concentrations, detection 

limits are becoming more important. Some of the more recent guidance documents suggest that 

monitoring organizations develop method detection limits (MDLs) for continuous instruments 

and or analytical methods. Many monitoring organizations use the default MDL listed in AQS for 

a particular method. These default MDLs come from instrument vendor advertisements and/or 

 

2 http://www.epa.gov/quality1/glossary.htm#R 3 http://www.epa.gov/quality1/qa_docs.html 
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method manuals. Monitoring organizations should not rely on instrument vendor’s documentation 

on detection limits but determine the detection limits that are being achieved in the field during 

routine operations. Use of MDL have been listed in the NCore Precursor Gas Technical 

Assistance Document (TAD)4

.

Accuracy is a measure of the overall agreement of a measurement to a known value and includes a 

combination of random error (precision) and systematic error (bias) components of both sampling and 

analytical operations. This term has been used throughout the CFR and in some sections of this 

document. Whenever possible, it is recommended that an attempt be made to distinguish measurement 

uncertainties into precision and bias components. In cases where such a distinction is not possible, the 

term accuracy can be used. 

Other indicators that are considered during the DQO process include completeness and comparability. 

Completeness describes the amount of valid data obtained from a measurement system compared to the 

amount that was expected to be obtained under correct, normal conditions. For example, a PM2.5 monitor 

that is designated to sample every sixth day would be expected to have an overall sampling frequency of 

one out of every six days. If, in a thirty day period, the sampler misses one sample, the completeness 

would be recorded as four out of five, or 80 percent. Data completeness requirements are included in the 

reference methods (40 CFR Part 50). Comparability is a measure of the confidence with which one data 

set or method can be compared to another, considering the units of measurement and applicability to 

standard statistical techniques. Comparability of datasets is critical to evaluating their measurement 

uncertainty and usefulness. 

Performance Based Measurement System Concept: Consistency vs. Comparability

The NATTS Program proposes to use of the performance based measurement system (PBMS) concept. In 

simple terms, this means that as long as the quality of data that the program requires (DQOs) are defined, 

the data quality indicators are identified, and the appropriate measurement quality objectives (MQOs) that 

quantify that the data quality are met, any sampling/analytical method that meets these data quality 

requirements should be appropriate to use in the program. The idea behind PBMS is that if the methods 

meet the data quality acceptance criteria the data are “comparable” and can be used in the program. 

Previous discussions in this document allude to the need for “nationally consistent data”, “utilization of 

standard monitoring methods” and “consistency in laboratory methods”. Comparability is a data quality 

indicator because one can quantify a number of data quality indicators (precision, bias, detectability) and 

determine whether two methods are comparable. Consistency is not a data quality indicator and requiring 

that a particular method be used for the sake of consistency does not assure that the data collected from 

different monitoring organizations and analyzed by different laboratories will yield data of similar 

(comparable) quality. Therefore, the quality system will continue to strive for the development of data 

quality indicators and measurement quality objectives that will allow one to judge data quality and 

comparability and allow program managers to determine whether or not to require the use of a particular 

method (assuming this method meets the data quality needs). However, PBMS puts a premium on upfront planning and a commitment from monitoring organizations to adhere to implementing quality 

control requirements. 

The data quality indicator comparability must be evaluated in light of a pollutant that is considered a 

method-defined parameter. The analytical result of a pollutant measurement, of a method-defined 

parameter, has a high dependence on the process used to make the measurement. Most analytical 

measurements are determinations of a definitive amount of a specific molecule or mixture of molecules. 

An example of this would be the concentration of carbon monoxide in ambient air. However, other 

 

4 http://www.epa.gov/ttn/amtic/ncore/guidance.html 
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measurements are dependent on the process used to make the measurement. Method-defined parameters 

include measurements of physical parameters such as temperature and solar radiation which are 

dependent on the collection height and the design of the instrumentation used. Measurements of 

particulate mass, especially fine particulate, are also method-defined parameters because they are not 

"true" measures of particulate mass, being dependent on criteria such as: size cut-points which are 

geometrically defined; level of volatilization of particulates during sampling; and analytical methods that 

control the level of moisture associated with particulates at a concentration that may not represent actual 

conditions. (This should not be interpreted to mean that using a method-defined measurement of 

particulate is inferior. A "true" measurement of fine particulate in some environments can include a 

significant contribution from water, which is not a concern from a public/environmental health 

perspective). When selecting methods or comparing data sets for method-defined parameter it is 

important to consider that there is no “correct” measurement only a “defined” method. However as 

mentioned above in the PBMS discussion, there are certain data quality acceptance limits for “defined” 

methods that can be used to accept alternative methods. 

3.1 The DQO Process

The DQO process is used to facilitate the planning of EDOs. It asks the data user to focus their EDO 

efforts by specifying the use of the data (the decision), the decision criteria, and the probability they can 

accept making an incorrect decision based on the data. The DQO process: 

• establishes a common language to be shared by decision makers, technical personnel, and 

statisticians in their discussion of program objectives and data quality; 

• provides a mechanism to pare down a multitude of objectives into major critical questions; 

• facilitates the development of clear statements of program objectives and constraints that will 

optimize data collection plans; and 

• provides a logical structure within which an iterative process of guidance, design, and feedback 

may be accomplished efficiently. 

The DQO process contains the following steps: 

• State the problem: Define the problem that necessitates the study; identify the planning team, 

examine budget, schedule. 

• Identify the goal: State how environmental data will be used in meeting objectives and solving 

the problem, identify study questions, define alternative outcomes. 

• Identify information inputs: Identify data and information needed to answer study questions. 

• Define boundaries: Specify the target population and characteristics of interest, define spatial 

and temporal limits, scale of inference. 

• Develop the analytical approach: Define the parameter of interest, specify the type of 

inference, and develop the logic for drawing conclusions from findings. 

• Specify performance or acceptance criteria: 

o Decision making (hypothesis testing): Specify probability limits for false rejection and 

false acceptance decision errors. 

o Estimation approaches: Develop performance criteria for new data being collected or 

acceptable criteria for existing data being considered for use. 

• Develop the plan for obtaining data: Select the resource-effective sampling and analysis plan 

that meets the performance criteria. 
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The DQO Process is fully discussed in the document titled Guidance on Systematic Planning using the 

Data Quality Objectives Process (EPA QA/G-4), and is available on the EPA’s Quality System for 

Environmental Data and Technology website5

. For an illustration of how the DQO process was applied to 

a particular ambient air monitoring problem, refer to the EPA document titled Systematic Planning: A 

Case Study of Particulate Matter Ambient Air Monitoring6

. 

3.2 Ambient Air Quality DQOs

As indicated above, the first steps in the DQO process are to identify the problems that need to be 

resolved and the objectives to be met. As described in Section 2, the ambient air monitoring networks are 

designed to collect data to meet three basic objectives:

1. provide air pollution data to the general public in a timely manner; 

2. support compliance with air quality standards and emission strategy development; and 

3. support air pollution research. 

These different objectives could potentially require different DQOs, making the development of DQOs 

complex. However, if one were to establish DQOs based upon the objective requiring the most stringent 

data quality requirements, one could assume that the other objectives could be met. Therefore, the DQOs 

have been initially established based upon ensuring that decision makers can make comparisons to the 

NAAQS within a specified degree of certainty. OAQPS has established formal DQOs for PM2.5, Ozone, 

the NCore Precursor Gas Network, the PM2.5 Speciation Trends Network (STN)7

, and the National Air 

Toxics Trends Network (NATTS)8

. As the NAAQS for the other criteria pollutants come up for review, 

EPA will develop DQOs for these pollutants. 

3.3 Measurement Quality Objectives

Once a DQO is established, the quality of the data must be evaluated and controlled to ensure that it is 

maintained within the established acceptance criteria. Measurement Quality Objectives (MQOs) are 

designed to evaluate and control various phases (e.g., sampling, transportation, preparation, analysis) of 

the measurement process to ensure that total measurement uncertainty is within the range prescribed by 

the DQOs. MQOs can be defined in terms of the following data quality indicators: precision, bias, 

representativeness, detection limit, completeness and comparability as described in Section 3.0. 

MQOs can be established to evaluate overall measurement uncertainty, as well as for an individual phase 

of a measurement process. As an example, the precision DQO for PM2.5 is 10% and it is based on 3 years 

of collocated precision data collected at a PQAO level. Since only 15% of the sites are collocated, the 

data can be used to control the quality from each site and since the results can be effected by field and 

laboratory processes one cannot pinpoint a specific phase of the measurement system when a precision 

result is higher than the 10% precision goal. Therefore individual precision values greater than 10% may 

be tolerated as long as the overall 3-year DQO is achieved. In contrast, the flow rate audit, which is 

specific to the appropriate functioning of the PM2.5 sampler, has an MQO of + 4% of the audit standard 

and + 5% of the design value. This MQO must be met each time or the instrument is recalibrated. In 

summary, since uncertainty is usually additive, there is much less tolerance for uncertainty for individual 

 

5 http://www.epa.gov/quality1/qa_docs.html 6 http://www.epa.gov/quality1/qs-docs/casestudy2-final.pdf 7 http://www.epa.gov/ttn/amtic/specguid.html 8 http://www.epa.gov/ttn/amtic/airtoxqa.html 
QA Handbook Vol II, Section 3.0 

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phases of a measurement system (e.g., flow rate) since each phase contributes to overall measurement. As 

monitoring organizations develop measurement specific MQOs they should think about being more 

stringent for individual phases of the measurement process since it will help to keep overall measurement 

uncertainty within acceptable levels. 

For each of these indicators, acceptance criteria can be developed for various phases of the EDO. Various 

parts of 40 CFR Parts 50 and 58 have identified acceptance criteria for some of these indicators. In 

theory, if these MQOs are met, measurement uncertainty should be controlled to the levels required by the 

DQO. Table 3-1 is an example of an MQO table for ozone. MQO tables for the remaining criteria 

pollutants can be found in Appendix D. The ozone MQO table has been “re-developed” into what is 

known as a validation template. In June 1998, a workgroup of QA personnel from the monitoring 

organizations, EPA Regional Offices, and OAQPS was formed to develop a procedure that could be used 

by monitoring organizations for consistent use of MQOs and the validation of the criteria pollutants 

across the US. The workgroup developed three tables of criteria: 

Critical Criteria- deemed critical to maintaining the integrity of a sample (or ambient air concentration 

value) or group of samples were placed on the first table. Observations that do not meet each and every 

criterion on the critical table should be invalidated unless there are compelling reason and justification for 

not doing so. Basically, the sample or group of samples for which one or more of these criteria are not 

met is invalid until proven otherwise. 

Operational Criteria Table- important for maintaining and evaluating the quality of the data collection 

system. Violation of a criterion or a number of criteria may be cause for invalidation. The decision 

should consider other quality control information that may or may not indicate the data are acceptable for 

the parameter being controlled. Therefore, the sample or group of samples for which one or more of these 

criteria are not met is suspect unless other quality control information demonstrates otherwise. The 

reason for not meeting the criteria should be investigated, mitigated or justified. 

Systematic Criteria Table- include those criteria which are important for the correct interpretation of the 

data but do not usually impact the validity of a sample or group of samples. For example, the data quality 

objectives are included in this table. If the data quality objectives are not met, this does not invalidate any 

of the samples but it may impact the error rate associated with the attainment/non-attainment decision. 

More information about data validation and the use of the validation templates can be found in Section 

17. 
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Table 3-1 Measurement Quality Objectives for Ozone Developed into a Validation Template 

Requirement Frequency Acceptance Criteria 

Critical Criteria 

One Point QC Check

Single analyzer

1/ 2 weeks < 7% (percent difference) 

Zero/span check 1/ 2 weeks Zero drift # " 3% of full scale 

Span drift # " 7 % 

Operational Criteria 

Shelter Temperature 

 Temperature range Daily 

(hourly values) 

20 to 30E C. (Hourly ave) 

or 

per manufacturers specifications if designated to 

a wider temperature range 

 Temperature Control Daily (hourly values) # " 2E C SD over 24 hours 

Precision 

(using 1-point QC checks)

Calculated annually and as appropriate 

for design value estimates 

90% CL CV < 7% 

Bias 

(using 1-point QC checks) 

Calculated annually and as appropriate 

for design value estimates 

95% CL < + 7% 

Annual Performance 

Evaluation

 Single analyzer Every site 1/year 25 % of sites 

quarterly 

Percent difference at each audit level < 15% 

 PQAO annually 95% of audit percent differences fall within the 

one point QC check 95% probability intervals at 

PQAO level of aggregation 

Federal Audits (NPAP) 1/year at selected sites 20% of sites 

audited 

Mean absolute difference # 10% 

State audits 1/year State requirements 

Calibration Upon receipt/adjustment/repair and 

1/6 months if manual zero/span 

performed biweekly 

1/year if continuous zero/span 

performed daily 

All points within " 2 % of full scale of best-fit 

straight line 

Zero Air Concentrations below LDL 

Gaseous Standards NIST Traceable (e.g., EPA Protocol Gas) 

Zero Air Check 1/year Concentrations below LDL 

Ozone Transfer standard 

 Qualification and certification Upon receipt of transfer standard "4% or "4 ppb (whichever greater) 

 Recertification to local 

 primary standard 

Beginning and end of O3 season or 1/6 

months whichever less 

RSD of six slopes # 3.7% 

Std. Dev. of 6 intercepts 1.5 

New slope = + 0.05 of previous 

Ozone local primary standard 

Certification/recertification to 

Standard Photometer

1/year single point difference # "5 % 

(preferably " 3%) 

(if recertified via a transfer 

standard)

1/year Regression slopes = 1.00 " 0.03 and two 

intercepts are 0 " 3 ppb 

Detection 

Noise NA 0.003 ppm 

Systematic Criteria 

Standard Reporting Units All data ppm (final units in AQS) 

Completeness (seasonal) Daily 75% of hourly averages for the 8-hour period 

Sample Residence Times < 20 seconds 

Sample Probe, Inlet, 

Sampling train 

 Pyrex Glass or Teflon 

Siting Un-obstructed probe inlet

EPA Standard Reference 

Photometer Recertification 

1/year Regression slope = 1.00 + 0.01 

and intercept < 3 ppb 
 QA Handbook Vol II Section 4.0 

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4.0 Personnel Qualifications and Training 

4.1 Personnel Qualifications 

Ambient air monitoring personnel may be required to perform a number of functions that are important to 

the quality of data. Table 4-1 identifies these functions and provides some of the key activities within the 

functional category. Once the list is completed for a monitoring organization, it can be used in the 

development of position descriptions for recruitment and training programs. 

Not all functions are needed for the entire duration of the project. Monitoring organizations may feel that 

it can contract some of the functions that are needed. For example, an organization may wish to contract 

the information technology (IT) function to have the monitoring instruments connected to a data logging 

system that would transfer data to a local data base and eventually to an external data base like AQS. 

This part of the process might be considered a “one-time” event needing a particular expertise whose 

function might not require a full time person. However, it is critical that someone within the program 

understands this IT function to ensure data collection is operating properly on a day-to-day basis. 

Table 4-1 Monitoring Functions that Need Some Level of Staffing or Expertise 

Function Activities 

Procurement 

- Purchasing capital equipment and consumables 

- Developing contracts and maintenance agreements 

- Applying for EPA grants 

Technical 

- Setting up a monitoring site, electricity, communications 

- Developing standard operating procedures 

- Selecting and installing monitoring equipment 

- Calibrating equipment, performing quality control 

- Shelter and equipment maintenance 

Data Analysis (Statistical) 

- Understanding population and measurement uncertainty 

- Developing sampling designs 

- Developing networks to achieve objectives 

- Assessing/interpreting data (data quality assessments) 

Quality Assurance 

- Developing quality systems, QMPs/QAPPs 

- Developing data quality objectives 

- Implementing technical systems audits, performance evaluations 

- Validating data 

- QA reporting 

Information Technology 

- Selecting information technology (data loggers and local data base) 

- Developing analyzer outputs to data loggers and data transfer to local data base 

- Transfering data from local data base to external data repositories (AQS, etc.) 

Personnel assigned to ambient air monitoring activities are expected to have the educational, work 

experience, responsibility, personal attributes and training requirements for their positions. In some 

cases, certain positions may require certification and/or recertification. These requirements should be 

outlined in the position advertisement and in personal position descriptions. Records on personnel 

qualifications and training should be maintained and accessible for review during audit activities (unless 

the records are maintained as part of confidential personnel records). These records should be retained as 

described in Section 5. 
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4.2 Training

Adequate education and training are integral to any monitoring program that strives for reliable and 

comparable data. It is recommended that monitoring organizations maintain some requirements for air 

personnel qualifications (combination of education and experience). Training is aimed at increasing the 

effectiveness of employees and their organization. As part of a quality assurance program, EPA QA/G10, Guidance for Developing a Training Program for Quality System1 suggests the development of 

operational procedures for training. These procedures should include information on: 

 personnel qualifications- general and position specific 

 training requirements - by position 

 frequency of training 

Appropriate training should be available to employees supporting the Ambient Air Quality Monitoring 

Program, commensurate with their duties. Such training may consist of classroom lectures, workshops, 

web-based courses, teleconferences, vendor provided, and on-the-job training. 

Along with suggested training, there are some EPA programs that require mandatory training and/or 

certifications. These programs include, but are not limited to, the National Performance Audit Program 

(NPAP), Performance Evaluation Program (PEP), Interagency Monitoring of Protected Visual 

Environments (IMPROVE), and PM2.5 Speciation Trends Network Audit Program. All personnel 

performing audits in these projects or programs are required to possess mandatory training or a current 

certification issued by the EPA Office responsible for the monitoring program. 

EPA encourages regional planning organizations and monitoring organizations to develop training 

programs that require some level of certification. 

4.2.1 Suggested Training

Over the years, a number of courses have been developed for personnel involved with ambient air 

monitoring and quality assurance aspects. Formal QA/QC training is offered through the following 

organizations: 

 Air Pollution Training Institute (APTI) http://www.epa.gov/apti/ 

 Air & Waste Management Association (AWMA) http://www.awma.org/ 

 American Society for Quality Control (ASQC) http://www.asq.org/ 

 EPA Quality Assurance Staff http://www.epa.gov/quality1/ 

 EPA Regional Offices http://www.epa.gov/epahome/locate2.htm 

 EPA Ambient Monitoring Technology Information Center (AMTIC) Technology Transfer 

Network (http://www.epa.gov/ttn/amtic/training.html) 

In addition, OAQPS uses contractors and academic institutions to develop and provide training for data 

collection activities that support regulatory efforts throughout EPA and monitoring organizations. In 

addition, instrument and data management manufacturers provide training on the equipment they sell. 

Sometimes this can be added to the purchase cost. 

 

1 http://www.epa.gov/quality1/qs-docs/g10-final.pdf 
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Table 4-2 provides a suggested sequence of core QA-related ambient air monitoring courses for ambient 

air monitoring staff by job position. The suggested course sequences assume little or no experience in 

QA/QC or air monitoring but some courses may have pre-requisites. Persons having experience in the 

subject matter described in the courses would select courses according to their appropriate experience 

level. Courses not included in the core sequence would be selected according to individual 

responsibilities, preferences, and available resources. 

Table 4-2 Suggested Sequence of Core QA-related Ambient Air Training Courses for Ambient Air Monitoring and QA 

Personnel

SourceSequenceCourse Title (SI = self instructional) Field Lab QCSupv. Data 

Mgt. 

Mon 

Supv. 

QA QA 

Mgt. 

APTI- SI:422 Air Pollution Control Orientation Course X X X X X X 

APTI 452 Principles and Practices of Air Pollution Control X X X X X 

APTI -SI:100 Mathematics Review for Air Pollution Control X X 

QS- QA1 Orientation to Quality Assurance Management X X X 

APTI-SI:434 Introduction to Ambient Air Monitoring X X X X X X X 

APTI -SI:471 General Quality Assurance Considerations for Ambient 

Air Monitoring 

X X X X X X X 

APTI- SI:409 Basic Air Pollution Meteorology X X X X X 

APTI SI:473A Beginning Environmental Statistical Techniques 

(Revised) 

X X X X X X X 

APTI-470 Quality Assurance for Air Pollution Measurement 

Systems 

 X X X X 

QS-QA2 Data Quality Objectives Workshop X X X 

QS-QA3 Quality Assurance Project Plan X X X X 

APTI-435 Atmospheric Sampling X X X X X 

No Source Basic Electronics X X X 

APTI-SI:476B Continuous Emission Monitoring Systems - Operation & 

Maintenance of Gas Monitors 

X X X X 

APTI-474 Continuous Emission Monitoring X X X X 

APTI-SI:433 Network Design and Site Selection for Monitoring PM2.5

and PM10 in Ambient Air 

 X X X 

APTI-464 Analytical Methods for Air Quality Standards X X X X 

APTI Chain Of Custody Procedures for Samples and Data X X X X X X X 

APTI- SI:436 Site Selection for Monitoring SO2 X X X X 

OAQPS AQS Training (annual AQS conference) X X X 

QS- QA4 Data Quality Assessment X X X 

QS- QA5 Management Systems Review X X X 

APTI-SI:473B Introduction to Environmental Statistics X X X X 

AWMA QA6 Quality Audits for Improved Performance X X 

ASQC-STAT1 Statistics for Effective Decision Making X X X X X 
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5.0 Documentation and Records

Organizations that perform Environmental Data Operations (EDO) and management activities must 

establish and maintain procedures for the timely preparation, review, approval, issuance, use, control, 

revision and maintenance of documents and records. Each organization should have a documented 

records management policy with the following elements addressed: 

1. A list of files considered the official records and their media type i.e., paper, electronic 

2. Schedule for retention and disposition of records 

3. Storage and retrieval system of records 

4. Person(s) responsible at each level of storage and retrieval for records 

5. Assignment of appropriate levels of security 

This information should be included in a monitoring organization’s Quality Assurance Project Plan. In 

ambient air monitoring, the majority of the records are data and related information. However, these steps 

could be used for other records management practices in a monitoring organization. Please refer to 

Section 14 for further information and the EPA records website1

A document, from a records 

management perspective, is a 

volume that contains 

information that describes, 

defines, specifies, reports, 

certifies, or provides data or 

results pertaining to 

environmental programs. As 

defined in the Federal Records 

Act of 1950 and the Paperwork 

Reduction Act of 1995 (now 

44 U.S.C. 3101-3107), records 

are: “...books, papers, maps, 

photographs, machine readable 

materials, or other documentary 

materials, regardless of 

physical form or 

characteristics, made or 

received by an agency of the 

United States Government 

under Federal Law or in 

connection with the transaction 

of public business and 

preserved or appropriate for 

preservation by that agency or 

its legitimate successor as 

evidence of the organization, 

functions, policies, decisions, 

 

1 http://www.epa.gov/records/ 

Table 5-1 Types of Information that Should be Retained Through Document 

Control.

Categories Record/Document Types

Management and 

Organization 

State Implementation Plan 

Reporting agency information 

Organizational structure of monitoring program 

Personnel qualifications and training 

Quality management plan 

Document control plan 

Support contracts 

Site Information 

Network description 

Site characterization file 

Site maps/pictures 

Environmental Data 

Operations 

QA Project Plans (QAPPs) 

Standard operating procedures (SOPs) 

Field and laboratory notebooks 

Sample handling/custody records 

Inspection/maintenance records 

Raw Data Any original data (routine and QC) 

Data Reporting 

Air quality index report 

Annual SLAMS air quality information 

Data/summary reports 

Journal articles/papers/presentations 

Data Management Data algorithms 

Data management plans/flowcharts 

Quality Assurance 

Control charts and strip charts 

Data quality assessments 

QA reports 

System audits 

Network reviews 
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procedures, operations, or other activities of the Government or because of the informational value of data 

in them....”. This section will provide guidance of documentation and records for the Ambient Air 

Quality Monitoring Program. 

Table 5-1 represents the categories and types of records and documents that are applicable for document 

control. Information on key documents in each category follows. It should be noted that the list contains 

documents that may not be applicable to particular organizations and, therefore, is not meant to be a list of 

required documentation. This list should also not be construed as the definitive list of record and 

document types. 

Electronic Records 

Today, more data are generated and retained electronically in the ambient air monitoring community. The 

majority of the documentation referred to in this section can be an electronic record. Retention of 

electronic records2

 is included in the above definition. It is recommended that electronic as well as paper 

records be stored in a logical order for ease of access should it be necessary. This is discussed more indepth in Section 14. 

Statute of Limitations

As stated in 40 CFR Part 31.42, in general, all information considered as documentation and records 

should be retained for 3 years from the date the grantee submits its final expenditure report unless 

otherwise noted in the funding agreement. However, if any litigation, claim, negotiation, audit or other 

action involving the records has been started before the expiration of the 3-year period, the records must 

be retained until completion of the action and resolution of all issues that arise from it, or until the end of 

the regular 3-year period, whichever is later. For clarification purposes, the retention of samples produced 

as a result of required monitoring may differ depending on the program and/or purpose collected. For 

example, CFR requires that PM2.5 filter samples be archived for a minimum of one year. For retention of 

samples for a specific program please refer to the appropriate reference in CFR for the individual 

program. 

5.1 Management and Organization

How the monitoring organization handles the document types listed in Table 5-1 for this category can be 

found in a single document, a quality management plan, which is a blueprint for how an organization’s 

quality management objectives will be attained. The Quality Management Plan documents management 

practices, including QA and QC activities, used to ensure that the results of technical work are of the type 

and quality needed for their intended use. The EPA Quality Staff provide requirements for quality 

management plans3

 that monitoring organizations may find helpful. 

5.2 Site Information

Site information provides vital data about each monitoring site. Historical site information can help 

determine and evaluate changes in measurement values at the site. This information should be kept to 

characterize the site through time. The Air Quality System (AQS) Site File is one record used to capture 

and retain site information. Another source where site information is provided is the quality assurance 

 

2 http://www.epa.gov/records/tools/erks.htm 3

 EPA Requirements for Quality Management Plans (QA/R-2) http://www.epa.gov/quality1/qa_docs.html 
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project plan. This should include specific documentation of site characteristics for each monitoring 

station. This information will assist in providing objective inputs into the evaluation of data gathered at 

that site. 

Most ambient air agencies retain these records in paper and/or electronic file format. Included in a site 

information file are maps and pictures of an individual site. Because monitoring organizations are 

required to file an annual network plan and perform network assessments at a minimum of every five 

years, (40 CFR Part 58.10), this information should be retained and updated periodically by both the 

agency responsible for the site and/or the office responsible for reviewing the site information as needed 

for the network assessment process. Typically, the kinds of information found in a site identification 

record should include: 

1. Purpose of measurements (e.g., monitoring to determine compliance with air quality standards). 

2. Station type. 

3. Instrumentation and methods (manufacturer’s model number, pollutant measurement technique, 

etc.). 

4. Sampling system. 

5. Spatial scale of the station (site category--i.e., urban/industrial, suburban/commercial, etc.; 

physical location--i.e., address, AQCR, UTM coordinates, etc.). 

6. Influential pollutant sources (point and area sources, proximity, pollutant density, etc.). 

7. Topography (hills, valleys, bodies of water, trees; type and size, proximity, orientation, etc., 

picture of a 360 degree view from the probe of the monitoring site). 

8. Atmospheric exposure (unrestricted, interferences, etc.). 

9. Site diagram (measurement flowsheet, service lines, equipment configuration, etc.). 

10. Site audits. 

5.3 Environmental Data Operations

A quality assurance program associated with the collection of ambient air monitoring data must include 

an effective procedure for preserving the integrity of the data. Ambient air monitoring results and in 

certain types of measurements, the sample itself, may be essential elements in proving the validity of the 

data or the decisions made using the data. Data can not be admitted as evidence unless it can be shown 

that they are representative of the conditions that existed at the time that the data (or sample) was 

collected. Therefore, each step in the sampling and analysis procedure must be carefully monitored and 

documented. There are basically four elements in the evidentiary phase of an overall quality assurance 

program: 

1. Data collection - includes measurement preparation and identification of the sample, location, 

time, and conditions during the measurements in the form of data sheets, logbooks, strip charts, 

and raw data. 

2. Sample and/or measurement result handling - includes evidence that the sample and data were 

protected from contamination and tampering during transfer between people and from the 

sampling site to the evidence locker (i.e., chain of custody) and during analysis, transmittal, and 

storage. 

3. Analysis - includes evidence that samples and data were properly stored prior to and after 

analysis interpretation, and reporting. 

4. Preparation and filing of measurement report - includes evidentiary requirements and retention of 

records.
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Failure to include any one of these elements in the collection and analysis of ambient air monitoring data 

may render the results of the program inadmissible as evidence, or may seriously undermine the 

credibility of any report based on these data. 

Environmental data operations include all the operations required to successfully measure and report a 

value within the data quality objectives. Documentation for environmental data operations would 

include: 

• QA Project Plans - Documents how environmental data operations are planned, implemented, 

and assessed during the life cycle of a program, project, or task (see below). 

• Standard operating procedures (SOPs)- Written documents that give detailed instruction on 

how a monitoring organization will perform daily tasks: field, laboratory and administrative. 

SOPs are a required element of a QAPP and therefore any EDO must include these (see below). 

• Field and laboratory notebooks- Any documentation that may provide additional information 

about the environmental data operation (e.g., calibration notebooks, strip charts, temperature 

records, site notes, maintenance records etc.) (see below). 

• Sample handling and/or custody records- Records tracing sample and data handling from the 

site through analysis, including transportation to facilities, sample storage, and handling between 

individuals within facilities. (Section 12 provides more information on this activity.) 

Quality Assurance Project Plan

As mentioned in the assistance agreement sections of 40 CFR Parts 30.54 (Non-State and Local Gov.) 

and 31.45 (State and Local Gov.) quality assurance programs must be established. In addition to the grant 

requirements, 40 CFR Part 58, Appendix A4

 states that each quality assurance program must be described 

in detail in accordance with the EPA Requirements for Quality Assurance Project Plans5

.

Standard Operating Procedures

In order to perform sampling and analysis operations consistently, standard operating procedures (SOPs) 

must be written as part of the QAPP. SOPs are written documents that detail the method for an operation, 

analysis, or action with thoroughly prescribed techniques and steps, and are officially approved as the 

method for performing certain routine or repetitive tasks. Although not every activity in the 

field/laboratory needs to be documented, the activities that could potentially cause measurement 

uncertainties, or significant variance or bias, should be described in an SOP. In general, approval of 

SOPs occurs during the approval of the QAPP. Individuals with appropriate training and experience with 

the particular SOPs in the QAPP need to review the SOPs. 

SOPs should ensure consistent conformance with organizational practices, serve as training aids, provide 

ready reference and documentation of proper procedures, reduce work effort, reduce error occurrences in 

data, and improve data comparability, credibility, and defensibility. They should be sufficiently clear and 

written in a step-by-step format to be readily understood by a person knowledgeable in the general 

concept of the procedure. 

 

4 http://www.gpoaccess.gov/cfr/index.html 5 http://www.epa.gov/quality1/qa_docs.html 
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Elements that may be included in SOPs which are explained in the guidance document Guidance for the 

Preparation of Standard Operating Procedures EPA QA/G-66 are: 

1. Scope and Applicability 

2. Summary of Method 

3. Definitions 

4. Health and Safety Warnings 

5. Cautions 

6. Interferences 

7. Personnel Qualifications 

8. Equipment and Supplies 

9. Procedure (section may include all or part of these sections): 

a. Instrument or Method Calibration 

b. Sample Collection 

c. Sample Handling and Preservation 

d. Sample Preparation and Analysis 

e. Troubleshooting 

f. Data Acquisition, Calculations & Data Reduction 

g. Computer Hardware & Software (used to manipulate analytical results and report data) 

10. Data Management and Records Management Parameters 

11. Quality Control/Quality Assurance 

Elements that are not needed may be excluded or listed as “NA” (not applicable). 

Personnel implementing SOPs may not be involved in the “larger picture” which includes the use of the 

data and whether or not DQOs are being achieved. Therefore, it’s very important that the SOP covers the 

objectives of the monitoring program and the importance of following each step in an SOP in order to 

achieve quality results. 

 

NOTE: There may be some incentive to rely on vendor developed methods manuals or to 

reference analytical methods on internet sites (e.g., TO-15 for NATTS VOCs) as a 

monitoring organization’s SOP without revision. Although the majority of information in 

these documents may be appropriate, many times the methods provide more than one 

option for method implementation and is not specific to the organization implementing 

the method. Therefore, organizations are encouraged to utilize these methods but edit 

them to make them specific to the organization. 

Many of these operational procedures listed above are included in the EPA reference and equivalent 

methods, and EPA guidance documents. However, it is the organization’s responsibility to develop its 

own unique written operational procedures applicable to air quality measurements made by the 

organization. 

SOPs should be written by individuals performing the procedures that are being standardized. SOPs for 

the Ambient Air Quality Monitoring Program environmental data operations must be included in QAPPs, 

either by reference or by inclusion of the actual method. If a method is referenced, it should be stated that 

the method is followed exactly or an addendum that explains changes to the method should be included in 

the QAPP (see NOTE above). If a modified method will be used for an extended period of time, the 

 

6 http://www.epa.gov/earth1r6/6pd/qa/qadevtools/mod4references/secondaryguidance/g6-final.pdf
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method should be revised to include the changes to appropriate sections. In general, approval of SOPs 

occurs during the approval of the QAPP. Individuals with appropriate training and experience with the 

particular SOPs in the QAPP need to review the SOPs. 

SOPs should have some level of documented approval by the monitoring organization and be 

reviewed/approved at some frequency. There should be some level of document control on SOPs so that 

personnel can quickly determine whether or not they are using the most current method. The document 

control information on the pages of this Handbook provide a good example. It is suggested that the 

monitoring organization create a “master” list of the current SOPs it uses and include some document 

control information to allow users to identify the appropriate SOPs. 

Field and Laboratory Notebooks-- 

Recording of some field and laboratory data is necessary for ambient air monitoring. Section 11 provides 

some details of activities that can be recorded in these notebooks. A standardized format should be 

utilized to ensure that all necessary information is obtained. The format should be designed to clearly 

identify the parameters during the measurements, the date and time, location of the measurement station, 

and operating personnel. This information may determine the credibility of the data and should not be 

erased or altered. Recording of the data should be legible. If a manual record is kept, any error should be 

crossed out with a single line, and the correct value recorded above the crossed-out entry. 

Electronic recording and storage of data is widely used. Electronic recording of the data allows for 

flagging and retention of additional information that is pertinent to day to day operations that could 

otherwise be lost with conventional systems. The same information as listed in the above paragraph 

should be recorded during routine quality checks. Some monitoring organizations like to electronically 

produce strip charts of data and/or supporting information. This data can be used to enhance and support 

the validity of the data. 

It is recommended a log book be kept for each instrument in a monitoring organization’s network. The 

information contained in this log should consist of the above information as well as any calibration, audit, 

and maintenance work performed on the instrument. This log should follow the instrument from site to 

site as the instrument may be moved. The date of any movement of the instrument should also be 

recorded in the log. This log can either be an electronic record or a hardbound book. 

Additionally, a site log can be kept documenting maintenance of a specific monitoring site and the 

auxiliary monitoring equipment located there. Information that could be recorded includes maintenance to 

station HVAC system, air conditioner cleaning, maintenance to external sample intake pumps, permeation 

tube changes, sample line replacement or cleaning, and replacement of any equipment associated with the 

shelter or monitoring system. This log can also be either electronic or a hard bound book. Keeping this 

log can alert a field technician to upcoming maintenance as well as serve as a tool in determining data 

quality as necessary. 

Do not discard original field records; copies of them are not normally admissible as evidence. For 

neatness, the field data may be transcribed or copied for incorporation in a final report, but the originals 

should be kept on file. Since these records may be subpoenaed, it is important that all field notes be 

legible. 
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5.4 Raw Data 

Raw data includes any original factual information from a measurement activity or study recorded in 

laboratory work sheets, records, memoranda, notes, computer (electronic) files or exact copies thereof and 

that are necessary for the reconstruction and evaluation of the report of the activity or study. Raw data 

may include photographs, microfilm or microfiche copies, computer printouts, magnetic media, including 

dictated observations, and recorded data from automated instruments. For automated information 

systems, raw data is considered the original observations recorded by the information system that are 

needed to verify, calculate, or derive data that are or may be reported. Organizations should critically 

review the Ambient Air Quality Monitoring Program and create a list of what the organization considers 

raw data and provide a means to store this information in a manner that is readily accessible. 

5.5 Data Reporting

In addition to samples and field records, the report of the analysis itself may serve as material evidence. 

Just as the procedures and data leading up to the final report are subject to the rules of evidence, so is the 

report. Written documents are generally considered as hearsay and are not admissible as evidence 

without a proper foundation. A proper foundation consists of introducing testimony from all persons 

having anything to do with the major portions of the measurement and analysis. Thus, the field operator, 

all persons having custody of the samples and data, and the analyst would be required to lay the 

foundation for the introduction of the measurement as evidence. This evidence can and should be 

recorded in the form of initials and notes written in indelible ink at the time of data collection on paper 

that is kept on file. The proper foundation is laid and available in case the data are questioned. Examples 

of this include strip charts dated and initialed by operator when visiting the site for routine quality checks 

and initials on routine paperwork and in logbooks when events are recorded. Electronic records should 

also allow for a recording of initials or be traceable to the operator performing the work. 

To ensure compliance with legal rules, all measurement reports should be filed in a safe place by a 

custodian having this responsibility. Although the field notes and calculations are not generally included 

in the summary report, these materials may be required at a future date to bolster the acceptability and 

credibility of the report as evidence in an enforcement proceeding. Therefore, the full report including all 

original notes and calculation sheets should be kept in the file. Signed receipts for all samples, strip 

charts, or other data, should also be filed. 

The original of a document is the best evidence; a copy is not normally admissible as evidence. 

Microfilm, snap-out carbon copies, and similar contemporary business methods of producing copies are 

acceptable in many jurisdictions if the unavailability of the original is adequately explained and if the 

copy was made in the ordinary course of business. 

In summary, although all original calculations and measurement data need not be included in the final 

report, they should be kept in the agency’s files. It is a good rule to file all reports together in a secure 

place. Keeping these documents under lock and key will ensure that the author can testify at future court 

hearings that the report has not been altered. 
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5.6 Data Management 

Much of the data collected for the Ambient Air Quality Monitoring Program will be collected through the 

use of automated systems. These systems must be effectively managed and documented by using a set of 

guidelines and principles by which adherence will ensure data integrity. Discussions of data management 

activities and the requirements for documentation can be found in Section 14. 

5.7 Quality Assurance 

Quality assurance information is necessary to document the quality of data. A monitoring organization’s 

plan for all quality assurance activities must be documented in its QAPP. This information should be 

retained in a manner that it can be associated with the routine data that it represents. QA information 

includes: 

• Control charts - Use of control charts is explained in Section 12. 

• Data quality assessments (DQAs) - These assessments are a statistical and scientific evaluation 

of the data set to determine the validity and performance of the data collection design and to 

determine the adequacy of the data set for its intended use. More discussion on DQAs can be 

found in Section 18. 

• QA Reports - Reports pertaining to the quality of data are discussed in Sections 3 and 16. 

• Evaluation/Audits - Assessments of various phases of the environmental data operation are 

discussed in Section 15. 
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6.0 Monitoring Network Design

The selection of a specific monitoring site includes four major activities: 

1. Developing and understanding the monitoring objective and appropriate data quality objectives. 

2. Identifying the spatial scale most appropriate for the monitoring objective of the site. 

3. Identifying the general locations where the monitoring site should be placed. 

4. Identifying specific monitoring sites. 

This section describes the general concepts for establishing the SLAMS, NCore, STN, PAMS, and open 

path monitoring. Additional details can be found in 40 CFR Part 58, Appendix D 1 and the guidance 

information for the various monitor networks that can be found on AMTIC2

. 

As described in Section 1, air quality samples are generally collected for one or more of the following 

purposes: 

• To provide air pollution data to the general public in a timely manner. 

• To judge compliance with and/or progress made towards meeting ambient air quality standards. 

• To activate emergency control procedures that prevent or alleviate air pollution episodes. 

• To observe pollution trends throughout the region, including non-urban areas. 

• To provide a data base for research evaluation of effects: urban, land-use, and transportation 

planning; development and evaluation of abatement strategies; and development and validation of 

diffusion models. 

Network information related to these 5 purposes is discussed below. 

“Real-Time” Air Quality Public Reporting

The U.S. EPA, NOAA, NPS, tribal, state, and local agencies developed the AIRNow3 Web site to provide 

the public with easy access to national air quality information. The Web site offers daily Air Quality 

Index (AQI): 

Conditions- Nationwide and regional real-time ozone and PM2.5 air quality maps covering 46 US 

States and parts of Canada. These maps are updated daily every hour. A click of a mouse brings up 

the U.S. map and a second click can bring up the AQI details of a region, state or local area within a 

state. 

Forecasts - Nationwide daily air quality forecasts provided by monitoring organizations for over 

300 major cities and areas in the U.S. 

Federal requirements state that Metropolitan Statistical Areas (MSAs) with a population of more than 

350,000 are required to report the AQI daily to the general public. The U.S. Office of Management and 

Budget defines MSAs according to the 2000 census. However, many other tribal, state and local 

monitoring organizations participate in AIRNow. 

There are no specific network requirements or guidelines for reporting to AIRNow. Sites used for 

 

1 http://www.epa.gov/ttn/amtic/40cfr53.html 2 http://www.epa.gov/ttn/amtic/ 3 http://airnow.gov/ 
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reporting to AIRNow are sites that have been set up for the other monitoring objectives discussed above. 

The air quality data used in these maps and to generate forecasts are collected using either federal 

reference or equivalent monitoring techniques or techniques approved by the monitoring organizations. 

Since the information needed to make maps must be as "real-time" as possible, the data are displayed as 

soon as practical after the end of each hour. Although some preliminary data quality assessments are 

performed, the data as such are not fully verified and validated through the quality assurance procedures 

monitoring organizations use to officially submit and certify data on the EPA AQS. Therefore, data are 

used on the AIRNow Web site only for the purpose of reporting the AQI. Information on the AIRNow 

web site is not used to formulate or support regulation, guidance or any other Agency decision or 

position. 

Compliance Monitoring

The information required for selecting the number of samplers4

 and the sampler locations include isopleth 

maps, population density maps, and source locations. The following are suggested guidelines: 

• the priority area is the zone of highest pollution concentration within the region; one or more 

stations should be located in this area; 

• close attention should be given to densely populated areas within the region, especially when they 

are in the vicinity of heavy pollution; 

• the quality of air entering the region is to be assessed by stations situated on the periphery of the 

region; meteorological factors (e.g., frequencies of wind directions) are of primary importance in 

locating these stations; 

• sampling should be undertaken in areas of projected growth to determine the effects of future 

development on the environment; 

• a major objective of compliance monitoring is the evaluation of progress made in attaining the 

desired air quality; for this purpose, sampling stations should be strategically situated to facilitate 

evaluation of the implemented control strategies; and 

• some information of air quality should be available to represent all portions of the region of 

concern. 

Some stations will be capable of fulfilling more than one of the functions indicated. For example, a 

station located in a densely populated area can indicate population exposures and can also document the 

changes in pollutant concentrations resulting from mitigation strategies used in the area. 

Emergency Episode Monitoring

For episode avoidance purposes, data are needed quickly--in no less than a few hours after the pollutant 

contacts the sensor. While it is possible to obtain data rapidly by on-site manual data reduction and 

telephone reporting, there is a trend towards using automated monitoring networks. The severity of the 

problem, the size of the receptor area, and the availability of resources all influence both the scope and 

sophistication of the monitoring system. 

It is necessary to use continuous air samplers because of the short durations of episodes and the control 

actions taken must be based on real-time measurements that are correlated with the decision criteria. 

Based on episode alert criteria and mechanisms now in use, 1-h averaging times are adequate for 

 

4

 A “sampler” in this context refers to both continuous instruments that provide an ambient air concentration without 

additional preparation or analytical techniques as well as instruments that provide a sample needing additional 

analysis. 
 QA Handbook Vol II, Section 6.0 

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surveillance of episode conditions. Shorter averaging times provide information on data collecting 

excursions, but they increase the need for automation because of the bulk of data obtained. Longer 

averaging times (>6 hours) are not desirable because of the delay in response that these impose. After an 

alert is announced, data are needed quickly so that requests for information on the event can be provided. 

Collection and analysis must be accomplished rapidly if the data are to be useful immediately. Collection 

instruments must be fully operable at the onset of an episode. For the instrument to be maintained in peak 

operating condition, either personnel must be stationed at the sites during an episode or automated 

equipment must be operated that can provide automatic data transmission to a central location. 

Monitoring sites should be located in areas where human health and welfare are most threatened: 

• in densely populated areas; 

• near large stationary source of pollution; 

• near hospitals; 

• near high density traffic areas; and 

• near homes for the aged. 

A network of sites is useful in determining the range of pollutant concentrations within the area, but the 

most desirable monitoring sites are not necessarily the most convenient. Public buildings such as schools, 

firehouses, police stations, hospitals, and water or sewage plants should be considered for reasons of 

access, security and existing communications. 

Trends Monitoring

Trends monitoring is characterized by locating a minimal number of monitoring sites across as large an 

area as possible while still meeting the monitoring objectives. The program objective is to determine the 

extent and nature of the air pollution and to determine the variations in the measured levels of the 

atmospheric contaminants in respect to the geographical, socio-economic, climatological and other 

factors. The data are useful in planning epidemiological investigations and in providing the background 

against which more intensive regional and community studies of air pollution can be conducted. 

Urban sampling stations are usually located in the most densely populated areas of the region. In most 

regions, there are several urban sites. Non-urban stations encompass various topographical categories 

such as farmland, desert, forest, mountain and coast. Non-urban stations are not selected specifically to 

be “clean air” control sites for urban areas, but they do provide a relative comparison between some urban 

and nearby non-urban areas. 

In interpreting trends data, limitations imposed by the network design must be considered. Even though 

precautions are taken to ensure that each sampling site is as representative as possible of the designated 

area, it is impossible to be certain that measurements obtained at a specific site are not unduly influenced 

by local factors. Such factors can include topography, structures, sources of pollution in the immediate 

vicinity of the site, and other variables; the effects which cannot always be accurately anticipated, but 

nevertheless, should be considered in network design. Comparisons among pollution levels for various 

areas are valid only if the sites are representative of the conditions for which the study is designed. 
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Research Monitoring 

Air monitoring networks related to health effects are composed of integrating samplers both for 

determining pollutant concentrations for <24 hours and for developing long term (>24 hour) ambient air 

quality standards. The research requires that monitoring points be located so that the resulting data will 

represent the population group under evaluation. Therefore, the monitoring stations are established in the 

centers of small well-defined residential areas within a community. Data correlations are made between 

observed health effects and observed air quality exposures. 

Requirements for aerometric monitoring in support of health studies are as follows: 

• the station must be located in or near the population under study; 

• pollutant sampling averaging times must be sufficiently short to allow for use in acute health 

effect studies that form the scientific basis for short-term standards; 

• sampling frequency, usually daily, should be sufficient to characterize air quality as a function of 

time; and 

• the monitoring system should be flexible and responsive to emergency conditions with data 

available on short notice. 

6.1 Monitoring Objectives and Spatial Scales

With the end use of the air quality samples as a prime consideration, the national ambient air monitoring 

networks are designed to determine one of six basic monitoring objectives listed below: 

1. Determine the highest concentration expected to occur in the area covered by the network. 

2. Measure typical concentrations in areas of high population density. 

3. Determine the impact of significant sources or source categories on air quality. 

4. Determine background concentration levels. 

5. Determine the extent of regional pollutant transport among populated areas; and in support of 

secondary standards. 

6. Measure air pollution impacts on visibility, vegetation damage, or welfare-based impacts. 

These six objectives indicate the nature of the samples that the monitoring network will collect that must 

be representative of the spatial area being studied. In the case of PAMS, the design criteria are site 

specific and, therefore, there are specific monitoring objectives associated with each location for which 

PAMS stations are required (see Table 6-4). 

Sampling equipment requirements are generally divided into three categories, consistent with the desired 

averaging times: 

1. Continuous- Pollutant concentrations determined with automated methods, and recorded or 

displayed continuously. 

2. Integrated- Pollutant concentrations determined with manual or automated methods from 

integrated hourly or daily samples on a fixed schedule (i.e., manual PM2.5). 

3. Static- Pollutant estimates or effects determined from long-term (weekly or monthly) exposure to 

qualitative measurement devices or materials (i.e., passive monitoring5

) 

 

5 http://www.epa.gov/ttn/amtic/passive.html 
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Air monitoring sites that use automated equipment to continually sample and analyze pollutant levels may 

be classified as primary. Primary monitoring stations are generally located in areas where pollutant 

concentrations are expected to be among the highest and in areas with the highest population densities; 

thus, they are often used in health effects research networks. These stations are also designed as part of 

the air pollution episode warning system and used to report data to the public through AIRNow6

 and the 

air quality index (AQI). 

The goal in siting stations is to correctly match the spatial scale represented by the sample of monitored 

air with the spatial scale most appropriate for the monitoring objective of the station. This achieves the 

goal of data quality indicator representativeness discussed in Section 3. The representative measurement 

scales of greatest interest are shown below: 

Micro Concentrations in air volumes associated with area dimensions ranging from 

several meters up to about 100 meters. 

Middle Concentrations typical of areas up to several city blocks in size with 

dimensions ranging from about 100 meters to 0.5 kilometer. 

Neighborhood Concentrations within some extended area of the city that has relatively 

uniform land use with dimensions in the 0.5 to 4.0 kilometers range. 

Urban Overall, citywide conditions with dimensions on the order of 4 to 

50 kilometers. This scale would usually require more than one site for 

definition. 

Regional Usually a rural area of reasonably homogeneous geography and extends from 

tens to hundreds of kilometers. 

National/Global Concentrations characterizing the nation and the globe as a whole. 

Table 6-1 illustrates the relationships among the four basic monitoring objectives and the scales of 

representativeness that are generally most appropriate for that objective. Appendix E provides more 

detailed spatial characteristics for each pollutant while Table 6-2 provides a summary for the various 

monitoring programs. 

Table 6-1 Relationship Among Monitoring Objectives and Scales of Representativeness 

Monitoring Objective Appropriate Siting Scale

Highest Concentration 

Population 

Source impact 

General/background & Regional Transport 

Welfare-related 

Micro, middle, neighborhood, sometimes urban 

Neighborhood, urban 

Micro, middle, neighborhood 

Urban/regional 

Urban/regional 

There is the potential for using open path monitoring for microscale spatial scales. For microscale areas, 

however, siting of open path analyzers must reflect proper regard for the specific monitoring objectives. 

Specifically, the path-averaging nature of open path analyzers could result in underestimations of high 

pollutant concentrations at specific points within the measurement path for other ambient air monitoring 

situations. In open path monitoring, monitoring path lengths must be commensurate with the intended 

scale of representativeness and located carefully with respect to local sources or potential obstructions. 

For short-term/high-concentration or source-oriented monitoring, the monitoring path may need to be 

further restricted in length and be oriented perpendicular to the wind direction(s) determined by air 

quality modeling leading to the highest concentration, if possible. Alternatively, multiple paths may be 

used advantageously to obtain both wider area coverage and peak concentration sensitivity. 

 

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Table 6-2 Summary of Spatial Scales for SLAMS, NCore, PAMS, and Open Path (OP) Sites 

Spatial Scale SLAMS Sites1 PM10-2.5 NCore STN NATTs PAMS OP 

 SO2 CO O3 NO2 Pb PM10 PM2.5 

Micro * * * * * * 

Middle * * * * * * * * 

Neighborhood * * * * * * * * * * * * 

Urban * * * * * * * * * 

Regional * * * * * * 

1 SLAMS Site scales based on current listing in 40 CFR Part 58, Appendix D and do not include NCore spatial scale objective.

6.1.1 Monitoring Boundaries

The NAAQS refer to several boundaries that are defined below. These definitions are derived from the 

U.S. Office of Management and Budget (OMB). 

Core-based Statistical Area (CBSA) – is defined by the OMB as a statistical geographic entity 

consisting of the county or counties associated with at least one urbanized area/urban cluster of at least 

10,000 population, plus adjacent counties having a high degree of social and economic integration. 

Metropolitan Statistical Area (MSA) - a category of CBSA with populations greater than 50,0007

. 

Micropolitan Statistical Area - are a category of CBSA with populations between 10,000 and 50,000 

Combined Statistical Area (CSA) - is defined by the OMB as a geographical area consisting of two or 

more adjacent Core Based Statistical Areas (CBSA) with employment interchange of at least 15 percent. 

Combination is automatic if the employment interchange is 25 percent and determined by local opinion if 

more than 15 but less than 25 percent8

. 

New England city and town areas (NECTAs) - are analogous to CBSAs and are similarly classified as 

either metropolitan NECTAs (corresponding to MSAs) or micropolitan NECTAs (corresponding to 

micropolitan statistical areas). The principal difference between a CBSA and a NECTA is that NECTAs 

use New England towns as building blocks instead of counties. In the New England region, towns are a 

much more important level of government than counties. Because of this, NECTAs are usually a much 

closer approximation to metropolitan areas in New England than MSAs 

Monitoring Planning Area (MPA) - means a contiguous geographic area with established, well defined 

boundaries, such as a CBSA, county or State, having a common area that is used for planning monitoring 

locations for PM2.5. An MPA may cross State boundaries, such as the Philadelphia PA–NJ MSA, and be 

further subdivided into community monitoring zones. MPAs are generally oriented toward CBSAs or 

CSAs with populations greater than 200,000, but for convenience, those portions of a State that are not 

associated with CBSAs can be considered as a single MPA. 

Community Monitoring Zone (CMZ) – means an optional averaging area with established, well defined 

boundaries, such as county or census block, within an MPA that has relatively uniform concentrations of 

annual PM2.5 as defined by 40 CFR Part 50, Appendix N. Two or more community oriented SLAMS 

monitors within a CMZ that meet certain requirements as set forth in Appendix N may be averaged 

(spatial averaging) for making comparisons to the annual PM2.5 NAAQS. 

 

7 http://www.census.gov/population/estimates/metro-city/List1.txt 8 http://www.census.gov/population/estimates/metro-city/List6.txt
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6.2 Monitoring Site Location

Four criteria should be considered, either singly or in combination when locating sites, depending on the 

sampling objective. Orient the monitoring sites to measure the following: 

1. Impacts of known pollutant emission categories on air quality. 

2. Population density relative to receptor-dose levels, both short and long term. 

3. Impacts of known pollutant emission sources (area and point) on air quality. 

4. Representative area-wide air quality. 

To select locations according to these criteria, it is necessary to have detailed information on the location 

of emission sources, geographical variability of ambient pollutant concentrations, meteorological 

conditions and population density. Therefore, selection of the number, locations and types of sampling 

stations is a complex process. The variability of sources and their intensities of emissions, terrains, 

meteorological conditions and demographic features require that each network be developed individually. 

Thus, selection of the network will be based upon the best available evidence and on the experience of the 

decision team. 

The sampling site selection process involves considerations of the following factors: 

Economics - The amount of resources required for the entire data collection activity, including operators, 

instrumentation, installation, safety equipment, maintenance, data retrieval/data transfer, data analysis, 

quality assurance and data interpretation. 

Security - Experience has shown that in some cases, a particular site may not be appropriate for the 

establishment of an ambient monitoring station simply due to problems with the security of the equipment 

in a certain area. If the problems cannot be remedied via the use of standard security measures such as 

lighting, fences, etc., then attempts should be made to locate the site as near to the identified sector as 

possible while maintaining adequate security. 

Logistics - Logistics is the process of dealing with the procurement, maintenance and transportation of 

material and personnel for a monitoring operation. This process requires the full knowledge of all aspects 

of the data collection operation including: 

Planning Staffing 

Reconnaissance Procurement of goods and services 

Training Communications 

Scheduling Inventory 

Safety

Atmospheric considerations - Atmospheric considerations may include the spatial and temporal 

variability of the pollutants and its transport to the monitoring site. Effects of buildings, terrain, and heat 

sources or sinks on the air trajectories can produce local anomalies of excessive pollutant concentrations. 

Meteorology must be considered in determining not only the geographical location of a monitoring site 

but also such factors as height, direction, and extension of sampling probes. The following 

meteorological factors can greatly influence the dispersal of pollutants: 
 QA Handbook Vol II, Section 6.0 

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Wind speed affects the travel time from the pollutant source to the receptor and the dilution of 

polluted air in the downwind direction. The concentrations of air pollutants are inversely 

proportional to the wind speed. 

Wind direction influences the general movements of pollutants in the atmosphere. Review of 

available data can indicate mean wind direction in the vicinity of the major sources of emissions.

Wind variability refers to the random motions in both horizontal and vertical velocity components 

of the wind. These random motions can be considered atmospheric turbulence, which is either 

mechanical (caused by structures and changes in terrain) or thermal (caused by heating and 

cooling of land masses or bodies of water). If the scale of turbulent motion is larger than the size 

of the pollutant plume, the turbulence will move the entire plume and cause looping and fanning; 

if smaller, it will cause the plume to diffuse and spread out. 

If the meteorological phenomena impact with some regularity, data may need to be interpreted in light of 

these atmospheric conditions. Other meteorological conditions to consider are atmospheric stability and 

lapse rate (the decrease of an atmospheric variable with height). 

A useful way of displaying wind data is a wind rose 

diagram constructed to show the distribution of wind 

speeds and directions. The wind rose diagram 

shown in Figure 6.1 represents conditions as they 

converge on the center from each direction of the 

compass. More detailed guidance for 

meteorological considerations is available9

. 

Relevant weather information, such as stability-wind 

roses, is usually available from local National 

Weather Service stations. For PAMS monitoring, in 

many areas there are three types of high ozone days: 

overwhelming transport, weak transport (or mixed 

transport and stagnation) and stagnation. The wind 

rose concept to site monitors is only applicable to 

the transport types, but not applicable to the 

stagnation type. In general, transport types 

dominate north of 40o N, stagnation types dominate 

the Ohio River Valley and northern Gulf Coast, and 

a mixture of the two is observed in the rest of the eastern United States. In areas where stagnation 

dominates the high ozone days, a well-defined primary wind direction (PWD) may not be available. If no 

well-defined PWD can be resolved, the major axes of the emissions sources should be used as substitutes 

for the PWDs and the PAMS monitors should be located along these axes. 

Meteorological conditions, particularly those that can affect light transmission, should also be considered 

in selecting the location for open path analyzers (e.g., the influence of relative humidity on the creation of 

fog, the percentage of heavy snow, and the possible formation of haze, etc.). The percent fog, percent 

snow fall, percent haze, and hourly visibility (from nearest airport) may impact data completeness. 

Although sites with high relative humidity may have data capture rates around 90 percent, sites with 

relative humidity greater than 80 percent more than 20 percent of the time should be carefully assessed 

 

9

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for data completeness, or avoided. Similarly, severe fog, snow fall, or haze that affects visibility can 

affect data completeness and should be kept to less than 20 percent of the time. The time of day or season 

when such conditions occur should also be determined to ensure that representative data from various 

time periods and seasons are collected. No more than 20 percent of data in any time period should be lost 

as a result of the aforementioned meteorological conditions. Sometimes, high data capture at locations 

with frequent fog or other obscurant conditions can be enhanced by using a shorter path length of 

50 to 100 meters. However, this can be done only for microscale sites. Meteorological data 

considerations therefore should include the following measurements: (1) hourly precipitation amounts for 

climatological comparisons, (2) hourly relative humidity, (3) percent haze, and (4) airport visibility. 

Topography - Both the transport and the diffusion of air pollutants are complicated by topographical 

features. Minor topographical features may exert small influences; major features, such as deep river 

valleys or mountain ranges, may affect large areas. Before final site selection, review the topography of 

the area to ensure that the purpose of monitoring at that site will not be adversely affected. Table 6-3 

summarizes important topographical features, their effects on air flow, and some examples of influences 

on monitoring site selection. Land use and topographical characterization of specific areas can be 

determined from U.S. Geological Survey (USGS) maps as well as from land use maps. 

Table 6-3 Relationships of Topography, Air Flow, and Monitoring Site Selection 

Topographical 

feature Influence on air flow Influence on monitoring site selection

Slope/Valley 

Downward air currents at night and on cold 

days; up slope winds on clear days when 

valley heating occurs. Slope winds and 

valley channeled winds; tendency toward 

down-slope and down-valley winds; 

tendency toward inversions 

Slopes and valleys as special sites for air monitors 

because pollutants generally are well dispersed; 

concentration levels not representative of other 

geographic areas; possible placement of monitor to 

determine concentration levels in a population or 

industrial center in valley 

Water 

Sea or lake breezes inland or parallel to 

shoreline during the day or in cold weather; 

land breezes at night. 

Monitors on shorelines generally for background readings 

or for obtaining pollution data on water traffic 

Hill 

Sharp ridges causing turbulence; air flow 

around obstructions during stable 

conditions, but over obstructions during 

unstable conditions 

Depends on source orientation; upwind source emissions 

generally mixed down the slope, and siting at foot of hill 

not generally advantageous; downwind source emissions 

generally down washed near the source; monitoring close 

to a source generally desirable if population centers 

adjacent or if monitoring protects workers 

Natural or manmade 

obstruction Eddy effects Placement near obstructions not generally representative in readings 

Pollutant Considerations - A sampling site or an array of sites for one pollutant may be appropriate for 

another pollutant species because of the configuration of sources, the local meteorology, or the terrain. 

Pollutants undergo changes in their compositions between their emission and their detection; therefore, 

the impact of that change on the measuring system should be considered. Atmospheric chemical 

reactions such as the production of O3 in the presence of NOx and hydrocarbons (HCs) and the time delay 

between the emission of NOx and HCs and the detection peak of O3 values may require either a sampling 

network for the precursors of O3 and/or a different network for the actual O3 measurement. 

The success of the PAMS monitoring program is predicated on the fact that no site is unduly influenced 

by any one stationary emissions source or small group of emissions sources. Any significant influences 

would cause the ambient levels measured by that particular site to mimic the emissions rates of this 

source or sources rather than following the changes in nonattainment area-wide emissions as intended by 

the Rule. For purposes of this screening procedure, if more than 10% of the typical “lower end” 
 QA Handbook Vol II, Section 6.0 

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concentration measured in an urban area is due to a nearby source of precursor emissions, then the PAMS 

site should be relocated or a more refined analysis conducted than is presented here. Detailed procedures 

can be found in the PAMS Implementation Manual10. 

None of the factors mentioned above stand alone. Each is dependent in part on the others. However, the 

objective of the sampling program must be clearly defined before the selection process can be initiated, 

and the initial definition of priorities may have to be reevaluated after consideration of the remaining 

factors before the final site selection. While the interactions of the factors are complex, the site selection 

problems can be resolved. Experience in the operation of air quality measurement systems; estimates of 

air quality, field and theoretical studies of air diffusion; and considerations of atmospheric chemistry and 

air pollution effects make up the required expertise needed to select the optimum sampling site for 

obtaining data representative of the monitoring objectives. 

6.2.1 PAMS Site Descriptions 

The PAMS network array for an area should be fashioned to supply measurements that will assist States 

in understanding and solving ozone nonattainment problems. Table 6-4 describes the five site types 

identified in the PAMS network. In 2007, EPA determined that the number of required PAMS sites could 

be reduced. Only one Type 2 site is required per area regardless of population; Type 4 sites would not be 

required; and only one Type 1 or one Type 3 site would be required per area. 

Table 6-4 Site Descriptions of PAMS Monitoring Sites 

Type # Meas. Scale Description 

1 Urban

Upwind and background characterization to identify those areas which are subjected to 

overwhelming incoming transport of ozone. The #1 Sites are located in the predominant morning 

upwind direction from the local area of maximum precursor emissions and at a distance sufficient to 

obtain urban scale measurements. Typically, these sites will be located near the upwind edge of the 

photochemical grid model domain.

2 Neighborhood

Maximum ozone precursor emissions impacts located immediately downwind (using the same 

morning wind direction as for locating Site #1) of the area of maximum precursor emissions and are 

typically placed near the downwind boundary of the central business district (CBD) or primary area 

of precursor emissions mix to obtain neighborhood scale measurements.

2a Neighborhood Maximum ozone precursor emissions impacts -second-most predominant morning wind 

direction 

3 Urban

Maximum ozone concentrations occurring downwind from the area of maximum precursor 

emissions. Locations for #3 Sites should be chosen so that urban scale measurements are obtained. 

Typically, these sites are located 10 to 30 miles from the fringe of the urban area

4 Urban

Extreme downwind monitoring of transported ozone and its precursor concentrations exiting the 

area and will identify those areas which are potentially contributing to overwhelming ozone transport 

into other areas. The #4 Sites are located in the predominant afternoon downwind direction from the 

local area of maximum precursor emissions at a distance sufficient to obtain urban scale 

measurements. Typically, these sites will be located near the downwind edge of the photochemical 

grid model domain.

There are three fundamental criteria to consider when locating a final PAMS site: sector analysis, 

distance, and proximate sources. These three criteria are considered carefully by EPA when approving or 

disapproving a candidate site for PAMS. 

 

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6.3 Monitor Placement

Final placement of the monitor at a selected site depends on physical obstructions and activities in the 

immediate area, accessibility/availability of utilities and other support facilities in correlation with the 

defined purpose of the specific monitor and its design. Because obstructions such as trees and fences can 

significantly alter the air flow, monitors should be placed away from obstructions. It is important for air 

flow around the monitor to be representative of the general air flow in the area to prevent sampling bias. 

Detailed information on urban physiography (e.g., buildings, street dimensions) can be determined 

through visual observations, aerial photography and surveys. Such information can be important in 

determining the exact locations of pollutant sources in and around the prospective monitoring site areas. 

Network designers should avoid sampling locations that are unduly influenced by down wash or ground 

dust (e.g., a rooftop air inlet near a stack or a ground-level inlet near an unpaved road); in these cases, the 

sample intake should either be elevated above the level of the maximum ground turbulence effect or 

placed at a reasonable distance from the source of ground dust. 

Depending on the defined monitoring objective, the monitors are placed according to exposure to 

pollution. Due to the various physical and meteorological constraints discussed above, tradeoffs will be 

made to locate a site in order to optimize representativeness of sample collection. The consideration 

should include categorization of sites relative to their local placements. Suggested categories relating to 

sample site placement for measuring a corresponding pollution impact are identified in Table 6-5. 

Table 6-5 Monitoring Station Categories Relating to Sample Site Placement 

Station Category Characterization

A (ground level) 

Heavy pollutant concentrations, high potential for pollutant buildup. A site 3 to 5 m (10-16 ft) from 

major traffic artery and that has local terrain features restricting ventilation. A sampler probe that is 

3 to 6 m (10-20 ft) above ground. 

B (ground level) 

Heavy pollutant concentrations, minimal potential for a pollutant buildup. A site 3 to 15 m 

(15-50 ft) from a major traffic artery, with good natural ventilation. A sampler probe that is 3 to 

6 m (10-20 ft) above ground. 

C (ground level) Moderate pollutant concentrations. A site 15 to 60 m (5-200 ft) from a major traffic artery. A 

sampler probe that is 3 to 6 m (10-20 ft ) above ground. 

D (ground level) Low pollutant concentrations. A site 60 > m (>200 ft) for a traffic artery. A sampler probe that is 

3 to 6 m (10-20 ft) above ground. 

E (air mass) 

Sampler probe that is between 6 and 45 m (20-150 ft) above ground. Two subclasses: (1) good 

exposure from all sides (e.g., on top of building) or (2) directionally biased exposure (probe 

extended from window). 

F (source-oriented) A sampler that is adjacent to a point source. Monitoring that yields data directly relatable to the 

emission source.

6.4 Minimum Network Requirements

In 2007, the minimum network site requirements for the criteria pollutants CO, NO2 and SO2 were 

removed. Where SLAMS monitoring for these three criteria pollutants are ongoing, at least one site must 

be a maximum concentration sites for that area under investigation. Rather than place tables for minimum 

monitoring site requirements in the Handbook (since they have a tendency to change), the reader is 

directed to 40 CFR Part 58, Appendix D11 of the most current regulation to find the appropriate minimum 

monitoring network requirements. 

 

11 http://www.gpoaccess.gov/cfr/index.html or http://www.epa.gov/ttn/amtic/40cfr53.html
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6.5 Operating Schedules 

NOTE: The reader should check the most current version of 40 CFR Part 58 to ensure the 

schedules below have not changed. 

For continuous analyzers, consecutive hourly averages must be collected except during: 

1. periods of routine maintenance; 

2. periods of instrument calibration; or 

3. periods or monitoring seasons exempted by the Regional Administrator. 

For Pb manual methods, at least one 24-hour sample must be collected every 6 days except during 

periods or seasons exempted by the Regional Administrator. 

For PAMS VOC samplers, samples must be collected as specified in 40 CFR Part 58, Appendix D 

Section 5. Area specific PAMS operating schedules must be included as part of the PAMS network 

description and must be approved by the Regional Administrator. 

For manual PM2.5 samplers: 

1. Manual PM2.5 samplers at SLAMS stations other than NCore stations must operate on at least a 

1-in-3 day schedule at sites without a collocated continuously operating PM2.5 monitor. For 

SLAMS PM2.5 sites with both manual and continuous PM2.5 monitors operating, the monitoring 

agency may request approval for a reduction to 1-in-6 day PM2.5 sampling at SLAMS stations or 

for seasonal sampling from the EPA Regional Administrator. The EPA Regional Administrator 

may grant sampling frequency reductions after consideration of factors, including but not limited 

to the historical PM2.5 data quality assessments, the location of current PM2.5 design value sites, 

and their regulatory data needs. Sites that have design values that are within plus or minus 10 

percent of the NAAQS; and sites where the 24-hour values exceed the NAAQS for a period of 3 

years are required to maintain at least a 1-in-3 day sampling frequency. Sites that have a design 

value within plus or minus 5 percent of the daily PM2.5 NAAQS must have an FRM or FEM 

operate on a daily schedule. The national sampling schedule can be found on AMTIC12. 

2. Manual PM2.5 samplers at NCore stations and required regional background and regional 

transport sites must operate on at least a 1-in-3 day sampling frequency. 

3. Manual PM2.5 speciation samplers at STN stations must operate on a 1-in-3 day sampling 

frequency. 

For PM10 samplers, a 24-hour sample must be taken from midnight to midnight (local time) to ensure 

national consistency. The minimum monitoring schedule for the site in the area of expected maximum 

concentration shall be based on the relative level of that monitoring site concentration with respect to the 

24-hour standard as illustrated in Figure 6.2. If the operating agency demonstrates by monitoring data 

that during certain periods of the year conditions preclude violation of the PM10 24-hour standard, the 

increased sampling frequency for those periods or seasons may be exempted by the Regional 

Administrator and permitted to revert back to once in six days. The minimum sampling schedule for all 

other sites in the area remains once every six days. 

 

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Figure 6.2 Sampling schedule based on ratio to the 24-hour PM10 NAAQS

For manual PM10–2.5 samplers: 

1. Manual PM10–2.5 samplers at NCore stations must operate on at least a 1-in-3 day schedule at 

sites without a collocated continuously operating federal equivalent PM10–2.5 method that has been 

designated in accordance with 40 CFR Part 53. 

2. Manual PM10–2.5 speciation samplers at NCore stations must operate on at least a 1-in-3 day 

sampling frequency. 

For NATTS Monitoring, samplers must operate year round and follow the national 1-in-6 day sampling 

schedule. 

6.5.1 Operating Schedule Completeness 

Data required for comparison to the NAAQS have specific completeness requirements. These 

completeness requirements generally start from completeness at hourly and 24-hour concentration values. 

However, the data used for NAAQS determinations include 3-hour, 8-hour, quarterly, annual and multiple 

year levels of data aggregation. Generally, depending on the calculation of the design value, EPA requires 

data to be 75% complete. All continuous measurements come down to what is considered a valid hour 

and currently all 24-hour estimates based on sampling (manual PM, Pb, TSP) are based on a 24-hour 

sampling period. Table 6-6 provides the completeness goals for the various ambient air program 

monitoring programs. 

The data cells highlighted in Table 6-6 refer to the standards that apply to the specific pollutant. Even 

though a highlighted cell lists the completeness requirement, CFR provides additional detail, in some 

cases, on how a design value might be calculated with less data than the stated requirement. Therefore, 

the information provided in Table 6-6 should be considered the initial completeness goal which should be 

attempted to be achieved. Completeness goals that are not highlighted, although not covered in CFR, are 

very important to the achievement of the CFR completeness goals. So, for example, even though there is 

only an 8-hour ozone standard, it’s important to have complete 1-hour values in order to compare to the 

8-hour standard. 
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Table 6-6 Completeness Goals for Ambient Air Monitoring Data 

Completeness Goals and Associated Standards (highlighted) 

Pollutants 1-hour 3-hour 8-hour 24-hour Quarterly Annual 

CO 45, 1 min. values 75% of 

hourly values 

75% of hourly 

values 

 75% of hourly 

values per quarter 

O3 45, 1 min. values 75% of 

hourly values 

 

SO2 45, 1 min. values All 3 hours 

75% 

complete 

75% of hourly 

values 

75% of hourly 

values per quarter 

NO2 45, 1 min. values 75% of hourly 

values per quarter 

PM10 Cont 45, 1 min. values 23 hours** 

PM2.5 Cont. 45, 1 min. values 23 hours 

PM10

Manual 

 23 Hours** 

PM2.5

Manual 

 23 hours 75% of 

samples 

Pb 23 Hours 75% of 

samples** 

PAMS 23 Hours 

NATTS 23 Hours 

STN 23 Hours 

** not defined in CFR 

For continuous instruments, it is suggested that 45, 1-minute values be considered a valid hour. Therefore, 

it is expected that 1-minute concentration values would be archived for a period of time (see statute of 

limitations in Section 5). Since various QC checks take time to complete, (zero/span/1-point QC) it is 

suggested that they be implemented in a manner that spans two hours (e.g., at 11:45 PM to 12:15 AM) in 

order to avoid losing an hour’s worth of data. 

6.5.2 Monitoring Seasons 

Most of the monitoring networks operate year round with the exception of PAMS and ozone monitoring. 

PAMS - 40 CFR 58, Appendix D10 stipulates that PAMS precursor monitoring must be conducted 

annually throughout the months of June, July and August (as a minimum) when peak O3 values are 

expected in each area. Alternate precursor monitoring periods may be submitted for approval to the 

Administrator as a part of the annual monitoring network plan. 

Ozone - Since O3 levels decrease significantly in the colder parts of the year in many areas, O3 is required 

to be monitored at SLAMS monitoring sites only during the ‘‘ozone season’’ as designated in the AQS 

files on a State-by-State basis and described in 40 CFR Part 58, Appendix D13. Deviations from the O3

monitoring season must be approved by the EPA Regional Administrator, documented within the annual 

monitoring network plan, and updated in AQS. 

 

13 http://www.gpoaccess.gov/cfr/index.html 
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7.0 Sampling Methods 

To establish the basic validity of ambient air monitoring data, it must be shown that: 

• the proposed sampling method complies with the appropriate monitoring regulations; 

• the equipment is accurately sited; 

• the equipment was accurately calibrated using correct and established calibration methods; and 

• the organization implementing the data collection operation are qualified and competent. 

For example, if the only reasonable monitoring site has a less than ideal location, the data collection 

organization must decide whether a representative sample can be obtained at the site. This determination 

should be recorded and included in the program's QAPP. Although after-the-fact site analysis may 

suffice in some instances, good quality assurance techniques dictate that this analysis be made prior to 

expending the resources required to collect the data. 

The purpose of this section is to describe the attributes of the sampling system that will ensure the 

collection of data of a quality acceptable for the Ambient Air Quality Monitoring Program. 

7.1 Environmental Control

7.1.1 Monitoring Station Design

State and local agencies should design their monitoring stations with the station operator in mind. Careful 

thought to safety, ease of access to instruments and optimal work space should be given every 

consideration. If the station operator has these issues addressed, then he/she will be able to perform their 

duties more efficiently and diligently. Having the instruments in an area that is difficult to work in creates 

frustration and prolongs downtime. The goal is to optimize data collection and quality. This must start 

with designing the shelter and laboratory around staff needs and requirements. 

Monitoring stations may be located in urban areas where space and land are at a premium, especially in 

large cities that are monitoring for NOx and CO. In many cases, the monitoring station is located in a 

building or school that is gracious enough to allow an agency to locate its equipment. Sometimes, a storage 

or janitorial closet is all that is available. However, this can pose serious problems. If the equipment is 

located in a closet, then it is difficult for the agency to control the effects of temperature, humidity, light, 

vibration and chemicals on the instruments. In addition, security can also be an issue if people other than 

agency staff have access to the equipment. Monitoring organizations should give serious thought to 

locating air monitoring equipment in stand-alone shelters with limited access, or modify existing rooms to 

the recommended station design if funds and staff time are available. 

In general, air monitoring stations should be designed for functionality and ease of access for operation, 

maintenance and repair. In addition, the shelter should be rugged enough to withstand local weather 

condition extremes. In the past, small utility trailers were the norm in monitoring shelters. However, in 

some areas, this will not suffice. Recently, steel and aluminum storage containers are gaining wide 

acceptance as monitoring shelters. It is recommended that monitoring stations be housed in shelters that 

are fairly secure from intrusion or vandalism. All sites should be located in fenced or secure areas with 

access only through locked gates or secure pathways. The shelter’s design dictates that they be insulated 

(R-19 minimum) to prevent temperature extremes within the shelter. All structures should be secured to 

their foundations and protected from damage during natural disasters. All monitoring shelters should be 
QA Handbook Volume II, Section 7.0 

Revision No: 1 

Date: 12/08 

Page 2 of 14 

designed to control excessive vibrations and external light falling on the instruments, and provide 110/220 

VAC voltage throughout the year. When designing a monitoring shelter, make sure that enough electrical 

circuits are secured for the current load of equipment plus other instruments that may be added later or 

audit equipment (e.g., NPAP/PEP). Every attempt should be made to reduce the environmental footprint of 

shelters to make them as energy efficient as possible. Some possibilities include venting of excess heat of 

monitoring instruments to the outside in summer months, use of energy efficient fixtures and HVAC 

systems, and ensuring that the amount of space devoted to the monitors is not excessive (remembering that 

space is needed at times for additional QA equipment). Figure 7.1 represents one shelter design that has 

proven adequate. 

The first feature of the shelter is that there are two rooms separated by a door. The reasons for this are twofold. The entry and access should be into the computer/data review area. This allows access to the site 

without having to open the room that houses the equipment. It also isolates the equipment from cold/hot air 

that can come into the shelter when someone enters. Also, the Data Acquisition System (DAS)/data review 

area is isolated from the noise and vibration of the equipment. This area can be a place where the operator 

can print data, and prepare samples for the laboratory. This also gives the operator an area where cursory 

data review can take place. If something is observed during this initial review then possible problems can 

be corrected or investigated at that time. The DAS can be linked through cables that travel through conduit 

into the equipment area. The conduit is attached to the ceiling or walls and then dropped down to the 

instrument rack. 

 

The air conditioning/heating unit 

should be mounted to heat and cool 

the equipment room. When 

specifying the unit, make sure it will 

cool the room on the warmest and 

heat on the coldest days of the year. 

Also, make sure the electrical circuits 

are able to carry the load. If 

necessary, keep the door closed 

between the computer and equipment 

room to lessen the load on the heating 

or cooling equipment. 

All air quality instrumentation should 

be located in an instrument rack or 

equivalent. The instruments and their 

support equipment are placed on 

sliding trays or rails. By placing the 

racks away from the wall, the rear of the instruments are accessible. The trays or rails allow the site 

operators access to the instruments without removing them from the racks. Most instrument vendors offer 

sliding rails as an optional purchase. 

7.1.2 Sampling Environment

A proper sampling environment demands control of all physical parameters external to the samples that 

might affect sample stability, chemical reactions within the sampler, or the function of sampler 

components. The important parameters to be controlled are summarized in Table 7-1.

Figure 7.1 Example Design for Shelter
QA Handbook Volume II, Section 7.0 

Revision No: 1 

Date: 12/08 

Page 3 of 14 

Table 7-1 Environment Control Parameters

Parameter Source of specification Method of Control

Instrument vibration Manufacturer’s specifications Design of instrument housings, benches, etc., per 

manufacturer’s specifications. 

Light Method description or 

manufacturer’s specifications 

Shield chemicals or instruments that can be affected by 

natural or artificial light 

Electrical voltage Method description or 

manufacturer’s specifications 

Constant voltage transformers or regulators; separate 

power lines; isolated high current drain equipment such 

as hi-vols, heating baths, pumps from regulated circuits 

Temperature Method description or 

manufacturer’s specifications 

Regulated air conditioning system 24-hour temperature 

recorder; use electric heating and cooling only 

Humidity Method description or 

manufacturer’s specifications 

Regulated air conditioning system; 24-hour 

temperature recorder

With respect to environmental temperature for designated analyzers, most such analyzers have been tested 

and qualified over a temperature range of 20o

C to 30oC; few are qualified over a wider range. This 

temperature range specifies both the range of acceptable operating temperatures and the range of 

temperature change which the analyzer can accommodate without excessive drift. The latter, the range of 

temperature change that may occur between zero and span adjustments, is the most important. When one 

is outfitting a shelter with monitoring equipment, it is important to recognize and accommodate the 

instrument with the most sensitive temperature requirement. 

To accommodate energy conservation regulations or guidelines specifying lower thermostat settings, 

designated analyzers located in facilities subject to these restrictions may be operated at temperatures 

down to 18o

C, provided the analyzer temperature does not fluctuate by more than 10oC between zero and 

span adjustments. Operators should be alert to situations where environmental temperatures might fall 

below 18o

C, such as during night hours or weekends. Temperatures below 18oC may necessitate 

additional temperature control equipment or rejection of the area as a sampling site. 

Shelter temperatures above 30o

C also occur, due to temperature control equipment that is malfunctioning, 

lack of adequate power capacity, or shelters of inadequate design for the environmental conditions. 

Occasional fluctuations above 30o

C may require additional assurances that data quality is maintained. 

Sites that continually have problems maintaining adequate temperatures may necessitate additional 

temperature control equipment or rejection of the area as a sampling site. If this is not an option, a waiver 

to operate beyond the required temperature range should be sought with the EPA Regional Office, if it 

can be shown that the site can meet established data quality requirements. 

In order to detect and correct temperature fluctuations, a 24-hour temperature recorder at the analyzer site 

is suggested. These recorders can be connected to data loggers and should be considered official 

documentation that should be filed (see Section 5). Many vendors offer these type of devices. Usually 

they are thermocouple/thermistor devices of simple design and are generally very sturdy. Reasons for 

using electronic shelter temperature devices are two-fold: 1) through remote interrogation of the DAS, 

the agency can tell if values collected by air quality instruments are valid, and 2) that the shelter 

temperature is within a safe operating range if the air conditioning/heating system fails. 
QA Handbook Volume II, Section 7.0 

Revision No: 1 

Date: 12/08 

Page 4 of 14 

7.2 Sampling Probes And Manifolds

7.2.1 Design of Probes and Manifolds for Automated Methods

Some important variables affecting the sampling manifold design are the diameter, length, flow rate, 

pressure drop, and materials of construction. With the development of NCore precursor gas monitoring, 

various types of probe/manifold designs were reviewed. This information can be found in the Technical 

Assistance Document (TAD) for Precursor Gas Measurements in the NCore Multi-pollutant Monitoring 

Network1 and is also included in Appendix F of this Handbook.

 

1 http://www.epa.gov/ttn/amtic/files/ambient/monitorstrat/precursor/tadversion4.pdf 

Of the probe and manifold material looked at over the years, only Pyrex® glass and Teflon® have been 

found to be acceptable for use as intake sampling lines for all the reactive gaseous pollutants. 

Furthermore, the EPA has specified borosilicate glass or FEP Teflon® as the only acceptable probe 

materials for delivering test atmospheres in the determination of reference or equivalent methods. 

Therefore, borosilicate glass (which includes Pyrex®), FEP Teflon® or their equivalent must be the only 

material in the sampling train (from inlet probe to the back of the analyzer) that can be in contact with the 

ambient air sample for existing and new SLAMS. 

For volatile organic compound (VOC) monitoring at PAMS, FEP Teflon® is unacceptable as the probe 

material because of VOC adsorption and desorption reactions on the FEP Teflon®. Borosilicate glass, 

stainless steel, or its equivalent, are the acceptable probe materials for VOC and carbonyl sampling. Care 

must be taken to ensure that the sample residence time is kept to 20 seconds or less. 

Residence Time Determination

No matter how nonreactive the sampling probe material may be, after a period of use, reactive particulate 

matter is deposited on the probe walls. Therefore, the time it takes the gas to transfer from the probe inlet 

to the sampling device is also critical. Ozone, in the presence of nitrogen oxide (NO), will show 

significant losses even in the most inert probe material when the residence time exceeds 20 seconds. 

Other studies indicate that a 10-second or less residence time is easily achievable. 

Residence time is defined as the amount of time that it takes for a sample of air to travel from the opening 

of the cane to the inlet of the instrument and is required to be less than 20 seconds for reactive gas 

monitors. The residence time of pollutants within the sampling manifold is also critical. It is 

recommended that the residence time within the manifold and sample lines to the instruments be less than 

10 seconds (of the total allowable 20 seconds). If the volume of the manifold does not allow this to occur, 

then a blower motor or other device (vacuum pump) can be used to decrease the residence time. The 

residence time for a manifold system is determined in the following way. First the volume of the cane, 

manifold and sample lines must be determined using the following equation: 

 Total Volume = Cv +Mv + Lv 

Where: 

Cv = Volume of the sample cane and extensions, cm3

Mv = Volume of the sample manifold and trap, cm3
QA Handbook Volume II, Section 7.0 

Revision No: 1 

Date: 12/08 

Page 5 of 14 

Lv = Volume of the instrument lines, cm3

Each of the components of the sampling system must be measured individually. To measure the volume 

of the components, use the following calculation: 

 V = pi * (d/2)2

 * L 

Where: 

V = volume of the component, cm3

pi = 3.14159 

L = Length of the component, cm 

d = inside diameter, cm 

Once the total volume is determined, divide the volume by the flow rate of all instruments. This will give 

the residence time. 

It has been demonstrated that there are no significant losses of reactive gas (O3) concentrations in 

conventional 13 mm inside diameter sampling lines of glass or Teflon if the sample residence time is 10 

seconds or less. This is true even in sample lines up to 38 m in length, which collect substantial amounts 

of visible contamination due to ambient aerosols. However, when the sample residence time exceeds 20 

seconds, loss is detectable, and at 60 seconds the loss is nearly complete. 

Placement of tubing on the Manifold: If the manifold that 

is employed at the station has multiple ports then placement 

of the instrument lines can be crucial. If a manifold similar 

to Figure 7.2 is used, it is suggested that instruments 

requiring lower flows be placed towards the bottom of the 

manifold. The general rule of thumb states that the 

calibration line (if used) placement should be in a location 

so that the calibration gases flow past the instruments before 

the gas is evacuated out of the manifold. Figure 7.2 

illustrates two potential introduction ports for the calibration 

gas. The port at the elbow of the sampling cane provides 

more information about the cleanliness of the sampling 

system. 

7.2.2 Placement of Probes and Manifolds 

Probes and manifolds must be placed to avoid introducing 

bias to the sample. Important considerations are probe 

height above the ground, probe length (for horizontal

Figure 7.2 Positions probes), and physical influences near the probe. of calibration line in 

sampling manifold

Pump

Analyzer 

 Calibrator

 Gas

Excess Cal. Gas

Analyzer

Analyzer
QA Handbook Volume II, Section 7.0 

Revision No: 1 

Date: 12/08 

Page 6 of 14 

Some general guidelines for probe and manifold placement are: 

• probes should not be placed next to air outlets such as exhaust fan openings 

• horizontal probes must extend beyond building overhangs 

• probes should not be near physical obstructions such as chimneys which can affect the air flow in 

the vicinity of the probe 

• height of the probe above the ground depends on the pollutant being measured 

Table 7-2 summarizes the probe and monitoring path siting criteria while Table 7-3 summarizes the 

spacing of probes from roadways. This information can be found in 40 CFR Part 58, Appendix E2

. For 

PM10 and PM2.5, Figure 7.3 provides the acceptable areas for micro, middle, neighborhood and urban 

samplers, with the exception of microscale street canyon sites. 

Table 7-2 Summary of Probe and Monitoring Path Siting Criteria 

Pollutant Scale (maximum 

monitoring path 

length, meters) 

Height from 

ground to probe, 

inlet or 80% of 

monitoring path 1 

(meters) 

Horizontal and 

vertical distance 

from supporting 

structures2

 to 

probe, inlet or 

90% of monitoring 

path1

 (meters) 

Distance from 

trees to probe, 

inlet or 90% of 

monitoring 

path1 (meters) 

Distance from 

roadways to probe, 

inlet or monitoring 

path1 (meters) 

SO2 3,4,5,6 Middle (300 m) 

Neighborhood Urban, 

and Regional (1 km). 

2–15 > 1 > 10 N/A 

CO 4,5,7 Micro, Middle (300 

m), Neighborhood (1 

km). 

3 +1⁄2: 2–15 > 1 > 10 2–10; see Table 7–3 of 

this section for middle 

and neighborhood scales. 

NO2, O3 3,4,5 Middle (300 m) 

Neighborhood, Urban, 

and Regional (1 km). 

2–15 > 1 > 10 See Table 7-3 of this 

section for all scales. 

Ozone 

precursors 

(for 

PAMS) 3,4,5.

Neighborhood and 

Urban (1 km) 

2–15 > 1 > 10 

PM,Pb 

3,4,5,6,8

Micro: Middle, 

Neighborhood, 

Urban and Regional. 

2–7 (micro); 

2–7 (middle PM10-2.5); 

2–15 (all other scales). 

> 2 (all scales, 

horizontal distance 

only). 

> 10 (all scales). 2–10 (micro); see Figure 

7.3 of this section for all 

other scales 

N/A—Not applicable. 

1

 Monitoring path for open path analyzers is applicable only to middle or neighborhood scale CO monitoring and all applicable scales for 

monitoring SO2,O3, O3 precursors, and NO2. 2

 When probe is located on a rooftop, this separation distance is in reference to walls, parapets, or penthouses located on roof. 3

 Should be >20 meters from the dripline of tree(s) and must be 10 meters from the dripline when the tree(s) act as an obstruction. 4 Distance from sampler, probe, or 90% of monitoring path to obstacle, such as a building, must be at least twice the height the obstacle protrudes 

above the sampler, probe, or monitoring path. Sites not meeting this criterion may be classified as middle scale (see text). 5 Must have unrestricted airflow 270 degrees around the probe or sampler; 180 degrees if the probe is on the side of a building. 6 The probe, sampler, or monitoring path should be away from minor sources, such as furnace or incineration flues. The separation distance is 

dependent on the height of the minor source’s emission point (such as a flue), the type of fuel or waste burned, and the quality of the fuel (sulfur, 

ash, or lead content). This criterion is designed to avoid undue influences from minor sources. 7 For microscale CO monitoring sites, the probe must be >10 meters from a street intersection and preferably at a midblock location. 8

 Collocated monitors must be within 4 meters of each other and at least 2 meters apart for flow rates 

 

2 http://www.access.gpo.gov/nara/cfr/cfr-table-search.html 
QA Handbook Volume II, Section 7.0 

Revision No: 1 

Date: 12/08 

Page 7 of 14 

Table 7-3 Minimum Separation Distance Between Roadways and Sampling Probes or Monitoring 

 Paths at Neighborhood and Urban Scales for O3 , Oxides of Nitrogen (NO, NO2, NOx, NOy) and CO 

Roadway ave. daily 

traffic vehicles per 

day

O3 and Oxides of N 

Neighborhood 

& Urban 1

O3 and Oxides of N 

Neighborhood. 

& Urban 1& 2

CO 

Neighborhood 

< 1,000 10 10 

10,000 10 20 

< 10,000 10 

15,000 20 30 25 

20,000 30 40 45 

30,000 80 

40,000 50 60 115 

50,000 135 

> 60,000 150 

70,000 100 100 

>110,000 250 250 1

 Distance from the edge of the nearest traffic lane. The distance for intermediate traffic counts should be interpolated 

from the table values based on the actual traffic count. 

2

 Applicable for ozone monitors whose placement has not already been approved as of December 18, 2006.

Figure 7.3 Acceptable areas for PM10 and PM2.5 micro, middle, neighborhood, and urban samplers except for 

microscale street canyon sites

0 20 40 60 80 100 120 140 160

0

20

40

60

80

100

Distance of PM10 and PM2.5 Samplers from Nearest Traffic Lane, (meters)

A

D

T

of Affe

ctin

g

R

o

a

d

s

x 10

No

Ca et gory

(a) Sites

Unacceptable at all traffic levels

Preferred area for category (a) site microscale if

monitor is 2 - 7 meters high, middle scale otherwise

 Middle Scale Suitable for

Category (a) site but not preferred

Neighborhood Scale Suitable

 for category (b) Site

Urban Scale

3
QA Handbook Volume II, Section 7.0 

Revision No: 1 

Date: 12/08 

Page 8 of 14 

Open Path Monitoring

To ensure that open path monitoring data are representative of the intended monitoring objective(s), 

specific path siting criteria are needed. 40 CFR Part 58, Appendix E, contains specific location criteria 

applicable to monitoring paths after the general station siting has been selected based on the monitoring 

objectives, spatial scales of representativeness, and other considerations presented in Appendix D. The 

 new open path siting requirements largely parallel the existing requirements for point analyzers, with the 

revised provisions applicable to either a "probe" (for point analyzers), a "monitoring path" (for open path 

analyzers), or both, as appropriate. Criteria for the monitoring path of an open path analyzer are given 

for horizontal and vertical placement, spacing from minor sources, spacing from obstructions, spacing 

from trees, and spacing from roadways. These criteria are summarized in Table 7-2. 

Cumulative Interferences on a Monitoring Path: To control the sum effect on a path measurement 

from all the possible interferences which exist around the path, the cumulative length or portion of a 

monitoring path that is affected by obstructions, trees, or roadways must not exceed 10 percent of the total 

monitoring path length. This limit for cumulative interferences on the monitoring path controls the total 

amount of interference from minor sources, obstructions, roadways, and other factors that might unduly 

influence the open path monitoring data. 

Monitoring Path Length: For NO2, O3 and SO2, the 

monitoring path length must not exceed 1 kilometer for 

analyzers in neighborhood, urban, or regional scales, or 

300 meters for middle scale monitoring sites. These path 

limitations are necessary in order to produce a path 

concentration representative of the measurement scale 

and to limit the averaging of peak concentration values. 

In addition, the selected path length should be long 

enough to encompass plume meander and expected 

plume width during periods when high concentrations are 

expected. In areas subject to frequent periods of rain, 

snow, fog, or dust, a shortened monitoring path length 

should be considered to minimize the loss of monitoring 

data due to these temporary optical obstructions. 

Mounting of Components and Optical Path 

Alignment: Since movements or instability can misalign 

the optical path, causing a loss of light and less accurate 

measurements or poor readings, highly stable optical 

platforms are critical. Steel buildings and wooden 

platforms should be avoided as they tend to move more 

than brick buildings when wind and temperature 

conditions vary. Metal roofing will, for example, expand 

when heated by the sun in the summer. A concrete pillar 

with a wide base, placed upon a stable base material, has 

been found to work well in field studies. A sketch of an optical platform is included in Figure 7.4. 
QA Handbook Volume II, Section 7.0 

Revision No: 1 

Date: 12/08 

Page 9 of 14 

7.2.3 Probe and Manifold Maintenance

After an adequately designed sampling probe and/or manifold has been selected and installed, the 

following steps will help in maintaining constant sampling conditions: 

1. Conduct a leak test. For the conventional manifold, seal all ports and pump down to 

approximately 1.25 cm water gauge vacuum, as indicated by a vacuum gauge or manometer 

connected to one port. Isolate the system. The vacuum measurement should show no change at 

the end of a 15-min period. 

2. Establish cleaning techniques and a schedule. A large diameter manifold may be cleaned by 

pulling a cloth on a string through it. Otherwise the manifold must be disassembled periodically 

and cleaned with distilled water. Soap, alcohol, or other products that may contain hydrocarbons 

should be avoided when cleaning the sampling train. These products may leave a residue that 

may affect volatile organic measurements. Visible dirt should not be allowed to accumulate. 

3. Plug the ports on the manifold when sampling lines are detached. 

4. Maintain a flow rate in the manifold that is either 3 to 5 times the total sampling requirements or 

at a rate equal the total sampling requirement plus 140 L/min. Either rate will help to reduce the 

sample residence time in the manifold and ensure adequate gas flow to the monitoring 

instruments. 

5. Maintain the vacuum in the manifold <0.64 cm water gauge. Keeping the vacuum low will help 

to prevent the development of leaks. 

7.2.4 Support Services

Most of the support services necessary for the successful operation of ambient air monitoring networks 

can be provided by the laboratory. The major support services are the generation of reagent water and the 

preparation of standard atmospheres for calibration of equipment. Table 7-4 summarizes guidelines for 

quality control of these two support services. 

In addition to the information presented above, the following should be considered when designing a 

sampling manifold: 

• suspending strips of paper in front of the blower's exhaust to permit a visual check of blower 

operation; 

• positioning air conditioner vents away from the manifold to reduce condensation of water vapor 

in the manifold ; 

• positioning sample ports of the manifold toward the ceiling to reduce the potential for 

accumulation of moisture in analyzer sampling lines, and using borosilicate glass, stainless steel, 

or their equivalent for VOC sampling manifolds at PAMS sites is to avoid adsorption and 

desorption reactions of VOC's on FEP Teflon; 

• if moisture in the sample train poses a problem (moisture can absorb gases, namely NOx and 

SO2), wrap the manifold and instrument lines with “heat wrap”, a product that has heating coils 

within a cloth covering that allows the manifold to be maintained at a constant temperature that 

does not increase the sampled air temperature by more than 3-5 degrees C above ambient 

temperature; 

• ensuring the manifold has a moisture trap and that it is emptied often; and 

• using water resistant particulate filters in-line with the instrument. 
QA Handbook Volume II, Section 7.0 

Revision No: 1 

Date: 12/08 

Page 10 of 14 

Table 7-4 Techniques for Quality Control of Support Services

Support Parameters affecting quality Control techniques 

Laboratory and 

calibration gases 

Purity specifications vary among manufacturers 

Variation among lots 

Atmospheric interferences 

Composition 

Develop purchasing guides 

Overlap use of old and new cylinders 

Adopt filtering and drying procedures 

Ensure traceability to primary standard 

Reagents and 

water 

Commercial source variation 

Purity requirements 

Atmospheric interferences 

Generation and storage equipment 

Develop purchasing guides. Batch test for conductivity 

Redistillation, heating, deionization with ion exchange 

columns 

Filtration of exchange air 

Maintenance schedules from manufacturers 

7.3 Reference/Equivalent Methods and Approved Regional Methods

For monitoring in a SLAMS network, either reference or equivalent methods are usually required. This 

requirement, and any exceptions, are specified in 40 CFR Part 58, Appendix C3

. In addition, reference or 

equivalent methods may be required for other monitoring applications, such as those associated with 

prevention of significant deterioration (PSD). Requiring the use of reference or equivalent methods helps 

to assure the reliability of air quality measurements including: ease of specification, guarantee of 

minimum performance, better instruction manuals, flexibility of application, comparability with other 

data and increased credibility of measurements. However, designation as a reference or equivalent 

method provides no guarantee that a particular analyzer will always operate properly. 40 CFR Part 58, 

Appendix A requires the monitoring organization to establish an internal QC program. Specific guidance 

for a minimum QC program is described in Section 10 of this Handbook. 

The definitions and specifications of reference and equivalent methods are given in 40 CFR Part 53. For 

most monitoring applications, the distinction between reference and equivalent methods is unimportant 

and either may be used interchangeably. 

Reference and equivalent methods may be either manual or automated (analyzers). For SO2, particulates, 

and Pb, the reference method for each is a unique manual method that is completely specified in 40 CFR 

Part 50 (Appendices A, and G respectively); all other approved methods for SO2 and Pb qualify as 

equivalent methods. For CO, NO2, and O3, Part 50 provides only a measurement principle and calibration 

procedure applicable to reference methods for these pollutants. Automated methods (analyzers) for these 

pollutants may be designated as either reference methods or equivalent methods, depending on whether 

the methods utilize the same measurement principle and calibration procedure specified in Part 50. 

Because any analyzer that meets the requirements of the specified measurement principle and calibration 

procedure may be designated as a reference method, there are numerous reference methods for CO, NO2, 

and O3. Further information on this subject is in the preamble to 40 CFR Part 53. 

 

3 http://www.access.gpo.gov/nara/cfr/cfr-table-search.html All references to CFR in following section can be found 

at this site. 
QA Handbook Volume II, Section 7.0 

Revision No: 1 

Date: 12/08 

Page 11 of 14 

Except for the unique reference methods for SO2, particulates, and Pb specified in 40 CFR Part 50, all 

reference and equivalent methods must be officially designated as such by EPA under the provisions of 

40 CFR Part 53. Notice of each designated method is published in the Federal Register at the time of 

designation. A current list of all designated reference and equivalent methods is maintained and updated 

by EPA whenever a new method is designated. This list can be found on AMTIC4

. Moreover, any 

analyzer offered for sale as a reference or equivalent method after April 16, 1976 must bear a label or 

sticker indicating that the analyzer has been designated as a reference or equivalent method by EPA. 

Sellers of designated automated methods must comply with the conditions summarized below: 

 

4 http://www.epa.gov/ttn/amtic/criteria.html 

1. A copy of the approved operation or instruction manual must accompany the analyzer when it is 

delivered to the purchaser. 

2. The analyzer must not generate any unreasonable hazard to operators or to the environment. 

3. The analyzer must function within the limits of the performance specifications in Table 7-5 for at 

least 1 year after delivery when maintained and operated in accordance with the operation 

manual. 

4. Any analyzer offered or sale as a reference or equivalent method must bear a label or sticker 

indicating that it has been designated as a reference or equivalent method in accordance with 40 

CFR Part 53. 

5. If such an analyzer has one or more selectable ranges, the label or sticker must be placed in close 

proximity to the range selector and must indicate which range or ranges have been designated as 

reference or equivalent methods. 

6. An applicant who offers analyzers for sale as reference or equivalent methods is required to 

maintain a list of purchasers of such analyzers and to notify them within 30 days if a reference or 

equivalent method designation applicable to the analyzers has been canceled or if adjustment of 

the analyzers is necessary under 40 CFR Part 53.11(b) to avoid a cancellation. 

Accordingly, in selecting a designated method for a particular monitoring application, consideration 

should be given to such aspects as: 

• the suitability of the measurement principle; 

• the suitability for the weather and/or geographic conditions at the site; 

• analyzer sensitivity and available operating ranges suitable for the site; 

• susceptibility to interferences that may be present at the monitoring site; 

• requirements for support gases or other equipment; 

• reliability; 

• maintenance requirements; 

• initial as well as operating costs; 

• features such as internal or fully automatic zero and span checking or adjustment capability, etc.; 

• compatibility to your current and future network, i.e. software and connections (RS 232, 

Ethernet); and 

• manual or automated methods. 
QA Handbook Volume II, Section 7.0 

Revision No: 1 

Date: 12/08 

Page 12 of 14 

It is important that the purchase order for a new reference or equivalent analyzer specify the designation 

by the EPA. 

The required performance specifications, terms of the warranty, time limits for delivery and acceptance 

testing, and what happens in the event that the analyzer falls short of performance requirements should be 

documented. Aside from occasional malfunctions, consistent or repeated noncompliance with any of 

these conditions should be reported to EPA. In selecting designated methods, remember that designation 

of a method indicates only that it meets certain minimum standards. Competitive differences still exist 

among designated analyzers. Some analyzers or methods may have performance, operational, economic 

or other advantages over others. A careful selection process based on the individual air monitoring 

application and circumstances is very important.

Some of the performance tests and other criteria used to qualify a method for designation as a reference or 

equivalent method are intended only as pass/fail tests to determine compliance with the minimum 

standards. Test data may not allow quantitative comparison of one method with another. 

Table 7-5 Performance Specifications for Automated Methods 

Performance Parameter Units SO2 O3 CO NO2 Def and Test 

procedure-CFR Sec 

1) Range ppm 0-0.5 0-0.5 0-50 0-0.5 53.23(a)

2) Noise ppm 0.005 0.005 0.50 0.005 53.23(b)

3) Lower detectable limit ppm 0.01 0.01 1.0 0.01 53.23(c)

4) Interference equivalent 

 Each Interferant 

 Total Interferant

ppm + 0.02 

0.06

+ 0.02 

0.06

+ 1.0 

1.5

+ 0.02 

0.04

53.23(d)

5) Zero drift, 14 and 24 hour ppm +.02 +.02 +1.0 +.02 53.23(e)

6) Span drift, 24 hour 

 20% of upper range limit 

 80% of upper range limit

percent

+ 20.0 

+ 5.0

+ 20.0 

+ 5.0

+ 10.0 

+ 2.5

+ 20.0 

+ 5.0

53.23(e)

7) Lag time minutes 20 20 10 20 53.23(e)

8) Rise Time minutes 15 15 5 15 53.23(e)

9) Fall Time minutes 15 15 5 15 53.23(e)

10) Precision 

 20% of upper range limit 

 80% of upper range limit

ppm 0.01 

0.015

0.01 

0.01

0.5 

0.5

0.02 

0.03

53.23(e)

FRM/FEM Designated Operating Ranges and the Affect of Span Checks 

Although all FRM/FEMs are required to meet the range specified in Table 7-5, many instruments are 

designated for ranges narrower and or broader than the requirement. During the equipment 

purchase/selection phase, monitoring organizations should select an instrument with ranges most 

appropriate to the concentration at the site which the instrument will be established and then use the range 

that is most appropriate for the monitoring situation. Earlier versions of this Handbook suggested that the 

concentration of the span checks be 70 – 90% of the analyzers measurement range. Using this guidance 

and the designated ranges of some of the FRM/FEM method being used, a span check might be selected 

at a concentration that is never found in the ambient air at the site for which the monitoring is operating. 

The span check concentration should be selected that is more beneficial to the quality control of the 

routine data at the site and EPA suggests: 1) the selection of an appropriate measurement range and 2) 

selecting a span that at a minimum is above 120% of the highest NAAQS (for sites used for designation 

purposes) and above the 99% of the routine data over a 3 year period. The multi-point 

verification/calibrations that are performed at a minimum annually can be used to challenge the 

instrument and confirm linearity and calibration slope of the selected operating range. 
QA Handbook Volume II, Section 7.0 

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PM2.5 Reference and Equivalent Methods

All formal sampler design and performance requirements and the operational requirements applicable to 

reference methods for PM2.5 are specified in 40 CFR Part 50, Appendix L. These requirements are quite 

specific and include explicit design specifications for the type of sampler, the type of filter, the sample 

flow rate, and the construction of the sample collecting components. However, various designs for the 

flow-rate control system, the filter holder, the operator interface controls, and the exterior housing are 

possible. Hence, various reference method samplers from different manufacturers may vary considerably 

in appearance and operation. Also, a reference method may have a single filter capability (single) or a 

multiple filter capability (sequential), provided no deviations are necessary in the design and construction 

of the sample collection components specified in the reference method regulation. A PM2.5 method is not 

a reference method until it has been demonstrated to meet all the reference method regulatory 

requirements and has been officially designated by EPA as a reference method for PM2.5. 

Equivalent methods for PM2.5 have a wider latitude in their design, configuration, and operating principle 

than reference methods. These methods are not required to be based on filter collection of PM2.5; 

therefore, continuous or semi-continuous analyzers and new types of PM2.5 measurement technologies are 

not precluded as possible equivalent methods. Equivalent methods are not necessarily required to meet all 

the requirements specified for reference methods, but they must demonstrate both comparability to 

reference method measurements and similar PM2.5 measurement precision. 

The requirements that some (but not all) candidate methods must meet to be designated by EPA as 

equivalent methods are specified in 40 CFR Part 53. To minimize the difficulty of meeting equivalent 

method designation requirements, three classes of equivalent methods have been established in the 40 

CFR Part 53 regulations, based on a candidate method’s extent of deviation from the reference method 

requirements. All three classes of equivalent methods are acceptable for SLAMS or SLAMS-related 

PM2.5 monitoring. But not all types of equivalent methods may be equally suited to various PM2.5

monitoring requirements or applications. 

Class I equivalent methods are very similar to reference methods, with only minor deviations, and must 

meet nearly all of the reference method specifications and requirements. The requirements for designation 

as Class I equivalent methods are only slightly more extensive than the designation requirements for 

reference methods. Also, because of their substantial similarity to reference methods, Class I equivalent 

methods operate very much the same as reference methods. 

Class II equivalent methods are filter-collection-based methods that differ more substantially from the 

reference method requirements. The requirements for designation as Class II methods may be 

considerably more extensive than for reference or Class I equivalent methods, depending on the specific 

nature of the variance from the reference method requirements. 

Class III equivalent methods cover any PM2.5 methods that cannot qualify as reference or Class I or II 

equivalent methods because of more profound differences from the reference method requirements. This 

class encompasses PM2.5 methods such as continuous or semi-continuous PM2.5 analyzers and potential 

new PM2.5 measurement technologies. The requirements for designation as Class III methods are the most 

extensive, and, because of the wide variety of PM2.5 measurement principles that could be employed for 

candidate Class III equivalent methods, the designation requirements are not explicitly provided in 40 

CFR Part 53. 
QA Handbook Volume II, Section 7.0 

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Approved Regional Methods (ARM) 

There are some continuous PM2.5 methods that currently may not be able to meet the national FRM and 

FEM designation criteria. However, these methods may operate at acceptable levels of data quality in 

certain regions of the country or under certain conditions. The EPA has expanded the use of alternative 

PM2.5 measurement methods through ARMs. A method for PM2.5 that has not been designated as an FRM 

or FEM as defined in 40 CFR Part 50.1 may be approved as an ARM. If a monitoring organization feels 

that a particular method may be suitable for use in its network, it can apply for the method to be 

designated as an ARM. The following provides a summary of the ARM requirements. 

 

PM2.5 ARM Criteria Summary 

1. Must meet Class III Equivalency Criteria 

o Precision 

o Correlation 

o Additive and multiplicative bias 

2. Tested at site(s) where it will be used 

o 1 site in each MSA/CMSA up to the first 2 highest pop MSA/CMSA 

o 1 site in rural area or Micropolitan Statistical Area 

o Total of 3 

If the ARM has been approved by another agency then: 

o 1 site in MSA/CMSA and 1 site in rural area or Micropolitan Statistical Area 

o Total of 2 

3. 1 year of testing all seasons covered 

o 90 valid sample pairs per site with at least 20 valid sample pairs per season. 

o Values < 3 ug/m3

 may be excluded in bias estimates but this does not affect completeness criteria. 

4. Collocation to establish precision not required 

o peer reviewed published literature or data in AQS that can be presented is enough 

5. ARM must be operated on an hourly sampling frequency providing for aggregation into 24-hour average 

measurements. 

6. Must use approved inlet and separation devices (Part 50 Appendix L or FEM Part 53) 

o Exception –methods that by their inherent measurement principle may not need an inlet or 

separation device. 

7. Must be capable of providing for flow audits 

o Exception –that by their inherent measurement principle measured flow is not required. 

8. Monitoring agency must develop and implement appropriate procedures for assessing and reporting 

precision and bias. 

Routine Monitoring Implementation 

9. Collocation of ARM and FRM/FEM at 30% of SLAMS network or at least 1/network 

o At 1 in 6 day sampling frequency 

o Located at design value site among the largest MSA/CMSA 

o Collocated FRM/FEM can be substituted for ARM if ARM is invalidated 

10. Collocation ARM with ARM 

o 7.5% of sites or at least 1 site 

11. Bias assessment (PEP) 

o Same frequency as Appendix A 

 

ARM Approval 

1. New ARM- EPA NERL, RTP, NC 

2. ARM that has been approved by another agency- EPA Regional Administrator 
QA Handbook Vol II , Section 8.0 

Revision No: 1 

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Page 1 of 6 

8.0 Sample Handling and Custody

A critical activity within any data collection phase involving physical samples is the handling of sample 

media prior to sampling, handling/transporting sample media to the field, handling samples from the field 

at the time of collection, storage of samples (at field or other locations), transport of samples from the 

field site, and the analysis of the samples. Documentation ensuring that proper handling has occurred 

throughout these activities is part of the custody record, which provides a mechanism for tracking samples 

through sample collection, processing and analysis. Custody records document the “chain of custody”; the 

date and person responsible for the various sample handling steps associated with each sample. Custody 

records also provide a reviewable trail for quality assurance purposes and as evidence in legal 

proceedings. 

Prior to the start of an EDO, the various types of samples should be identified and the following questions 

asked: 

• Does the sample need to be analyzed within a specified time period? 

• What modes of sample transport are necessary and how secure should they be? 

• What happens if a sample is collected on Friday? Is the sample shipped or stored at the field 

office and what are the procedures? 

• Can the sample’s integrity be affected by outside influences (e.g. temperature, pressure, humidity, 

jostling/dropping during shipment, other influences) and do these need to be monitored (e.g., 

max/min thermometers, pressure sensors)? 

• How critical is it that sample integrity be known (e.g., is evidence tape necessary)? 

• How can it be documented that sample integrity was maintained from the collection to reporting? 

• What are the procedures when sample integrity is compromised (e.g., flag, don’t analyze)? 

These are some of the questions that should be answered and documented in the monitoring 

organization’s QAPP and SOPs. 

This section specifically addresses the handling and custody of physical environmental samples (e.g., 

exposed filters for particulate matter (PM) determinations and canisters containing whole air samples) 

that are collected at a field location and transported to a laboratory for analysis. For specific details of 

sample handling and custody (i.e., PAMS, NATTS, STN etc) monitoring organization should consult the 

appropriate technical assistance documents located in the National Programs summaries in Appendix A. 

In addition to physical samples, some types of field data collected in hard copy (e.g., strip charts, sampler 

flow data, etc.) or electronic (e.g., data downloaded from a data logger with limited storage space) format 

are irreplaceable and represent primary information about physical samples or on-site measurements that 

are needed to report a final result. When such hard copy or electronic data are transported and/or change 

custody, it is advised that the same chain of custody practices described in this section for physical 

samples be employed to ensure that irreplaceable data can be tracked and are not altered or tampered 

with. 

For additional information, an EPA on-line self-instructional course, “Chain-of-Custody Procedures for 

Samples and Data1

” is available for review. The National Enforcement Investigation Center2 (NEIC) also 

offers a course relevant to chain of custody issues. 

 

1 http://www.epa.gov/apti/coc/

2 http://www.epa.gov/compliance/about/offices/division/neic.html
QA Handbook Vol II , Section 8.0 

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Page 2 of 6 

Laboratory Information Management Systems 

A laboratory information management system or LIMS, is a computer system used in the laboratory for 

the management and tracking of samples, instruments, standards and other laboratory functions such as 

data reductions, data transfer and reporting. The goal is to create an EDO where: 

• Instruments used are integrated in the lab network; receive instructions and worklists from the 

LIMS and return finished results including raw data back to a central repository where the LIMS 

can update relevant information to external systems (i.e., AIRNow or AQS). 

• Lab personnel will perform calculations, documentation and review results using online 

information from connected instruments, reference databases and other resources using electronic 

lab notebooks connected to the LIMS. 

• Management can supervise the lab process, react to bottlenecks in workflow and ensure 

regulatory demands are met. 

• External participants can review results and print out analysis certificates and other 

documentation (QA Reports, quality control charts, outlier reports etc.). 

For monitoring programs that are fairly stable, such as criteria pollutant monitoring, development of a 

LIMS system may be very cost effective and should be considered. There is an upfront cost in the 

development of these systems but monitoring organizations that have devoted resources to their 

development have seen pay offs in improved data quality, sample tracking and data reporting. 

8.1 Sample Handling

In the Ambient Air Quality Monitoring Program, discrete samples from manual methods associated with 

SLAMS, PAMS, NATTS, and other networks, are physically handled prior to analysis. One must pay 

particular attention to the handling of filters for particulate matter and lead since it has been suggested 

that the process of filter handling may be the largest source of measurement error (especially low-volume 

methods). Due to the manner in which concentrations are determined, it is critical that samples are 

handled as specified in SOPs. The various phases of sample handling that should be documented in a 

QAPP and SOP include: 

• Sample preparation, labeling and identification; 

• sample collection; 

• transportation; 

• sample analysis; and 

• storage and archival 

8.1.1 Sample Preparation, Labeling and Identification

Sample containers or filters are cleaned and prepared (pre-weighing of filters) before being used to collect 

samples. SOPs should indicate the proper care and handling of the containers/filters to ensure their 

integrity. Proper lab documentation that tracks the disposition of containers/filters through preparation is 

just as important as the documentation after sampling. Care must be taken to properly mark all samples to 

ensure positive, unambiguous identification throughout the sample collection, handling, and analysis 

procedures. Figure 8.1 shows a standardized identification sticker that may be used to label physical 

samples. Additional information may be added as required, depending on the particular monitoring 
QA Handbook Vol II , Section 8.0 

Revision No: 1 

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Page 3 of 6 

program. The rules of evidence used in legal proceedings require that procedures for identification of 

samples used in analyses form the basis for future evidence. An admission by the laboratory analyst that 

he/she cannot be positive whether he/she analyzed sample No. 6 or sample No. 9, for example, could 

destroy the validity of the entire test report. Any information that can be used to assess sample integrity, 

such as the pressure of canisters or liquid level, should be recorded at the time of sample collection. 

Liquid levels for samples in non-graduated containers can be marked on the side of the container with a 

grease pencil or permanent marker. 

Positive identification also must be provided for any filters used in the program. If ink is used for 

marking, it must be indelible and unaffected by the gases and temperatures to which it will be subjected. 

Other methods of identification can be used (e.g., bar coding), if they provide a positive means of 

identification and do not impair the capacity of the filter to function. 

(Name of Sampling Organization) 

Sample ID No: _________________________ Storage Conditions: _________________________ 

Sample Type:___________________________ Site Name:_________________________________ 

Date/Time Collected: _____________________ Site Address:_______________________________ 

Sampler:_______________________________ 

Figure 8.1 Example Sample Label.

8.1.2 Sample Collection 

To reduce the possibility of invalidating the results, all collected samples must be carefully removed from 

the monitoring device, placed in labeled, nonreactive containers, and sealed. Use of tamper-evident 

custody seals are suggested and may be required in certain cases. The sample label must adhere firmly to 

the container to ensure that it cannot be accidentally removed. Custody seals on sample containers serve 

two purposes: to prevent accidental opening of the sample container and to provide visual evidence 

should the container be opened or tampered with. The best type of custody seal depends on the sample 

container; often, a piece of tape placed across the seal and signed by the operating technician is sufficient; 

for other containers, wire locks or tie wraps may be the best choice. In some cases, the opening of sample 

containers by unauthorized personnel, such as Transportation Security Administration officers, cannot be 

avoided. The proper use of custody seals minimizes the loss of samples and provides direct evidence 

whether sample containers have been opened and possibly compromised. Samples whose integrity is 

questioned should be qualified (flagged). 

8.1.3 Sample Transportation

Samples should be delivered to the laboratory for analysis as soon as possible following sample 

collection. It is recommended that this be done on the same day that the sample is taken from the 

monitor. If this is impractical, all the samples should be placed in transport containers (e.g., carrying 

case, cooler, shipping box, etc.) for protection from breakage, contamination, and loss and in an 

appropriate controlled-temperature device (i.e., refrigerator or freezer) if the samples have specific 

temperature requirements. Each transport container should have a unique identification, such as sampling 

location, date, and transport container number (e.g., number 2 of 5) to avoid interchange and aid in 

tracking the complete shipment. The number of the transport containers should be subsequently recorded 
QA Handbook Vol II , Section 8.0 

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on the chain of custody (COC) form (described in Section 8.2) along with the sample identification 

numbers of the samples included within each transport container. It is advised that the container be sealed 

using an appropriate tamper-evident method, such as with custody tape or a wire lock. 

In transporting samples, it is important that precautions be taken to eliminate the possibility of tampering, 

accidental destruction, and/or physical and chemical action on the sample. The integrity of samples can 

be affected by temperature extremes, air pressure (air transportation), and the physical handling of 

samples (packing, jostling, etc.). These practical considerations must be dealt with on a site-by-site basis 

and should be documented in the organization’s QAPP and site specific SOPs. 

The person who has custody of the samples must be able to testify that no tampering occurred. Security 

must be continuous. If the samples are put in a vehicle, lock the vehicle. After delivery to the laboratory, 

the samples must be kept in a secured place with restricted access. 

8.1.4 Sample Analysis 

SOPs, if properly developed, have detailed information on the handling of samples at the analysis phase. 

Similar to the preparation step, if the sample undergoes a number of steps (preparation, equilibration, 

extraction, dilution, analysis, etc.), and these steps are performed by different individuals, there should be 

a mechanism in place to track the sample through the steps to ensure SOPs are followed and the integrity 

of the sample was maintained. Laboratories make extensive use of laboratory notebooks at the various 

steps (stations) of the analytical process to record the sample handling process and maintain sample 

integrity. 

8.1.5 Storage and Archival 

Samples must be properly handled to ensure that there is no contamination and that the sample analyzed 

is actually the sample taken under the conditions reported. For this reason, whenever samples are not 

under the direct control of the sample custodian, they should be kept in a secured location. This may be a 

locked vehicle, locked refrigerator, or locked laboratory with limited access. It is highly recommended 

that all samples be secured until discarded. These security measures should be documented by a written 

record signed by the handlers of the sample on the COC form or in a laboratory notebook, indicating the 

storage location and conditions. Any samples not destroyed during the analysis process (e.g., exposed 

filters for PM) should be archived as directed by the method requirements or applicable QAPP. 40 CFR 

Part 58.16 requires PM10, PM10-2.5 and PM2.5 filters from SLAMS manual lo-volume samplers be 

archived for 1 year from collection. However, it is suggested that they be archived the first year in cold 

conditions (e.g., at 4° C) and at room temperature for 2 additional years. It is also suggested that nondestructive lead analysis and STN samples follow this guidance. 

8.2 Chain of Custody (COC)

In order to use the results of a sampling program as evidence, a written record must be available listing 

the location of the samples at all times. This is also an important component of good laboratory 

practices3

. The COC record is necessary to make a prima facie showing of the integrity of the samples. 

Without it, one cannot be sure that the samples and sampling data analyzed were the same as the samples 

and data reported to have been taken at a particular time. Procedures may vary, but an actual COC record 

sheet with the names and signatures of the relinquishers/receivers works well for tracking physical 

 

3 http://www.fda.gov/ora/compliance_ref/bimo/glp/default.htm 
QA Handbook Vol II , Section 8.0 

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samples. The samples should be handled only by persons associated in some way with the monitoring 

program. A good general rule to follow is “the fewer hands the better,” even though a properly sealed 

sample may pass through a number of hands without affecting its integrity. 

Each person handling the samples must be able to state from whom and when the item was received and 

to whom and when it was delivered. A COC form should be used to track the handling of the samples 

through various stages of storage, processing, and analysis at the laboratory. It is recommended practice 

to have each person who relinquishes or receives samples sign the COC form for the samples. An 

example of a form that may be used to establish the COC for samples generated in the field is shown in 

Figure 8.2. This form should accompany the samples at all times from the field to the laboratory. All 

persons who handle the samples should sign the form. Figure 8.3 is an example of a laboratory COC 

form. COC forms should be retained and archived as described in Section 5 (Documents and Records). 

When using professional services to transport physical samples, only reliable services that provide a 

tracking number should be used. Information describing the enclosed samples should be placed on the bill 

of lading. A copy of the shipping receipt and tracking number should be kept as a record. The package 

should be addressed to the specific person authorized to receive the package, although it is recognized 

that staff not typically part of the COC may receive the samples and deliver them to the authorized 

addressee. A procedure must be in place to ensure that samples are delivered to the appropriate person 

without being opened or damaged. In this circumstance, the sample is considered still in transport until 

received by the authorized addressee. It may be necessary to ship and/or receive samples outside of 

normal business hours. A procedure should be developed in advance that considers staff availability, 

secure storage locations, and appropriate storage conditions (e.g., temperature-controlled). 

8.2.1 Sample Inspection and Acceptance 

Once the samples arrive at their destination and at every custody change, the samples should first be 

checked to ensure that their integrity is intact. The contents of the shipment should be checked against 

the COC form to ensure that all samples listed were included in the shipment. The levels of liquid 

samples should be compared to original levels (if marked on the container or recorded), to identify 

whether major leaks have occurred. When using passivated stainless steel canisters, the canister pressure, 

upon receipt, should be recorded and compared to the final sample collection pressure to indicate canister 

leakage and sample loss. It is recommended that this comparison be made using a certified gauge that is 

calibrated annually. Any samples whose integrity or identity are questionable should be brought to the 

attention of the relinquisher and flagged. All flags should be “carried” along with the samples until the 

validity of the samples can be proven. This information can be included in the remark section of the COC 

form. 
QA Handbook Vol II , Section 8.0 

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Chain of Custody Record

Project No. 

Organization 

Shipping 

Container No. 

Project Title 

Contact 

Field Samplers: print signature Address 

 

 

 

Date Time Site/Location Sample Type Sample ID Remarks 

 

 

 

 

 

 

Relinquished by (print and signature): Received by (print and signature): Comments 

 

 

Figure 8.2 Example Field COC Form.

Chain of Custody Record 

Project No. Project Title Organization 

 

Laboratory/Plant: _________________________________________________

Sample Number Number of 

Container 

Sample Description 

 

Person responsible for samples Time: Date: 

Sample Number Relinquished By: Received By: Time: Date: Reason for change in custody 

 

Figure 8.3 Example Laboratory COC Form.
QA Handbook Vol II, Section 9.0 

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9.0 Analytical Methods

The choice of methods used for any EDO should be influenced by the DQO. From the DQO and an 

understanding of the potential population uncertainty, one can then determine what measurement 

uncertainty is tolerable and select the method most appropriate in meeting that tolerance. Methods are 

usually selected based upon their performance characteristics (precision, bias, limits of detection), ease of 

use, and their reliability in field and laboratory conditions. 

Since both field and analytical procedures have been developed for the criteria pollutants in the Ambient 

Air Quality Monitoring Program, and in the various technical assistance documents for the other national 

ambient air programs, this section will discuss the general concepts of standard operating procedures and 

good laboratory practices as they relate to the reference and equivalent methods. A more detailed 

discussion on the attributes of SOPs can be found in Section 5. Information on reference and equivalent 

methods can be found on the AMTIC website1

 as well as the current list of designated Federal Reference 

and Equivalent Methods2

. 

Many ambient air methods utilize continuous instruments and therefore do not involve laboratory 

analysis. However particulate matter methods involve both continuous and manual methods and some of 

the other major monitoring programs involve sampling which requires the use of laboratory analysis. 

Table 9-1 provides a summary of the pollutants measured and the analytical methods for these programs. 

Table 9-1 Acceptable Analytical Methods 

Network Pollutant Acceptable Method Reference 

SLAMS PM10 – Hi-Vol Gravimeteric 40 CFR Part 50 App B 

SLAMS PM10- dichot Gravimeteric 40 CFR Part 50 App J 

SLAMS PM2.5 Gravimeteric 40 CFR Part 50 App L 

SLAMS PM10-2.5 Gravimeteric- difference 

SLAMS Pb Atomic Absorption Spectrometry 40 CFR Part 50 App G 

PAMS VOCs Gas Chromatography/Mass Spectrometry (GC/MS) TO-15 

PAMS Carbonyl 

compounds 

High Performance Liquid Chromatography (HPLC) TO11-A 

PAMS Non-Methane 

Organic Compounds 

(NMOC) 

Cryogenic Preconcentration and Direct Flame Ionization 

Detection (PDFID) 

TO-12 

NATTS Metals Inductively coupled plasma (ICP) IO 3.5 

NATTS Aldehydes High Pressure Liquid Chromatography TO11-A 

NATTS VOCs Gas Chromatography TO-15 

STN PM2.5 Gravimeteric 40 CFR Part 50 App L 

STN Elements Energy Dispersive X-Ray Fluorescence (EDXRF) STN QAPP and SOPs 

STN Anions STN QAPP and SOPs 

STN Cations STN QAPP and SOPs 

STN Organic, Elemental, 

Carbonate, Total 

Carbon 

Thermal Optical Carbon Analyzer STN QAPP and SOPs 

STN Semi-volatile 

Organic Compounds 

Gas Chromatography/Mass Spectrometry (GC/MS) STN QAPP and SOPs 

The SLAMS network provides more rigorous quality control requirements for the analytical methods. 

These methods are found in 40 CFR Part 50, as described in the references. In addition, the method 

identified for Pb is the reference method. There are a number of equivalent analytical methods that are 

 

1 http://www.epa.gov/ttnamti1/pmfrm.html

2 http://www.epa.gov/ttn/amtic/criteria.html 
QA Handbook Vol II, Section 9.0 

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available for the Pb. Some of the NATTS methods are derived from the Toxics Organic Method 

Compendium3. Others, like the STN Network4 may be developed specifically for the program, based on 

the national laboratory currently performing the analysis. The PAMS, NATTS and STN networks follow 

the performance based measurement process paradigm. These Networks’ QA project plans or technical 

assistance documents suggest a method, but also allow some flexibility to use other methods that meet the 

network’s measurement quality objectives. Various, independent proficiency test samples and technical 

systems audits are performed to ensure that the data quality within these networks remains acceptable. 

9.1 Good Laboratory Practices

Good laboratory practices (GLPs)5 refer to general practices that relate to many, if not all, of the 

measurements made in a laboratory. They are usually independent of the SOP and cover subjects such as 

maintenance of facilities, records, sample management and handling, reagent control, and cleaning of 

laboratory glassware. In many cases, the activities mentioned above may not be formally documented 

because they are considered common knowledge. However, for consistency in laboratory technique, these 

activities should have some form of documentation. 

9.2 Laboratory Activities

For ambient air samples to provide useful information or evidence, laboratory analyses must meet the 

following four basic requirements: 

1. Equipment must be frequently and properly calibrated and maintained (Section 12). 

2. Personnel must be qualified to make the analysis (Section 4). 

3. Analytical procedures must be in accordance with accepted practice (Section 9.1 above). 

4. Complete and accurate records must be kept (Section 5). 

As indicated, these subjects are discussed in other sections of this document. For the Ambient Air 

Quality Monitoring Program, laboratory activities are mainly focused on the pollutants associated with 

manual measurements for lead, particulate matter (PM and STN), NATTS6

 and PAMS7 (VOCs). 

However, many laboratories also prepare reference material, test or certify instruments, and perform other 

activities necessary to collect and report measurement data. Each laboratory should define these critical 

activities and ensure there are consistent methods for their implementation. 

 

3 http://www.epa.gov/ttn/amtic/airtox.html 4 http://www.epa.gov/ttn/amtic/specsop.html 5 http://www.epa.gov/Compliance/monitoring/programs/fifra/glp.html 6 http://www.epa.gov/ttn/amtic/files/ambient/airtox/NATTS_TAD_SECT_4.pdf 7 http://www.epa.gov/ttn/amtic/files/ambient/pams/newtad.pdf 
QA Handbook Vol II, Section 10 

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10.0 Quality Control 

As described in Section 3, any data 

collection process that provides an 

estimate of a concentration contains 

uncertainties related to spatial/temporal 

variability (population) and the 

measurement process. DQOs define 

the data quality needed to make a 

correct decision an acceptable 

percentage of the time. Data quality is 

defined through quantification of the 

following data quality indicators. 

Representativeness - the degree in which data accurately and precisely represent a characteristic of a population, 

parameter variation at a sampling point, a process condition, or an environmental condition. 

Precision - a measure of mutual agreement among individual measurements of the same property usually under 

prescribed similar conditions. This is the random component of error. Precision is estimated by various statistical 

techniques using some derivation of the standard deviation. 

Bias - the systematic or persistent distortion of a measurement process which causes error in one direction. Bias 

will be determined by estimating the positive and negative deviation from the true value as a percentage of the true 

value. 

Detectability - The determination of the low range critical value of a characteristic that a method specific procedure 

can reliably discern.

Completeness - a measure of the amount of valid data obtained from a measurement system compared to the 

amount that was expected to be obtained under correct, normal conditions. Data completeness requirements are 

included in the reference methods (40 CFR Pt. 50). 

Comparability - a measure of confidence with which one data set can be compared to another.

Measurement quality objectives (MQOs) identify the quality control samples and the acceptance 

criteria for those samples that will allow one to quantify the data quality indicators. 

Data quality assessments (DQAs) are the statistical assessments that determine if the DQOs are met and 

to provide descriptions of data uncertainty. If the DQOs are not met, the DQAs are used to determine 

whether modifications to the DQOs are necessary or “tighter” quality control is required. 

 Within any phase or step of the data collection process, errors can occur. For example: 

• samples and filters can be mislabeled; 

• data can be transcribed or reported incorrectly or information management systems can be 

programmed incorrectly; 

• calibration or check standards can be contaminated or certified incorrectly resulting in faulty 

calibrations; 

 Uncertainty = Population + Measurement 

2.Precision 

3.Bias 

4. Completeness

5. Comparability

6. Detectability

MQOs

Preparation 

 Field 

Laboratory 

DQO

DQ

1. Representativeness }

Data Quality Indicators
QA Handbook Vol II, Section 10 

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• instruments can be set up improperly or over time fail to operate within specifications; and 

• procedures may not be followed. 

Quality Control (QC) is the overall system of technical activities that measures the attributes and 

performance of a process, item, or service against defined standards to verify that they meet the stated 

requirements established by the customer1

. Quality control includes establishing specifications or 

acceptance criteria for each quality characteristic of the monitoring/analytical process, assessing 

procedures used in the monitoring/analytical process to determine conformance to these specifications, 

and taking any necessary corrective actions to bring them into conformance. The EPA’s QAPP guidance 

document QA/G52

 suggests that “QC activities are those technical activities routinely performed, not to 

eliminate or minimize errors, but to measure their effect”. Although there is agreement that the 

measurement or assessment of a QC check or procedure does not itself eliminate errors, the QC data can 

and should be used to take appropriate corrective actions which can minimize error or control data to an 

acceptable level of quality in the future. So, QC is both proactive and corrective. It establishes 

techniques to determine if field and lab procedures are producing acceptable data and identifies actions to 

correct unacceptable performance. 

The goal of quality control is to provide a reasonable level of checking at various stages of the data 

collection process to ensure that data quality is maintained and if it is found that the quality has not been 

maintained, that it is discovered with a minimal loss of data (invalidation). Figure 10.1 provides an 

example of some of the QC samples used in the PM2.5 data collection process. The figure also identifies 

what sources of error are associated with the QC sample. So, in developing a quality control strategy, one 

must weigh the costs associated with quality control against the risks of data loss. 

With the objective to 

minimize data loss, 

quality control data is 

most beneficial when it is 

assessed as soon as it is 

collected. Therefore, 

information management 

systems can play a very 

important role in 

reviewing QC data and 

flagging or identifying 

spurious data for further 

review. These 

information management 

procedures can help the 

technical staff review 

these QC checks coming 

from a number of 

monitoring sites in a consistent and time efficient manner. There are many graphical techniques (e.g., 

control charts and outlier checks) that can be employed to quickly identify suspect data. More details of 

information management systems are discussed later in this section. 

 

1

 American Nation Standard ANSI/ASQ E4-2000 http://www.asq.org/ 2 http://www.epa.gov/quality/qa_docs.html 

Field 

Blank Laboratory

Pre- Field Weighing 

 Field 

Sampling 

 Laboratory

Post-Field Weighing 

 Lab 

Blank QC 

 Checks 

Field 

Blank 

Field 

Blank 

Routine 

Sample 

Collocated 

 Sample 

Routine 

Sample 

Collocated 

 Sample 

Routine 

Sample 

Collocated 

 Sample 

 QC 

Checks PEP 

 PEP 

 PEP 

 Lab 

Blank

 QC 

 Checks 

 Meas. System 

Contamination 

 Instrument 

precision/bias 

Meas. System 

 Precision 

Meas. System 

 Bias 

 Lab 

Contamination 

Weighing lab 

Precision/Bias 

Figure 10.1 QC samples for PM2.5 placed at various stages of measurement process 
QA Handbook Vol II, Section 10 

Revision No:1 

Date: 12/08 

Page 3 of 8 

It is the responsibility of the monitoring organization, through the development of its QAPP, policies and 

procedures, to develop and document the: 

• QC techniques; 

• frequency of the QC checks and the point in the measurement process that the check is 

introduced; 

• traceability of QC standards; 

• matrix of the check sample; 

• appropriate test concentrations; 

• actions to be taken in the event that a QC check identifies a failed or changed measurement 

system; 

• formulae for estimating data quality indicators; 

• QC results, including control charts; and 

• the means by which the QC data will be used to determine that the measurement performance is 

acceptable. 

10.1 QC Activity Areas 

For air monitoring projects the following three areas must have established QC activities, procedures and 

criteria: 

1. Data Collection. 

2. Data management and the verification and validation process. 

3. Reference materials. 

Data collection includes any process involved in acquiring a concentration or value, including but not 

limited to: sample preparation, field sampling, sample transportation, field analytical (continuous) 

methods, and laboratory preparation/analytical processes. Depending on the importance of the data and 

resources available, monitoring programs can implement QC samples, as illustrated in Figure 10.1, to 

identify the errors occurring at various phases of monitoring process. Many of the QC samples can 

identify errors from more than one phase. Table 10-1 provides a list of the majority of the QC samples 

utilized in the ambient air program and include both their primary and secondary uses in error 

identification. Many of these checks are required in CFR; others are strongly suggested in the method 

guidance. The MQO/validation templates provided in Appendix D provide the minimum requirements 

for the frequency that these checks be implemented but many monitoring organization choose more 

frequent checking in order to reduce the risk of data invalidation. A good example of this is the zero/span 

and one-point precision checks for the gaseous criteria pollutants. Although CFR requires the check to 

be performed once every two weeks, due to the advent of more sophisticated automated monitoring 

systems, many monitoring organization perform these checks every 24-hours (11:45 PM – 12:15 AM). In 

addition, once the QC checks are developed for a particular monitoring method, it is important to identify 

the acceptance criteria and what corrective action will be taken once a QC check fails. The 

MQO/Validation template in Appendix D can be used to list the QC samples with a column added to 

include corrective action. Table 10-2 provides an example of a QC Sample Table for PM2.5. Although 

the validation templates provide guidance for when data should be invalidated, it is up to the monitoring 

organization to provide the specific corrective actions for the failure of a specific QC check and therefore, 

Table 10-2 does not identify specific corrective actions. 
QA Handbook Vol II, Section 10 

Revision No:1 

Date: 12/08 

Page 4 of 8 

Data management quality control is discussed in more detail in Section 14 and the 

verification/validation process in Section 17. However, both processes require some frequency of checks 

to ensure that they are performed consistently and without error. This is especially true for data 

management since errors in programming can cause consistent errors for long periods of time if not 

checked. 

Reference materials are the standards by which many of the QC checks are performed. Reference 

material can be gaseous standards as well as devices (e.g., flow rate standards). If these standards are not 

checked and verified as to their certified values, then the quality of data becomes suspect. Reference 

materials need to be certified and recertified at acceptable frequencies in order to maintain the integrity of 

the reference material. It is suggested that standards be certified annually. More discussion on standards is 

included in Section 12. 

10.2 Internal vs. External Quality Control 

Quality control can be separated into 2 major categories: internal QC and external QC. Most of the 

quality control activities take place internally, meaning the monitoring organization responsible for 

collecting the data also develops and implements the quality control activities, evaluates the data, and 

takes corrective action when necessary. The internal activities can be used to take immediate action if 

data appear to be out of acceptance. External quality control samples are usually of two types: “doubleblind” meaning the QC sample is not known (looks like a routine sample) and therefore its concentration 

in unknown, or “single-blind” meaning they are known to be a QC sample but its concentration is 

unknown. These samples are also called performance evaluation or proficiency test samples and are 

explained in Section 15. Because these checks are performed by external organizations, the results are 

not always immediately available and therefore have a diminished capacity to control data quality in 

“real-time.” However they are useful as an objective test of the internal QC procedures and may identify 

errors (i.e., biased or contaminated standards) that might go unnoticed in an internal QC system. Both 

types of quality control are important in a well implemented quality system. Other elements of an 

organization’s QAPP that may contain related sampling and analytical QC requirements include: 

• Sampling Design which identifies the planned field QC samples as well as procedures for QC 

sample preparation and handling; 

• Sampling Methods Requirements which includes requirements for determining if the collected 

samples accurately represent the population of interest; 

• Sample Handling and Custody Requirements which discusses any QC devices employed to 

ensure samples are not tampered with (e.g., custody seals) or subjected to other unacceptable 

conditions during transport; 

• Analytical Methods Requirements which includes information on the subsampling methods and 

information on the preparation of QC samples (e.g., blanks and replicates); and 

• Instrument Calibration and Frequency which defines prescribed criteria for triggering 

recalibration (e.g., failed calibration checks).
QA Handbook Vol II, Section 10 

Revision No: Final Draft 

Date: 12/08 

Page 5 of 8 

Table 10-1 QC Samples Used in Various Ambient Air Monitoring Programs

Sources of Measurement Error 

Sample Collection Sample 

Transport 

Field (continuous)/ Laboratory Analytical Method 

Data Quality 

Indicator 

QC Check and 

QC Sample 

Sampling 

Equipment 

Conditions 

During 

Sampling 

Preservation 

Technique 

Sampling 

Matrix 

Shipment 

Process 

Sample 

Storage 

Sample 

Preparation 

Reagents 

Sample 

Preparation

Analytical Methods 

Reagents/ 

Standards 

Analytical 

Equipment 

Purpose 

To evaluate or determine the source 

of measurement error arising from: 

Lot Blank Filters that have not equilibrated 

Exposure Lot Blanks A batch of filters that have not equilibrated 

Laboratory Blanks Ambient contamination arising within 

laboratory or balance not operating 

Trip Blanks Contamination from shipping and/or lab 

Field Blanks Ambient contamination from field activities 

sampling equipment, shipping and/or lab 

Reagent Blank Contamination introduced by reagents used in 

sample preparation/preservation. 

Accuracy/Bias 

Positive or 

negative bias 

primarily due to 

contamination. 

(could also be 

due to operator 

error) 

Equipment Blank 

(Rinsate Blank) 

Carryover contamination resulting from successive use of sampling equipment. 

Matrix Spike Preparation/analytical bias for specific 

compounds in sample matrices 

Surrogate Spike Preparation/analytical bias for specific sample 

matrices 

Accuracy/Bias 

Due to sample 

matrix or sample 

preparation/ 

Analytical 

methodology 

Lab Control Samples Labs ability to accurately identify and 

quantitate target compounds 

Cooler Temp Check High temperatures causing volitilization 

affecting mass concentration 

Accuracy/Bias 

due to inadequate 

temp. control Temp Verifications Sampler, sample storage, or laboratory prep 

facilityproblems 

Balance Check Analytical balance precision and stability 

Flow Rate Verifications/ 

Audits 

Equipment not operating within specified parameters 

Humidity 

Verifications 

Laboratories inability to have an adequate measurement environment 

Pressure Verifications Sampler malfunction 

Leak Checks Sampler malfunction 

Timer Verifications Sampler malfunction 

Accuracy/Bias 

Primarily due to 

equipment 

malfunction or not 

properly 

calibrated and/or 

operator error 

Zero/Span Analyzer out of calibration or bad standards 

Precision/ Bias One-Point QC Check Analyzer out of calibration or bad standards 

Collocated Samples Cumulative effects of both field & lab precision 

to measure overall precision 

Field Duplicates Cumulative effects of both field & lab precision 

to measure overall precision 

Precision 

Sample /Analytical 

Replicate 

Filters not equilibrating, incorrect weighing procedure or balance problems 

 Standard Certifications Contaminated Reagents/Standards  Calibrations Sampling analytical equipment bias or drift 

Round Robins Overall sampling/analysis process Accuracy/Bias 

Proficiency Tests Overall sampling/analysis process 

Bias PEP Overall sampling/analysis process 

 NPAP Overall sampling/analysis process 

Sensitivity MDL Studies 
QA Handbook Vol II, Section 10 

Revision No: Final Draft 

Date: 12/08 

Page 6 of 8 

Table 10-2 PM2.5 Field and Lab QC Checks

Requirement Frequency Acceptance Criteria Corrective Action 

Field QC Checks 

Calibration Standards 

 Flow Rate Transfer Std. 

 Field Thermometer 

 

 Field Barometer 

1/yr 

1/yr 

1/yr 

+2% of NIST-traceable Std. 

+ 0.1o

 C resolution 

+ 0.5o C accuracy 

+ 1 mm Hg resolution 

+ 5 mm Hg accuracy 

Calibration/Verification

 Flow Rate (FR) Calibration 

 FR multi-point verification 

 One point FR verification 

 External Leak Check 

 Internal Leak Check 

 Temperature Calibration 

 Temp multi-point verification 

 One- point temp Verification 

 Pressure Calibration 

 Pressure Verification 

 Clock/timer Verification 

If multi-point failure 

1/yr 

1/4 weeks 

every 5 sampling events 

every 5 sampling events 

If multi-point failure 

on installation, then 1/yr 

1/4 weeks 

on installation, then 1/yr 

1/4 weeks 

1/ 4 weeks 

+ 2% of transfer standard 

+ 2% of transfer standard 

+ 4% of transfer standard 

80 mL/min 

80 mL/min 

+ 2% of standard 

+ 2EC of standard 

+ 4EC of standard 

"10 mm Hg 

"10 mm Hg 

1 min/mo 

Blanks

Field Blanks See 2.12 reference +30 Fg 

Precision Checks

 Collocated samples every 6 days CV < 10% 

Audits (external assessments) 

 FRM PEP 

 Flow rate audit 

 External Leak Check 

 Internal Leak Check 

 Temperature Audit 

 Pressure Audit 

5 or 8 sites/year 

1/6mo 

1/6mo 

1/6mo 

1/6mo 

1/6mo 

+ 10% 

+ 4% of audit standard 

< 80 mL/min 

< 80 mL/min 

+ 2EC 

"10 mm Hg 

Laboratory QC Checks

Blanks

 Lot Blanks 

 Lab Blanks 

3-lot 

3 per batch 

+15 Fg difference 

+15 Fg difference 

Calibration/Verification

 Balance Calibration 

 Lab Temp. Calibration 

 Lab Humidity Calibration 

1/yr 

3 mo 

3 mo 

Manufacturers spec. 

+ 2EC 

"2% 

Bias

 Balance Audit 

 Balance Check 

1/year 

beginning, every 10th 

samples, end 

+15 Fg for unexposed filters 

< +3 Fg 

Calibration standards 

 Working Mass Stds. 

 Primary Mass Stds. 

3-6 mo. 

1/yr 

25 Fg 

25 Fg 

Precision

 Duplicate filter weighings 1 per weighing session +15 Fg difference 
QA Handbook Vol II, Section 10 

Revision No: Final Draft 

Date: 12/08 

Page 7 of 8 

10.3 CFR Related Quality Control Samples 

40 CFR Part 58, Appendix A identifies a number of quality control samples that must be implemented for 

the SLAMS (and NCore) SPM and PSD networks. By 2009, any special purpose monitors that use FRMs 

or FEMs will be required to follow these requirements unless granted a waiver by the Regional 

Administrator. Table 10-3 provides a summary of the QC checks for the criteria pollutants and the CFR 

reference where an explanation of each check is described. The reader should distinguish the 

requirements that are related to automated and manual methods since there are some differences.

Table 10-3 Ambient Air Monitoring Measurement Quality Samples 

Method CFR Reference Coverage (annual) Minimum frequency MQOs* 

Automated Methods

One-Point QC:

for SO2, NO2, O3, CO Section 3.2.1 Each analyzer Once per 2 weeks 

O3 Precision 7%, Bias + 7%. 

SO2, NO2, CO 

 Precision 10% , Bias + 10% 

Annual performance 

evaluation

for SO2, NO2, O3, CO 

Section 3.2.2 Each analyzer Once per year < 15 % for each audit 

concentration 

Flow rate verification

PM10,PM2.5, PM10-2.5, 

TSP 

Section 3.2.3 Each sampler Once every month 

< 4% of standard and 5% of 

design value 

Semi-annual flow rate 

audit

PM10, PM2.5, PM10-2.5, 

TSP 

Section 3.2.4 

Each sampler Once every 6 months 

< 4% of standard and 5% of 

design value 

Collocated sampling

PM2.5, PM10-2.5, TSP 

Section 3.2.5 15% within PQAO Every twelve days PM2.5, - 10% precision 

PM10-2.5- - 15% precision 

TSP – 10% precision 

PM Performance 

evaluation program

 PM2.5,PM10-2.5

Section 3.2.7 1. 5 valid audits for primary 

QA orgs, with < 5 sites 

2. 8 valid audits for primary 

QA orgs, with > 5 sites 

3. All samplers in 6 years 

over all 4 quarters 

PM2.5, - + 10% bias 

PM10-2.5- - +15% bias 

Manual Methods 

Collocated sampling

PM10, TSP, PM10-2.5, 

PM2.5

3.3.1 and 3.3.5 15% within PQAO Every 12 days 

PSD every 6 days 

PM10, TSP, PM2.5, - 10% 

precision 

PM10-2.5- - 15% precision 

Flow rate verification

PM10 (low Vol),PM10-2.5, 

PM2.5,, TSP 

3.3.2 

 Each sampler Once every month 

< 4% of standard and 5% of 

design value 

Flow rate verification

PM10 (High-Vol), TSP

3.3.2 Each sampler Once every quarter < 10% of standard and design 

value 

Semi-annual flow rate 

audit

PM10 (low Vol), PM10-2.5, 

PM2.5, TSP 

3.3.3 

Each sampler, all locations 

 Once every 6 months < 4% of standard and 5% of 

design value 

Semi-annual flow rate 

audit

PM10 (High-Vol), TSP 

3.3.3 Each sampler, all locations Once every 6 months < 10% of standard and design 

value 

Manual Methods

 Lead 3.3.4 

1. Each sampler 

2. Analytical (lead strips) 

1. Include with TSP 

2. Each quarter 

 1. Same as for TSP. 

2. - + 10% bias 

Performance evaluation 

program

PM2.5, PM10-2.5

3.3.7 and 3.3.8 1. 5 valid audits for primary 

QA orgs, with < 5 sites 

2. 8 valid audits for primary 

QA orgs, with > 5 sites 

3. All samplers in 6 years 

Over all 4 quarters 

PM2.5, + 10% bias 

PM10-2.5-, +15% bias 

* Some of the MQOs are found in CFR and others in Appendix D of this guidance document. 
QA Handbook Vol II, Section 10 

Revision No: Final Draft 

Date: 12/08 

Page 8 of 8 

10.4 Use of Computers for Quality Control 

With the wide range of economical computers now available, and the advancements in data acquisition 

system (DAS) technologies, consideration should be given to a computer system that can process and 

output the information in a timely fashion. Such a computer system should be able to: 

• compute calibration equations 

• compute measures of linearity of 

calibrations (e.g., standard error 

or correlation coefficient) 

• plot calibration curves 

• compute zero/span drift results 

• plot zero/span drift data 

• compute precision and bias 

results 

• compute control chart limits 

• plot control charts3

• automatically flag out-of-control 

results 

• maintain and retrieve calibration 

and performance records 

 

3

 http://www.sixsigmaspc.com/ 

Some of these checks (e.g., calibrations) only need to be reviewed as needed or when the actual check is 

performed. Other checks, like zero/span/one point QC checks or programmed routine data range or 

outlier checks that may occur every day are much more easily performed automatically by properly 

programmed computer systems. Earlier versions of this Handbook provided examples of quality control 

charts for zero and span drifts but with the advanced data acquisition system technologies available, the 

development of these charts is fairly straight forward. 

Many vendors offering newer generation data loggers and ambient air information management systems 

provide programming of some of the QC checking capabilities listed above. EPA has also provided 

guidance and a Data Assessment Statistical Calculator (DASC) tool for the precision and bias calculations 

of the quality control checks required in CFR Part 58, Appendix A. In addition, the AMP 255 Report in 

AQS also provides these statistics for many of the QC samples described in Table 10-3 but use of these 

reports requires data reporting to AQS which does not usually occur in time frames needed for quality 

control. 

Figure 10.2 Example Control Chart (courtesy of Six Sigma SPC 

see footnote) 
QA Handbook Vol II, Section 11.0 

Revision No: 1 

Date: 12/08 

Page 1 of 6 

11.0 Instrument Equipment Testing, Inspection and Maintenance

Implementing an ambient air monitoring network, with the various types of equipment needed, is no easy 

task. Through appropriate testing, inspection and maintenance programs, monitoring organizations can 

be assured that equipment is capable of operating at acceptable performance levels. Every piece of 

equipment has an expected life span, and its use should be discontinued if its performance quality ceases 

to meet appropriate standards. For amortization purposes, EPA estimates a 7 year lifespan for most 

monitoring instruments and a somewhat longer lifespan for more permanent types of equipment 

(instrument racks, monitoring shelters etc.). This means that funds for replacing capital equipment are 

provided in resource allocations and monitoring organizations should make the best use of equipment 

replacement resources. Monitoring organizations may be able to prolong the life of equipment but in 

doing so they may run the risk of additional downtime, more upkeep and a greater chance of data 

invalidation, while losing out on newer technologies, better sensitivity/stability and the opportunities for 

better information management technologies. 

Due to the many types of equipment that can be used in an ambient air monitoring program, this section 

provides general guidance on testing, inspection, and maintenance procedures for broad categories of 

equipment only. In most cases, equipment manufacturers include inspection and maintenance 

information in the operating manuals. The role of monitoring organizations, in developing a quality 

system, is to address the scheduling and documentation of routine testing, inspection, and maintenance. 

Detailed maintenance documents should be available for each monitoring site. Elements incorporated 

into testing, inspection and maintenance documents include: 

• equipment lists - by organization and station; 

• spare equipment/parts lists - by equipment, including suppliers; 

• inspection/maintenance frequency - by equipment; 

• testing frequency and source of the test concentrations or equipment; 

• equipment replacement schedules; 

• sources of repair - by equipment; 

• service agreements that are in place; and 

• monthly check sheets and entry forms for documenting testing, inspections and maintenance 

performed. 

11.1 Instrumentation

11.1.1 Analyzers and Samplers

Aside from the specific exceptions described in Appendix C of Part 581

, monitoring methods used for 

SLAMS monitoring must be a reference or equivalent method, designated as such by 40 CFR Part 532

. 

Reference or equivalent methods also must be used at NCore monitoring sites intended for comparison 

with any NAAQS. Among reference and equivalent methods, a variety of analyzer designs and features 

are available. For certain pollutants, analyzers employing different measurement principles are available. 

Some analyzer models only meet the minimum performance specifications (see Table 7-5), while others 

provide a higher level of performance. Section 7 provides information on what aspects to consider when 

selecting a particular monitoring instrument/analyzer. Upon receiving the new analyzer, the user should 

 

1

 Code of Federal Regulations, Title 40, Part 58, Appendix C, U.S. Government Printing Office, 2006. 

2

 Code of Federal Regulations, Title 40, Part 53, U.S. Government Printing Office, 2006. 
QA Handbook Vol II, Section 11.0 

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Page 2 of 6 

carefully read the instructions or operating manual provided by the manufacturer. Information or 

instructions concerning the following should be found in the manufacturer’s manual: 

• unpacking and verifying that all component parts were delivered; 

• checking for damage during shipment; 

• checking for loose fittings and electrical connections; 

• assembling the analyzer; 

• installing the analyzer; 

• calibrating the analyzer; 

• operating the analyzer; 

• electrical and plumbing diagrams; 

• preventive maintenance schedule and procedures; 

• troubleshooting; and 

• a list of expendable parts. 

Many vendors have specific time periods when the initial checks for damage in transit need to be made. 

The monitor should be assembled and set up according to the instructions in the manufacturer’s manual. 

It may be important to do this initial set-up and testing at the main office or laboratory facility (see 

Section 11.1.3) before taking the equipment to the site. Following analyzer set-up, an initial verification 

of performance characteristics such as power flow, noise, and response time and a muti-point verification 

should be performed to determine if the analyzer is operating properly. These guidelines assume that the 

instrument was previously calibrated. If the instrument was disassembled after calibration, or no 

calibration of the instrument had previously been performed, the monitor must have a multi-point 

verification/calibration to ensure it is within acceptable calibration requirements prior to use. Short-term 

span, zero drift and precision should be checked during the initial calibration or measured using 

abbreviated forms of the test procedures provided in 40 CFR Part 533

. Acceptance of the analyzer should 

be based on results from these performance tests. Once accepted, reference and equivalent analyzers are 

guaranteed by the manufacturer to operate within the required performance specifications for one year4

, 

unless major repairs are performed or parts are replaced. In such instances, the analyzers must be 

recalibrated before use. 

11.1.2 Support Instrumentation

Experiences of monitoring organization staff; preventive maintenance requirements, ease of maintenance 

and general reliability play crucial roles in the selection of support equipment. The following examples 

depict general categories of support equipment and typical features to look for when selecting this 

equipment. This list is meant to guide agencies in the selection of equipment and does not represent 

required specifications. 

• Calibration Standards: Calibration standards fall into several categories: 

- mass flow controlled (MFC) devices; 

- standards that meet the 1997 Traceability Protocol for Gaseous Calibration Standards5; 

- permeation devices; 

- photometers; 

 

3

 Code of Federal Regulations, Title 40, Part 53, U.S. Government Printing Office, 2006. 

4

 Code of Federal Regulations, Title 40, Part 53, U.S. Government Printing Office, 2006. 

5

 EPA 600/R-97/121: Traceability Protocol for Gaseous Calibration Standards, September 1997 
QA Handbook Vol II, Section 11.0 

Revision No: 1 

Date: 12/08 

Page 3 of 6 

- flow measurement devices; 

- water pressure measurement devices; 

- barometric pressure measurement devices; and 

- temperature measurement devices. 

It is recommended that the devices be 110 VAC, be compatible with data acquisition systems for 

automated calibrations, and have digital compatibility or true transistor-transistor logic (TTL). 

The most common standards are MFC devices and permeation devices. Both use dilution air to 

obtain the needed output pollutant concentration. 

• Data Acquisition Systems (DAS): DAS should have at least 32-bit logic for improved 

performance (DAS with at least 16-bit logic can still be used); have modem and internet 

capabilities; allow remote access and control; allow for digital input; and be able to initiate 

automated calibrations and polling. It is also recommended that DAS have software compatible 

with AQS and AQI reporting and editing. Both data loggers and analog chart recorders may be 

used for recording data; however, the storage, communicability, and flexibility of DAS coupled 

with data loggers makes the DAS systems the preferred option. More information on DAS is 

found in Section 14. 

• Instrument Racks: Instrument racks should be constructed of steel and be able to accept sliding 

trays or rails. Open racks help to keep instrument temperatures down and allow air to circulate 

freely. 

• Instrument Benches: Instrument benches should be of sufficient space to allow adequate room 

for multiple instruments with room to work and be capable of supporting a fair amount of weight 

(> 100 lbs). Slate or other hard, water-proof materials (e.g., steel) are recommended. 

• Zero Air Systems: Zero air systems should be able to deliver 10 liters/min of air that is free of 

ozone, NO, NO2, and SO2 to 0.001 ppm and CO and non-methane hydrocarbons to 0.1 ppm. 

There are many commercially available systems; however, simple designs can be obtained by 

using a series of canisters. 

11.1.3 Laboratory Support

While it is not required, monitoring organizations should employ full laboratory facilities. These facilities 

should be equipped to test, repair, troubleshoot, and calibrate all analyzers and support equipment 

necessary to operate the ambient air monitoring network. In cases where individual laboratories are not 

feasible, a monitoring organization may be able to find a central laboratory where these activities can be 

performed. 

It is recommended that the laboratory be designed to accommodate the air quality laboratory/shop and 

PM10 and PM2.5 filter rooms, as well as enforcement instrumentation support activities. The air quality 

portion consists of several benches flanked by instrument racks. One bench and rack are dedicated to 

ozone traceability. The other instrument racks are designated for calibration and repair. A room should 

be set aside to house spare parts and extra analyzers. 

A manifold/sample cane should be mounted behind the bench. If possible, a sample cane that passes 

through the roof to allow analyzers that are being tested to sample outside air should be mounted to the 
QA Handbook Vol II, Section 11.0 

Revision No: 1 

Date: 12/08 

Page 4 of 6 

bench. This also allows any excess calibration gas to be exhausted to the atmosphere. It is recommended 

that the pump room be external to the building to eliminate noise. 

Each bench area should have an instrument rack attached to the bench. The instrument rack should be 

equipped with sliding trays or rails that allow easy installation of instruments. If instrumentation needs to 

be repaired and then calibrated, this can be performed on the bench top or within the rack. Analyzers then 

can be allowed to warm up and be calibrated by a calibration unit. Instruments that are to be tested are 

connected to the sample manifold and allowed to sample air in the same manner as if the analyzer were 

being operated within a monitoring station. The analyzer is connected to an acquisition system (e.g., 

DAS, data logger, chart recorder, etc.) and allowed to operate. Any intermittent problems that occur can 

be observed on the data logger/chart recorder. The analyzer can be allowed to operate over several days 

to see if anomalies or problems reoccur; if they do, there is a record of them. If the instrument rack has a 

DAS and calibrator, nightly auto calibrations can be performed to see how the analyzer reacts to known 

gas concentrations. In addition, the ozone recertification bench and rack should be attached to a work 

bench. The rack should house the local ozone primary standard and the ozone transfer standards that are 

being checked for recertification. Zero air is plumbed into this rack for the calibration and testing of 

ozone analyzers and transfer standards. 

11.2 Preventive Maintenance

Every monitoring organization should develop a preventive maintenance program. Preventive 

maintenance is what its name implies; maintaining the equipment within a network to prevent downtime 

and costly repairs and data loss. Preventive maintenance is an ongoing element of quality control and is 

typically enveloped into the daily routine. In addition to the daily routine, scheduled activities must be 

performed monthly, quarterly, semi-annually and annually. 

Preventive maintenance is the responsibility of the station operators and the supervisory staff. It is 

important that the supervisor review the preventive maintenance work and continually check the schedule. 

The supervisor is responsible for making sure that preventive maintenance is being accomplished in a 

timely manner. Preventive maintenance is not a static process; procedures must be updated for many 

reasons, including, but not limited to, new models or types of instruments and new or updated methods. 

The preventive maintenance schedule is changed whenever an activity is completed or performed at an 

alternate time. For instance, if a multipoint calibration is performed in February instead of on the 

scheduled date in March, then the subsequent six-month calibration date moves from September to 

August. On a regular basis, the supervisor should review the preventive maintenance schedule with the 

station operators. Following all repairs, the instruments must be verified (multi-point) or calibrated. 

Lists can facilitate the organization and tracking of tasks and improve the efficiency of preventive 

maintenance operations. A checklist of regular maintenance activities (e.g., periodic zero-span checks, 

daily routine checks, data dump/collection, calibrations, etc.) is recommended. A spare parts list, 

including relevant catalog numbers, is also recommended, as it facilitates the ordering of replacement 

parts. Such a list should be readily accessible and should include the types and quantities of spare parts 

already on-hand. 
QA Handbook Vol II, Section 11.0 

Revision No: 1 

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Page 5 of 6 

11.2.1 Station Maintenance

Station maintenance is an element of preventive maintenance that does not occur on a routine basis; 

rather, these tasks usually occur on an “as needed” basis. Station maintenance items are checked monthly 

or whenever an agency knows that the maintenance needs to be performed. Examples of station 

maintenance items include: 

• floor cleaning; 

• shelter inspection; 

• air conditioner repair; 

• AC filter replacement; 

• weed abatement and grass cutting; 

• roof repair; 

• general cleaning; 

• inlet and manifold cleaning; 

• manifold exhaust blower lube; 

• desiccant replacement; and 

• ladder, safety rails, safety inspection, if applicable. 

Simple documentation of these activities, whether in station logs or electronic logs, helps provide 

evidence of continuous attention to data quality. 

11.2.2 Routine Operations 

Routine operations are the checks that occur at specified periods of time during a monitoring station visit. 

These duties must be performed and documented in order to operate a monitoring network at optimal 

levels. Examples of typical routine operations are detailed in Table 11-1. 

Table 11-1 Routine Operation Checks 

Item Each Visit Weekly/Monthly Minimum 

Review Data X 

Mark charts, where applicable X 

Check/Oil Exhaust Blower X 

Check Exterior X 

Check/Change Desiccant X 

Manifold Leak Test X 

Inspect tubing X 

Replace Tubing Annually1

Inspect manifold and cane X 

Clean manifold and cane Every 6 months or as needed 

Check HVAC systems X 

Check electrical connections X 

Field site supply inventory X 1

If tubing is used externally as an inlet devices it may need to be replaced every 6 months or more frequently depending upon site 

specific issues. 

In addition to these items, the exterior of the building, sample cane, meteorological instruments and 

tower, entry door, electrical cables, and any other items deemed necessary to check, should be inspected 

for wear, corrosion, and weathering. Costly repairs can be avoided in this manner. 
QA Handbook Vol II, Section 11.0 

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Page 6 of 6 

11.2.3 Instrument and Site Logs

Each instrument and piece of support equipment (with the exception of the instrument racks and benches) 

should have an Instrumentation Repair Log (either paper or electronic). The log should contain the repair 

and calibration history of that particular instrument. Whenever multipoint calibration, instrument 

maintenance, repair, or relocation occurs, detailed notes are written in the instrumentation log. The log 

contains the most recent multipoint calibration report, a preventive maintenance sheet, and the acceptance 

testing information or reference to the location of this information. If an instrument is malfunctioning and 

a decision is made to relocate that instrument, the log travels with that device. The log can be reviewed 

by staff for possible clues to the reasons behind the instrument malfunction. In addition, if the instrument 

is shipped to the manufacturer for repairs, it is recommended that a copy of the log be sent with the 

instrument. This helps non-agency repair personnel with troubleshooting instrument problems. Improper 

recording of instrument maintenance can complicate future repair and maintenance procedures. The 

instrument log should be detailed enough to determine easily and definitively which instrument was at 

which sites over any given time period. If a problem is found with a specific instrument, the monitoring 

staff should be able to track the problem to the date it initially surfaced and invalidate data even if the 

instrument was used at multiple sites. 

The site log is a chronology of the events that occur at the monitoring station. The log is an important 

part of station maintenance because it contains the narrative of past problems and solutions to those 

problems. Site log notes should be written in the form of a narrative, rather than shorthand notes or 

bulleted lists. Examples of items that should be recorded in the site log are: 

• the date, time, and initials of the person(s) who have arrived at the site; 

• brief description of the weather (e.g., clear, breezy, sunny, raining); 

• brief description of exterior of the site. Any changes that might affect the data should be recorded 

– for instance, if someone is parking a truck or tractor near the site, this may explain high NOx

values; 

• any unusual noises, vibrations, or anything out of the ordinary; 

• records of any station maintenance or routine operations performed; 

• description of the work accomplished at the site (e.g., calibrated instruments, repaired analyzer); 

and 

• detailed information about the instruments that may be needed for repairs or troubleshooting. 

It is not required that the instrument and site logs be completely independent of each other. However, 

there is an advantage to having separate instrument logs. If instruments go in for repair, they may 

eventually be sent to another site. Having a separate instrument log allows the log to “travel” with the 

instrument. Keeping electronic instrument and station maintenance logs at stations and at centralized 

facilities (see LIMS discussion Section 8) also has record keeping advantages, but there needs to be a way 

that these records can be considered official and not be tampered with or falsified. Newer electronic 

signature technologies are helping ensure that electronic records can be considered official. It is 

important, however, that all of the required information for each instrument and site be properly recorded 

using a method that is comprehensive and easily understood. Many monitoring organizations have 

developed standard station maintenance forms that contain all the items to be checked and the frequency 

of those checks. It then becomes a very simple procedure to use this form to check off and initial the 

activities that were performed. 
QA Handbook Vol II, Section 12.0 

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Page 1 of 11 

12.0 Calibrations

Calibration is defined as: 

the comparison of a measurement standard, instrument, or item with a standard or instrument of 

higher accuracy to detect and quantify inaccuracies and to report or eliminate those 

inaccuracies by adjustment1

. 

Prior to the implementation of any ambient air monitoring activities, the sampling and analysis equipment 

must be checked to assure it is within calibration tolerances, and if it fails these tolerances, must be 

appropriately calibrated. This function is most routinely carried out at the field monitoring location. 

 

1

 American National Standard Quality Systems for Environmental Data and Technology Programs ANSI /ASQ E4 

http://www.asq.org/ 

Calibration of an analyzer or instrument establishes the quantitative relationship between an actual value 

of a standard, be it a pollutant concentration, a temperature, or a mass value (in ppm, o

C or Fg, etc.) and 

the analyzer's response (chart recorder reading, output volts, digital output, etc.). This relationship is 

used to convert subsequent analyzer response values to corresponding concentrations. Once an 

instrument’s calibration relationship is established it is checked/verified at reasonable frequencies to 

verify that it remains in calibration. 

Verification Versus Calibration 

Since the term calibration is associated with an adjustment in either the instrument or software, these 

adjustments should be minimized as much as possible. Sometimes performing frequent adjustments to 

provide the “most accurate data possible” can be self-defeating and be the cause of additional 

measurement uncertainty. Therefore, quality control procedures that include verification checks and 

multi-point calibration verifications are considered “checks without correction” and are used to ensure 

the instruments are within the calibration tolerances. Usually these tolerances have been developed so 

that as long as the instrument is within these tolerances, adjustments do not need to be made. However, 

verifications should be implemented at reasonable frequencies to avoid invalidating significant amounts 

of data. 

NOTE: When the term “calibration” is used in the remainder of this section, it is assumed 

that multi-point verification is initially performed and the operator has concluded that 

calibration (adjustment) is necessary. 

NOTE: EPA does not recommend post-processing of data to “correct” for data failing one 

point or multi-point verifications. 
QA Handbook Vol II, Section 12.0 

Revision No: 1 

Date: 12/08 

Page 2 of 11 

Each analyzer should be calibrated as directed by the analyzer's operation or instruction manual and in 

accordance with the general guidance provided here. For reference methods for CO, NO2, SO2 and O3, 

detailed calibration procedures may also be found in the appropriate reference method Appendix in 40 

CFR Part 502

 and the method guidance and technical assistance documents listed in the fact sheets in 

Appendix A. 

Calibrations should be carried out at the field monitoring site by allowing the analyzer to sample test 

atmospheres containing known pollutant concentrations. The analyzer to be calibrated should be in 

operation for at least several hours (preferably overnight) prior to the calibration so that it is fully 

warmed up and its operation has stabilized. During the calibration, the analyzer should be operating in 

its normal sampling mode, and it should sample the test atmosphere through all filters, scrubbers, 

conditioners, and other components used during normal ambient sampling and through as much of the 

ambient air inlet system as is practicable. All operational adjustments to the analyzer should be 

completed prior to the calibration (see section 12.7). Some analyzers can be operated on more than one 

range. For sites requiring the use of FRM or FEMs (NAAQS sites), the appropriate ranges are identified 

in the Designated Reference and Equivalent Method List found on AMTIC3

. Analyzers that will be used 

on more than one range or that have auto-ranging capability should be calibrated separately on each 

applicable range. 

 

2 http://www.access.gpo.gov/nara/cfr/cfr-table-search.html 3 http://www.epa.gov/ttn/amtic/criteria.html 

Calibration documentation should be maintained with each analyzer and also in a central backup file. 

Documentation should be readily available for review and should include calibration data, calibration 

equation(s) (and curve, if prepared), analyzer identification, calibration date, analyzer location, 

calibration standards used and their traceability, identification of calibration equipment used, and the 

person conducting the calibration. 

12.1 Calibration Standards and Reagents 

Calibration standards are: 

• Reagents of high grade 

• Gaseous standards of known concentrations that are certified as EPA protocol gasses 

• Instruments and or standards of high sensitivity and repeatability. 

12.1.1 Reagents 

In some cases, reagents are prepared prior to sampling. Some of these reagents will be used to calibrate 

the equipment, while others will become an integral part of the sample itself. In any case, their integrity 

must be carefully maintained from preparation through analysis. If there are any doubts about the method 

by which the reagents for a particular test were prepared or about the competence of the laboratory 

technician preparing them, the credibility of the ambient air samples and the test results will be 

diminished. It is essential that a careful record be kept listing the dates the reagents were prepared, by 

whom, and their locations at all times from preparation until actual use. Prior to the test, one individual 

should be given the responsibility of monitoring the handling and the use of the reagents. Each use of the 

reagents should be recorded in a field or lab notebook. 
QA Handbook Volume II, Section 12.0 

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Date: 12/08 

Page 3 of 11 

Chemical reagents, solvents, and gases are available in various grades. Reagents can be categorized into 

the following six grades4

: 

1. Primary standard - Each lot is analyzed, and the percentage of purity is certified. 

2. Analyzed reagents- Can fall into 2 classes: (a) each lot is analyzed and the percentages of 

impurities are reported; and (b) conformity with specified tolerances is claimed, or the maximum 

percentages of impurities are listed. 

3. USP and NF Grade - These are chemical reference standards where identity and strength 

analysis are ensured. 

4. “Pure,” “c.p.,” “chemically pure,” “highest purity” - These are qualitative statements for 

chemicals without numerical meaning. 

5. “Pure,” “purified,” “practical grades” - These are usually intended as starting substances for 

laboratory syntheses. 

6. Technical or commercial grades - These are chemicals of widely varying purity. 

The reference and equivalent methods define the grades and purities needed for the reagents and gases 

required in the Ambient Air Quality Monitoring Program. 

All reagent containers should be properly labeled either with the original label or, at a minimum, the 

reagent, date prepared, expiration date, strength, preparer, and storage conditions. Leftover reagents used 

during preparation or analysis should never be returned to bottles. 

12.1.2 Gaseous Standards 

In general, ambient monitoring instruments should be calibrated by allowing the instrument to sample and 

analyze test atmospheres of known concentrations of the appropriate pollutant in air. The following is an 

excerpt from 50 CFR Part 58, Appendix A Section 2.6.1: 

 

“Gaseous pollutant concentration standards (permeation devices or cylinders of compressed gas) 

used to obtain test concentrations for carbon monoxide (CO), sulfur dioxide (SO2), nitrogen 

oxide (NO), and nitrogen dioxide (NO2) must be traceable to either a National Institute of 

Standards and Technology (NIST) Traceable Reference Material (NTRM) or a NIST-certified 

Gas Manufacturer’s Internal Standard (GMIS), certified in accordance with one of the 

procedures given in reference 4 of this appendix. Vendors advertising certification with the 

procedures provided in reference 4 of this appendix and distributing gasses as ‘‘EPA Protocol 

Gas’’ must participate in the EPA Protocol Gas Verification Program or not use ‘‘EPA’’ in any 

form of advertising.” 

"Traceable" is defined in 40 CFR Parts 50 and 58 as meaning that a local standard has been compared and 

certified, either directly or via not more than one intermediate standard, to a primary standard such as a 

National Institute of Standards and Technology Standard Reference Material (NIST SRM) or a 

USEPA/NIST-approved Certified Reference Material (CRM)”. Normally, the working standard should 

be certified directly to the SRM or CRM, with an intermediate standard used only when necessary. Direct 

use of a CRM as a working standard is acceptable, but direct use of an NIST SRM as a working standard 

is discouraged because of the limited supply and expense of SRM's. At a minimum, the certification 

 

4

 Quality Assurance Principles for Analytical Laboratories, 3rd Edition. By Frederick M. Garfield, Eugene Klesta, 

and Jerry Hirsch. AOAC International (2000). http://www.aoac.org/
QA Handbook Volume II, Section 12.0 

Revision No: 1 

Date: 12/08 

Page 4 of 11 

procedure for a working standard should: 

• establish the concentration of the working standard relative to the primary standard; 

• certify that the primary standard (and hence the working standard) is traceable to a NIST primary 

standard; 

• include a test of the stability of the working standard over several days; and 

• specify a recertification interval for the working standard. 

Table 12-1 suggests the requirements for the certification period for verification and calibration standards 

used in the ambient air program. 

Certification of the working standard may be established by either the supplier or the user of the standard. 

As describe in CFR, gas supplier advertising “EPA Protocol Gas” will be required to participate in the 

EPA Protocol Gas Verification Program. Information on this program, including the gas supplier 

participating in the program, can be found on AMTIC5

. EPA has developed procedures for the 

establishment of protocol gasses in the document: EPA Traceability Protocol for Assay and Certification 

of Gaseous Calibration Standards6

. 

Test concentrations of ozone must be traceable to a primary standard (see discussion of primary standards 

below) UV photometer as described in 40 CFR Part 50, Appendix D and the guidance document: 

Transfer Standards for the Calibration of Ambient Air Monitoring Analyzers for Ozone7

. 

Test concentrations at zero concentration are considered valid standards. Although zero standards are not 

required to be traceable to a primary standard, care should be exercised to ensure that zero standards are 

adequately free of all substances likely to cause a detectable response from the analyzer and at a 

minimum, below the lower detectable limit of the criteria pollutants being measured. Periodically, 

several different and independent sources of zero standards should be compared. The one that yields the 

lowest response can usually (but not always) be assumed to be the “best zero standard.” If several 

independent zero standards produce exactly the same response, it is likely that all the standards are 

adequate. 

Table 12-1 Certification Periods for Compressed Gas Calibration Standards in Aluminum Cylinders That 

Are Certified Under the EPA Protocol Gas Program

Certified components Balance gas Applicable 

concentration range

Certification period 

(months)

Ambient nonmethane organics (15 components) Nitrogen 5 ppb 24 

Ambient toxic organics (19 components) Nitrogen 5 ppb 24 

Aromatic organic gases Nitrogen >0.25 ppm 36 

Carbon dioxide Nitrogen or air

a

 >300 ppm 36 

Carbon monoxide Nitrogen or air >8 ppm 36 

Hydrogen sulfide Nitrogen >4 ppm 12 

 

5 http://www.epa.gov/ttn/amtic/ 6 http://www.epa.gov/ttn/emc/news.html 7 EPA-600/4-79-056. U.S. Environmental Protection Agency, Research Triangle Park, NC 27711. September 1979.

http://www.epa.gov/ttn/amtic/files/ambient/criteria/reldocs/4-79-056.pdf 
QA Handbook Volume II, Section 12.0 

Revision No: 1 

Date: 12/08 

Page 5 of 11 

Certified components Balance gas Applicable 

concentration range

Certification period 

(months)

Methane Nitrogen or air >1 ppm 36 

Nitric oxide Oxygen-free nitrogenb >4 ppm 24 

Nitrous oxide Air >300 ppb 36 

Oxides of nitrogen (i.e., sum of nitrogen dioxide 

and nitric acid) Air >80 ppm 24 

Oxygen Nitrogen >0.8% 36 

Propane Nitrogen or air >1 ppm 36 

Sulfur dioxide Nitrogen or air 40 to 499 ppm 24 

Sulfur dioxide Nitrogen or air >500 ppm 36 

Multicomponent mixtures — — See textc

Mixtures with lower concentrations — — See text 

a

When used as a balance gas, "air" is defined as a mixture of oxygen and nitrogen where the minimum concentration of oxygen is 

10 percent and the concentration of nitrogen is greater than 60 percent. b

Oxygen-free nitrogen contains >0.5 ppm of oxygen. 

c

 Text refers to Section 2 of EPA Protocol Gas Guidance Document 

Certification periods decrease for concentrations below the applicable concentration ranges provide in 

Table 12-1. For example the certification period for SO2 standards between 13-40 ppm is 6 months. 

Also, tank size may affect stability in low level standards. Some gas manufacturers claim that standards 

supplied in smaller tanks are stable for longer periods of time then the same concentration in larger tanks. 

Although this claim has not been verified if true it may be helpful in making purchasing decisions. 

Primary Reference Standards

A primary reference standard can be defined as a homogenous material with specific properties, such as 

identity, unity, and potency that has been measured and certified by a qualified and recognized 

organization8

, such as the NIST SRMs. NIST also describes a Primary Reference Standard as a standard 

that is designated or widely acknowledged as having the highest metrological qualities and whose value is 

accepted without reference to other standards of the same quantity. For example, the NIST-F1 Atomic 

Clock9

, is recognized as a primary standard for time and frequency. A true primary standard like NIST-F1 

establishes maximum levels for the frequency shifts caused by environmental factors. By summing or 

combining the effects of these frequency shifts, it is possible to estimate the uncertainty of a primary 

standard without comparing it to other standards. NIST maintains a catalog of SRMs that can be accessed 

through the Internet10. Primary reference standards are usually quite expensive and are often used to 

calibrate, develop, or assay working or secondary standards. In order to establish and maintain NIST 

traceability the policies posted at the NIST Website11 should be observed. 

 

8

 Garfield, Frederick M. , “Quality Assurance Principles for Analytical Laboratories” Association of Official 

Analytical Chemists, Arlington VA, 1984 

9 http://tf.nist.gov/timefreq/cesium/fountain.htm 10 http://www.nist.gov 11 http://ts.nist.gov/traceability/
QA Handbook Volume II, Section 12.0 

Revision No: 1 

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Page 6 of 11 

It is important that primary reference standards are maintained, stored, and handled in a manner that 

maintains their integrity. These samples should be kept under secure conditions and records should be 

maintained that document chain of custody information. 

12.1.3 Instruments 

The accuracy of various measurement devices in sampling and continuous instruments is very important 

to data quality. For example, in order to produce the correct flow rate to establish an accurate PM2.5 cut 

point, the temperature and barometric pressure sensors, as well as the flow rate device, must be producing 

accurate measurements. Table 12-2 provides some of the more prevalent instruments that need to be 

calibrated at a minimum annually or when shown through various verification checks to be out of 

acceptable tolerances. In addition, the audit standards used to implement the checks and calibrations 

should be certified annually in order to establish their accuracy and traceability to higher standards 

(NIST). 

Table 12-2 Instruments and Devices Requiring Calibration and Certifications. 

Criteria Acceptable Range

40 CFR 

Reference

Verification/Calibration of devices in sampler/analyzer/laboratory against an authoritative standard 

Barometric Pressure " 10 mm Hg Part 50, App.L, Sec 9.3 

Temperature " 2EC of standard Part 50, App.L, Sec 9.3 

Flow Rate " 2% of transfer standard Part 50, App.L, Sec 9.2 

Design Flow Rate Adjustment " 2% of design flow rate Part 50, App.L, Sec 9.2.6 

Clock/timer Verification 1 min/mo Part 50, App.L, Sec 7.4 

Mirobalance Calibration Readability 1 Fg 

Repeatability 1Fg 

Part 50, App.L, Sec 8.1 

Verification/Calibration of devices in shelter or lab against an authoritative standard

Lab Temperature " 2EC not described 

Lab Humidity " 2% not described 

Mirobalance Calibration Readability 1 Fg 

Repeatability 1Fg 

Part 50, App.L, Sec 8.1 

Verification/calibration standards requiring certification annually 

Standard Reference 

Photometer (SRP) 

"4% or "4 ppb (whichever greater) 

RSD of six slopes # 3.7%

not described 

SRP recertification to local 

primary standard 

Std. Dev. of 6 intercepts 1.5 

New slope = + 0.05% of previous

not described 

Flow rate " 2% of NIST –Traceable Standard Part 50, App L Sec 9.2 

Pressure " 1 mm Hg resolution, " 1 mm Hg 

accuracy

not described 

Temperature " 0.1EC of standard resolution," 0.5EC 1 

mm Hg accuracy

not described 

Gravimetric Standards 0.025 mg not described 
QA Handbook Volume II, Section 12.0 

Revision No: 1 

Date: 12/08 

Page 7 of 11 

12.2 Multi-point Verifications/Calibrations

Multi-point calibrations consist of a zero and 4 upscale points, the highest being a concentration between 

80 percent and 90 percent of the full scale range of the analyzer under calibration. Multi-point 

calibrations are used to establish or verify the linearity of analyzers upon initial installation, after major 

repairs and at specified frequencies. Most modern analyzers have a linear or very nearly linear response 

with concentration. If a non-linear analyzer is being calibrated, additional calibration points should be 

included to adequately define the calibration relationship, which should be a smooth curve. Calibration 

points should be plotted or evaluated statistically as they are obtained so that any deviant points can be 

investigated or repeated immediately. 

Most analyzers have zero and span adjustment controls, which should be adjusted based on the zero and 

highest test concentrations, respectively, to provide the desired scale range within the analyzer's 

specifications (see section 12.5). For analyzers in routine operation, unadjusted (''as is") analyzer zero 

and span response readings should be obtained prior to making any zero or span adjustments. 

NO/NO2/NOx analyzers may not have individual zero and span controls for each channel; the analyzer's 

operation/instruction manual should be consulted for the proper zero and span adjustment procedure. 

Zero and span controls often interact with each other, so the adjustments may have to be repeated several 

times to obtain the desired final adjustments. 

After the zero and span adjustments have been completed and the analyzer has been allowed to stabilize 

on the new zero and span settings, all calibration test concentrations should be introduced into the 

analyzer for the final calibration. The final, post-adjusted analyzer response readings should be obtained 

from the same device (chart recorder, data acquisition system, etc.) that will be used for subsequent 

ambient measurements. The analyzer readings are plotted against the respective test concentrations, and 

the best linear (or nonlinear if appropriate) curve to fit the points is determined. Ideally, least squares 

regression analysis (with an appropriate transformation of the data for non-linear analyzers) should be 

used to determine the slope and intercept for the best fit calibration line of the form, y = mx + a, where y 

represents the analyzer response, x represents the pollutant concentration, m is the slope, and a is the xaxis intercept of the best fit calibration line. When this calibration relationship is subsequently used to 

compute concentration measurements (x) from analyzer response readings (y), the formula is transposed 

to the form, x = (y - a)/m. 

For the gaseous pollutants, the verification/calibration is considered acceptable if all calibration points fall 

within 2% of the full scale, best fit straight line. For manual samplers, devices (flow rate, temperature, 

pressure) are checked at different settings. Acceptance criteria for these devices can be found in the 

MQO Tables in Appendix D. 

As a quality control check on calibrations, the standard error or correlation coefficient can be calculated 

along with the regression calculations. A control chart of the standard error or correlation coefficient 

could then be maintained to monitor the degree of scatter in the calibration points and, if desired, limits of 

acceptability can be established. 
QA Handbook Volume II, Section 12.0 

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12.3 Frequency of Calibration and Analyzer Adjustment

An analyzer should be calibrated (or recalibrated): 

• upon initial installation, 

• following physical relocation, 

• after any repairs or service that might affect its calibration, 

• following an interruption in operation of more than a few days, 

• upon any indication of analyzer malfunction or change in calibration, and 

• at some routine interval (see below). 

When calibration relationships are applied to 

analyzer responses to determine actual 

concentrations, it is suggested that the analyzer be 

recalibrated periodically to maintain close 

agreement. The frequency of this routine periodic 

recalibration is a matter of judgment and is a 

tradeoff among several considerations, including: 

the inherent stability of the analyzer under the 

prevailing conditions of temperature, pressure, line 

voltage, etc., at the monitoring site; the cost and 

inconvenience of carrying out the calibrations; the 

quality of the ambient measurements needed; the 

number of ambient measurements lost during the 

calibrations; and the risk of collecting invalid data 

because of a malfunction or response problem with 

the analyzer that wouldn't be discovered until a 

calibration is carried out. 

When a new monitoring instrument is first installed, 

zero/span and one point QC checks should be very 

frequent, perhaps daily or 3 times per week, 

because little or no information is available on the 

drift performance of the analyzer. With the 

advancement in data acquisition system technology, 

many monitoring organizations are running these 

QC checks daily. However, the QC checks are 

required to be implemented every two weeks. 

Information on another unit of the same model 

analyzer may be useful; however, individual units of the same model may perform quite differently. 

After enough information on the drift performance of the analyzer has been accumulated, the calibration 

frequency can be adjusted to provide a suitable compromise among the various considerations mentioned 

above. 

To facilitate the process of determining calibration frequency, it is strongly recommended that control 

charts be used to monitor the zero/span and one-point QC drift performance of each analyzer. Control 

charts can be constructed in different ways, but the important points are to visually represent and 

statistically monitor drift, and to be alerted if the drift becomes excessive so that corrective action can be 

Invalidate data, adjust 

and recalibrate analyzer

Zero

Drift

Span 

Drift

 + 10 to 15 ppb +15%

(1 to 1.5 ppm CO)

Adjust and recalibrate analyzer

+3 std dev

+1 std dev

 0

 -1 std dev

-3 std dev

Invalidate data, adjust 

and recalibrate analyzer

Adjustment

 optional

Analyzer adjustment

not recommended

Adjustment

 optional

 -10 to -15 ppb

(-1 to -1.5 ppm CO) -15%

adjust and recalibrate analyzer

Normal analyzer

range

Figure 12.1 Suggested zero/span drift limits 
QA Handbook Vol II, Section 12.0 

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Page 9 of 11 

taken. Such control charts make important use of the unadjusted zero and span response readings. 

NOTE: Many newer technology analyzers have an “auto-zeroing” function incorporated in the 

instrument that can be implemented at user defined frequencies. Use of internal auto-zero functions 

typically does not need any post-processing of the data. EPA finds auto or manual zero adjustment 

acceptable, but does not recommend making automatic or manual adjustments (corrections) to the span 

until drift is unacceptable and warrants a calibration. 

In continuous monitoring, the total cumulative drift, average of the absolute values of the individual 

drifts, and the standard deviation of the individual drifts should be calculated on a running basis over the 

last 100 or so days. Figure 12.1 summarizes some of the ranges and control chart limits that can be used 

to decide when calibration is warranted. 

12.4 Adjustments to Analyzers 

Ideally, all ambient measurements obtained from an analyzer should be calculated on the basis of the 

most current multipoint calibration or on the basis of both the previous and subsequent calibrations (see 

Section 12.5). Some acceptable level of drift (i.e., deviation from an original or nominal response curve) 

can be allowed before physical adjustments (a calibration) must be made because the calibration curve 

used to calculate the ambient measurements is kept in close agreement with the actual analyzer response. 

The chief limitations are the amount of change in the effective scale range of the analyzer that can be 

tolerated and possible loss of linearity in the analyzer's response due to excessive deviation from the 

design range. Cumulative drifts of up to 15 percent of full scale from the original or nominal zero and 

span values may not be unreasonable, subject to the limitations mentioned above. 

Due to the advancement in monitoring technologies, ambient air monitors are much more stable and 

adjustments not as necessary. Earlier versions of this Handbook included sections for zero/span 

calibrations as well as physical zero/span adjustments. Precise adjustment of the zero and span controls 

may not be possible because of: (1) limited resolution of the controls, (2) interaction between the zero 

and span controls, and (3) possible delayed reaction to adjustment or a substantial stabilization period 

after adjustments are made. Precise adjustments may not be necessary because calibration of the analyzer 

following zero and span adjustments will define the precise response characteristic (calibration curve). 

EPA feels that frequent adjustments of instruments should not be necessary and may in fact lead to more 

data quality uncertainty. EPA does not recommend span adjustments be made between multi-point 

calibrations but zero adjustments are appropriate. 

EPA is no longer including guidance suggesting that the calibration equation be updated after each 

zero/span check and suggests the ambient readings be calculated from the most recent multipoint 

calibration curve or from a fixed nominal or "universal" calibration curve (Section 12.5). In this case, the 

zero and span checks serve only to measure or monitor the deviation (drift error) between the actual 

analyzer response curve and the calibration curve used to calculate the ambient measurements. 

Automatic Self-Adjusting Analyzers

Some air monitoring analyzers are capable of periodically carrying out automatic zero and span 

calibrations and making their own zero and span self adjustments to predetermined readings. Automatic 

zero adjustments are considered reasonable, but EPA discourages the use of automatic span adjustments. 
QA Handbook Vol II, Section 12.0 

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If the automatic zero standards pass through the sample inlet and sample conditioning system and both the 

adjusted and unadjusted zero response readings can be obtained from the data recording device, then the 

zero adjustment can be implemented. 

12.5 Data Reduction Using Calibration Information

As noted previously, an analyzer's response calibration curve relates the analyzer response to actual 

concentration units of measure, and the response of most analyzers tends to change (drift) 

unpredictably with passing time. These two conditions must be addressed in the mechanism that is used 

to process the raw analyzer readings into final concentration measurements. Three practical methods are 

described below. They are listed in order of preference, 

1) "Universal" Calibration--A fixed, "universal" calibration is established for the analyzer and used to 

calculate all ambient readings. All verifications and checks are used to measure the deviation of the 

current analyzer response from the universal calibration. Whenever this deviation exceeds the established 

zero and span adjustment limits, the analyzer is recalibrated. 

2) Major Calibration Update--In this method, the calibration slope and intercept used to calculate 

ambient measurements are updated only for "major" calibration (i.e., semi-annual or annual multi-point 

verification/calibrations). All ambient measurements are calculated from the most recent major 

calibration. Between major calibrations, periodic zero and span calibrations are used to measure the 

difference between the most recent major calibration and the current instrument response. Physical or 

automated adjustments of the zero may be appropriate however span adjustment to restore a match 

between the current analyzer response and the most recent major calibration is not suggested. Whenever 

this deviation exceeds the established zero and span adjustment limits, the analyzer is recalibrated. 

3) Step-Change Update-- the adjusted slope and intercept of the most recent calibration are used to 

calculate all subsequent ambient readings until updated by another calibration (i.e., no interpolation). No 

unadjusted zero or span readings are used, and ambient measurements can be calculated in real time if 

desired. 

A significant problem with this method is acquiring the requisite calibration data and making sure they 

are merged correctly with the ambient data to facilitate the required calculations. Some automated data 

acquisition systems support this application by making special provisions to acquire and process periodic 

zero and span data. One way to ensure that the zero/span data are correctly merged with the ambient 

readings is to code the zero and span values directly into the data set at the location corresponding to the 

time of calibration, replacing the normal hourly reading that is lost anyway because of the calibration. 

These data can be marked (such as with a negative sign) to differentiate them from ambient data and later 

deleted from the final report printout. When zero and span data are acquired automatically by a data 

acquisition system for direct computer processing, the system must be sufficiently sophisticated to: 

• ensure that zero or span data is never inadvertently reported as ambient measurements 

• ignore transient data during the stabilization period before the analyzer has reached a stable zero 

or span response (this period may vary considerably from one analyzer to another) 
QA Handbook Vol II, Section 12.0 

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Page 11 of 11 

• average the stable zero and span readings over some appropriate time period so that the zero or 

span reading obtained accurately represents the analyzers true zero or span response 

• ignore ambient readings for an appropriate period of time immediately following a zero or span 

reading until the analyzer response has restabilized to the ambient-level concentration 

12.6 Validation of Ambient Data Based on Calibration Information

When zero or span drift validation limits (see Figure 12.1) are exceeded, ambient measurements should 

be invalidated back to the most recent acceptable zero/span/one-point QC check where such 

measurements are known to be valid. Also, data following an analyzer malfunction or period of nonoperation should be regarded as invalid until the next subsequent calibration unless unadjusted zero and 

span readings at that calibration can support its validity. 

Documentation 

All data and calculations involved in these calibration activities should be recorded in the instrument log 

book described in Section 11. 
 QA Handbook Vol II, Section 13.0 

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13.0 Inspection/Acceptance for Supplies and Consumables

Both field operations and laboratory operations need supplies and consumables. The focus of this section 

is the management of laboratory and field sampling supplies and consumables. For information on the 

actual field/lab supplies and consumables needed for any specific method, see the reference method in 40 

CFR Part 501

, the general guidance methods and technical assistance documents on AMTIC2 and the 

manufacturer’s operations manuals. From this information, monitoring organizations, as part of the 

QAPP requirements, will develop specific SOPs for its monitoring and analytical methods. One section of 

the SOPs requires a listing of the acceptable supplies and consumables for the method. 

Pollutant parameters are measured using electronic (e.g., continuous emission monitors, FTIRs, etc...), 

wet chemical techniques, or physical methods. Chemical analysis always involves the use of consumable 

supplies that must be replaced on a schedule consistent with their stability and with the rate at which 

samples are taken. Currently used physical methods require adequate supplies of chemicals for operation 

for three months so that the supplier can comply with the delivery schedules. In some cases, analytical 

reagents for specific air contaminants deteriorate rapidly and need protective storage. The following 

information may be helpful when considering the use of these consumable items. Much of the 

information presented below is derived from the document Quality Assurance Principles for Analytical 

Laboratories3

.

13.1 Supplies Management

Control of supplies and consumables is important to the success of the quality assurance program. It is 

important that specifications for each item are prepared and adhered to during the procurement process. 

When specifications are prepared, the following points should be considered: identity, purity, potency, 

source, tests to be conducted for quality and purity, need for further purification, storage and handling 

procedures, and replacement dates. As part of supplies management, the following actions are 

recommended: 

• establish criteria and specifications for the important supplies and consumables. 

• check and test the supplies and consumables against specifications, before placing them in use. 

• design and maintain a supplies management program to ensure the quality of reagents used in 

day-to-day operations, paying particular attention to primary reference standards, working 

standards, and standard solutions. 

• decide on the kinds of purified water that are necessary, and develop suitable tests and testing 

intervals to ensure the quality of water used in analytical work and for cleaning glassware. 

• purchase only Class A volumetric glassware and perform calibrations and recalibrations that are 

necessary to achieve reliable results. 

• establish procedures for cleaning and storing glassware/sample containers with due consideration 

for the need for special treatment of glassware/sample containers used in trace analysis. 

• establish a useful life for glassware/sample containers and track this. 

• discard chipped and etched glassware or damaged containers. 

 

1 http://www.access.gpo.gov/nara/cfr/cfr-table-search.html 2 http://www.epa.gov/ttn/amtic/ 3

 Quality Assurance Principles for Analytical Laboratories, 3rd Edition. By Frederick M. Garfield, Eugene Klesta, 

and Jerry Hirsch. AOAC International (2000). http://www.aoac.org/ 
QA Handbook Vol II, Section 13.0 

Revision No: 1 

Date: 12/08 

Page 2 of 4 

13.2 Standards and Reagents

Discussions on gaseous standards and reagents are discussed in Section 12. What is most important is 

that the standards and reagents used are of appropriate purity and certified within the acceptable limits of 

the program for which they are used. Table 12-1 provides certification frequencies for gaseous standards, 

but within these timeframes, and as new cylinders are purchased, monitoring organizations need to 

develop a standard checking scheme to establish ongoing acceptance of standards. For example a new 

SRM should be purchased months prior to the expiration (or need for recertification) or complete use of 

an older standard in order to develop a overlapping cylinder acceptance process so there is some 

establishment of traceability and consistency in monitoring. For example, if a new SRM is put into use in 

a monitoring organization and all monitoring instruments traced to the cylinder start failing calibration, it 

may mean that either the new or older cylinder was not properly certified or has integrity problems. By 

checking both cylinders prior to new cylinder use, this issue can be avoided. 

13.2.1 Standard Solutions

Most laboratories maintain a stock of standard solutions. The following information on these solutions 

should be kept in a log book: 

 identity of solution 

 strength 

 method of preparation (reference to SOP) 

 standardization calculations 

 recheck of solution for initial strength 

 date made/expiration date 

 initials of the analyst 

 storage 

As mentioned above, all standard solutions should contain appropriate labeling as to contents and 

expiration dates. 

13.2.2 Purified Water

Water is one of the most critical but most often forgotten reagent. The water purification process should 

be documented from the quality of the starting raw water to the systems used to purify the water, 

including how the water is delivered, the containers in which it is stored, and the tests and the frequency 

used to ensure the quality of the water. 

13.3 Volumetric Glassware

Use of the appropriate glassware is important since many preparations and analyses require the 

development of reagents, standards, dilutions, and controlled delivery systems. It is suggested that 

“Class A” glassware be used in all operations requiring precise volumes. SOPs requiring volumetric 

glassware should specify the size/type required for each specific operation. 
QA Handbook Vol II, Section 13.0 

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13.4 Sample Containers 

Samples may be contaminated by using containers that have not be properly cleaned and prepared (e.g., 

VOC canisters, particulate filter cassettes/containers) or purchased from vendors without proper 

inspection prior to use. In addition, all sample containers have a “useful” life. Some containers, such as 

the low volume PM sample filter cassettes can be damaged over time and cause leaks in the sampling 

system. It is important to track the inventory of sampling containers from: 

• date of purchase; 

• first use; 

• frequency of use (estimate); 

• time of retirement. 

An inventory of this type can help ensure new containers are purchased prior to old ones expiring and/or 

causing sample integrity problems. Use of appropriate sample containers is important since the matter of 

the container could potentially affect the collected sample. Always refer to the specific method to see if a 

particular type of container (e.g., high density polyethylene [HDPE] bottles, amber glass) is required for 

the storage of the sample. 

13.5 Particulate Sampling Filters

Filters are used for the manual methods for criteria pollutants (e.g., PM10, PM2.5, PM10-2.5 , total PM, Pb, 

etc...). No commercially available filter is ideal in all respects. The sampling program should determine 

the relative importance of certain filter evaluation criteria (e.g., physical and chemical characteristics, 

ease of handling, cost). The reference methods provide detailed acceptance criteria for filters. Some of 

the basic criteria that must be met regardless of the filter type follows: 

• Visual inspection - for pinholes, tears, creases, or other flaws that may affect the collection 

efficiency of the filter, which may be consistent through a batch. This visual inspection would 

also be made prior to filter installation and during laboratory pre- and post-weighings to assure 

the integrity of the filter is maintained and, therefore, the ambient air sample obtained with each 

filter adequately represents the sampled pollutant conditions. 

• Collection efficiency - greater than 99% as measured by DOP test (ASTM 2988) with 

0.3 micrometer particles at the sampler’s operating face velocity. 

• Integrity - (pollutant specific) measured as the concentration equivalent corresponding to the 

difference between the initial and final weights of the filter when weighed and handled under 

simulated sampling conditions (equilibration, initial weighing, placement on inoperative sampler, 

removal from a sampler, re-equilibration, and final weighing). 

• Alkalinity - less than 0.005 milliequivalent/gram of filter following at least two months of 

storage at ambient temperature and relative humidity. 

Note: Some filters may not be suitable for use with all samplers. Due to filter handling characteristics or 

rapid increases in flow resistance due to episodic loading, some filters, although they meet the above 

criteria, may not be compatible with the model of sampler chosen. It would be prudent to evaluate more 

than one filter type before purchasing large quantities for network use. In some cases, EPA Headquarters 

may have national contracts for acceptable filters that will be supplied to monitoring organizations. 
QA Handbook Vol II, Section 13.0 

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Page 4 of 4 

13.6 Field Supplies 

Field instrumentation, which includes samplers and analyzers, require supplies for the actual collection 

process as well as quality control activities and crucial operational maintenance. These supplies can 

include, but are not limited to: 

 Gas standards/Permeation standards 

 HVAC units 

 Maintenance equipment (tools, ladders) 

 Safety supplies (first aid kit) 

 Information technology supplies (PC, printers, paper, ink, diskettes) 

 Sample line filters 

 Charcoal 

 Desiccant 

 Gaskets and O-rings 

 Sample lines and manifolds 

 Disposable gloves 

 Water/distilled water 

 Pumps and motors 

 Chart paper and ink 

 Impaction oil 

 TEOM FDMS filter 

The site logbook discussed in Section 11 should include a list and inventory of these critical field 

supplies. As part of routine maintenance activates, this inventory can be reviewed to determine if any 

supplies are in need of restocking. 
QA Handbook Vol II, Section 14 

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Page 1 of 14 

14.0 Data Acquisition and Information Management 

Success of the Ambient Air Quality Program 

objectives relies on data and its correct 

interpretation. It is critical that data be available to 

users and that these data are: 

• reliable; 

• of known quality; 

• easily accessible to a variety of users; and 

• aggregated in a manner consistent with its 

prime use 

In order to accomplish this activity, information must be collected and managed in a manner that protects 

and ensures its integrity. 

Most of the data collected from the Ambient Air Monitoring Program will be collected through automated 

systems at various facilities. These systems must be effectively managed by using a set of guidelines and 

principles by which adherence will ensure data integrity. The EPA has a document entitled Good 

Automated Laboratory Practices (GALP)1

. The GALP defines six data management principles: 

1. DATA: The system must provide a method of assuring the integrity of all entered data. 

Communication, transfer, manipulation, and the storage/recall process all offer potential for data 

corruption. The demonstration of control necessitates the collection of evidence to prove that the system 

provides reasonable protection against data corruption. 

2. FORMULAE: The formulas and decision algorithms employed by the system must be accurate and 

appropriate. Users cannot assume that the test or decision criteria are correct; those formulas must be 

inspected and verified. 

3. AUDIT: An audit trail that tracks data entry and modification to the responsible individual is a critical 

element in the control process. The trail generally utilizes a password system or equivalent to identify the 

person or persons entering a data point, and generates a protected file logging all unusual events. 

4. CHANGE: A consistent and appropriate change control procedure capable of tracking the system 

operation and application software is a critical element in the control process. All software changes 

should follow carefully planned procedures, including a pre-install test protocol and appropriate 

documentation update. 

5. STANDARD OPERATING PROCEDURES (SOPs): Control of even the most carefully designed and 

implemented systems will be thwarted if appropriate procedures are not followed. The principles implies 

the development of clear directions and Standard Operating Procedures (SOPs); the training of all users; 

and the availability of appropriate user support documentation. 

6. DISASTER: Consistent control of a system requires the development of alternative plans for system 

failure, disaster recovery, and unauthorized access. The control principle must extend to planning for 

reasonable unusual events and system stresses. 

 

1

 http://www.epa.gov/irmpoli8/ciopolicy/2185.pdf 
QA Handbook Vol II, Section 14.0 

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The principles listed above apply to both the local and central information management systems. 

The ambient pollutant data generated by gas analyzers or manual samplers must be captured, organized, 

and verified in order to be useful. The process of capturing the data is known as data acquisition. The 

organization of the data is known as data management. This section provides guidance in these areas, 

including identification of advanced equipment and procedures that are recommended for 

implementation. The recommended procedures rely on digital communication by the data acquisition 

system to collect a wider variety of information from the analyzers, to control instrument calibrations, and 

to allow for more routine, automated, and thorough data quality efforts. The section will discuss: 

1. Data acquisition- collecting the raw data from the monitor/sampler, storing it for an appropriate 

interval, aggregating or reducing the data, and transferring this data to final storage in a local data 

base (monitoring organizations database) 

2. Data transfer- preparing and moving data to external data bases such as AIRNow or the Air 

Quality System (AQS). 

3. Data management- ensuring the integrity of the data collection systems 

In response to guidelines issued by the Office of Management and Budget (OMB) under Section 515(a) of 

the Treasury and General Government Appropriations Act for Fiscal Year 2001 (Public Law 106-554; 

H.R. 5658), EPA developed the document titled Guidelines for Ensuring and Maximizing the Quality, 

Objectivity, Utility, and Integrity of Information Disseminated by the Environmental Protection Agency2

. 

The Guideline contains EPA’s policy and procedural guidance for ensuring and maximizing the quality of 

information it disseminates. The Guideline also incorporates the following performance goals: 

• Disseminated information should adhere to a basic standard of quality, including objectivity, 

utility, and integrity. 

• The principles of information quality should be integrated into each step of EPA’s development 

of information, including creation, collection, maintenance, and dissemination. 

• Administrative mechanisms for correction should be flexible, appropriate to the nature and 

timeliness of the disseminated information, and incorporated into EPA’s information resources 

management and administrative practices. 

EPA suggests monitoring organizations review this document since it is relevant to the ambient air 

information it generates and can help to ensure that data can withstand challenges to its quality. 

14.1 Data Acquisition 

Data acquisition technology is advancing and ever changing. Computer systems are now available in 

most air quality instruments. This has changed data acquisition in a profound way; most data is available 

in an instantaneous digital format from the instrument. This can be a powerful tool to quickly recognize 

and mitigate data quality problems. These digital systems should increase data capture and reporting. On 

the other hand, this increase in instantaneous data can be overwhelming if the monitoring organization is 

not prepared. The timely reporting of high quality, highly time-resolved ambient monitoring data will 

require a coordinated effort to ensure data management systems are meeting desired performance needs. 

These data management systems will need to provide validated data, to the extent possible, in near real 

time to multiple clients within minutes from the end of a sample period. Data management systems used 

 

2 http://www.epa.gov/quality/informationguidelines/documents/EPA_InfoQualityGuidelines.pdf 
QA Handbook Vol II, Section 14.0 

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Page 3 of 14 

in ambient air monitoring will need to provide efficient processing and validation of data, and provide 

appropriate communication of that data in a format appropriate and available for multiple users. As an 

example, improved data management systems from all NCore continuous monitors can provide near realtime, high quality, hourly data during episodes. This will allow technical and policy staff to better 

understand the exposure and interactions of air pollutants in the atmosphere of most interest. This section 

provides information on Data Acquisition Systems (DAS), a term used for systems that collect, store, 

summarize, report, print, calculate or transfer data. The transfer is usually from an analog or digital 

format to a digital medium. This section will also discuss limitations of data collected with DAS. 

14.1.1 Automated Data Acquisition Requirements

DAS have been available to air quality professionals since the early 1980s. The first systems were single 

and multi-channel systems that collected data on magnetic media. This media was usually hand 

transferred to a central location or laboratory for downloading to a central computer. With the advent of 

digital data transfer from the stations to a central location, the need to hand transfer data has diminished. 

However, errors in data reporting can occur with digital data. For DAS, there are two sources of error 

between the instrument (sensor) and the recording device: 1) the output signal from the sensor, and 2) the 

errors in recording by the data logger. For DAS that collect digital meta and reported data, these are not 

issues. Digital transfer of data does not suffer from the same problems as digital to analog transfer. 

When one digital device sends digital signals, the data is sent in data package streams that are coded then 

decoded at the receiving end. This digital transfer does not suffer from signal degradation. Most 

automated data acquisition systems support the acquisition of QC data like zero, one point QC and span 

data. One way to ensure that the QC data are correctly merged with the ambient readings is to code the 

QC values directly into the data set at the location corresponding to the time of the checks, replacing the 

normal hourly reading that is lost anyway because of the check. These data can be marked or flagged to 

differentiate it from ambient data and later deleted from the final routine data report printout. When QC 

data is acquired automatically by a data acquisition system for direct computer processing, the system 

must be sufficiently sophisticated to: 

• ensure that the QC data is never inadvertently reported as ambient measurements, 

• ignore transient data during the stabilization period before the analyzer has reached a stable QC 

response (this period may vary considerably from one analyzer to another), 

• average the stable QC readings over some appropriate time period so that the readings obtained 

accurately represents the analyzer’s QC response, 

• ignore ambient readings for an appropriate period of time immediately following a QC reading 

until the analyzer response has restabilized to the ambient-level concentration. 

14.1.2 Instrument to Data logger 

Figure 14.1 shows the basic transfer of data from the instrument to the final product; a hard copy report, 

or data transfer to a central computer. Most continuous monitors have the ability to output data in at least 

two ways: analog output and an RS232 digital port. Some instrumentation may now be including USB, 

Ethernet and firewire capability. The instrument has a voltage potential that generally is a DC voltage. 

This voltage varies directly with the concentration collected. Most instruments’ output is a DC voltage in 

the 0-1 or 0-5 volts range. The following provide a brief summary of the analog (A) or digital (D) steps 
QA Handbook Vol II, Section 14.0 

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• (A) the voltage is measured by the multiplexer 

which allows voltages from many instruments to 

be read at the same time. 

• (A) the multiplexer sends a signal to the a/d 

converter which changes the analog voltage to a 

low amperage digital signal. 

• (A) the a/d converter send signals to the central 

processing unit (cpu) that directs the digital 

electronic signals to a display or to the random 

access memory (ram) which stores the short-term 

data until the end of a pre-defined time period. 

• (A/D) the cpu then shunts the data from the ram to 

the storage medium which can be magnetic tape, 

computer hard-drive or computer diskette. 

• (A/D) the computer storage medium can be 

accessed remotely or at the monitoring location. 

The data transfer may occur via modem to a central computer storage area or printed out as hard copy. In 

some instances, the data may be transferred from one storage medium (i.e. hard drive to a diskette, tape, 

or CD) to another storage medium. The use of a data logging device to automate data handling from a 

continuous sensor is not a strict guarantee against recording errors. Internal validity checks are necessary 

to avoid serious data recording errors. 

Analog Versus Digital DAS - 

Most analyzers built within 

the last 15 years have the 

capability (RS232 ports) to 

transfer digital signals, yet 

many monitoring 

organizations currently 

perform data acquisition of 

automated monitors by 

recording an analog output 

from each gas analyzer 

using an electronic data 

logger. As explained above, 

the analog readings are 

converted and stored in 

digital memory in the data 

logger for subsequent 

automatic retrieval by a 

remote data management 

system. This approach can 

reliably capture the 

monitoring data, but does not 

allow complete control of monitoring operations, and the recorded analog signals are subject to noise that 

limits the detection of low concentrations. Furthermore, with the analog data acquisition approach, the 

data review process is typically labor-intensive and not highly automated. For these reasons, EPA 

Station Desktop 

CO System

PM

(continuous or FRM)

SO2

NOy

Calibrator

Zero Air Supply

RS-232 Multi-drop

(within manufacturer)

MET

RS 232 connections Digital I/O

Dial-up/DSL

Cable

Satellite Wireless

Status

Relay control

Measurements

Diagnostics

Data pushed or pulled 

from multiple stations

Database

Server

Public reporting

AQS

S/L/T validation

(optional)

Manifold/external valves

Figure 14.2 Flow of data from gas analyzers to final reporting 

Ambient 

Instrument

Storage 

Medium

RAM 

Memory CPU

analog/digital

converter Multiplexer

On site

printer

Data logger

Analog 

Signal

Digital

Signal

Modem

Local 

central

computer

On-site

computer

Hard copy

report

Ambient 

Instrument

Storage 

Medium

RAM 

Memory CPU

analog/digital

converter Multiplexer

On site

printer

Data logger

Analog 

Signal

Digital

Signal

Modem

Local 

central

computer

On-site

computer

Hard copy

report

Figure 14.1 DAS data flow

Ambient 

Instrument

Storage 

Medium

RAM 

Memory CPU

analog/digital

converter Multiplexer

On site

printer

Data logger

Analog 

Signal

Digital

Signal

Modem

Local 

central

computer

On-site

computer

Hard copy

report

Ambient 

Instrument

Storage 

Medium

RAM 

Memory CPU

analog/digital

converter Multiplexer

On site

printer

Data logger

Analog 

Signal

Digital

Signal

Modem

Local 

central

computer

On-site

computer

Hard copy

report

Figure 14.1 DAS data flow
QA Handbook Vol II, Section 14.0 

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encourages the adoption of digital data acquisition methods. In that regard, the common analog data 

acquisition approach often does not fully utilize the capabilities of the electronic data logger. Many data 

loggers have the capability to acquire data in digital form and to control some aspects of calibrations and 

analyzer operation, but these capabilities are not utilized in typical analog data acquisition approaches. 

Digital data acquisition reduces noise in the recording of gas monitoring data, thereby improving 

sensitivity. It also records and controls the instrument settings, internal diagnostics, and programmed 

activities of monitoring and calibration equipment. Such data acquisition systems also typically provide 

automated data quality assessment as part of the data acquisition process. 

It may be cost-effective for monitoring organizations to adopt digital data acquisition and calibration 

control simply by more fully exploiting the capabilities of their existing electronic data loggers. For 

example, many gas analyzers are capable of being calibrated under remote control. The opportunity to 

reduce travel and personnel costs through automated calibrations is a strong motivator for monitoring 

organizations to make greater use of the capabilities of their existing data acquisition systems. The 

NCore multi-pollutant sites are taking advantage of the newer DAS technologies. Details of these 

systems can be found in the technical assistance document for this program3

. 

Figure 14.2 illustrates the recommended digital data acquisition approach for the NCore sites. It presents 

the data flow from the gas monitors, through a local digital data acquisition system, to final reporting of 

the data in various public databases. This schematic shows several of the key capabilities of the 

recommended approach. A basic capability is the acquisition of digital data from multiple analyzers and 

other devices, thereby reducing noise and minimizing the effort needed in data processing. Another 

capability is two-way communication, so that the data acquisition system can interrogate and/or control 

the local analyzers, calibration systems, and even sample inlet systems, as well as receive data from the 

analyzers. Data transfer to a central location is also illustrated, with several possible means of that 

transfer shown. Monitoring organizations are urged to take advantage of the latest technology in this part 

of the data acquisition process, as even technologies such as satellite data communication are now well 

established, commercially available, and inexpensive to implement for monitoring operations. 

Depending on the monitoring objective, it may be important that data are reported in formats of 

immediate use in public data bases such as AQS4

, and the multi-monitoring organization AIRNow5 sites. 

An advantage of DAS software is the ability to facilitate the assembly, formatting and reporting of 

monitoring data to these databases. 

Digital data acquisition systems such as those in Figure 14.2 offer a great advantage over analog systems 

in the tracking of calibration data, because of the ability to control and record the internal readings of gas 

analyzers and calibration systems. That is, a digital data acquisition system not only can record the 

analyzer’s output readings, but can schedule and direct the performance of analyzer calibrations, and 

record calibrator settings and status. Thus, flagging of calibration data to distinguish them from ambient 

monitoring data is conducted automatically during data acquisition with no additional effort or postanalysis. These capabilities greatly reduce the time and effort needed to organize and quantify calibration 

results. 

 

3

 Version 4 of the Technical Assistance Document for Precursor Gas Measurements in the NCore Multi-pollutant 

Monitoring Network. http://www.epa.gov/ttn/amtic/pretecdoc.html 4 http://www.epa.gov/ttn/airs/airsaqs/aqsweb/ 5 http://airnow.gov/ 
QA Handbook Vol II, Section 14.0 

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14.1.3 DAS Quality Assurance/Quality Control 

Quality assurance aspects of the DAS deal with whether the system is being operated within defined 

guidelines. Usually, this means that each value that is collected on the DAS is the same value that is 

generated from the analyzer and reported to the Air Quality System (AQS) data base. This usually is 

accomplished by calibrations, data trail audits and performance audits. 

Calibration- In the case where analog signals from monitoring equipment are recorded by the DAS, the 

calibration of a DAS is similar to the approach used for calibration of a strip chart recorder. To calibrate 

the DAS, known voltages are supplied to each of the input channels and the corresponding measured 

response of the DAS is recorded. Specific calibration procedures in the DAS owner’s manual should be 

followed when performing such DAS calibrations. For DAS that receive digital data from the 

instruments, a full scale check (the instrument is in a mode and the output is at the full scale of the 

instrument) should be performed to see if the data received digitally is the same as the display of the 

instrument. The DAS should be calibrated at least once per year. Appendix G provides a simple approach 

for calibration of the DAS. 

In addition, gas analyzers typically have an option to set output voltages to full scale or to ramp the 

analog output voltages supplied by the analyzer over the full output range. Such a function can be used to 

check the analog recording process from the analyzer through the DAS. 

Data Trail Audit- The data trail audit consists of following a value or values collected by the DAS to the 

central data collection site and then eventually to AQS. A person other than the normal station operator 

should perform this duty. The following procedure should be followed:

• A data point should be collected from the DAS (usually an hourly value or another aggregated 

value reported to AQS) and be checked on the DAS storage medium against the hard copy report. 

Also if strip chart recorders are used, a random number of hourly values should be compared to 

the data collected by the DAS. This audit should be completed on a regular defined frequency and 

for every pollutant reported. 

• From the central computer, the auditor checks to see if this hourly value is the same. 

The above actions should be completed well in advance of data submittal to AQS. If the data has been 

submitted to AQS, then the AQS data base should be checked and modified as necessary per the 

appropriate AQS procedures. 

Whether a monitoring organization is transferring the data from an instrument via an on-site DAS or 

transferring the data digitally, the data trail audit should be performed on a routine basis. 

Performance Audit- The performance audit consists of challenging the instrument and DAS to a known 

audit source gas and observing the final response. The response should correspond to the value of the 

audit source gas. Section 15 discusses these performance audits. 

Initialization Errors 

All data acquisition systems must be initialized. The initialization consists of an operator “setting up” the 

parameters so that the voltages produced by the instruments can be read, scaled correctly and reported in 

the correct units. Errors in initializations can create problems when the data is collected and reported. 

Read the analyzer manufacturer’s literature before parameters are collected. If the manufacturer does not 
QA Handbook Vol II, Section 14.0 

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state how these parameters are collected, request this information. The following should be performed 

when setting up the initializations: 

• Check the full scale outputs of each parameter. 

• Calibrations should be followed after each initialization (each channel of a DAS should be 

calibrated independently). Appendix G provides an example of a DAS calibration technique. 

• Review the instantaneous data stream, if possible, to see if the DAS is collecting the data 

correctly. 

• Save the initializations to a storage medium; if the DAS does not have this capability, print out 

the initialization and store it at the central computer location and at the monitoring location. 

• Check to see if the flagging routines are performed correctly; data that are collected during 

calibrations and down time should be flagged correctly. 

• Check the DAS for excessive noise (variability in signal). Noisy data that are outside of the 

normal background are a concern. Noisy data can be caused by improperly connected leads to 

the multiplexer, noisy AC power, or a bad multiplexer. Refer to the owner’s manual for help on 

noisy data. 

• Check to see that the average times are correct. Some DAS consider 45 minutes to be a valid 

hour, while others consider 48 minutes. Agency guidelines should be referred to before setting 

up averaging times. 

14.1.4 Data Logger to Database

Once data are on the data logger at the ambient air monitoring station, they need to be sent to servers 

where they can be summarized and disseminated to data users. In most cases this will occur by using a 

server at the office of the monitoring organization. The conventional way to get data from the monitoring 

stations has been to poll each of the stations individually. With more widespread availability of the 

internet, pushing data from monitoring sites on a regular basis will be especially effective in mapping and 

public reporting of data. Note, in some cases it is possible to report data directly from a monitor to a 

database without the use of a station data logger. This solution is acceptable so long as the monitor is 

capable of data storage for periods when telemetry is off-line.

Data transfer is usually accomplished in three ways: hard copy printout, downloading data from internal 

storage medium to external storage medium, or digital transfer via the telephone lines, internet, satellite or 

other advanced means of communication. Due to the desire for real time data for the Air Quality Index 

(AQI) and other related needs, monitoring organizations should plan to upgrade to digital data acquisition 

and communication systems. 

Hard copy report- Most DAS have the ability to create a hard copy report. Usually, this report is in 

tabular format showing 1 minute, 5 minute or hourly averages. Monitoring organization are encouraged 

to keep hard copy printouts for several reasons: 

• they can be reviewed by the station operators prior to and/or during site visits to ascertain the 

quality of the data; 

• they can be compared against the historical data stored on the DAS at the site for validation; 

• notes can be made on the hard copy reports for later review by data review staff; and

• they create a “back-up” to the electronically based data. 

NOTE: It is strongly recommended that monitoring organizations create an electronic back-up 

of their data on a defined schedule. The frequency of the back-ups and any other associated 
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information should be reflected in their Quality Assurance Project Plan (QAPP) and Standard 

Operating Procedures (SOP). 

External Storage- This term refers to storing and transferring the data on diskettes or CD. Many new 

generation DAS are computer platforms. The newer generation computers generally have the ability to 

download data to CD or zip drive. If remote access via telephone is not an option, then data can be hand 

transferred to a central office for downloading and data review. 

Digital Transfer- All new generation DAS allow access to the computer via the telephone and modem. 

These systems allow fast and effective ways to download data to a central location. The EPA 

recommends using these systems for the following reasons:

• in case of malfunction of an ambient instrument, the appropriate staff at the central location can 

begin to diagnose problems and decide a course of action; 

• down loading the data allows the station operators, data processing team, and/or data validators to 

get a head start on reviewing the data; and 

• when pollution levels are high or forecasted to be high, digital transfer allows the pollution 

forecaster the ability to remotely check trends and ensure proper operation of instruments prior to 

and during an event. 

14.1.5 DAS Data Review

The data review is an ongoing process that is performed by the station operators (SO) and the data 

processing team (DP). At a minimum a cursory review is performed daily, preferably in the morning to 

provide a status of the data and instrument performance at monitoring sites. Detailed analysis can be 

extremely difficult for the data processing team when reviewing the raw data without the notations, notes 

and calibration information that the station operators provide for the group. The typical review process 

for the station operator and data reviewer(s) include: 

• (SO) Review of zero, span, one point QC verification information, the hourly data, and any flags 

that could effect data and record any information on the daily summaries that might be vital to 

proper review of the data. 

• (SO) Transfer strip charts both analog and digital information, daily summaries, monthly 

maintenance sheets, graphic displays of meta data and site log notes to the central location for a 

secondary and more thorough review. 

• (SO) At the central location, review the data, marking any notations of invalidations and provide 

electronic strip charts, meta data charts, daily summaries, site notes, and monthly maintenance 

sheets for ready access by the data processing staff. 

• (DP) Review zero, span and one point QC verifications, station notes, and monthly maintenance 

sheets for the month; check a percentage of all zero, span and one point verifications. Compare a 

defined number of hand reduced and/or strip chart readings to electronic data points generated by 

the DAS. If significant differences are observed, determine what corrective action steps are 

required. 
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Outliers 

Outliers are “measurements that are extremely large or small relative to the rest of the data and are 

suspected of misrepresenting the population from which they were collected” (EPAQA/G9R)6

. When 

reviewing data, some potential outliers will be obvious such as, spikes in concentrations, data remaining 

the same for hours, or a sudden drop in concentration but still in the normal range of observed data. Many 

of these outlier checks can be automated and provide efficient real-time checks of data. Outliers do not 

necessarily indicate the data is invalid; they serve to alert the station operator and/or data reviewers there 

may be a problem. In fact, the rule of thumb for outliers should be that the data be considered valid until 

there is an explanation for why the data should be invalidated. At some point it may be necessary to 

exclude outliers from instantaneous reporting to the AIRNow network and/or AQI reporting until further 

investigation has occurred. EPA Guidance Documents7 Guidance on Environmental Data Verification 

and Validation (EPA QA/G8) and Guidance for Data Quality Assessment – a Reviewers Guide (EPA 

QA/G9R) provide insight on outlier and data reviews in general. 

 

6 http://www.epa.gov/quality1/qs-docs/g9r-final.pdf 7 http://www.epa.gov/quality1/qa_docs.html 

14.2 Data Transfer – Public Reporting 

The area of public reporting for air monitoring data may provide the largest number of users of data. This 

area has been growing rapidly in the last few years as a result of the increased availability of air quality 

reporting, especially for ozone and PM2.5. For public reporting of the AQI, the AIRNow web site will 

remain the EPA’s primary medium for distribution of air monitoring data. The additional continuous 

monitoring parameters collected from NCore will also be reported to AIRNow. These parameters are 

expected to be made publicly available for sharing throughout technical user communities. However, 

they are not expected to be widely distributed through AIRNow as products for public consumption. 

This section will discuss the transfer of data from the monitoring organization to two major data 

repositories: 1) AIRNow for near real-time reporting of monitoring data, and 2) AQS for long term 

storage of validated data. 

14.2.1 Real-time Data Reporting for AIRNow and NCore 

One of the most important emerging uses of ambient monitoring data has been public reporting of the Air 

Quality Index (AQI). This effort has expanded on EPA’s AIRNow web site from regionally-based near 

real-time ozone mapping products color coded to the AQI, to a national multi-pollutant mapping, 

forecasting, and data handling system of real-time data. Since ozone and PM2.5 drive the highest 

reporting of the AQI in most areas, these two pollutants are the only two parameters currently publicly 

reported from AIRNow. While other pollutants such as CO, SO2, NO2, and PM10 may not drive the AQI, 

they are still important for forecasters and other data users to understand for model evaluation and 

tracking of air pollution episodes. Therefore, the NAAMS seeks the following goals: 

 

• Share all continuous O3, PM2.5 and PM10 data, where available, across the nation; 

• For NCore sites, share all gaseous CO, SO2, NO and NOy data and base meteorological 

measurements across the nation. 
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This program allows for short term non-validated data to be collected by a centrally located computer that 

displays the data in near real time data formats such as tables and contour maps. In addition, EPA, in 

conjunction with the monitoring organizations, developed the National Ambient Air Monitoring Strategy 

(NAAMS) which includes the development of the NCore network. This section will discuss the needs of 

real time data acquisition for the deployment of AIRNow and the NAAMS.

Reporting Intervals 

Currently, hourly averages are the reporting interval for continuous particulate and gaseous data. These 

are the reporting intervals for both AQS (AQS supports a variety of reporting intervals) and to AIRNow 

for AQI purposes. These reporting intervals will meet most of the multiple objectives of NCore for 

supporting health effects studies, AQI reporting, trends, NAAQS attainment decisions, and accountability 

of control strategies. However, with these objectives also comes the desire for data at finer time 

resolutions: 5 minute averages for gaseous pollutants and sub-hourly averages for certain particulate 

matter monitors. Examples of this need for finer time resolution of data include, but are not limited to: 

tracking air pollution episodes, providing data for exposure studies, model evaluation, and evaluating 

shorter averaging periods for potential changes to the NAAQS. Monitoring organizations generally have 

the hardware and software necessary to log and report this data. The challenge to obtaining and reporting 

the data is the current communication packages used, such as conventional telephone modem polling. One 

widely available solution to this would be the use of internet connectivity, allowing data at individual 

monitoring sites to be pushed to a central server rather than being polled. Monitoring organizations 

should begin to investigate the possibilities of using this media. 

With this generation of data having a shorter averaging interval, the challenge becomes validation of all 

the data. The historical perception has been that each criteria pollutant measurement needs to be verified 

and validated manually. With the amount of data generated, this would be a time-consuming task. To 

provide a nationally consistent approach for the reporting interval of data, the NCore networks will take a 

tiered approach to data reporting. At the top tier, hourly data intervals will remain the standard for data 

reporting. Long term, the NCore networks will be capable of providing at least 5 minute intervals for 

those methods that have acceptable data quality at those averaging periods. For QA/QC purposes such as 

zero/span and one-point QC, monitoring organizations should be capable of assessing data on at least a 1-

minute interval. 

With instantaneous data going to external websites, monitoring organizations operating their own 

websites containing the same local and/or regional data should add a statement about the quality of data 

being displayed at the site. This cautionary statement will notify the public that posted data has not been 

fully quality assured and discrepancies may occur. For an example, the AIRNow Website makes the 

statement 

“Although some preliminary data quality assessments are performed, the data as such are 

not fully verified and validated through the quality assurance procedures monitoring 

organizations use to officially submit and certify data on the EPA AQS(Air Quality 

System). Therefore, data are used on the AIRNow Web site only for the purpose of 

reporting the AQI. Information on the AIRNow web site is not used to formulate or 

support regulation, guidance or any other Agency decision or position.” 
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14.2.2 Reporting Frequency and Lag Time for Reporting Data

Continuous monitoring data that are being shared in near real-time from NCore monitoring stations are to 

be reported each hour. Data should be reported as soon as practical after the end of each hour. For the 

near term, the goal is to report data within twenty minutes past the end of each hour. This will provide 

enough time for data processing and additional validation at the Data Management Center (DMC); 

generation of reports and maps; distribution of those products to a variety of stakeholders and web sites; 

and still allow enough time for staff review before the end of the hour. This is an important goal to 

support reporting of air pollution episodes on news media programs by the top of the hour. The long term 

goal is to report all data within five minutes after the end of an hour. This will further enhance NCore’s 

ability to deliver timely data within a reasonable time period that takes advantage of existing 

commercially available technology.

14.3 Data Transfer-Reporting to External Data Bases

Today, the need for the ambient air monitoring data reaches outside the monitoring community. In 

addition to the traditional needs of the data, determination of NAAQS compliance and the daily AQI 

report, a health researcher or modeler may want a very detailed accounting of the available data in the 

shortest time intervals possible. Atmospheric scientists typically desire data in a relatively unprocessed 

yet comprehensive form with adequate descriptions (meta data) to allow for further processing for 

comparability to other data sets. These needs increase the demands for the data and require multiple 

reports of the information. 

14.3.1 AQS Reporting

All ambient air monitoring data will eventually be transferred and stored in AQS. The current system, 

implemented in early 2002, has much more functionality than the previous main-frame system. As stated 

in 40 CFR Part 58.168

, the monitoring organization shall report all ambient air monitoring and associated 

quality assurance data and information specified by the AQS Users Guide into the AQS format. The data 

is to be submitted electronically and on a specified quarterly basis. Since changes in reporting 

requirement occur, monitoring organization should review CFR for the specifics of this requirement. 

The AQS manuals are located at the AQS Website9. This site contains the old AIRS/AQS manuals as 

well as the new AQS Manuals. The AQS Data Coding Manual replaces the previous Volume II and 

provides coding instructions, edits performed, and system error messages. The AQS User Guide replaces 

the former Volume III and describes the procedures for data entry. Both manuals will be updated as 

needed and the new versions will be available at the web site. Table 14-1 provides the units and the 

number of decimal places that, at a minimum, are required for reporting to AQS for the criteria pollutants. 

These decimal places are used for comparison to the NAAQS and are displayed in AQS summary reports. 

However, monitoring organizations can report data up to 5 values to the right of the decimal (beyond five 

AQS will truncate). Within the five values to the right of the decimal place, AQS will round to the 

minimum displayed in Table 14-1. Reported values will remain in raw data files.

 

8 http://www.access.gpo.gov/nara/cfr/cfr-table-search.html 9 http://www.epa.gov/ttn/airs/airsaqs/manuals/ 
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Table 14-1 AQS Data Reporting Requirements 

Pollutant Decimal Places Example Units 

PM2.5 1 10.2 μg/m3

PM10 1 26.2 μg/m3

PM10-2.5 1 10.2 μg/m3

Lead 1 1.5 μg/m3

SO2 2 0.03 ppm 

NO2 3 0.053 ppm 

CO 1 2.0 ppm 

O3 3 0.108 ppm 

PAMS (VOCs) 2 6.23 ppb-carbon 

14.3.2 Standard Format for Reporting to AQS 

AQS allows flexibility in reporting formats. The formats previously used by AQS can be used for raw 

data (hourly, daily, or composite) and for reporting precision and bias data. The system also has new 

report formats for this data as well as formats for registering new sites and monitors. These new formats 

are defined in the AQS Data Coding Manual. Work is also in progress to define an Extensible Markup 

Language (XML) schema for AQS to allow for that reporting format as well. Use of XML as a data 

format is consistent with EPA and Federal guidelines towards better data integration and sharing. 

14.3.3 Annual Certification of Data

The annual data certification is also stored in AQS. The monitoring organization is required to certify the 

data (by formal letter) for a calendar year (Jan 1-Dec 31) by July 1 through the year 2009. Beginning in 

2010 the annual data certification letter is due by May 1. See 40 CFR Part 58.15 for details. This 

certification requires the monitoring organization to review the air quality data and precision/bias data for 

completeness and validity and to submit a certification letter to the Regional Office. The certification 

letter and accompanying reports are reviewed and if the results of the review are consistent with the 

criteria for certification, the certification flag is set in the AQS database. After certification is complete, 

any updates to the data will cause the critical review process to identify that the certified data has been 

changed and the certification flag will be dropped.

14.3.4 Summary of Desired Performance for Information Transfer Systems 

To define the needed performance criteria of a state-of-the art information technology system, a table of 

needs has been developed. This table provides performance needs for an optimal information technology 

system, but is not intended to address what the individual components should look like. For instance, 

once low level validated data for a specific time period are ready to leave the monitoring station, a 

number of telemetry systems may actually accomplish moving those data. By identifying the needed 

performance criteria of moving data, rather than the actual system to move it, monitoring organizations 

may be free to identify the most optimal system for their network. Table 14-2 summarizes the 

performance elements of the data management systems used to log, transfer, validate, and report data 

from NCore ambient air monitoring stations.
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Table 14-2 NCore (Level 2 and 3) Information Technology Performance Needs 

Performance Element Performance Criteria Notes 

Sample Periods 5 minutes (long term goal), and 1 hour data 

(current standard) 5 minutes and 1 hour data to support exposure, 

mapping and modeling. 1 hour data for Air Quality 

Index reporting and NAAQS. 

Sample period may need to be higher for certain 

pollutant measurement systems depending on 

method sample period and measurement precision 

when averaging small time periods.

Data Delivery Near Term goal - Within 20 minutes nationally 

each hour 

Long term goal - Within 5 minutes nationally 

each hour 

As monitoring organizations migrate to new 

telemetry systems the goal will be to report data 

within 5 minutes. This should be easily obtained 

with broadband pushing of data to a central server. 

Low Level Validation - Last automated zero and QC check acceptable 

- Range check acceptable 

- Shelter parameters acceptable 

-Instrument parameters acceptable 

Other validation should be applied as available: 

- site to site checks 

- rate of change 

-lack of change. 

Data Availability - all QC data, operator notes, calibrations, and 

pollutant data within network 

- Low level validated pollutant data externally 

Create log of all monitoring related activities 

internally. Allow only validated data to leave 

monitoring organization network. 

Types of monitoring data to 

disseminate-externally -continuous and semi-continuous pollutant data 

-accompanying meteorological data 

Associated manual method supporting data (for 

instance FRM ambient Temperature) should be 

collected but not reported externally. 

Additional data for internal 

tracking 

Status of ancillary equipment such as shelter 

temperature, power surges, zero air system, 

calibration system 

Relevant site information Latitude, longitude, altitude, land use category, 

scale of representativeness, pictures and map of 

area 

Other site information may be necessary. 

Remote calibration Ability to initiate automated calibrations on 

regular schedule or as needed 

Reviewing calibration - allow for 1 minute data as part of electronic 

calibration log 

Initialization of manual collection 

method 

Need to be able to remotely initiate these or have 

them set at an action level from a specific 

monitor 

Reporting Format Short Term - Maintain “Obs” file format and pipe 

delimited formats for AIRNow and AQS 

reporting, respectively 

Near Term -XML 

Need to coordinate development of XML schema 

with multiple stakeholders. XML is an open 

format that will be able to be read by most 

applications. 

 

14.4 Data Management

Managing the data collected is just as important as correctly collecting the data. The amount of data 

collected will continue to grow based on the needs of the data users. Previous sections have confirmed 

this statement providing a glimpse of the potential data users and the uses. Generally, data is to be 

retained for a period of 3 years from the date the grantee submits its final expenditure report unless 

otherwise noted in the funding agreement. Refer to 40 CFR Part 31.42. With electronic records and 

electronic media, this information can be stored and managed with less use of space than with the 

conventional paper records. However, even with today’s technology there will be some paper records and 

those need to be managed in an orderly manner. The manner in which a monitoring organization manages 

its data is documented in its QMP and QAPP. 

All information collected in any ambient air monitoring program should be organized in a logical and 

systematic manner. There is no one best way to organize a system. How a monitoring organization 
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organizes its information is required to be discussed in its QMP (QA/R-2)10 and QAPP (QA/R-5)11. 

Monitoring organizations should consult EPA’s records management webpage12 for other useful 

information when beginning to plan or revise how its data records are stored. 

This information should be reviewed not only by those in a monitoring organization responsible for 

overall data management but also by the monitoring organization’s Systems or Network Administrator. 

The latter person(s) can provide helpful information in designing the overall data management system 

according to today’s industry standards. Remember, the data has to be of known quality, reliable and 

defensible. In order for monitoring organizations to continue to meet those objectives, many sources of 

information need to be reviewed. 

Section 5 presented guidance on documentation and records. This information can be helpful in managing 

ambient air monitoring data. In addition, the EPA Office of Environmental Information (OEI) has a 

website13 that provides information management policies and guidance. As an example the document 

Good Automated Laboratory Practices, described earlier in this document, is posted on the OEI website 

and can be very useful in developing information management systems. 

 

10 http://www.epa.gov/quality1/qs-docs/r2-final.pdf 11 http://www.epa.gov/quality1/qs-docs/r5-final.pdf 12 http://www.epa.gov/records/ 13 http://www.epa.gov/irmpoli8/policies.htm 
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15.0 Assessment and Corrective Action 

An assessment is an evaluation process used to measure the performance or effectiveness of a system and 

its elements. It is an all-inclusive term used to denote any of the following: audit, performance 

evaluation, management systems review, peer review, inspection and surveillance. For the Ambient Air 

Quality Monitoring Program, the following assessments will be discussed: network reviews, performance 

evaluations, technical systems audits and data quality assessments. 

15.1 Network Reviews 

Beginning July 2007, the State, or where applicable, local monitoring organizations shall adopt and 

submit to the Regional Administrator an annual monitoring network plan which shall provide for the 

establishment and maintenance of an air quality surveillance system that consists of a network of SLAMS 

monitoring stations including FRM, FEM, and ARM monitors that are part of SLAMS, NCore stations, 

STN stations, State speciation stations, SPM stations, and/or, in serious, severe and extreme ozone 

nonattainment areas, PAMS stations, and SPM stations. The plan shall include a statement of purposes for 

each monitor and evidence that siting and operation of each monitor meets the requirements of 

appendices A, C, D, and E of Part 58, where applicable. The annual monitoring network plan must be 

made available for public inspection for at least 30 days prior to submission to EPA. The AMTIC 

Website has a page1

 devoted to the progress and adherence to this requirement. This page contains links 

to State and local ambient air monitoring plans. 

In addition to an annual network plan, starting in 2010, the State, or where applicable local, monitoring 

organization shall perform and submit to the EPA Regional Administrator an assessment of the air quality 

surveillance system every 5 years to determine, at a minimum, if the network meets the monitoring 

objectives defined in 40 CFR Part 58, Appendix D, whether new sites are needed, whether existing sites 

are no longer needed and can be terminated, and whether new technologies are appropriate for 

incorporation into the ambient air monitoring network. The network assessment must consider the ability 

of existing and proposed sites to support air quality characterization for areas with relatively high 

populations of susceptible individuals (e.g., children with asthma), and, for any sites that are being 

proposed for discontinuance, the effect on data users other than the monitoring organization itself, such as 

nearby States and Tribes or health effects studies. For PM2.5, the assessment also must identify needed 

changes to population-oriented sites. The State, or where applicable, local monitoring organization must 

submit a copy of this 5-year assessment, along with a revised annual network plan, to the Regional 

Administrator. 

Conformance with network requirements of the Ambient Air Monitoring Network set forth in 40 CFR 

Part 58, Appendices D and E are determined through annual network reviews of the ambient air quality 

monitoring system. The annual review of the network is used to determine how well the network is 

achieving its required monitoring objectives and how it should be modified to continue to meet its 

objectives. Most network reviews are accomplished by the EPA Regional Office, however, the following 

information can be useful to State and local organizations to prepare for reviews or assess their networks. 

In order to maintain consistency in implementing and collecting information from a network review, EPA 

has developed SLAMS/PAMS Network Review Guidance. The information presented in this section 

provides some excerpts from this guidance document. 

 

1 http://www.epa.gov/ttn/amtic/plans.html 
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15.1.1 Network Selection 

Due to the resource-intensive nature of network reviews, it may be necessary to prioritize monitoring 

organizations and/or pollutants to be reviewed. The following criteria may be used to select networks: 

• date of last review; 

• areas where attainment/nonattainment designations are taking place or are likely to take place; 

• results of special studies, saturation sampling, point source oriented ambient monitoring, etc.; and 

• monitoring organizations which have proposed network modifications since the last network 

review. 

In addition, pollutant-specific priorities may be considered (e.g., newly designated ozone nonattainment 

areas, PM10 "problem areas", etc.). Once the monitoring organizations have been selected for review, 

significant data and information pertaining to the review should be compiled and evaluated. Such 

information might include the following: 

• network files for the selected monitoring organization (including updated site information and site 

photographs); 

• AQS reports (AMP220, 225, 255, 380, 390, 450); 

• air quality summaries for the past five years for the monitors in the network; 

• emissions trends reports for major metropolitan areas; 

• emission information, such as emission density maps for the region in which the monitor is 

located and emission maps showing the major sources of emissions; and 

• National Weather Service summaries for monitoring network area. 

Upon receiving the information, it should be checked to ensure it was the latest revision and for 

consistency. Discrepancies should be noted on the checklist (Appendix H) and resolved with the 

monitoring organization during the review. Files and/or photographs that need to be updated should also 

be identified. 

15.1.2 Conformance to 40 CFR Part 58 Appendix D- Network Design Requirements 

With regard to 40 CFR Part 58 Appendix D requirements, the network reviewer must determine the 

adequacy of the network in terms of number and location of monitors: specifically, (1) is the monitoring 

organization meeting the number of monitors required by the design criteria requirements; and (2) are the 

monitors properly located, based on the monitoring objectives and spatial scales of representativeness? 

Number of Monitors 

For SLAMS, the minimum number of monitors required is specified in the regulations for ozone, PM10, 

PM 2.5, and PAMS. The other criteria pollutants do not have minimum requirements and is determined by 

the Regional Office and the monitoring organizations on a case-by-case basis to meet the monitoring 

objectives specified in Appendix D. Adequacy of the network may be determined by using a variety of 

tools, including the following: 

• maps of historical monitoring data; 

• maps of emission densities; 

• dispersion modeling; 

• special studies/saturation sampling; 

• best professional judgment; 

• SIP requirements; and 

• revised monitoring strategies (e.g., lead strategy, reengineering air monitoring network). 
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Location of Monitors 

For the ozone, PM10, and PM 2.5 SLAMS sites, Appendix D does provide general locations of sites in 

regards to NAAQS related concentrations. For other criteria pollutants the location of monitors is not 

specified in the regulations, but is determined by the Regional Office and State monitoring organizations 

on a case-by-case basis to meet the monitoring objectives specified in Appendix D. Adequacy of the 

location of monitors can only be determined on the basis of stated objectives. Maps, graphical overlays, 

and GIS-based information can be extremely helpful in visualizing or assessing the adequacy of monitor 

locations. Plots of potential emissions and/or historical monitoring data versus monitor locations are 

especially useful. 

For PAMS, there is considerable flexibility when locating each PAMS within a nonattainment area or 

transport region. The three fundamental criteria which need to be considered when locating a final PAMS 

site are: (1) sector analysis - the site needs to be located in the appropriate downwind (or upwind) sector 

(approximately 45o

) using appropriate wind directions; (2) distance - the sites should be located at 

distances appropriate to obtain a representative sample of the areas precursor emissions and represent the 

appropriate monitoring scale; and (3) proximate sources. 

 

15.1.3 Conformance to 40 CFR Part 58, Appendix E - Probe Siting Requirements 

Applicable siting criteria for SLAMS, and PAMS are specified in 40 CFR Part 58, Appendix E. The onsite visit itself consists of the physical measurements and observations needed to determine compliance 

with the Appendix E requirements, such as height above ground level, distance from trees, paved or 

vegetative ground cover, etc. Prior to the site visit, the reviewer should obtain and review the following: 

• most recent hard copy of site description (including any photographs) 

• data on the seasons with the greatest potential for high concentrations for specified pollutants 

• predominant wind direction by season 

The checklist provided in Appendix H of this Handbook is also intended to assist the reviewer in 

determining conformance with Appendix E. In addition to the items on the checklist, the reviewer should 

also do the following: 

• ensure that the manifold and inlet probes are clean 

• estimate probe and manifold inside diameters and lengths 

• inspect the shelter for weather leaks, safety, and security 

• check equipment for missing parts, frayed cords, etc. 

• check that monitor exhausts are not likely to be introduced back to the inlet 

• record findings in field notebook and/or checklist 

• take photographs/videotape in the 8 directions 

• document site conditions, with additional photographs/videotape 
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15.1.4 Checklists and Other Discussion Topics 

Checklists are provided in Appendix H to assist network reviewers (SLAMS and PAMS) in conducting 

the review. In addition to the items included in the checklists, other subjects for possible discussion as 

part of the network review and overall adequacy of the monitoring program include: 

• installation of new monitors; 

• relocation of existing monitors; 

• siting criteria problems and suggested solutions; 

• problems with data submittals and data completeness; 

• maintenance and replacement of existing monitors and related equipment; 

• quality assurance problems; 

• air quality studies and special monitoring programs; and 

• other issues (proposed regulations/funding).

15.1.5 Summary of Findings 

Upon completion of the network review, a written network evaluation should be prepared. The 

evaluation should include any deficiencies identified in the review, corrective actions needed to address 

the deficiencies, and a schedule for implementing the corrective actions. The kinds of 

discrepancies/deficiencies to be identified in the evaluation include discrepancies between the monitoring 

organization network description and the AQS network description; and deficiencies in the number, 

location, and/or type of monitors. 

15.2 Performance Evaluations 

Performance evaluations (PEs) are a type of audit in which the 

quantitative data generated in a measurement system are obtained 

independently and compared with routinely obtained data to 

evaluate the proficiency of an analyst, or a laboratory2

. The 

National Performance Evaluation Programs: 

• Allow one to determine data comparability and usability 

across sites, monitoring networks (Tribes, States, and 

geographic regions), instruments and laboratories. 

• Provide a level of confidence that monitoring systems are 

operating within an acceptable level of data quality so data 

users can make decisions with acceptable levels of certainty. 

• Help verify the precision and bias estimates performed by 

monitoring organizations. 

• Identify where improvements (technology/training) are 

needed. 

• Assure the public of non-biased assessments of data quality. 

 

2

 American National Standard-Quality Systems for Environmental Data and Technology Programs-Requirements 

with Guidance for Use (ANSI/ASQC E4-2004) 

PEP Audit 

NPAP through the probe audit 
QA Handbook Vol II, Section 15.0 

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• Provide a quantitative mechanism to defend the quality of data. 

• Provide information to monitoring organizations on how they compare with the rest of the nation, 

in relation to the acceptance limits and to assist in corrective actions and/or data improvements. 

Some type of national PE program is implemented for all of the ambient air monitoring activities. Table 

15-1 provides more information on these activities. It is important that these performance evaluations be 

independent in order to ensure they are non-biased and objective. With the passage of the Data Quality 

Act3

, there is potential for EPA to receive challenges to the quality of the ambient air data. Independent 

audits help provide another piece of objective evidence on the quality of a monitoring organizations data 

and can help EPA defend the quality of the data.

Table 15-1 National Performance Evaluation Activities Performed by EPA 

Program/ 

Lead Agency 

Explanation 

NPAP 

OAQPS 

National Performance Audit Program provides audit standards for the gaseous pollutants either as devices that the site 

operator connects to the back of the instrument or through the probe in which case the audits are conducted by 

presenting audit gases through the probe inlet of ambient air monitoring stations. Flow audit devices and lead strips are 

also provided through NPAP. NPAP audits are required at 20% of a primary quality assurance organizations sites each 

year with a goal of auditing all sites in 5-7 years. 

PM2.5 PM10-2.5 PEP 

OAQPS 

Performance Evaluation Program. The strategy is to collocate a portable FRM PM2.5 or PM10-2.5 air sampling audit 

instrument with an established primary sampler at a routine air monitoring site, operate both samplers in the same 

manner, and then compare the results. Each year five PEP audits are required for primary quality assurance 

organizations (PQAOs) with less than or equal to 5 monitoring sites or eight audits are required for PQAOs with greater 

than five sites. These audits are not required for PM10

NATTS PT 

OAQPS 

A National Air Toxics Trend Sites (NATTS) proficiency test (PT) is a type of assessment in which a sample, the 

composition of which is unknown to the analyst, is provided to test whether the analyst/laboratory can produce 

analytical results within the specified acceptance criteria. PTs for volatile organic carbons (VOCs), carbonyls and 

metals are performed quarterly for the ~22 NATTS laboratories 

SRP 

ORIA-LV 

The Standard Reference Photometer (SRP) Program provides a mechanism to establish traceability among the ozone 

standards used by monitoring organizations with the National Institute of Standards and Technology (NIST). Every year 

NIST certifies an EPA SRP. Upon certification, this SRP is shipped to the EPA Regions who use this SRP to certify the 

SRP that remains stationary in the Regional Lab. These stationary SRPs are then used to certify the ozone transfer 

standards that are used by the State, Local and Tribal monitoring organizations who bring their transfer standards to the 

Regional SRP for certification. 

PAMS Cylinder 

Certs 

ORIA LV 

EPA developed a system to certify the standards used by the monitoring organizations to calibrate their PAMS 

analytical systems. The standards are sent to the EPA Office of Radiation and Indoor Air (ORIA-LV) who perform an 

independent analysis/certification of the cylinders. This analysis is compared to the vendor concentrations to determine 

if they are within the contractually required acceptance tolerance. 

STN/IMPROVE 

Round Robins PTs 

and Audits 

ORIA-AL 

PM2.5 Speciation Trends Network (STN) and IMPROVE Round Robins are a type of performance evaluation where the 

audit samples are developed in ambient air; therefore, the true concentration is unknown. The Office of Indoor Air and 

Radiation (ORIA) in Montgomery, AL) implement these audits for the STN/IMPROVE programs and for the PEP 

weighing laboratories. The audit is performed by collecting samples over multiple days and from multiple samplers. 

These representative samples are then characterized by the ORIA lab and sent to the routine sample laboratories for 

analysis. Since the true concentrations are unknown, the reported concentrations are reviewed to determine general 

agreement among the laboratories. In addition ORIA implements technical systems audits of IMPROVE and STN 

laboratories 

Protocol Gas 

OAQPS 

EPA Protocol Gases are used in quality control activities (i.e., calibrations, audits etc.) to ensure the quality of data 

derived from ambient air monitors used by every State in the country. EPA developed the Protocol Gas Program to 

allow standards sold by specialty gas producers to be considered traceable to NIST standards. This program was 

discontinued in 1998. In 2002, there was interest by the gas vendors and EPA to reestablish this program. The program 

is presently (as of 2008) undergoing re-structuring. 

Although Table 15-1 lists seven performance evaluation programs operating at the federal level, the 

NPAP and PEP Programs will be discussed in more detail. Additional information on both programs can 

be found on the AMTIC Website4

. The October 17, 2006 monitoring rule identified the monitoring 

organizations as responsible for ensuring the implementation of these audits5

. Monitoring organizations 

 

3

 see www.eenews.net/Greenwire/Backissues/081604/08160403.htm 4 http://www.epa.gov/ttn/amtic/npepqa.html 5 http://www.epa.gov/ttn/amtic/40cfr53.html-Final - Revisions to Ambient Air Monitoring Regulations. 
QA Handbook Vol II, Section 15.0 

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can either implement the program itself or continue to participate in the federally implemented program. 

This choice is provided to the monitoring organization on an annual basis through a memo from OAQPS 

through the EPA Regions. In order for monitoring organization to self-implement the program they must 

meet criteria related to the adequacy of the audit (number of audits and how it is accomplished) as well as 

meet independence requirements (see Figure 15.1). 

15.2.1 National Performance Audit Program6

Monitoring organizations operating SLAMS/PAMS/PSD are required to participate in the National 

Performance Evaluation Programs by providing adequate and independent audits for its monitors as per 

Section 2.4 of 40 CFR Part 58, Appendix. One way of providing the audits is to participate in the NPAP 

program either through self-implementation or federal implementation. 

The NPAP is a cooperative effort among OAQPS, the 10 EPA Regional Offices, and the monitoring 

organizations that operate the SLAMS/PAMS/PSD air pollution monitors. The NPAP’s goal is to provide 

audit materials and devices that will enable EPA to assess the proficiency of monitoring organizations 

that are operating monitors in the SLAMS/PAMS/PSD networks. To accomplish this, the NPAP has 

established acceptable limits or performance criteria, based on the data quality needs of the networks, for 

each of the audit materials and devices used in the NPAP. 

All audit devices and materials used in the NPAP are certified as to their true value, and that certification 

is traceable to a National Institute of Standards and Technology (NIST) standard material or device 

wherever possible. The audit materials used in the NPAP are as representative and comparable as 

possible to the calibration materials and actual air samples used and/or collected in the 

SLAMS/PAMS/PSD networks. The audit material/gas cylinder ranges used in the NPAP are specified in 

the Federal Register. 

Initially the NPAP system was a mailable system where standards and gasses were mailed to monitoring 

organizations for implementation. In 2003, OAQPS started instituting a through the probe audit system 

where mobile laboratories are sent to monitoring sites and audit gasses are delivered through the inlet 

probe of the analyzers. The goal of the NPAP audit is: 

• Performing audits at 20 percent of monitoring sites per year, and 100% in 5-7 years. 

• Data submission to AQS. 

• Development of a delivery system that will allow for the audit concentration gasses to be 

introduced to the probe inlet where logistically feasible. 

• Use of audit gases that are NIST certified and validated at least once a year for CO, SO2, and 

NO2. 

• Validation/certification with the EPA NPAP program through collocated auditing, at an 

acceptable number of sites each year. The comparison tests would have to be no greater than 5 

percent different from the EPA NPAP results. 

• Incorporation of NPAP in the monitoring organization’s quality assurance project plan (if self 

implementing). 

Table 15-2 lists the acceptance limits of the NPAP audits. 

 

6 http://www.epa.gov/ttn/amtic/npapgen.html 
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Table 15-2 NPAP Acceptance Criteria 

 Audit EPA determined limits 

High volume/PM10 (SSI) 

Dichot (PM10) 

Pb (analytical) 

SO2, NO2, and CO 

O3

PAMS 

 Volatile Organic Compounds 

 Carbonyls

% difference <15% for 1 or more flows 

% difference <15% for 1 or more flows 

% difference  <15% for 1 or more levels 

Mean absolute % difference < 15% 

Mean absolute % difference < 10% 

Compound Specific 

Compound and level specific

15.2.2 PM2.5 and PM10-2.5 Performance Evaluation Program (PEP) 

The Performance Evaluation Program7 is a quality assurance activity which will be used to evaluate 

measurement system bias of the PM2.5 and the PM10-2.5 monitoring networks. The pertinent regulations 

for this performance audit are found in 40 CFR Part 58, Appendix A. The strategy is to collocate a 

portable PEP instrument with an established routine air monitoring site, operate both monitors in exactly 

the same manner and then compare the results of this instrument against the routine sampler at the site. 

For primary quality assurance organizations with less than or equal to five monitoring sites, five valid 

performance evaluation audits must be collected and reported each year. For primary quality assurance 

organizations with greater than five monitoring sites, eight valid performance evaluation audits must be 

collected and reported each year. A valid performance evaluation audit means that both the primary 

monitor and PEP audit 

concentrations are valid and 

above 3 μg/m3

. Additionally, 

each year, every designated 

FRM or FEM within a 

primary quality assurance 

organization must: (1) have 

each method designation 

evaluated each year; and, (2) 

have all FRM or FEM 

samplers subject to a PEP 

audit at least once every six 

years; which equates to 

approximately 15 percent of 

the monitoring sites audited 

each year. 

 

7 http://www.epa.gov/ttn/amtic/pmpep.html 

Since performance 

evaluations are independent 

assessments, Figure 15.1 was 

developed to define 

independence for the FRM 

performance evaluation to 

allow monitoring 

organizations to implement 

this activity. 

Organization

3rd Level 

Supervision

Organization

2nd Level 

Supervision

Organization 

1st Level 

Supervision

Organization

Personnel

QA Lab Analysis

Organization

1st Level 

Supervision

Organization

Personnel

QA Field Sampling

Organization

2nd Level 

Supervision

Organization

1st Level 

Supervision

Organization 

Personnel

Routine Lab Analysis

Organization

1st Level 

Supervision

Organization

Personnel 

Routine Field Sampling

Independent assessment - an assessment performed by a qualified individual, group, or 

organization that is not part of the organization directly performing and accountable for 

the work being assessed. This auditing organization must not be involved with the 

generation of the routine ambient air monitoring data. An organization can conduct the 

PEP if it can meet the above definition and has a management structure that, at a 

minimum, will allow for the separation of its routine sampling personnel from its 

auditing personnel by two levels of management, as illustrated in the figure below. In 

addition, the pre and post weighing of audit filters must be performed by separate 

laboratory facility using separate laboratory equipment. Field and laboratory personnel 

would be required to meet the FRM Performance Audit field and laboratory training and 

certification requirements. The State and local organizations are also asked to consider 

participating in the centralized field and laboratory standards certification process.

Figure 15.1 Definition of independent assessment 
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Since the regulations define the performance evaluations as an NPAP like activity, EPA has made 

arrangements to implement this audit. Monitoring organizations can determine, on a yearly basis, to 

utilize federal implementation by directing their appropriate percentage of grant resources back to the 

OAQPS or implement the audit themselves. The following activities will be established for federal PEP 

implementation: 

• field personnel assigned to each EPA Region, the hours based upon the number of required audits 

in the Region; and 

• one national laboratory in Region 4 will serve as a national weighing lab and will include data 

submittal to AQS. 

All documentation including the PEP Implementation Plan, QAPP, Field and Laboratory SOPs, and 

reports can be found on the AMTIC Bulletin Board at the PEP Website8

. 

15.2.3 State and Local Organization 

Performance Audits 

Any of the performance evaluation activities 

mentioned in this section can be performed 

internally by the monitoring organizations. If 

the monitoring organization intends to selfimplement NPAP or PEP then they will be 

required to meet the adequacy and 

independence criteria mentioned in earlier 

sections. Since a monitoring organization may 

want more audits then can be supplied by the 

NPAP and PEP, it may decide to “augment” 

the federally implemented programs with 

additional performance audits. These audits 

can be tailored to the needs of the monitoring 

organization and do not necessarily need to 

follow NPAP and PEP adequacy and 

independence requirements. Some information 

on the procedures for this audit can be found 

in Appendix H. 

15.3 Technical Systems Audits 

A systems audit is an on-site review and 

inspection of a monitoring organization’s 

ambient air monitoring program to assess its 

compliance with established regulations 

governing the collection, analysis, validation, 

and reporting of ambient air quality data. A systems audit of each monitoring organization within an EPA 

Region is performed every three years by a member of the Regional Quality Assurance (QA) staff. 

 

8 http://www.epa.gov/ttn/amtic/pmpep.html 
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Detailed discussions of the audits performed by the EPA and the State and local organizations are found 

in Appendix H; the information presented in this section provides general guidance for conducting 

technical systems audits. A systems audit should consist of three separate phases: 

• Pre-audit activities. 

• On-site audit activities. 

• Post-audit activities.

Summary activity flow diagrams have been included as Figures 15.2, 15.3 and 15.5, respectively. The 

reader may find it useful to refer to these diagrams while reading this guidance. 

15.3.1 Pre-Audit Activities 

At the beginning of each fiscal year, the audit lead or a designated member of the audit team should 

establish a tentative schedule for on-site systems audits of the monitoring organizations within their 

Region. It is suggested that the audit lead develop an audit plan. This plan should address the 

elements listed in Table 15-3. The audit plan is not a major undertaking and in most cases will be a 

one page table or report. However, the document represents thoughtful and conscious planning for an 

efficient and successful audit. The audit plan should be made available to the organization audited, 

with adequate lead time to ensure that appropriate personnel and documents are available for the 

audit. Three months prior to the audit, the audit lead should contact the quality assurance officer 

(QAO) of the organization to be audited to coordinate specific dates and schedules for the on-site 

audit visit. During this initial contact, the audit lead should arrange a tentative schedule for meetings 

with key personnel as well as for inspection of selected ambient air quality monitoring and 

measurement operations. At the same time, a schedule should be set for the exit interview used to 

debrief the monitoring organization director or his/her designee, on the systems audit outcome. As 

part of this scheduling, the audit lead should indicate any special requirements such as access to 

specific areas or activities. The audit lead should inform the monitoring organization QAO that the 

QAO will receive a questionnaire, which is to be reviewed and completed. 

Table 15-3 Suggested Elements of an Audit Plan 

Audit Title - Official title of audit that will be used on checksheets and reports 

Audit #- Year and number of audit can be combined; 08-1, 08-2 Date of audit 

Scope - Establishes the boundary of the audit and identifies the groups and activities to be evaluated. 

The scope can vary from general overview, total system, to part of system, which will 

determine the length of the audit. 

Purpose - What the audit should achieve 

Standards - Standards are criteria against which performance is evaluated. These standards must be clear 

and concise and should be used consistently when auditing similar facilities or procedures. The 

use of audit checklists is suggested to assure that the full scope of an audit is covered. An 

example checklist for the Regional TSA is found in Appendix H. 

Audit team - Team lead and members. 

Auditees - People who should be available for the audit from the audited organization. This should include 

the program manager(s), principal investigator(s), monitoring leads, organizations QA 

representative(s), and other management and technicians as necessary. 

Documents - Documents that should be available in order for the audit to proceed efficiently. Too often 

documents are asked for during an audit, when auditors do not have the time to wait for these 

documents to be found. Documents could include QMPs, QAPPs, SOPs, GLPs, control charts, 

raw data, QA/QC data, previous audit reports etc. 

Timeline - A timeline of when organizations (auditors/auditees) will be notified of the audit in order for 

efficient scheduling and full participation of all parties. 
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The audit lead should emphasize that the completed questionnaire is to be returned within one (1) month 

(or time frame deemed appropriate) of receipt. The information within the questionnaire is considered a 

minimum, and both the Region and the monitoring organization under audit should feel free to include 

additional information. Once the completed questionnaire has been received, it should be reviewed and 

compared with the pertinent criteria and regulations. The AQS precision, bias and completeness data as 

well as any other information on data quality can augment the documentation received from the reporting 

organization under audit. This preliminary evaluation will be instrumental in selecting the sites to be 

evaluated and in the decision on the extent of the monitoring site data audit. The audit team should then 

prepare a checklist detailing specific points for discussion with monitoring organization personnel. 

The audit team should be made of several members to offer a wide variety of backgrounds and expertise. 

This team may then divide into groups once on-site, so that both audit coverage and time utilization can 

be optimized. A possible division may be that one group assesses the support laboratory and headquarters 

operations while another evaluates sites, and subsequently assesses audit and calibration information. 

The audit lead should confirm the proposed audit schedule with the audited organization immediately 

prior to traveling to the site. 

15.3.2. On-Site Activities 

The audit team should meet initially 

with the audited monitoring 

organization’s director or his/her 

designee to discuss the scope, 

duration, and activities involved with 

the audit. This should be followed by 

a meeting with key personnel 

identified from the completed 

questionnaire, or indicated by the 

monitoring organization QAO. Key 

personnel to be interviewed during 

the audit are those individuals with 

responsibilities for: planning, field 

operations, laboratory operations, 

QA/QC, data management and 

reporting. At the conclusion of these 

introductory meetings, the audit team 

may begin work as two or more 

independent groups, as illustrated in 

Figure 15.3. To increase uniformity 

of site inspections, it is suggested that 

a site checklist be developed and 

used. The format for Regional TSAs 

can be found in Appendix H. 

The importance of the audit of data 

quality (ADQ) cannot be overstated. 

Thus, sufficient time and effort should 

be devoted to this activity so that the audit team has a clear understanding and complete documentation of 
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data flow. Its importance stems from the need to have documentation on the quality of ambient air 

monitoring data for all the criteria pollutants for which the monitoring organization has monitoring 

requirements. The ADQ will serve as an effective framework for organizing the extensive 

amount of information gathered during the audit of laboratory, field monitoring and support functions 

within the monitoring organization. 

The entire audit team should prepare a brief written summary of findings, organized into the following 

areas: planning, field operations, laboratory operations, quality assurance/quality control, data 

management, and reporting. Problems with specific areas should be discussed and an attempt made to 

rank them in order of their potential impact on data quality. For the more serious problems, audit findings 

should be drafted (Fig. 15.4). 

The audit finding form has been designed such that one is filled out for each major deficiency that 

requires formal corrective action. They inform the monitoring organization being audited about a serious 

finding that may compromise the quality of the data and therefore require specific corrective actions. 

They are initiated by the audit team, and discussed at the debriefing. During the debriefing discussion, 

evidence may be presented that reduces the significance of the finding; in which case the finding may be 

Audit Finding

Audit Title: Audit #: Finding #: 

 

Finding: 

 

 Discussion: 

QA Lead Signature: Date: 

Audited Agencies 

 Signature: Date: 

Figure 15.4 Audit finding form 
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removed. If the audited monitoring organization is in agreement with the finding, the form is signed by 

the monitoring organization's director or his/her designee during the exit interview. If a disagreement 

occurs, the QA Team should record the opinions of the monitoring organization audited and set a time at 

some later date to address the finding at issue. 

The audit is now completed by having the audit team members meet once again with key personnel, the 

QAO and finally with the monitoring organization's director to present their findings. This is also the 

opportunity for the monitoring organization to present their disagreements. 

The audit team should simply state the audit results, including an indication of the potential data quality 

impact. During these meetings, the audit team should also discuss the systems audit reporting schedule 

and notify monitoring organization personnel that they will be given a chance to comment in writing, 

within a certain time period, on the prepared audit report in advance of any formal distribution. 

15.3.3 Post-Audit Activities 

The major post-audit activity is the preparation of the 

systems audit report. The report will include: 

• audit title, number and any other identifying 

information; 

• audit team leaders, audit team participants 

and audited participants; 

• background information about the project, 

purpose of the audit, dates of the audit, 

particular measurement phase or parameters 

that were audited, and a brief description of 

the audit process; 

• summary and conclusions of the audit and 

corrective action requirements; and 

• attachments or appendices that include all 

audit evaluations and audit finding forms. 

To prepare the report, the audit team should meet and 

compare observations with collected documents and 

results of interviews and discussions with key 

personnel. Expected QA project plan implementation 

is compared with observed accomplishments and 

deficiencies and the audit findings are reviewed in 

detail. Within thirty (30) calendar days of the 

completion of the audit, the audit report should be 

prepared and submitted. 

The technical systems audit report is submitted to the 

audited monitoring organization. It is suggested that 

a cover letter be used to reiterate the fact that the audit report is being provided for review and written 

comment. The letter should also indicate that, should no written comments be received by the audit lead 

within thirty (30) calendar days from the report date, it will be assumed acceptable to the monitoring 

organization in its current form, and will be formally distributed without further changes. 
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If the monitoring 

organization has written 

comments or questions 

concerning the audit report, 

the audit team should 

review and incorporate 

them as appropriate, and 

subsequently prepare and 

resubmit a report in final 

form within thirty (30) days 

of receipt of the written 

comments. Copies of this 

report should be sent to the 

monitoring organization 

director or his/her designee 

for internal distribution. 

The transmittal letter for the 

amended report should 

indicate official distribution 

and again draw attention to 

the agreed-upon schedule 

for corrective action 

implementation. 

15.3.4 Follow-up and Corrective Action Requirements 

As part of corrective action and follow-up, an audit finding response form (Fig 15.6) is generated by the 

audited organization for each finding form submitted by the audit team. The audit finding response form 

is signed by the audited organization’s director and sent to the organization responsible for oversight who 

reviews and accepts the corrective action. The audit response form should be completed by the audited 

organization within 30 days of acceptance of the audit report.

 Audit Finding Response Form

Audit Title: Audit #: Finding #: 

 

Finding: 

Cause of the problem: 

Actions taken or planned for correction: 

Responsibilities and timetable for the above actions: 

Prepared by: Date: 

 

Reviewed by: Date: 

Remarks: 

 

 Is this audit finding closed? When? 

 File with official audit records. Send copy to auditee 

Figure 15.6 Audit response form
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15.4 Data Quality Assessments 

A data quality assessment (DQA) is the statistical analysis of environmental data, to determine whether 

the quality of data is adequate to support the decisions which are based on the DQOs. Data are 

appropriate if the level of uncertainty in a decision, based on the data, is acceptable. The DQA process is 

described in detail in the guidance document: Data Quality Assessment: A Reviewers Guide (EPA QA/G9R)9

, in Section 18 and is summarized below. 

 

9 http://www.epa.gov/quality1/qs-docs/g9r-final.pdf 

1) Review the data quality objectives (DQOs) and sampling design of the program: review the DQO 

and develop one, if it has not already been done. Define statistical hypothesis, tolerance limits, 

and/or confidence intervals. 

2) Conduct preliminary data review. Review QA data and other available QA reports, calculate 

summary statistics, plots and graphs. Look for patterns, relationships, or anomalies. 

3) Select the statistical test: select the best test for analysis based on the preliminary review, and 

identify underlying assumptions about the data for that test. 

4) Verify test assumptions: decide whether the underlying assumptions made by the selected test hold 

true for the data and the consequences. 

5) Perform the statistical test: perform test and document inferences. Evaluate the performance for 

future use. 

A companion document to EPA QA/G-R, EPA QA/G-9S document provides many appropriate statistical 

tests. QAD is also developing statistical software to complement the document. Both can be found on 

the QAD Homepage (http://es.epa.gov/ncerqa). 

OAQPS plans on performing data quality assessments for the pollutants of the Ambient Air Quality 

Monitoring Network at a yearly frequency for data reports and at a 3-year frequency for more 

interpretative reports. Reporting organizations and State and local monitoring organizations are 

encouraged to implement data quality assessments at their levels. Attaining the DQOs at a local level will 

ensure that the DQOs will be met when data is aggregated at higher levels. 
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16.0 Reports to Management

This section provides guidance and suggestions to air monitoring organizations on how to report the 

quality of the aerometric data, and how to convey personnel information and requests for assistance 

concerning quality control and quality assurance problems. The guidance offered here is primarily 

intended for PQAOs that provide data to one or more of these national networks: 

 SLAMS (State and Local Air Monitoring Stations) 

 PAMS (Photochemical Air Monitoring Stations) 

 PSD (Prevention of Significant Deterioration stations) 

 NCore (National Core Monitoring Network) 

 Chemical Speciation Network 

 NATTS (National Air Toxic Trend Stations) 

This guidance may also be useful in preparing reports that summarize data quality of other pollutant 

measurements such as those made at Special Purpose Monitoring Stations (SPMS) and state-specific 

programs. 

Several kinds of reports can be prepared. The size and frequency of the reports will depend on the 

information requested or to be conveyed. A brief, corrective action form or letter-style report might ask 

for attention to an urgent problem. On the other hand, an annual quality assurance report to management 

would be a much larger report containing sections such as: 

 executive summary 

 network background and present status 

 quality objectives for measurement data 

 quality assurance procedures 

 results of quality assurance activities, and 

 recommendations for further quality assurance work, with suggestions for improving 

performance and fixing equipment problems, personnel training, infrastructure needs, etc. 

A report to management should not solely consist of tabulations of analyzer-by-analyzer precision and 

bias check results for criteria pollutants. This information is required to be submitted with the data each 

quarter and is thus already available to management through AQS. Instead, the annual quality assurance 

report to management should summarize and discuss the results of such checks. These summaries from 

individual PQAOs can be incorporated into additional reports issued by the state, local, tribal and/or the 

EPA Regional Office. 

This section also provides general information for the preparation of reports to management and includes: 

 the types of reports that might be prepared, the general content of each type of report, and a 

suggested frequency for their preparation 

 sources of information that can be tapped to retrieve information for the reports, and 

 techniques and methods for concise and effective presentation of information. 

Appendix I presents examples of two types of reports to management; the annual quality assurance report 

to management and a corrective action request. 
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16.1 Guidelines for Preparation of Reports to Management

16.1.1 Types of QA Reports to Management

Listed in Table 16-1 are examples of typical QA reports to management. An individual reporting 

organization may have others to add to the list or may create reports that are combinations of those listed 

below. 

Table 16-1 Types of QA Reports to Management

Suggested Reporting Frequency Type of QA Report 

to Management Contents As 

required Week Month Quarter Year

Corrective action 

request 

Description of problem; recommended 

action required; feedback on resolution 

of problem. 

x 

Control chart with 

summary 

Repetitive field or lab activity; control 

limits versus time. Prepare monthly or 

whenever new check or calibration 

samples are used. 

x x x x 

National Performance 

Evaluation Program 

results 

Summary of PEP,NPAP, NATTS PT 

and CSN audit results. x x 

State and local 

organization 

performance audits 

Summary of audit results; 

recommendations for action, as needed. x x 

Technical systems 

audits 

Summary of system audit results; 

recommendations for action, as needed. x x 

Quality assurance 

report to management 

Executive summary. Precision, bias, and 

system and performance audit results. x x 

Network reviews (by 

EPA Regional 

Office) 

Review results and suggestions for 

actions, as needed. x x 

16.1.2 Sources of Information

Information for inclusion in the various reports to management may come from a variety of sources, 

including: records of precision and bias checks (AMP255 reports), results of systems and performance 

audits, laboratory and field instrument maintenance logbooks, NPAP audits, etc. Table 16-2 lists useful 

sources and the type of information expected to be found. 

Table 16-2 Sources of Information for Preparing Reports to Management

Information Source Expected Information and Usefulness

State implementation plan Types of monitors, locations, and sampling schedule. 

Quality assurance program and project plans Data quality indicators and goals for precision, bias, 

completeness, timeliness. 

Quality objectives for measurement data document Quality objectives for measurement data. Audit procedures 

and frequency. 

Laboratory and field instrument maintenance logbooks Record of maintenance activity, synopsis of failures, 

recommendations for equipment overhaul or replacement. 

Laboratory weighing room records of temperature, humidity A record of whether or not environmental control in the 

weighing room is adequate to meet goals. 

Audit results (NPAP, local, etc.) Results of audit tests on ambient air pollutant measurement 

devices. 

Quality control data on local information management 

systems or AQS 

Results are generally considered valid and can be used to 

determine achievement of data quality objectives. 
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16.1.3 Methods of Presenting Information

Reports to management are most effective when the information is given in a succinct, well-summarized 

fashion. Methods useful for distilling and presenting information in ways that are easy to comprehend are 

listed in Table 16-3. A 2008 Guidance Document, designed to assist Tribes in developing monitoring 

programs contains an expanded section (Section 7) that discusses many of the statistical techniques 

described in Table 16-31

. Several of these methods are available on-line in AQS; others are available in 

commercially available statistical and spreadsheet computer programs. 

Table 16-3 Presentation Methods for Use in Reports to Management

Presentation Method Typical Use Examples

Written text Description of results and responses to 

problems 

Appendix I 

Control chart Shows whether a repetitive process 

stays within QC limits. 

Figure 10.2 of this Handbook 

Black box report Shows if project goals were met. Executive Summary of Appendix I 

Bar charts Shows relationships between numerical 

values. 

Included in most graphic and 

spreadsheet programs

X Y (scatter) charts Shows relationships between two 

variables. 

Included in most graphic and 

spreadsheet programs 

Probability limit charts and box and 

whisker plots 

Show a numerical value with its 

associated precision range. 

Figure 1 of Appendix I

16.1.4 Annual Quality Assurance Report

The annual quality assurance report (an example is provided in Appendix I) should consist of a number of 

sections that describe the quality objectives for measurement data and how those objectives have been 

met. A suggested organization might include: 

Executive Summary of Report to Management - The executive summary should be a short section 

(no more than two pages) that summarizes the annual quality assurance report to management. It 

should contain a checklist graphic that lets the reader know how the reporting organization has met 

its goals for the report period. In addition, a short discussion of future needs and plans should be 

included. 

Introduction - This section describes the quality objectives for measurement data and serves as an 

overview of the reporting organization’s structure and functions. It also briefly describes the 

procedures used by the reporting organization to assess the quality of field and laboratory 

measurements. 

Quality Information for each Ambient Air Pollutant Monitoring Program - These sections are 

organized by ambient air pollutant category (e.g., gaseous criteria pollutants, air toxics). Each 

section includes the following topics: 

 program overview and update 

 quality objectives for measurement data 

 data quality assessment 

 

1

 Technical Guidance for the Development of Tribal Monitoring Programs 

http://www.epa.gov/ttn/oarpg/t1/memoranda/techguidancetribalattch.pdf
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16.1.5 Corrective Action Request

A corrective action request should be made whenever anyone in the reporting organization notes a 

problem that demands either immediate or long-term action to correct a safety defect, an operational 

problem, or a failure to comply with procedures. A typical corrective action request form, with example 

information entered, is shown in Appendix I. A separate form should be used for each problem identified. 

The corrective action report form is designed as a closed-loop system. First it identifies the originator; the 

person who reports and identifies the problem, states the problem and may suggest a solution. The form 

then directs the request to a specific person or persons (i.e., the recipient), who would be best qualified to 

“fix” the problem. Finally, the form closes the loop by requiring that the recipient state how the problem 

was resolved and the effectiveness of the solution. The form is signed and a copy is returned to the 

originator and other copies are sent to the supervisor and the applicable files for the record. 
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17.0 Data Review, Verification and Validation 

Data review, verification and validation are techniques used to accept, reject or qualify data in an 

objective and consistent manner. Verification can be defined as confirmation, through provision of 

objective evidence that specified requirements have been fulfilled1

. Validation can be defined as 

confirmation through provision of objective evidence that the particular requirements for a specific 

intended use are fulfilled. It is important to describe the criteria for deciding the degree to which each 

data item has met its quality specifications as described in an organization’s QAPP. This section will 

describe the techniques used to make these assessments. 

In general, these assessment activities are performed by persons implementing the environmental data 

operations as well as by personnel “independent” of the operation, such as the organization’s QA 

personnel and at some specified frequency. The procedures, personnel and frequency of the assessments 

should be included in an organization’s QAPP. These activities should occur prior to submitting data to 

AQS and prior to final data quality assessments that will be discussed in Section 18. 

Each of the following areas of discussion should be considered during the data 

review/verification/validation processes. Some of the discussion applies to situations in which a sample 

is separated from its native environment and transported to a laboratory for analysis and data generation; 

others are applicable to automated instruments. The following information is an excerpt from EPA G-52

: 

Sampling Design - How closely a measurement represents the actual environment at a given time and 

location is a complex issue that is considered during development of the sampling design. Each sample 

should be checked for conformity to the specifications, including type and location (spatial and temporal). 

By noting the deviations in sufficient detail, subsequent data users will be able to determine the data’s 

usability under scenarios different from those included in project planning. 

Sample Collection Procedures- Details of how a sample is separated from its native time/space location 

are important for properly interpreting the measurement results. Sampling methods and field SOPs 

provide these details, which include sampling and ancillary equipment and procedures (including 

equipment decontamination). Acceptable departures (for example, alternate equipment) from the QAPP, 

and the action to be taken if the requirements cannot be satisfied, should be specified for each critical 

aspect. Validation activities should note potentially unacceptable departures from the QAPP. Comments 

from field surveillance on deviations from written sampling plans also should be noted. 

Sample Handling- Details of how a sample is physically treated and handled during relocation from its 

original site to the actual measurement site are extremely important. Correct interpretation of the 

subsequent measurement results requires that deviations from the sample handling section of the QAPP 

and the actions taken to minimize or control the changes, be detailed. Data collection activities should 

indicate events that occur during sample handling that may affect the integrity of the samples. At a 

minimum, investigators should evaluate the sample containers and the preservation methods used and 

ensure that they are appropriate to the nature of the sample and the type of data generated from the 

sample. Checks on the identity of the sample (e.g., proper labeling and chain of custody records) as well 

as proper physical/chemical storage conditions (e.g., chain of custody and storage records) should be 

made to ensure that the sample continues to be representative of its native environment as it moves 

through the analytical process. 

 

1

 ISO-9000 http://www.iso.org/iso/iso_catalogue/management_standards/iso_9000_iso_14000.htm 2

 EPA Guidance to Quality Assurance Project Plans http://www.epa.gov/quality1/qs-docs/g5-final.pdf 
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Analytical Procedures- Each sample should be verified to ensure that the procedures used to generate 

the data were implemented as specified. Acceptance criteria should be developed for important 

components of the procedures, along with suitable codes for characterizing each sample's deviation from 

the procedure. Data validation activities should determine how seriously a sample deviated beyond the 

acceptable limit so that the potential effects of the deviation can be evaluated during DQA. 

Quality Control- The quality control section of the QAPP specifies the QC checks that are to be 

performed during sample collection, handling and analysis. These include analyses of check standards, 

blanks and replicates, which provide indications of the quality of data being produced by specified 

components of the measurement process. For each specified QC check, the procedure, acceptance 

criteria, and corrective action (and changes) should be specified. Data validation should document the 

corrective actions that were taken, which samples were affected, and the potential effect of the actions on 

the validity of the data. 

Calibration- Calibration of instruments and equipment and the information that should be presented to 

ensure that the calibrations: 

• were performed within an acceptable time prior to generation of measurement data 

• were performed in the proper sequence 

• included the proper number of calibration points 

• were performed using standards that “bracketed” the range of reported measurement results 

otherwise, results falling outside the calibration range should be flagged as such 

• had acceptable linearity checks and other checks to ensure that the measurement system was 

stable when the calibration was performed 

When calibration problems are identified, any data produced between the suspect calibration event and 

any subsequent recalibration should be flagged to alert data users. 

Data Reduction and Processing- Checks on data integrity evaluate the accuracy of “raw” data and 

include the comparison of important events and the duplicate keying of data to identify data entry errors. 

Data reduction may be an irreversible process that involves a loss of detail in the data and may involve 

averaging across time (for example, 5-minute, hourly or daily averages) or space (for example, 

compositing results from samples thought to be physically equivalent) such as the Pb sample aggregation 

or PM2.5 spatial averaging techniques. Since this summarizing process produces few values to represent a 

group of many data points, its validity should be well-documented in the QAPP. Potential data anomalies 

can be investigated by simple statistical analyses. 

The information generation step involves the synthesis of the results of previous operations and the 

construction of tables and charts suitable for use in reports. How information generation is checked, the 

requirements for the outcome, and how deviations from the requirements will be treated, should be 

addressed. 
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17.1 Data Review Methods

The flow of data from the field environmental data operations to the storage in the database requires 

several distinct and separate steps: 

• initial selection of hardware and software for the acquisition, storage, retrieval and transmittal of 

data 

• organization and the control of the data flow from the field sites and the analytical laboratory 

• input and validation of the data 

• manipulation, analysis and archival of the data 

• submittal of the data into the EPA’s AQS database. 

Both manual and computer-oriented systems require individual reviews of all data tabulations. As an 

individual scans tabulations, there is no way to determine that all values are valid. The purpose of manual 

inspection is to spot unusually high (or low) values (outliers) that might indicate a gross error in the data 

collection system. In order to recognize that the reported concentration of a given pollutant is extreme, 

the individual must have basic knowledge of the major pollutants and of air quality conditions prevalent 

at the reporting station. Data values considered questionable should be flagged for verification. This 

scanning for high/low values is sensitive to spurious extreme values but not to intermediate values that 

could also be grossly in error. 

Manual review of data tabulations also allows detection of uncorrected drift in the zero baseline of a 

continuous sensor. Zero drift may be indicated when the daily minimum concentration tends to increase 

or decrease from the norm over a period of several days. For example, at most sampling stations, the 

early morning (3:00 a.m. to 4:00 a.m.) concentrations of carbon monoxide tend to reach a minimum 

(e.g., 2 to 4 ppm). If the minimum concentration differs significantly from this, a zero drift may be 

suspected. Zero drift could be confirmed by review of the original strip chart. 

In an automated data processing system, procedures for data validation can easily be incorporated into the 

basic software. The computer can be programmed to scan data values for extreme values, outliers or 

ranges. These checks can be further refined to account for time of day, time of week, and other cyclic 

conditions. Questionable data values are then flagged on the data tabulation to indicate a possible error. 

Other types of data review can consist of preliminary evaluations of a set of data, calculating some basic 

statistical quantiles and examining the data using graphical representations. 

17.2 Data Verification Methods

Verification can be defined as confirmation, through provision of objective evidence that specified 

requirements have been fulfilled3

. The verification requirements for each data operation are included in 

the organizations’ QAPP and in SOPs and should include not only the verification of sampling and 

analysis processes but also operations like data entry, calculations and data reporting. The data 

verification process involves the inspection, analysis, and acceptance of the field data or samples. These 

inspections can take the form of technical systems audits (internal or external) or frequent inspections by 

 

3 Guidance on Environmental Data Verification and Data Validation (QA/G-8) http://www.epa.gov/quality1/qa_docs.html throgh 

proviosion of objective evidence 
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field operators and lab technicians. Questions that might be asked during the verification process include: 

• Were the environmental data operations performed according to the SOPs governing those 

operations? 

• Were the environmental data operations performed on the correct time and date originally 

specified? Many environmental operations must be performed within a specific time frame; for 

example, the NAAQS samples for particulates are collected once every six days from midnight to 

midnight. The monitor timing mechanisms must have operated correctly for the sample to be 

collected within the time frame specified. 

• Did the sampler or monitor perform correctly? Individual checks such as leak checks, flow 

checks, meteorological influences, and all other assessments, audits, and performance checks 

must have been acceptably performed and documented. 

• Did the environmental sample pass an initial visual inspection? Many environmental samples can 

be flagged (qualified) during the initial visual inspection. 

• Have manual calculations, manual data entry, or human adjustments to software settings been 

checked? Automated calculations should be verified and accepted prior to use, but at some 

frequencies these calculations should be reviewed to ensure that they have not changed. 

• Were the environmental data operations performed to meet data quality objectives designed for 

those specific data operations and were the operations performed as specified? The objectives for 

environmental data operations must be clear and understood by all those involved with the data 

collection. 

17.3 Data Validation Methods

Data validation is a routine process designed to ensure that reported values meet the quality goals of the 

environmental data operations. Data validation is further defined as examination and provision of 

objective evidence that the particular requirements for a specific intended use are fulfilled. A progressive, 

systematic approach to data validation must be used to ensure and assess the quality of data. 

The purpose of data validation is to detect and then verify any data values that may not represent actual 

air quality conditions at the sampling station. Effective data validation procedures usually are handled 

completely independently from the procedures of initial data collection. 

Because the computer can perform computations and make comparisons extremely rapidly, it can also 

make some determination concerning the validity of data values that are not necessarily high or low. Data 

validation procedures should be recommended as standard operating procedures. For example, one can 

evaluate the difference between successive data values, since one would not normally expect very rapid 

changes in concentrations of a pollutant during a 5-min or 1-h reporting period. When the difference 

between two successive values exceeds a predetermined value, the tabulation can be flagged, with an 

appropriate symbol. 

Quality control data can support data validation procedures (see section 17.3.3). If data assessment 

results clearly indicate a serious response problem with the analyzer, the agency should review all 

pertinent quality control information to determine whether any ambient data, as well as any associated 

assessment data, should be invalidated. Therefore if ambient data are determined to be invalid, then the 

associated precision, bias and accuracy readings should also be invalidated. Any data quality calculations 
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using the invalidated readings should be redone. Also, the precision, bias or accuracy checks should be 

rescheduled, preferably in the same calendar quarter. The basis or justification for all data invalidations 

should be permanently documented. 

Certain criteria, based upon CFR and field operator and laboratory technician judgment, may be used to 

invalidate a sample or measurement. These criteria should be explicitly identified in the organization’s 

QAPP. Many organizations use flags or result qualifiers to identify potential problems with data or a 

sample. A flag is an indicator of the fact and the reason that a data value (a) did not produce a numeric 

result, (b) produced a numeric result but it is qualified in some respect relating to the type or validity of 

the result, or (c) produced a numeric result but for administrative reasons is not to be reported outside the 

organization. Flags can be used both in the field and in the laboratory to signify data that may be suspect 

due to contamination, special events or failure of QC limits. Flags can be used to determine if individual 

samples (data), or samples from a particular instrument, will be invalidated. In all cases, the sample 

(data) should be thoroughly reviewed by the organization prior to any invalidation. 

Flags may be used alone or in combination to invalidate samples. Since the possible flag combinations 

can be overwhelming and can not always be anticipated, an organization needs to review these flag 

combinations and determine if single values or values from a site for a particular time period will be 

invalidated. The organization should keep a record of the combination of flags that resulted in 

invalidating a sample or set of samples. These combinations should be reported to the EPA Region and 

can be used to ensure that the organization evaluates and invalidates data in a consistent manner. 

Procedures for screening data for possible errors or anomalies should also be implemented. The data 

quality assessment document series (EPA QA/G-9R4

, EPA QA/G-9s5) provide several statistical 

screening procedures for ambient air quality data that should be applied to identify gross data anomalies. 

NOTE: it is strongly suggested that flags, specifically the appropriate null data code flags, be used in 

place of any routine values that are invalidated. This provides some indication to data users and data 

quality assessors to the reasons why data that was expected to be collected was missing. 

17.3.1 Automated Methods

When zero, span or one-point QC checks exceed acceptance limits, ambient measurements should be 

invalidated back to the most recent point in time where such measurements are known to be valid. 

Usually this point is the previous check, unless some other point in time can be identified and related to 

the probable cause of the excessive drift or exceedance (such as a power failure or malfunction). Also, 

data following an analyzer malfunction or period of non-operation should be regarded as invalid until the 

next subsequent (level 1) acceptable check or calibration. Based on the sophistication of DAS (see 

Section 14) monitoring organization may have other automated programs for data validation. These 

programs should be described in the monitoring organization’s approved QAPP prior to implementation. 

Even though the automated technique may be considered acceptable, the raw invalidated data should be 

archived for statute of limitations discussed in Section 5.

 

4

Data Quality Assessment: A Reviewer’s Guide http://www.epa.gov/quality1/qs-docs/g9r-final.pdf

5 Data Quality Assessment: Statistical Methods for Practitioners http://www.epa.gov/quality1/qs-docs/g9s-final.pdf
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17.3.2 Manual Methods

For manual methods, the first level of data validation should be to accept or reject monitoring data based 

upon results from operational checks selected to monitor the critical parameters in all three major and 

distinct phases of manual methods--sampling, analysis, and data reduction. In addition to using 

operational checks for data validation, the user must observe all limitations, acceptance limits, and 

warnings described in the reference and equivalent methods per se that may invalidate data. It is further 

recommended that results from performance audits/evaluations required in 40 CFR 58, Appendix A not 

be used as the sole criteria for data invalidation because these checks (performance audits) are intended to 

assess the quality of the data. 

17.3.3 Validation Templates 

In June 1998, a workgroup was formed to develop a procedure that could be used by monitoring 

organizations that would provide for a consistent validation of PM2.5 mass concentrations across the US. 

The Workgroup developed three tables of criteria where each table has a different degree of implication 

about the quality of the data. The criteria included on the tables are from 40 CFR Part 50, Appendices L 

and N, 40 CFR Part 58, Appendix A, Method 2.12, and a few criteria that are neither in CFR nor Method 

2.12. 

One of the tables has the criteria that must be met to ensure the quality of the data. An example criterion 

is that the average flow rate for the sampling period must be maintained to within 5% of 16.67 liters per 

minute. The second table has the criteria that indicate that there might be a problem with the quality of 

the data and further investigation is warranted before making a determination about the validity of the 

sample or samples. An example criterion is that the field filter blanks should not change weight by more 

than 30:g between weighings. The third table has criteria that indicate a potentially systematic problem 

with the environmental data collection activity. Such systematic problems may impact the ability to make 

decisions with the data. An example criterion is that at least 75% of the scheduled samples for each 

quarter should be successfully collected and validated. 

To determine the appropriate table for each criterion, the members of the workgroup considered how 

significantly the criteria impact the resulting PM2.5 mass. This was based on experience from workgroup 

members, experience from non-workgroup members, and feasibility of implementing the criterion. 

Criteria that were deemed critical to maintaining the integrity of a sample or group of samples were 

placed on the first table. Observations that do not meet each and every criterion on the Critical Criteria 

Table should be invalidated unless there are compelling reason and justification for not doing so. 

Basically, the sample or group of samples for which one or more of these criteria are not met is invalid 

until proven otherwise. The cause of not operating in the acceptable range for each of the violated criteria 

must be investigated and minimized to reduce the likelihood that additional samples will be invalidated. 

Criteria that are important for maintaining and evaluating the quality of the data collection system are 

included on the second table, the Operational Criteria Table. Violation of a criterion or a number of 

criteria may be cause for invalidation. The decision should consider other quality control information that 

may or may not indicate the data are acceptable for the parameter being controlled. Therefore, the sample 

or group of samples for which one or more of these criteria are not met is suspect unless other quality 
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control information demonstrates otherwise. The reason for not meeting the criteria MUST be 

investigated, mitigated or justified. 

Finally, those criteria which are important for the correct interpretation of the data but do not usually 

impact the validity of a sample or group of samples are included on the third table, the Systematic 

Criteria Table. For example, the data quality objectives are included in this table. If the data quality 

objectives are not met, this does not invalidate any of the samples but it may impact the error rate 

associated with the attainment/non-attainment decision. 

Based on the success and use of the PM2.5 validation template, the Workgroup embarked on the 

development of similar templates for the remaining criteria pollutants. Appendix D provides templates 

for each criteria pollutant. The validation templates are based on the current state of knowledge at the 

time of development of the Handbook. The template will evolve as new information is discovered about 

the impact of the various criterion on the error in the resulting concentration estimate. Interactions of the 

criteria, whether synergistic or antagonistic, should also be incorporated when the impact of these 

interactions becomes quantified. Due to the potential misuse of invalid data, data that are invalidated will 

not be uploaded to AQS but should be retained on the monitoring organizations local database. This data 

will be invaluable to the evolution of the validation template. 

NOTE: Strict adherence to the validation templates is not required. They are meant to be a guide 

based upon the knowledge of the Workgroup who developed them and may be a starting point for 

monitoring organization specific validation requirement. 

 
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18.0 Reconciliation with Data Quality Objectives

Section 3 described the data quality objective (DQO) process, which is an important planning tool to 

determine the objectives of an environmental data operation, to understand and agree upon the allowable 

uncertainty in the data and, with that, to optimize the sampling design. This information, along with 

sampling and analytical methods and appropriate QA/QC, should be documented in an organization’s 

QAPP. The QAPP is then implemented by the monitoring organizations under the premise that if it is 

followed, the DQOs should be met. Reconciliation with the DQO involves reviewing both routine and 

QA/QC data to determine whether the DQOs have been attained and that the data are adequate for their 

intended use. This process of evaluating the data against the DQOs has been termed data quality 

assessment (DQA). 

The DQA process has been developed for cases where formal DQOs have been established. However, 

these procedures can also be used for data that do not formally have DQOs. Guidance on the DQA 

process can be found in the documents titled Data Quality Assessment: A Reviewer’s Guide (EPA QA/G9R)1 and its companion document Data Quality Assessment: Statistical Tools for Practitioners (EPA 

QA/G-9S)

2

. This document focuses on evaluating data for fitness in decision-making and also provides 

many graphical and statistical tools. 

As stated in EPA QA/G-9R “Data quality, as a concept, is meaningful only when it relates to the intended 

use of the data”. By using the DQA Process, one can answer four fundamental questions: 

1. Can the decision (or estimate) be made with the desired level of certainty, given the quality of the 

data set? 

2. How well did the sampling design perform? 

3. If the same sampling design strategy is used again for a similar study, would the data be expected 

to support the same intended use with the desired level of uncertainty? 

4. Is it likely that sufficient samples were taken to enable the reviewer to see an effect if it was 

really present? 

DQA is a key part of the assessment phase of the data life cycle (Figure 18.1), which is very similar to the 

ambient air QA life cycle described in Section 1. As the part of the assessment phase that follows data 

validation and verification, DQA determines how well the validated data can support their intended use. 

18.1 Five Steps of the DQA Process

As described in EPA QA/G-9R1

 and EPA QA/G-9S2, the DQA process is comprised of five steps. The 

steps are detailed below. Since DQOs are available for the PM2.5 program, they will be used as an 

example for the type of information that might be considered in each step. The PM2.5 information is 

italicized and comes from a model PM2.5 QAPP3

 for a fictitious reporting organization called 

Palookaville. The model QAPP was developed to help monitoring organizations develop QAPPs based 

upon the new R-5 QAPP requirements. 

 

1 http://www.epa.gov/quality1/qs-docs/g9r-final.pdf

2 http://www.epa.gov/quality1/qs-docs/g9s-final.pdf 3 http://www.epa.gov/ttn/amtic/pmqainf.html 
QA Handbook Vol II, Section 18.0 

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Figure 18.1 DQA in the context of data life cycle. 

Step 1. Review DQOs and Sampling Design. Review the DQO outputs to assure that they are still 

applicable. If DQOs have not been developed, specify DQOs before evaluating the data (e.g., for 

environmental decisions, define the statistical hypothesis and specify tolerable limits on decision errors; 

for estimation problems, define an acceptable confidence probability interval width). Review the 

sampling design and data collection documentation for consistency with the DQOs observing any 

potential discrepancies. 

The PM2.5 DQOs define the primary objective of the PM2.5 ambient air monitoring network (PM2.5 NAAQS 

comparison), translate the objective into a statistical hypothesis (3-year average of annual mean PM2.5

concentrations less than or equal to 15 μg/m3 and 3-year average of annual 98th percentiles of the PM2.5

concentrations less than or equal to 35 μg/m3

), and identify limits on the decision errors (incorrectly 

conclude area in non-attainment when it truly is in attainment no more than 5% of the time, and 

incorrectly conclude area in attainment when it truly is in non-attainment no more than 5% of the time). 

The CFR contains the details for the sampling design, including the rationale for the design, the design 

assumptions, and the sampling locations and frequency. If any deviations from the sampling design have 

occurred, these will be indicated and their potential effect carefully considered throughout the entire 

DQA.

Step 2. Conduct Preliminary Data Review. Review QA reports, calculate basic statistics, and generate 

graphs of data. Use this information to understand the structure of the data and identify patterns, 

relationships, or potential anomalies. 
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A preliminary data review will be performed to uncover potential limitations of using the data, to reveal 

outliers, and generally to explore the basic structure of the data. The first step is to review the quality 

assurance reports. The second step is to calculate basic summary statistics, generate graphical 

presentations of the data, and review these summary statistics and graphs. 

Review Quality Assurance Reports. Palookaville will review all relevant quality assurance reports that 

describe the data collection and reporting process. Particular attention will be directed to looking for 

anomalies in recorded data, missing values, and any deviations from standard operating procedures. 

This is a qualitative review. However, any concerns will be further investigated in the next two steps. 

Calculation of Summary Statistics and Generation of Graphical Presentations. Palookaville will 

generate prominent summary statistics for each of its primary and QA samplers. These summary 

statistics will be calculated at the quarterly, annual, and three-year levels and will include only valid 

samples. The summary statistics are: 

Number of samples, mean concentration, median concentration, standard deviation, coefficient of 

variation, maximum concentration, minimum concentration, interquartile range, skewness and 

kurtosis. 

These statistics will also be calculated for the percent differences at the collocated sites. The results will 

be summarized in a table. Particular attention will be given to the impact on the statistics caused by the 

observations noted in the quality assurance review. For example, Palookaville may evaluate the 

influence of a potential outlier by evaluating the change in the summary statistics resulting from 

exclusion of the outlier. 

Palookaville will generate graphics to present the results from the summary statistics and show the 

spatial continuity over the sample areas. Maps will be created for the annual and three-year means, 

maxima, and interquartile ranges for a total of 6 maps. The maps will help uncover potential outliers and 

will help in the network design review. Additionally, basic histograms will be generated for each of the 

primary and QA samplers and for the percent difference at the collocated sites. The histograms will be 

useful in identifying anomalies and evaluating the normality assumption in the measurement errors.

Step 3. Select the Statistical Test. Select the most appropriate procedure for summarizing and 

analyzing the data, based upon the reviews of the performance and acceptance criteria associated with the 

DQOs, the sampling design, and the preliminary data review. Identify the key underlying assumptions 

that must hold for the statistical procedures to be valid. 

The primary objective for the PM2.5 mass monitoring is determining compliance with the PM2.5 NAAQS. 

As a result, the null and alternative hypotheses are:

3 3

3 3

0

: 15 / 35 /

: 15 / 35 /

H X g m or Y g m

H X g m and Y g m

A μ μ

μ μ

> >

≤ ≤

where X is the three-year average PM2.5 concentration and Y is the three-year average of the annual 98th 

percentiles of the PM2.5 concentrations recorded for an individual monitor. The exact calculations for X 

and Y are specified in 40 CFR Part 50, Appendix N. The null hypothesis is rejected; that is, it is 

concluded that the area is not in compliance with the PM2.5 NAAQS when the observed three-year 

average of the annual arithmetic mean concentration exceeds 15.05 μg/m3

 or when the observed 
QA Handbook Vol II, Section 18.0 

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Page 4 of 9 

three-year average of the annual 98th percentiles exceeds 35.5 μg/m3. If the bias of the sampler is ± 10% 

and the precision is within 10%, then the error rates (Type I and Type II) associated with this statistical 

test are less than or equal to 5%. The definitions of bias and precision will be outlined in the following 

step. 

Step 4. Verify Assumptions of Statistical Test. Evaluate whether the underlying assumptions hold, or 

whether departures are acceptable, given the actual data and other information about the study. 

The assumptions behind the statistical test include those associated with the development of the DQOs in 

addition to the bias and precision assumptions. The method of verification will be addressed in this step. 

Note that when less than three years of data are available, this verification will be based on as much data 

as are available.

The DQO is based on the annual arithmetic mean NAAQS. For each primary sampler, Palookaville 

will determine which, if either, of the PM2.5 NAAQS concentration is violated. In the DQO development, 

it was assumed that the annual standard is more restrictive than the 24-hour standard. If there are any 

samplers that violate ONLY the 24-hour NAAQS, then this assumption is not correct. The seriousness of 

violating this assumption is not clear. Conceptually, the DQOs can be developed based on the 24-hour 

NAAQS and the more restrictive bias and precision limits selected. However, Palookaville will assume 

the annual standard is more restrictive, until proven otherwise. 

Normal distribution for measurement error. Assuming that measurement errors are normally 

distributed is common in environmental monitoring. Palookaville has not investigated the sensitivity of 

the statistical test to violate this assumption; although, small departures from normality generally do not 

create serious problems. Instead, Palookaville will evaluate the reasonableness of the normality 

assumption by reviewing a normal probability plot, and calculating the Shapiro-Wilk W Test statistic (if 

sample size less than 50) or calculating the Kolmogorov-Smirnoff Test statistic (if sample size greater 

than 50). All three techniques are provided by standard statistical packages. If the plot or statistics 

indicate possible violations of normality, Palookaville may need to determine the sensitivity of the DQOs 

to departures in normality. 

Decision error can occur when the estimated 3-year average differs from the actual (true) 3-year 

average. This is not really an assumption as much as a statement that the data collected by an ambient 

air monitor is stochastic, meaning that there are errors in the measurement process, as mentioned in the 

previous assumption. 

The limits on precision and bias are based on the smallest number of required sample values in a 3-year 

period. In the development of the DQOs, the smallest number of required samples was used. The reason 

for this was to ensure that the confidence was sufficient in the minimal case; if more samples are 

collected, then the confidence in the resulting decision will be even higher. For each of the samplers, 

Palookaville will determine how many samples were collected in each quarter. If this number meets or 

exceeds 12, then the data completeness requirements for the DQO are met. 

The decision error limits were set at 5%. If the other assumptions are met, then the decision error limits 

are less than or equal to 5%. 

Measurement imprecision was established at 10% coefficient of variation (CV). For each sampler, 

Palookaville will review the coefficient of variation calculated in Step 2. If any exceed 10%, Palookaville 

may need to determine the sensitivity of the DQOs to larger levels of measurement imprecision. 
QA Handbook Vol II, Section 18.0 

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Table 18-1 will be completed during each DQA. The table summarizes which, if any, assumptions have 

been violated. A check will be placed in each of the row/column combinations that apply. Ideally, there 

will be no checks. However, if there are checks in the table, the implication is that the decision error 

rates are unknown, even if the bias and precision limits are achieved. As mentioned above, if any of the 

DQO assumptions are violated, then Palookaville will need to reevaluate its DQOs. 

Achievement of bias and precision limits. Lastly, Palookaville will check the assumption that at the 

3-year level of aggregation, the sampler bias is within + 10% and precision is < 10%. The data from the 

collocated samplers will be used to calculate quarterly, annual, and 3-year bias and precision estimates 

even though it is only the 3-year estimates that are critical for the statistical test. 

Since all the initial samplers being deployed by Palookaville will be FRMs, the samplers at each of the 

collocated sites will be identical method designations. As such, it is difficult to determine which of the 

collocated samplers is closer to the true PM2.5 concentration. Palookaville will calculate an estimate of 

precision. A bias measure will also be calculated, but it can only describe the relative difference of one 

sampler to the other, not definitively indicate which sampler is closer to the “true” value. The following 

paragraphs contain the algorithms for calculating precision and bias. These are similar, but differ 

slightly, from the equations in 40 CFR Part 58, Appendix A. 

Table 18-1 Summary of Violations of DQO Assumptions

Site Violate 24-Hour 

Standard ONLY? 

Measurement Errors 

Non-Normal? 

Data Complete? 

($ 12 samples per quarter) 

Measurement CV 

> 10%? 

Primary Samplers 

A1 

A2 

A3 

A4 

B1 

QA Samplers 

A1 

B1 

Before describing the algorithm, some ground work is necessary. When less than three years of 

collocated data are available, then the three-year bias and precision estimates must be predicted. 

Palookaville’s strategy for accomplishing this will be to use all available quarters of data as the basis for 

projecting where the bias and precision estimates will be at the end of the three-year monitoring period. 

Three-year point estimates will be computed by weighting the quarterly components, using the most 

applicable of the following assumptions: 

1. Most recent quarter’s precision and bias are most representative of what the future quarters will 

be. 

2. All previous quarters precision and bias are equally representative of what the future quarter’s 

will be. 

3. Something unusual happened in the most recent quarter, so the most representative quarters are 

all the previous ones, minus the most recent. 
QA Handbook Vol II, Section 18.0 

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Each of these scenarios results in weights that will be used in the following algorithms. The weights are 

shown in Table 18-2 where the variable Q represents the number of quarters for which observed bias and 

precision estimates are available. Note that when Q=12, that is, when there are bias and precision 

values for all of the quarters in the three-year period, then all of the following scenarios result in the 

same weighting scheme. 

Table 18-2 Weights for Estimating Three-Year Bias and Precision

Scenario Assumption Weights 

1 Latest quarter most representative wq = 12-(Q-1) for latest quarter, 

wq = 1 otherwise 

2 All quarters equally representative wq = 12/Q for each quarter 

3 Latest quarter unrepresentative wq = 1 for latest quarter, 

wq = 11/(Q-1) otherwise

In addition to point estimates, Palookaville will develop confidence intervals for the bias and precision 

estimates. This will be accomplished using a re-sampling technique. The protocol for creating the 

confidence intervals are outlined in Box 18.1. 

The algorithms for determining whether the bias and precision DQOs have been achieved for each 

sampler follow: 

Box 18.1 Method for Estimating Confidence in Achieving Bias and Precision DQOs

Let Z be the statistic of interest (bias or precision). For a given weighting scenario, the re-sampling will be 

implemented as follows: 

1. Determine M, the number of collocated pairs per quarter for the remaining 12-Q quarters (default is M=15 

or can use M=average number observed for the previous Q quarters. 

2. Randomly select with replacement M collocated pairs per quarter for each of the future 12-Q quarters in a 

manner consistent with the given weighting scenario. 

Scenario 1: Select pairs from latest quarter only. 

Scenario 2: Select pairs from any quarter. 

Scenario 3: Select pairs from any quarter except the latest one. 

Result from this step is “complete” collocated data for a three-year period, from which bias and precision 

estimates can be determined. 

3. Based on the “filled-out” three-year period from step 2, calculate three-year bias and precision estimate, 

using Equation 1 where wq = 1 for each quarter. 

4. Repeat steps 2 and 3 numerous times, such as 1000 times. 

5. Determine P, the fraction of the 1000 simulations for which the three-year bias and precision criteria are 

met. P is interpreted as the probability that the sampler is generating observations consistent with the 

three-year bias and precision DQOs.
QA Handbook Vol II, Section 18.0 

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Bias Algorithm

1. For each measurement pair, estimate the percent relative bias, di. 

( ) 100

/ 2

×

+

− =

i i

i i

i Y X

Y X d % 

 where Xi represents the concentration recorded by the primary sampler and Yi represents the 

concentration recorded by the collocated sampler. 

2. Summarize the percent relative bias to the quarterly level, Dj,q, according to 

∑=

=

n j q

i

i

j q

j q d

n

D

,

, 1

,

1

 where nj,q is the number of collocated pairs in quarter q for site j.

3. Summarize the quarterly bias estimates to the three-year level using 

 

∑

∑

=

= = q

q

n

q

q

n

q

q j q

j

w

w D

D

1

1

,

ˆ Equation 18-1

where nq is the number of quarters with actual collocated data and wq is the weight for quarter q 

as specified by the scenario in Table 18-2. 

4. Examine Dj,q to determine whether one sampler is consistently measuring above or below the 

other. To formally test this, a non-parametric test will be used (Wilcoxon Signed Rank Test), 

which is described in EPA QA/G-9S2

. If the null hypothesis is rejected, then one of the samplers 

is consistently measuring above or below the other. This information may be helpful in directing 

the investigation into the cause of the bias. 

Precision Algorithm

1. For each measurement pair, calculate the coefficient of variation, cvi, 

2

i

i

d

c v =
QA Handbook Vol II, Section 18.0 

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Date: 12/08 

Page 8 of 9 

2. Summarize the coefficient of variation to the quarterly level, CVj,q, according to 

j q

n

i

i

j q n

CV

CV

j

,

1

2

,

∑= =

 where nj,q is the number of collocated pairs in quarter q for site j. 

3. Summarize the quarterly precision estimates to the three-year level using 

 

( )

∑

∑

=

= = q

q

n

q

q

n

q

q j q

j

w

w CV

CV

1

1

2

, ^

 Equation 18-2 

where nq is the number of quarters with actual collocated data and wq is the weight for quarter q 

as specified by the scenario in Table 24-2 (reference to Model QAPP). 

4. If the null hypothesis in the Wilcoxon Signed Rank Test was not rejected, then the coefficient of 

variation can be interpreted as a measure of precision. If the null hypothesis in the Wilcoxon 

Ssigned Rank Test was rejected, the coefficient of variation has both a component representing 

precision and a component representing the (squared) bias. 

Confidence in Bias and Precision Estimates

1. Follow the method described in Box 18.1 to estimate the probability that the sampler is 

generating observations consistent with the three-year bias and precision DQOs. The 

re-sampling must be done for each collocated site. 

Summary of Bias and Precision Estimation

The results from the calculations and re-sampling will be summarized in Table 18-3. There will be one 

line for each site operating a collocated sampler. 

 Table 18-3 Summary of Bias and Precision

Collocated Three-year Bias Estimate 

(Equation. 1) 

Three-year Precision Estimate 

 (Equation. 2) 

Null Hypothesis of Wilcoxon Test 

Rejected? 

P

(Box 18-1) 

A1 

B1
QA Handbook Vol II, Section 18.0 

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Page 9 of 9 

Step 5. Draw Conclusions from the Data. Perform the calculations required for the statistical test and 

document the inferences drawn as a result of these calculations. If the design is to be used again, evaluate 

the performance of the sampling design. 

Before determining whether the monitored data indicate compliance with the PM2.5 NAAQS, Palookaville 

must first determine if any of the assumptions upon which the statistical test is based are violated. This 

can be easily checked in Step 5 because of all the work done in Step 4. In particular, as long as 

 in Table 18-1, there are no checks, and 

 in Table 18-3, 

R the three year bias estimate is in the interval [-10%,10%], and 

R the three year precision estimate is less than or equal to 10% 

then the assumptions underlying the test appear to be valid. As a result, if the observed three-year 

average PM2.5 concentration is less than 15 μg/m3 and the observed three-year average 98th percentile is 

less than 35 μg/m3

, the conclusion is that the area seems to be in compliance with the PM2.5 NAAQS, with 

an error rate of 5%. 

If any of the assumptions have been violated, then the level of confidence associated with the test is 

suspect and will have to be further investigated. 

DQA without DQOs

Even though DQOs, based upon the EPA G-4 guidance, have not been developed for all criteria 

pollutants, a process very similar to this approach was originally used4

. In addition, monitoring 

organizations collect enough types of QA/QC data to estimate the quality of their data and should be able 

to express the confidence in that information. 

 

4 Curran, Thomas C. et.al., “Establishing Data Quality Acceptance Criteria for Air Pollution Data” Transactions of 

the 35 Annual Conference of the American Society for Quality Control (May 27-29,1981) 
QA Handbook Volume II, Appendix A 

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Page 1 of 11 

Appendix A 

National Air Quality Monitoring Program Fact Sheets 

The following information provides a fact sheet on a number of national ambient air 

monitoring networks including: 

• State or Local Air Monitoring Stations (SLAMS) Network 

• National Core (NCore) Network 

• Photochemical Assessment Monitoring Stations (PAMS) 

• PM2.5 Chemical Speciation Network (CSN) 

• National Toxics Trends Network (NATTS) 

• Interagency Monitoring of Protected Visual Environments (IMPROVE) 

• Clean Air Status and Trends Network (CASTNET) 

• National Atmospheric Deposition Network (NADP) 

• National Air Toxics Assessment (NATA) 

Only the SLAMS, NCore, PAMS, CSN and NATTS pertain to the information 

covered in the Handbook. The other networks described are for the benefit of the 

reader. 
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QA Handbook Volume II, Appendix A 

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State or Local Air Monitoring Stations (SLAMS) Network 

Background 

The SLAMS make up the ambient air quality monitoring sites that are operated by State or local agencies 

for the primary purpose of comparison to the National Ambient Air Quality Standards (NAAQS), but may 

serve other purposes such as: 

• provide air pollution data to the general public in a timely manner; 

• support compliance with air quality standards and emissions strategy development; and 

• support air pollution research studies. 

The SLAMS network includes stations classified as NCore, PAMS, and Speciation, and formerly 

categorized as NAMS, and does not include Special Purpose Monitors (SPM) and other monitors used for 

non-regulatory or industrial monitoring purposes. 

In order to support the objectives, the monitoring networks are designed with a variety of monitoring sites 

that generally fall into the following categories which are used to determine: 

 

1. the highest concentrations expected to occur in the area covered by the network; 

2. typical concentrations in areas of high population density; 

3. the impact on ambient pollution levels of significant sources or source categories; 

4. the general background concentration levels; 

5. the extent of regional pollutant transport among populated areas, and in support of secondary 

standards; and 

6. air pollution impacts on visibility, vegetation damage, or other welfare- based impacts. 

The monitoring aspects of the SLAMS program are found in the Code of Federal Regulations, Title 40, 

Parts 50, 53 and 58. 

SLAMS must use approved Federal reference method (FRM), Federal equivalent method (FEM), or Approved 

Regional Method (ARM) monitors for ambient pollutant levels being compared to the NAAQS. 

Reference Category References Comments 

Program References 40 CFR Part 50, 53 and 58 

http://www.epa.gov/ttn/amtic/

Pollutants Measured O3, CO, SO2, NO2 PM2.5, PM10, Pb 

Methods References 40 CFR Part 50 and 58 Appendix C 

http://www.epa.gov/ttn/amtic/criteria.html

Must be FRM, FEM, or ARM for 

NAAQS comparisons. 

Website lists designated methods 

Network Design References 40 CFR Part 58 Appendix D, E 

Siting Criteria 40 CFR Part 58 Appendix E 

Quality System References 40 CFR Part 58 Appendix A 

http://www.epa.gov/ttn/amtic/quality.html

http://www.epa.gov/ttn/amtic/met.html 

Website for QA Handbook Vol II 

Eebsite for QA Handbook Vol IV 

Data Management 

References

http://www.epa.gov/ttn/airs/airsaqs/ Air Quality System 
QA Handbook Volume II, Appendix A 

Revision No. 1 

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Page 4 of 11 

 

National Core (NCore) Network 

Background 

The NCore multi-pollutant stations are part of an overall strategy to integrate multiple monitoring networks 

and measurements. As required by the revised monitoring regulations promulgated in 2006, monitors at 

NCore multi-pollutant sites will measure particles (PM2.5, speciated PM2.5, PM10-2.5, speciated PM10-2.5), O3, 

SO2, CO, nitrogen oxides (NO/NO2/NOy), and basic meteorology. Monitors for all the gases except for O3

will be more sensitive than standard FRM/FEM monitors, so they could accurately report concentrations 

that are well below the respective NAAQS but that can be important in the formation of O3 and PM. 

The objective is to locate sites in broadly representative urban (about 55 sites) and rural (about 20 sites) 

locations throughout the country to help characterize regional and urban patterns of air pollution. The 

NCore network must be fully operational by 2011. Many stations will be operational before that deadline. 

In many cases, states will collocate these new stations with STN sites measuring speciated PM2.5

components, PAMS sites already measuring O3 precursors, and/or NATTS sites measuring air toxics. By 

combining these monitoring programs at a single location, EPA and its partners will maximize the multipollutant information available. This greatly enhances the foundation for future health studies, NAAQS 

revisions, validation of air quality models, assessment of emission reduction programs, and studies of 

ecosystem impacts of air pollution. 

Reference Category References Comments 

Program References http://www.epa.gov/ttn/amtic/monitor.html

Pollutants Measured SO2, CO, NO and NOy, and O3, PM2.5, 

PM10-2.5 , basic meteorological parameters 

Methods References http://www.epa.gov/ttn/amtic/precursop.html

http://www.epa.gov/ttn/amtic/pretecdoc.html

Network Design References http://www.epa.gov/ttn/amtic/monstratdoc.html

Siting Criteria http://www.epa.gov/ttn/amtic/pretecdoc.html

Quality System References http://www.epa.gov/ttn/amtic/qaqcrein.html

Data Management 

References

http://www.epa.gov/ttn/amtic/pretecdoc.html
QA Handbook Volume II, Appendix A 

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Photochemical Assessment Monitoring Stations (PAMS) 

Background 

Section 182(c)(1) of the 1990 Clean Air Act Amendments (CAAA) require the Administrator to 

promulgate rules for the enhanced monitoring of ozone, oxides of nitrogen (NOx), and volatile organic 

compounds (VOC) to obtain more comprehensive and representative data on ozone air pollution. 

Immediately following the promulgation of such rules, the affected states were to commence such actions 

as were necessary to adopt and implement a program to improve ambient monitoring activities and the 

monitoring of emissions of NOx and VOC. Each State Implementation Plan (SIP) for the affected areas 

must contain measures to implement the ambient monitoring of such air pollutants. The subsequent 

revisions to Title 40, Code of Federal Regulations, Part 58 (40 CFR 58) required states to establish 

Photochemical Assessment Monitoring Stations (PAMS) as part of their SIP monitoring networks in ozone 

nonattainment areas classified as serious, severe, or extreme. 

The chief objective of the enhanced ozone monitoring revisions is to provide an air quality database that 

will assist air pollution control agencies in evaluating, tracking the progress of, and, if necessary, refining 

control strategies for attaining the ozone NAAQS. Ambient concentrations of ozone and ozone precursors 

will be used to make attainment/nonattainment decisions, aid in tracking VOC and NOx emission inventory 

reductions, better characterize the nature and extent of the ozone problem, and prepare air quality trends. In 

addition, data from the PAMS will provide an improved database for evaluating photochemical model 

performance, especially for future control strategy mid-course corrections as part of the continuing air 

quality management process. The data will be particularly useful to states in ensuring the implementation 

of the most cost-effective regulatory controls. 

Reference Category References Comments 

Program References http://www.epa.gov/ttn/amtic/pamsrein.html

http://www.epa.gov/air/oaqps/pams/docs.html

Pollutants Measured Ozone, Nitrogen Oxides, VOCs, surface meteorological 

http://www.epa.gov/oar/oaqps/pams/general.html#parameters

Methods References

Network Design 

References

http://www.epa.gov/air/oaqps/pams/network.html

Siting Criteria http://www.epa.gov/oar/oaqps/pams/general.html#siting

Quality System 

References

Data Management 

References
QA Handbook Volume II, Appendix A 

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Page 6 of 11 

PM2.5 Chemical Speciation Network 

Background 

As part of the effort to monitor particulate matter, EPA monitors and gathers data on the chemical makeup 

of these particles. EPA established a chemical speciation network consisting of approximately 300 

monitoring sites. These sites are placed at various NAMS and SLAMS across the Nation. Fifty-four of 

these chemical speciation sites, the Speciation Trends Network (STN), will be used to determine, over a 

period of several years, trends in concentration levels of selected ions, metals, carbon species, and organic 

compounds in PM2.5. Further breakdown on the location or placement of the trends sites requires that 

approximately 20 of the monitoring sites be placed at existing Photochemical Assessment Monitoring 

Stations (PAMS). The placement of the remaining trends sites will be coordinated by EPA, the Regional 

offices, and the monitoring agencies. Locations will be primarily in or near larger Metropolitan Statistical 

Areas (MSAs). The remaining chemical speciation sites will be used to enhance the required trends 

network and to provide information for developing effective State Implementation Plans (SIPs). 

The STN is a component of the National PM2.5 Monitoring Network. Although the STN is intended to 

complement the activities of the much larger gravimetric PM2.5 measurements network component (whose 

goal is to establish if NAAQS are being attained), STN data will not be used for attainment or 

nonattainment decisions. The programmatic objectives of the STN network are: 

• annual and seasonal spatial characterization of aerosols; 

• air quality trends analysis and tracking the progress of control programs; 

• compare the chemical speciation data set to the data collected from the IMPROVE network; and 

• development of emission control strategies. 

Stakeholders in the STN will be those at EPA seeking to determine concentration trends of PM2.5 chemical 

species over a period of 3 or more years and decision-makers at tribal, state and local levels who will use 

the data as input to models and for development of emission control strategies and determination of their 

long-term effectiveness. Other users will be public health officials and epidemiological researchers. 

However, expectations for data sets from the STN must be put in context. 

Reference Category References Comments 

Program References http://www.epa.gov/ttn/amtic/speciepg.html

Pollutants Measured ions, metals, carbon species, and organic 

compounds

Methods References

Network Design References

Siting Criteria 

Quality System References http://www.epa.gov/ttn/amtic/specqual.html

Data Management 

References

http://www.epa.gov/ttn/amtic/specdat.html
QA Handbook Volume II, Appendix A 

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Page 7 of 11 

National Toxics Trends Network (NATTS) 

Background 

There are currently 188 hazardous air pollutants (HAPs), or Air Toxics (AT), regulated under the 

Clean Air Act (CAA) that have been associated with a wide variety of adverse health effects, 

including cancer, neurological, reproductive and developmental effects, as well as eco-system effects. In 

1999. EPA finalized the Urban Air Toxics Strategy (UATS). The UATS states that emissions data are 

needed to quantify the sources of air toxics impacts and aid in the development of control strategies, while 

ambient monitoring data are needed to understand the behavior of air toxics in the atmosphere after they are 

emitted. Part of this strategy included the development of the National Air Toxics Trends Stations 

(NATTS). Specifically, it is anticipated that the NATTS data will be used for: 

• tracking trends in ambient levels to facilitate tracking progress toward emission and risk reduction 

goals, which is the major objective of this program; 

• directly evaluating public exposure & environmental impacts in the vicinity of monitors; 

• providing quality assured data AT for risk characterization; 

• assessing the effectiveness of specific emission reduction activities; and 

• evaluating and subsequently improving air toxics emission inventories and model performance. 

Currently the NATTS program is made up of 22 monitoring sites; 15 representing urban communities and 7 

representing rural communities. 

Reference Category References Comments 

Program References http://www.epa.gov/ttn/amtic/natts.html

Pollutants Measured 33 HAPS which include metals, VOCs and carbonyls 

Methods References http://www.epa.gov/ttn/amtic/airtox.html

Network Design 

References

http://www.epa.gov/ttn/amtic/airtoxqa.html, Reference : National Air 

Toxics Trends Stations – 

Quality Management Plan –

final 09/09/05 

Siting Criteria http://www.epa.gov/oar/oaqps/pams/general.html#siting Reference : 40 CFR part 58 

Appendix E, PAMS Probe and 

Path Siting Criteria 

Quality System 

References

http://www.epa.gov/ttn/amtic/airtoxqa.html

Data Management 

References

http://www.epa.gov/ttn/amtic/toxdat.html
QA Handbook Volume II, Appendix A 

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Page 8 of 11 

Interagency Monitoring of Protected Visual Environments (IMPROVE)

Background 

The Interagency Monitoring of Protected Visual Environments (IMPROVE) program is a cooperative 

measurement effort governed by a steering committee composed of representatives from federal and 

regional-state organizations. The IMPROVE monitoring program was established in 1985 to aid the 

creation of Federal and State Implementation Plans for the protection of visibility in Class I areas (156 

national parks and wilderness areas) as stipulated in the 1977 amendments to the Clean Air Act. 

 The objectives of IMPROVE are: 

1. to establish current visibility and aerosol conditions in mandatory class I areas; 

2. to identify chemical species and emission sources responsible for existing man-made visibility 

impairment; 

3. to document long-term trends for assessing progress towards the national visibility goal; 

4. and with the enactment of the Regional Haze Rule, to provided regional haze monitoring 

representing all visibility-protected federal class I areas where practical. 

IMPROVE has also been a key participant in visibility-related research, including the advancement of 

monitoring instrumentation, analysis techniques, visibility modeling, policy formulation and source 

attribution field studies. In addition to 110 IMPROVE sites at visibility-protected areas, IMPROVE 

Protocol sites are operated identically at locations to serve the needs of state, tribes and federal agencies. 

Reference 

Category 

References Comments 

Program 

References 

http://vista.cira.colostate.edu/improve/

http://vista.cira.colostate.edu/improve/Overview/IMPROVEP

rogram_files/frame.htm

Pollutants 

Measured 

PM10 & PM2.5 mass concentration, and PM2.5 elements 

heavier than sodium, anions, organic and elemental carbon 

concentrations. Optical & met. parameters at select sites 

All sites have aerosol speciation 

monitoring by one day in three 

24-hour duration sampling 

Methods 

References

http://vista.cira.colostate.edu/improve/Publications/IMPROV

E_SOPs.htm

Network Design 

References

http://vista.cira.colostate.edu/improve/Publications/IMPROV

E_SOPs.htm

Siting Criteria http://vista.cira.colostate.edu/improve/Publications/IMPROV

E_SOPs.htm

Quality System 

References

http://vista.cira.colostate.edu/improve/Data/QA_QC/qa_qc_B

ranch.htm

http://www.epa.gov/ttn/amtic/visinfo.html

Data 

Management 

References

http://vista.cira.colostate.edu/improve/Data/data.htm
QA Handbook Volume II, Appendix A 

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Page 9 of 11 

Clean Air Status and Trends Network (CASTNET) 

Background 

EPA, in coordination with the National Oceanic and Atmospheric Administration (NOAA), established 

CASTNET with the goal of assessing the impact and effectiveness of Title IV of the 1990 Clean Air Act 

Amendments (CAAA) through a large-scale monitoring network. CASTNET was designed to compile a 

sound scientific data base through routine environmental monitoring for the evaluation of air-quality 

management and control strategies. The network provides estimates of dry deposition using an inferential 

modeling method that relies on atmospheric concentrations, meteorological variables and other input as 

recorded at each site. The data record extends back to 1987, when routine field measurements first began 

under National Dry Deposition Network (NDDN). CASTNET currently consists of over 80 sites across the 

eastern and western United States and is cooperatively operated and funded with the National Park Service. 

CASTNET complements the National Atmospheric Deposition Program/National Trends Network 

(NADP/NTN) which provides information on precipitation chemistry and wet deposition values. 

The main objective of the network is to: 

1) track the effectiveness of national and regional scale emission control programs; 

2) report high quality, publicly available data on the temporal and geographic patterns of air 

quality and atmospheric deposition trends; and 

3) provide the necessary information for understanding the environmental effects in sensitive 

terrestrial and aquatic receptor areas associated with atmospheric loadings of pollutants.

Reference 

Category 

References Comments 

Program 

References 

http://www.epa.gov/castnet/

Pollutants 

Measured 

-- weekly average atmospheric concentrations of sulfate, nitrate, 

ammonium, sulfur dioxide, nitric acid and base cations 

--hourly concentrations of ambient ozone levels 

--hourly averages of meteorological variables required for 

calculating dry deposition rates 

Methods 

References

CASTNET Quality Assurance Project Plan 

http://www.epa.gov/castnet/library.html

Network Design 

References

CASTNET Quality Assurance Project Plan 

http://www.epa.gov/castnet/library.html

Siting Criteria CASTNET Quality Assurance Project Plan 

http://www.epa.gov/castnet/library.html

Quality System 

References

CASTNET Quality Assurance Project Plan 

http://www.epa.gov/castnet/library.html

Data Management 

References

http://www.epa.gov/castnet/library.html

http://cfpub.epa.gov/gdm/index.cfm?fuseaction=aciddeposition.wizard
QA Handbook Volume II, Appendix A 

Revision No. 1 

Date:12/08 

Page 10 of 11 

National Atmospheric Deposition Network (NADP)

Background 

The National Atmospheric Deposition Program (NADP) provides quality-assured data and information in 

support of research on the exposure of managed and natural ecosystems and cultural resources to acidic 

compounds, nutrients, base cations, and mercury in precipitation. NADP data serve science and education 

and support informed decisions on air quality issues related to precipitation chemistry.

The NADP operates three precipitation chemistry networks: the 250-station National Trends Network 

(NTN), 7-station Atmospheric Integrated Research Monitoring Network (AIRMoN), and 100-station 

Mercury Deposition Network (MDN). The NTN provides the only long-term nationwide record of the wet 

deposition of acids, nutrients, and base cations. NTN stations collect one-week precipitation samples in 48 

states, Puerto Rico, the Virgin Islands, and Quebec Province, Canada. Complementing the NTN is the 7-

station AIRMoN. The daily precipitation samples collected at AIRMoN stations support continued research 

of atmospheric transport and removal of air pollutants and the development of computer simulations of 

these processes. The 100-station MDN offers the only regional measurements of mercury in North 

American precipitation. MDN data are used to quantify mercury deposition to water bodies that have fish 

and wildlife consumption advisories due to this toxic chemical. Presently, 48 states and 10 Canadian 

provinces list advisories warning people to limit fish consumption due to high mercury levels. Advisories 

also were issued for Atlantic Coastal waters from Maine to Rhode Island and North Carolina to Florida, for 

the entire U.S. Gulf Coast, and for Hawaii. 

In addition to these long-term monitoring networks, the NADP is responsive to emerging issues requiring 

new or expanded measurements. Its measurement system is efficient, its data meet pre-defined data quality 

objectives, and its reports and products are designed to meet user needs. 

Reference Category References Comments 

Program References NADP http://nadp.sws.uiuc.edu/ 

AIRMoN http://nadp.sws.uiuc.edu/airmon/

MDN http://nadp.sws.uiuc.edu/mdn/

Pollutants Measured sulfate, nitrate, chloride, ammonium, calcium, 

magnesium, sodium, potassium, pH, mercury

Methods References http://nadp.sws.uiuc.edu/lib/manuals/opman.pdf

http://nadp.sws.uiuc.edu/lib/manuals/mdnopman.pdf

Network Design 

References

http://nadp.sws.uiuc.edu/lib/manuals/siteinst.pdf

Siting Criteria http://nadp.sws.uiuc.edu/lib/manuals/siteinst.pdf

Quality System 

References

http://nadp.sws.uiuc.edu/QA/

http://nadp.sws.uiuc.edu/lib/qaplans/NADP-QMPDec2003.pdf 

http://nadp.sws.uiuc.edu/lib/qaplans/qapCal2006.pdf

Data Management 

References

http://nadp.sws.uiuc.edu/airmon/getamdata.asp
QA Handbook Volume II, Appendix A 

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Page 11 of 11 

National Air Toxics Assessment (NATA) 

Background 

NATA is a national-scale assessment of 33 air pollutants (a subset of 32 air toxics on the Clean Air Act's list of 188, 

plus diesel particulate matter). The assessment considers the year 1996 (an update to 1999 is in preparation), including: 

• compilation of a national emissions inventory of air toxics emissions from outdoor sources; 

• estimates of ambient concentrations across the contiguous United States; 

• estimates of population exposures; and 

• characterizations of potential public health risks including both cancer and non-cancer effects. 

NATA identifies those air toxics which are of greatest potential concern, in terms of contribution to population risk. 

This information is relevant and useful in assessing risk for tribal programs. 

Reference Category References Comments 

Program References http://www.epa.gov/ttn/atw/nata/index.html

Pollutants Measured http://www.epa.gov/ttn/atw/nata/34poll.html 33 air pollutants (see link) 

 

Methods References

Network Design References

Siting Criteria 

Quality System References

Data Management 

References
QA Handbook Volume II, Appendix B 

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Page 1 of 4 

Appendix B 

Ambient Air Monitoring Quality Assurance Information and 

Web Addresses 

The following information provides key guidance documents and reports that can 

be found on various sites within the Ambient Monitoring Technical Information 

Center (AMTIC) Website. The following identifiers are used to describe national 

ambient air monitoring programs 

SLAMS- State or Local Air Monitoring Stations Network 

NCore- National Core Network 

PAMS - Photochemical Assessment Monitoring Stations 

CSN PM2.5 Chemical Speciation Network 

NATTS- National Toxics Trends Network 

SLAMS-NPAP- National Performance Audit Program 

SLAM-PEP- National PM2.5 Performance Evaluation Program 
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Ambient Air Quality Assurance Information 

Identifier Title EPA Number Pub Date Year URL

CSN Particulate Matter (PM2.5) Speciation Guidance Document

1999 http://www.epa.gov/ttn/amtic/files/ambient

NATTS NATTS Technical Assistance Document (TAD) 2007 http://www.epa.gov/ttn/amtic/airtox.htmlNCore NCore Technical Assistance Document (TAD)

2005

http://www.epa.gov/ttn/amtic/files/ambient

version4.pdf

NCore QA Handbook for Air Pollution Measurement Systems Volume 

IV Meteorlogical Measurment Systems EPA-454/B-08-002 2008 http://www.epa.gov/ttn/amtic/met.html

PAMS Technical Assistance Document (TAD) for Sampling and 

Analysis of Ozone Precursors; EPA/600-R-98/161 1998 http://www.epa.gov/ttn/amtic/files/ambient

SLAMS QA Handbook for Air Pollution Measurement Systems Volume II

EPA-454/R-98-004 1998 http://www.epa.gov/ttn/amtic/files/ambient

SLAMS Guideline on the Meaning and the Use of Precision and Bias 

Data Required by 40 CFR Part 58 Appendix A EPA-545/B-07-001 2007

http://www.epa.gov/ttn/amtic/files/ambient

2010.10.07%20vers1.1.pdf 

SLAMS Transfer Standards for the Calibration of Air Monitoring 

Analyzers for Ozone EPA-600/4-79-056 1979

http://www.epa.gov/ttn/amtic/files/ambient

056.pdf

SLAMS Techical Assitance Document for the Calibration of Ozone 

Monitors EPA-600/4-79-057 1979

http://www.epa.gov/ttn/amtic/files/ambient

057.pdf

SLAMS PM2.5 PM2.5 Quality Assurance Program Overview

1997 http://www.epa.gov/ttn/amtic/files/ambient

CSN PM 2.5 Speciation Lab Audit Reports and Assessments Various Years http://www.epa.gov/ttn/amtic/pmspec.html NATTS National Air Toxics Trends Stations Quality Assurance Annual 

Reports and Proficiency Reports Various Years http://www.epa.gov/ttn/amtic/airtoxqa.htm

SLAMS 2007 Quality Management Plan and Quality Assurance Project 

Plan Tracking Matrix as of June 25, 2007 2007

http://www.epa.gov/ttn/amtic/files/ambient

06.25.07.pdf 

SLAMS Annual Precision, Bias and Completeness Reports for Criteria 

Pollutants Various Years http://www.epa.gov/ttn/amtic/parslist.html 

SLAMS-PM2.5 3-Year and Annual QA Reports Various Years http://www.epa.gov/ttn/amtic/anlqa.htmlSLAMS-PEP Laboratory Comparison Study of Gravimetric Laboratories 

Performing PM2.5 Filter Weighing for the PM2.5 Performance 

Evaluation Program and Tribal Air Monitoring Support Various Years http://www.epa.gov/ttn/amtic/pmpep.html

Methods

CSN Speciation Field Guidance Documents Various Years http://www.epa.gov/ttn/amtic/specguid.htm

NATTS Air Toxics Methods- Various Methods 2007 http://www.epa.gov/ttn/amtic/airtox.htmlNCore Calibration of Meterological Measurement -Videos 2008 http://www.epa.gov/ttn/amtic/met.htmlSLAMS QA Handbook Vol II (DRAFT Procedure for the "Determination 

of Ozone By Ultraviolet Analysis") 1998 http://www.epa.gov/ttn/amtic/files/ambient

SLAMS Sec. 2.10 of QA Handbook - Draft - PM10- Dichot revised to 

local standard and pressure EPA-600/4-77-027a 1997 http://www.epa.gov/ttn/amtic/files/ambient

SLAMS Sec. 2.11 of QA Handbook - Draft - PM10 Hi Vol revised to local 

standard and pressure 1997 http://www.epa.gov/ttn/amtic/files/ambient

SLAMS Section 2.3 -- DRAFT - Reference Method for the Determination 

of Nitrogen Dioxide in the Atmosphere (Chemiluminescence)

2002 http://www.epa.gov/ttn/amtic/files/ambient

SLAMS-NPAP DRAFT SOP for Through-the-Probe Performance Evaluations of 

Ambient Air Quality Monitoring of Criteria Air Pollutants

2007 http://www.epa.gov/ttn/amtic/files/ambient

GUIDANCE DOCUMENTS

QA REPORTS

3
Ambient Air Quality Assurance Information 

Identifier Title EPA Number Pub Date Year URL

SLAMS-NPAP Quality Assurance Project Plan for the Audit Support Program - 

NPAP and NATTS 2006 http://www.epa.gov/ttn/amtic/files/ambient

007onforTTP.pdf

SLAMS-PEP Method Compendium "Field Standard Operating Procedures for 

the PM2.5 Performance Evaluation Program" 2006 http://www.epa.gov/ttn/amtic/files/ambient

SLAMS-PEP Method Compendium "PM 2.5 Mass Weighing Laboratory 

Standard Operating Procedures for the Performance Evaluation Program 1998 http://www.epa.gov/ttn/amtic/files/ambient

SLAMS-PM2.5 2.12 "Monitoring PM2.5 in Ambient Air Using Designated 

Reference or Class I Equivalent Methods" 1998 http://www.epa.gov/ttn/amtic/files/ambient

CSN Speciation Laboratory Standard Operating Procedures Various Years http://www.epa.gov/ttn/amtic/specsop.htmCSN Quality Management Plan for the PM 2.5 Speciation Trends 

Network EPA-454/R-01-009 2001 http://www.epa.gov/ttn/amtic/files/ambient

CSN "Speciation Trends Network Quality Assurance Project Plan"

EPA-454/R-01-001 2001 http://www.epa.gov/ttn/amtic/files/ambient

NATTS Model Quality Assurance Project Plan for the National Air Toxics 

Trends Stations - updated version 1.1 2007

http://www.epa.gov/ttn/amtic/files/ambient

PP.pdf

NATTS Model QAPP for Local-Scale Monitoring Projects" EPA-454/R-01-007 2006 http://www.epa.gov/ttn/amtic/files/ambientNATTS National Air Toxics Trends Stations - Quality Management Plan 

Final 2005 http://www.epa.gov/ttn/amtic/files/ambient

PAMS PAMS Implementation Manual EPA-454/B-93-051 1994 http://www.epa.gov/ttn/amtic/files/ambientSLAMS Quality Assurance Project Plan for the Audit Support Program - 

NPAP and NATTS 2008

http://www.epa.gov/ttn/amtic/files/ambient

007onforTTP.pdf 

SLAMS PM2.5 PM2.5 Model QA Project Plan (QAPP)" EPA-454/R-98-005 1998 http://www.epa.gov/ttn/amtic/files/ambientSLAMS PM2.5 PM2.5 FRM Network Federal Performance Evaluation Program 

Quality Assurance Project Plan (QAPP) 2007

http://www.epa.gov/ttn/amtic/files/ambient

T_12-2007_cmt_vrsn.pdf

SLAMS PM2.5 PM2.5 Performance Evaluation Program Implementaion Plan 1998 http://www.epa.gov/ttn/amtic/files/ambientCSN Current List of CSN Sites as of 07-11-2007 2007 http://www.epa.gov/ttn/amtic/specgen.htmCSN Modification of Carbon Procedures in the Speciation Network; 

Overview and Frequently Asked Questions 2006 http://www.epa.gov/ttn/amtic/files/ambient

SLAMS QA National Meeting Presentations Various Years http://www.epa.gov/ttn/amtic/qamsmtg.htmSLAMS QA Newsletters Various Years http://www.epa.gov/ttn/amtic/qanews.html

IMPLEMENTATION PLANS and QAPPs

WHITE PAPERS/IMPORTANT MEMOS

4
QA Handbook Volume II, Appendix C 

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Appendix C 

Using the Graded Approach for the Development of QMPs and 

QAPPs in Ambient Air Quality Monitoring Programs 
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Using the Graded Approach for the Development of QMPs and QAPPs in Ambient Air 

Quality Monitoring Programs 

 

EPA policy requires that all organizations funded by EPA for environmental data operations 

(EDOs) develop quality management plans (QMPs) and quality assurance project plans 

(QAPPs). In addition, EPA has provided flexibility to EPA organizations on how they implement 

this policy, allowing for use of a graded approach. The following proposal explains the graded 

approach for data collection activities related to ambient air monitoring. OAQPS proposes a 

graded approach for the development of QAPPs and QMPs. 

The Graded Approach 

The QMP describes the quality system in terms of the organizational structure, functional 

responsibilities of management and staff, lines of authority, and required interfaces for those 

planning, implementing, and assessing activities involving EDOs. Each program should provide 

appropriate documentation of their quality system. Here are a few ways that this could be 

handled. 

Concept - Small organizations may have limited ability to develop and implement a quality 

system. EPA should provide options for those who are capable of making progress towards 

developing a quality system. If it is clear that the EDO goals are understood and that progress in 

quality system development is being made, a non-optimal quality system structure, for the 

interim, is acceptable. The concept is to work with the small organization to view the QMP as a 

long-term strategic plan with an open ended approach to quality system development that will 

involve continuous improvement. The graded approach to QMP development is described below 

and is based on the size of the organization and experience in working with EPA and the 

associated QA requirements. 

1. Small organization that just received its first EPA grant or using a grant for a discrete, 

small, project-level EDO. Such organizations could incorporate a description of its 

quality system into its QAPP. 

2. Small organization implementing EDOs with EPA at more frequent intervals or 

implementing long-term monitoring programs with EPA funds. If such an organization 

demonstrates capability of developing and implementing a stand-alone quality system, it 

is suggested that an appropriate separate QMP be written. 

3. Medium or large organization. Develop QMP to describe its quality system and QAPPs 

for specific EDOs. Approval of the recipient's QMP by the EPA Project Officer and the 

EPA Quality Assurance Manager may allow delegation of the authority to review and 

approve Quality Assurance Project Plans (QAPPs) to the grant recipient based on 

acceptable procedures documented in the QMP. 
QA Handbook Volume II, Appendix C 

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Quality Assurance Project Plans

The QAPP is a formal document describing, in comprehensive detail, the necessary QA/QC and 

other technical activities that must be implemented to ensure that the results of work performed 

will satisfy the stated performance criteria, which may be in the form of a data quality objective 

(DQO). The quality assurance policy of the EPA requires every EDO to have written and 

approved quality assurance project plans (QAPPs) prior to the start of the EDO. It is the 

responsibility of the EPA Project Officer (person responsible for the technical work on the 

project) to adhere to this policy. If the Project Officer gives permission to proceed without an 

approved QAPP, he/she assumes all responsibility. If a grantee’s QMP is approved by EPA and 

provides for delegation of QAPP approval to the grantee, the grantee is responsible to ensuring 

approval of the QAPP prior to the start of the EDO.

The Ambient Air Monitoring Program recommends a four-tiered project category approach to 

the Ambient Air QA Program in order to effectively focus QA. Category I involves the most 

stringent QA approach, utilizing all QAPP elements as described in EPA R5a

 (see Table 2), 

whereas category IV is the least stringent, utilizing fewer elements. In addition, the amount of 

detail or specificity required for each element will be less as one moves from category I to IV. 

Table 1 provides information that helps to define the categories of QAPPs based upon the data 

collection objective. Each type of ambient air monitoring program EDO will be associated with 

one of these categories. The comment area of the table will identify whether QMPs and QAPPs 

can be combined and the type of data quality objectives (DQOs) required (see below). Table 2 

identifies which of the 24 QAPP elements are required for each category of QAPP. Based upon 

a specific project, the QAPP approving authority may add/delete elements for a particular 

category as it relates to the project but in general, this table will be applicable based on the 

category of QAPP. 

Flexibility on the systematic planning process and DQO development 

Table 1 describes 4 QAPP/QMP categories which require some type of statement about the 

program or project objectives. Three of the categories use the term data quality objectives 

(DQOs), but there should be flexibility with the systematic planning process on how these DQOs 

are developed based on the particular category. For example, a category 1 project would have 

formal DQOs. Examples of category I projects, such as the State and Local Monitoring Stations 

(SLAMS), have DQOs developed by OAQPS. Category II QAPPS may have formal DQOs 

developed if there are national implications to the data (i.e., Speciation Trends Network) or less 

formal DQOs if developed by organizations implementing important projects that are more local 

in scope. Categories 3 and 4 would require less formal DQOs to a point that only project goals 

(category 4) may be necessary. 

 

a EPA Requirements for QA Project Plans (QA/R-5) http://www.epa.gov/quality/qa_docs.html 
QA Handbook Volume II, Appendix C 

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Standard Operating Procedures- (SOP)

SOPs are an integral part of the QAPP development and approval process and usually address 

key information required by the QAPP elements. Therefore, SOPs can be referenced in QAPP 

elements as long as the SOPs are available for review or are part of the QAPP. 
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QA Handbook Volume II, Appendix C 

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 Table 2 QAPP Elements

QAPP Element Category 

Applicability

A1 Title and Approval Sheet 

A2 Table of Contents 

A3 Distribution List 

A4 Project/Task Organization 

A5 Problem Definition/Background 

A6 Project/Task Description 

A7 Quality Objectives and Criteria for Measurement Data 

A8 Special Training Requirements/Certification 

A9 Documentation and Records 

B1 Sample Process (Network) Design 

B2 Sampling Methods Requirements 

B3 Sample Handling and Custody Requirements 

B4 Analytical Methods Requirements 

B5 Quality Control Requirements 

B6 Instrument/Equipment Testing, Inspection & Maintenance 

B7 Instrument Calibration and Frequency 

B8 Inspection/Acceptance Requirements for Supplies and Con. 

B9 Data Acquisition Requirements for Non-direct Measurements 

B10 Data Management 

C1 Assessments and Response Actions 

C2 Reports to Management 

D1 Data Review, Validation, and Verification Requirements 

D2 Validation and Verification Methods 

D3 Reconciliation and User Requirements 

I, II, III, IV 

I, II, III 

I, 

I, II, III 

I, II, III 

I, II, III, IV 

I, II, III, IV 

I 

I, II, III 

I, II, III, IV 

I, II, III, 

I, II, III 

I, II, III, IV 

I, II, III, IV 

I, II, III 

I, II, III 

I, 

I, II, III 

I, II 

I, II, 

I, II, 

I, II, III 

I, II 

I, II, 
QA Handbook Volume II, Appendix D 

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Page 1 of 30 

 

Appendix D 

Measurement Quality Objectives and Validation Templates

In June 1998, a workgroup was formed to develop a procedure that could be used by State and 

locals that would provide for a consistent validation of PM2.5 mass concentrations across the US. 

The workgroup included personnel from the monitoring organizations, EPA Regional Offices, 

and OAQPS who are involved with assuring the quality of PM2.5 mass and was headed by a State 

and local representative. The workgroup developed three tables of criteria where each table has 

a different degree of implication about the quality of the data. The criteria included on the tables 

are from 40 CFR Part 50 Appendices L and N, 40 CFR Part 58 Appendix A, Method 2.12, and a 

few criteria that are neither in CFR nor Method 2.12. Upon completion and use of the table, it 

was decided that a “validation template” should be developed for all the criteria pollutants. 

One of the tables has the criteria that must be met to ensure the quality of the data. An example 

criterion is that the average flow rate for the sampling period must be maintained to within 5% of 

16.67 liters per minute. The second table has the criteria that indicate that there might be a 

problem with the quality of the data and further investigation is warranted before making a 

determination about the validity of the sample or samples. An example criterion is that the field 

filter blanks should not change weight by more than 30 :g between weighings. The third table 

has criteria that indicate a potentially systematic problem with the environmental data collection 

activity. Such systematic problems may impact the ability to make decisions with the data. An 

example criterion is that at least 75% of the scheduled samples for each quarter should be 

successfully collected and validated. 

To determine the appropriate table for each criterion, the members of the workgroup considered 

how significantly the criterion impact the resulting concentration. This was based on experience 

from workgroup members, experience from non-workgroup members, and feasibility of 

implementing the criterion. 

Criteria that were deemed critical to maintaining the integrity of a sample or group of samples 

were placed on the first table. Observations that do not meet each and every criterion on the 

Critical Criteria Table should be invalidated unless there are compelling reason and 

justification for not doing so. Basically, the sample or group of samples for which one or more 

of these criteria are not met is invalid until proven otherwise. The cause of not operating in the 

acceptable range for each of the violated criteria must be investigated and minimized to reduce 

the likelihood that additional samples will be invalidated. 
QA Handbook Volume II, Appendix D 

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Criteria that are important for maintaining and evaluating the quality of the data collection 

system are included on the second table, the Operational Evaluations Table. Violation of a 

criterion or a number of criteria may be cause for invalidation. The decision should consider 

other quality control information that may or may not indicate the data are acceptable for the 

parameter being controlled. Therefore, the sample or group of samples for which one or more of 

these criteria are not met is suspect unless other quality control information demonstrates 

otherwise. The reason for not meeting the criteria MUST be investigated, mitigated or justified. 

Finally, those criteria which are important for the correct interpretation of the data but do not 

usually impact the validity of a sample or group of samples are included on the third table, the 

Systematic Issues Table. For example, the data quality objectives are included in this table. If 

the data quality objectives are not met, this does not invalidate any of the samples but it may 

impact the error rate associated with the attainment/non-attainment decision. 

Following are the tables. For each criterion, the tables include (1) the operational range that is 

acceptable, (2) the frequency with which compliance is to be evaluated, (3) the number of 

samples that are impacted if violation of a criterion occurs (possible values include single filters, 

a batch of filters, or a group of filters from a specific instrument);.(4) sections of 40 CFR and (5) 

Method 2.12 that describe the criterion. The table also indicates whether samples violating the 

criterion must be flagged before entering them into AQS. 

This validation template has been developed based on the current state of knowledge. The 

template should evolve as new information is discovered about the impact of the various 

criterion on the error in the resulting mass estimate. Interactions of the criteria, whether 

synergistic or antagonistic, should also be incorporated when the impact of these interactions 

becomes quantified. Due to the potential misuse of invalid data, data that are invalidated will not 

be uploaded to AQS but should be retained on the monitoring organizations local database. This 

data will be invaluable to the evolution of the validation template. 

PM10 Note of Caution 

The validation templates for PM10 get complicated because PM10 is required to be reported at 

standard temperature and pressure (STP) for comparison to the NAAQS (and follow 40 CFR Part 

50 App J) and at local conditions if using it to monitor for PM10-2.5 (and follow 40 CFR Part 50 

App O) in addition PM10 is measured with filter based sampling techniques as well as with 

automated methods. The validation templates developed for PM10 try to accommodate these 

differences but monitoring organizations are cautioned to review the operations manual for the 

monitors/samplers they use and augment the validation template with QC information specific to 

their method.
QA Hand

Ozone Validation Template 

Requirement Frequency Acceptance Criteria Informatio

CRITICAL CRITERIA-Ozone

One Point QC CheckSingle analyzer

1/ 2 weeks < +7% (percent difference) 0.01 - 0.

Relative to routin

40 CFR Part 58 

Zero/span check 1/ 2 weeks Zero drift # " 2% of full scale 

Span drift # " 7 % 

OPERATIONAL CRITERIA - Ozone

Shelter Temperature Temperature range Daily 

(hourly values) 

20 to 30E C. (Hourly ave) 

or 

per manufacturers specifications if designated 

to a wider temperature range 

Generally the 20-30 E C ranmost restrictive operable rathe shelter may also be used 

 Temperature Control Daily (hourly values) # " 2E C SD over 24 hours  Temperature Device Check 2/year " 2EC of standardPrecision(using 1-point QC checks)

Calculated annually and as 

appropriate for design value estimates 

90% CL CV < 7% 90% Confidence Limit of c

CFR Part 58 App A sec 4.1

Bias (using 1-point QC checks) Calculated annually and as 

appropriate for design value estimates 

95% CL < + 7% 95% Confidence Limit of a

CFR Part 58 App A sec 4.1

Annual Performance EvaluationSingle analyzer Every site 1/year 25 % of sites 

quarterly 

Percent difference of each audit level < 15% 3 consecutive audit concent

40 CFR Part 58 App A sec 

Primary QA Organization (PQAO) 

annually 95% of audit percent differences fall within the 

one point QC check 95% probability intervals 

at PQAO level of aggregation 

40 CFR Part 58 App A sec 

Federal Audits (NPAP) 1/year at selected sites 20% of sites 

audited 

Mean absolute difference # 10% 40 CFR Part 58 App A sec 

State audits 1/year State requirements Verification/Calibration Upon receipt/adjustment/repair/ 

installation/moving 

1/6 months if manual zero/span 

performed biweekly 

1/year if continuous zero/span 

performed daily 

All points within " 2 % of full scale of best-fit 

straight line 

Linearity error <5% 

Multi-point calibration (0 aCFR Part 50 App D sec 5.2

Zero Air Concentrations below LDL Gaseous Standards NIST Traceable 

(e.g., EPA Protocol Gas) 

40 CFR Part 58 App A sec 

Zero Air Check 1/year Concentrations below LDL 
QA Hand

Requirement Frequency Acceptance Criteria Informatio

Ozone Local primary standard Certification/recertification to  Standard Reference Photometer 

1/year single point difference # " 3% Primary Standards usually t

Regions SRP for compariso

 (if recertified via a transfer standard)

1/year Regression slopes = 1.00 " 0.03 and two 

intercepts are 0 " 3 ppb 

Ozone Transfer standard Qualification Upon receipt of transfer standard "4% or "4 ppb (whichever greater) Transfer Standard Doc EPA 

6.4 

 Certification After qualification and upon 

receipt/adjustment/repair 

RSD of six slopes # 3.7% 

Std. Dev. of 6 intercepts 1.5 

Transfer Standard Doc EPA 6.6 

Recertification to local primary standard 

Beginning and end of O3 season or 

1/6 months whichever less 

New slope = + 0.05 of previous and 

RSD of six slopes # 3.7% 

Std. Dev. of 6 intercepts 1.5 

1 recertification test that therecent 5 tests. If does not mcertification fails 

Lower detectable level 1/year 0.003 ppm 

SYSTEMATIC CRITERIA- Ozone

Requirement Frequency Acceptance Criteria Informatio

Standard Reporting Units All data ppm (final units in AQS) Completeness (seasonal) Daily 75% of hourly averages for the 8-hour period 8-Hour ASample Residence Times < 20 seconds Sample Probe, Inlet, Sampling train 

Borosilicate glass (e.g., Pyrex®) or Teflon® 40 CFR Part 58 App E 

Siting Un-obstructed probe inlet 40 CFR Part 58 App E EPA Standard Ozone Reference Photometer (SRP) Recertification 

1/year Regression slope = 1.00 + 0.01 

and intercept < 3 ppb 

This is usually at a Regionaagainst the traveling SRP 
QA Hand

CO Validation Template

Requirement Frequency Acceptance Criteria Informat

CRITICAL CRITERIA-CO

One Point QC CheckSingle analyzer

1/ 2 weeks < +10% (percent difference) 1 - 1

Relative to rout

40 CFR Part 5

Zero/span check 1/ 2 weeks Zero drift # " 2% of full scale 

Span drift # " 10 % 

OPERATIONAL CRITERIA-CO

Shelter Temperature Temperature range Daily 

(hourly values) 

20 to 30E C. (Hourly ave) 

or 

per manufacturers specifications if designated to 

a wider temperature range 

Generally the 20-30 E C most restrictive operable in the shelter may also be 

 Temperature Control Daily (hourly values) # " 2E C SD over 24 hours  Temperature Device Check 2/year " 2EC of standardPrecision(using 1-point QC checks)

Calculated annually and as 

appropriate for design value estimates 

90% CL CV < 10% 90% Confidence Limit o

40 CFR Part 58 App A s

Bias (using 1-point QC checks) Calculated annually and as 

appropriate for design value estimates 

95% CL < + 10% 95% Confidence Limit o

CFR Part 58 App A sec 4

Annual Performance Evaluation Single analyzer Every site 1/year 25 % of sites 

quarterly 

Percent difference of each audit level < 15% 3 consecutive audit conc

zero. 40 CFR Part 58 Ap

 Primary QA Organization  (PQAO) 

annually 95% of audit percent differences fall within the 

one point QC check 95% probability intervals at 

PQAO level of aggregation 

40 CFR Part 58 App A s

Federal Audits (NPAP) 1/year at selected sites 20% of sites 

audited 

Mean absolute difference # 15% 40 CFR Part 58 App A se

State audits 1/year State requirements Verification/Calibration Upon receipt/adjustment/repair/ 

installation/moving 

1/6 months if manual zero/span 

performed biweekly 

1/year if continuous zero/span 

performed daily 

All points within " 2 % of full scale of best-fit 

straight line 

Multi-point calibration  (0 and 4 upscale points) 

Gaseous Standards NIST Traceable 

(e.g., EPA Protocol Gas) 

Vendor must participate Verification Program 40 2.6.1 

Zero Air/Zero Air Check 1/year Concentrations below LDL 
QA Hand

Requirement Frequency Acceptance Criteria Informat

Gas Dilution Systems 1/3 months Accuracy " 2 % Detection  Noise NA 0.50 ppm 40 CFR Part 53.20  Lower detectable level 1/year 1.0 ppm 40 CFR Part 53.20 

SYSTEMATIC CRITERIA-CO

Standard Reporting Units All data ppm (final units in AQS) Completeness (seasonal) Hourly 75% of hourly averages for the 8-hour period 8-Hour Sample Residence Times < 20 seconds Sample Probe, Inlet, Sampling train 

Borosilicate glass (e.g., Pyrex®) or Teflon® 40 CFR Part 58 App E 

Siting Un-obstructed probe inlet 40 CFR Part 58 App E 
QA Hand

NO2 Validation Template

Requirement Frequency Acceptance Criteria Informa

CRITICAL CRITERIA- NO2

One Point QC CheckSingle analyzer

1/ 2 weeks < +10% (percent difference) 0.01 - 

Relative to rou

40 CFR Part 

Zero/span check 1/ 2 weeks Zero drift # " 3% of full scale 

Span drift # " 10 % 

OPERATIONAL CRITERIA- NO2

Shelter Temperature Temperature range Daily 

(hourly values) 

20 to 30E C. (Hourly ave) 

or 

per manufacturers specifications if designated 

to a wider temperature range 

Generally the 20-30 E C most restrictive operablin the shelter may also b

 Temperature Control Daily (hourly values) # " 2E C SD over 24 hours  Temperature Device Check 2/year " 2EC of standardPrecision (using 1-point QC checks)

Calculated annually and as appropriate 

for design value estimates 

90% CL CV < 10% 90% Confidence Limit 

40 CFR Part 58 App A 

Bias (using 1-point QC checks) Calculated annually and as appropriate 

for design value estimates 

95% CL < + 10% 95% Confidence Limit 

40 CFR Part 58 App A 

Annual Performance Evaluation Single analyzer Every site 1/year 25 % of sites quarterly Percent difference of each audit level < 15% 3 consecutive audit con

zero. 40 CFR Part 58 A

 Primary QA Organization  (PQAO) 

annually 95% of audit percent differences fall within the 

one point QC check 95% probability intervals 

at PQAO level of aggregation 

40 CFR Part 58 App A 

Federal Audits (NPAP) 1/year at selected sites 20% of sites 

audited 

Mean absolute difference # 15% 40 CFR Part 58 App A 

State audits 1/year State requirements Verification/Calibration Upon receipt/adjustment/repair/ 

installation/moving 

1/6 months if manual zero/span 

performed biweekly 

1/year if continuous zero/span performed 

daily 

Intrument residence time < 2 min 

Dynam. parameter > 2.75 ppm-min 

All points within " 2 % of full scale of best-fit 

straight line 

Multi-point calibration CFR Part 50 App F 

Converter Efficiency During multi-point calibrations, span and 

audit 

1/ 2 weeks 

96% 

Gaseous Standards NIST Traceable Vendor must participate 
QA Hand

Requirement Frequency Acceptance Criteria Informa

(e.g., EPA Protocol Gas) Verification Program 40 

2.6.1 

Zero Air/ Zero Air Check 1/year Concentrations below LDL Gas Dilution Systems 1/3 months Accuracy " 2 % Detection Noise NA 0.005 ppm 40 CFR Part 53.20 Lower detectable level 1/year 0.01 ppm 40 CFR Part 53.20 

SYSTEMATIC CRITERIA- NO2

Standard Reporting Units All data ppm (final units in AQS) Completeness (seasonal) Quarterly 75% Annual standard (hourly Sample Residence Times < 20 seconds Sample Probe, Inlet, Sampling train 

Borosilicate glass (e.g., Pyrex®) or Teflon® 40 CFR Part 58 App E 

Siting Un-obstructed probe inlet 40 CFR Part 58 App E 
QA Hand

SO2 Validation Template 

Requirement Frequency Acceptance Criteria Informat

CRITICAL CRITERIA- SO2

One Point QC CheckSingle analyzer

1/ 2 weeks < +10% (percent difference) 0.01 - 0

Relative to rout

40 CFR Part 5

Zero/span check 1/ 2 weeks Zero drift # " 3% of full scale 

Span drift # " 10 % 

OPERATIONAL CRITERIA- SO2

Shelter Temperature Temperature range Daily 

(hourly values) 

20 to 30E C. (Hourly ave) 

or 

per manufacturers specifications if designated 

to a wider temperature range 

Generally the 20-30 E C rmost restrictive operable the shelter may also be us

 Temperature Control Daily (hourly values) # " 2E C SD over 24 hours  Temperature Device Check 2/year " 2EC of standardPrecision (using 1-point QC checks)

Calculated annually and as appropriate 

for design value estimates 

90% CL CV < 10% 90% Confidence Limit of 

CFR Part 58 App A sec 4

Bias (using 1-point QC checks) Calculated annually and as appropriate 

for design value estimates 

95% CL < + 10% 95% Confidence Limit of 

CFR Part 58 App A sec 4

Annual Performance Evaluation Single analyzer Every site 1/year 25 % of sites quarterly Percent difference of each audit level < 15% 3 consecutive audit conce

zero 40 CFR Part 58 App 

 Primary QA Organization  (PQAO) 

annually 95% of audit percent differences fall within the 

one point QC check 95% probability intervals 

at PQAO level of aggregation 

40 CFR Part 58 App A se

Federal Audits (NPAP) 1/year at selected sites 20% of sites 

audited 

Mean absolute difference # 15% 40 CFR Part 58 App A se

State audits 1/year State requirements Verification/Calibration Upon receipt/adjustment/repair/ 

installation/moving 

1/6 months if manual zero/span 

performed biweekly 

1/year if continuous zero/span 

performed daily 

All points within " 2 % of full scale of best-fit 

straight line 

Multi-point calibration  (0 and 4 upscale points) 

Zero Air Concentrations below LDL Gaseous Standards NIST Traceable 

(e.g., EPA Protocol Gas) 

Vendor must participate iVerification Program 40 2.6.1 
QA Hand

Requirement Frequency Acceptance Criteria Informat

Zero Air/ Zero Air Check 1/year Concentrations below LDL Gas Dilution Systems 1/3 months Accuracy " 2 % Detection  Noise NA 0.005 ppm 40 CFR Part 53.20  Lower detectable level 1/year 0.01 ppm 40 CFR Part 53.20 

SYSTEMATIC CRITERIA- SO2

Standard Reporting Units All data ppm (final units in AQS) Completeness (seasonal) Quarterly 75% Annual 

24 hours 75% 24-hour 

3 hours 75% 3-hour 

Sample Residence Times < 20 seconds Sample Probe, Inlet, Sampling train 

Borosilicate glass (e.g., Pyrex®) or Teflon® 40 CFR Part 58 App E 

Siting Un-obstructed probe inlet 40 CFR Part 58 App E 
QA Hand

PM2.5 Filter Based Local Conditions Validation Template 

Criteria Frequency Acceptable Range

Informati

CRITICAL CRITERIA- PM2.5 Filter Based Local Conditions

Filter Holding Times Sample Recovery all filters # 7 days 9 hours from sample end date Part 5Post-sampling Weighing all filters # 10 days from sample end date if shipped at ambient temp, or 

# 30 days if shipped below ave ambient (or 4E C or below for 

ave sampling temps < 4E C ) from sample end date 

Part 5

Sampling Period (including multiple power failures) 

all filters 1380-1500 minutes, or 

value if < 1380 and exceedance of NAAQS 1/

midnight to midnight 

Part 

Part 50

Sampling Instrument Average Flow Rate every 24 hours of op average within 5% of 16.67 liters/minute Part Variability in Flow Rate every 24 hours of op CV # 2% Part 50FilterVisual Defect Check (unexposed) all filters see reference Part 5Filter Conditioning Environment 

Equilibration all filters 24 hours minimum Part Temp. Range all filters 24-hr mean 20-23E C Part Temp.Control all filters " 2E C SD* over 24 hr Part Humidity Range all filters 24-hr mean 30% - 40% RH or 

# 5% sampling RH but > 20%RH 

Part 

Humidity Control all filters " 5% SD* over 24 hr. Part Pre/post Sampling RH all filters difference in 24-hr means # " 5% RH Part 5Balance all filters located in filter conditioning environment Part 5

Verification/CalibrationOne-point Flow Rate Verification 1/4 weeks " 4% of transfer standard Part 5

Part 58, App

OPERATIONAL EVALUATIONS TABLE PM2.5 Filter Based Local Conditions

Filter Checks Lot Blanks 9 filters per lot less than 15 Fg change between weighings MetExposure Lot Blanks 3 filters per lot less than 15 Fg change between weighings MetFilter Integrity (exposed) each filter no visual defects MetFilter Holding TimesPre-sampling all filters < 30 days before sampling Part Lab QC ChecksField Filter Blank 10% or 1 per weighing session " 30 Fg change between weighings Part Lab Filter Blank 10% or 1 per weighing session " 15 Fg change between weighings Part Balance Check beginning, 10th sample, end #3 Fg MDuplicate Filter Weighing 1 per weighing session " 15 Fg change between weighings MSampling Instrument
QA Hand

Criteria Frequency Acceptable Range

Informati

Individual Flow Rates every 24 hours of op no flow rate excursions > "5% for > 5 min. 1/ Part 50Filter Temp Sensor every 24 hours of op no excursions of > 5E C lasting longer than 30 min 1/ Part Verification/CalibrationRoutine Verifications External Leak Check every 5 sampling events < 80 mL/min Part 5Internal Leak Check every 5 sampling events < 80 mL/min Part 5One-point Temp Verification 1/4 weeks " 2EC Part 5Pressure Verification 1/4 weeks " 10 mm Hg Part 5Lab Temperature 1/6 months " 2EC MLab Humidity 1/6 months " 2% MAnnual Multi-point Verifications /Calibrations Temperature multi-point Verification/Calibration 

1/yr " 2EC Part 5

Pressure Verification/Calibration on installation, then 1/yr " 10 mm Hg Part 5Flow Rate Multi-point Verification/ Calibration 

1/yr " 2% of transfer standard Part 5

Design Flow Rate Adjustment at one-point or multi-point " 2% of design flow rate Part 5Other Monitor Calibrations per manufacturers’ op manual per manufacturers’ operating manual Mirobalance Calibration 1/yr Manufacturer’s specification Part 5PrecisionCollocated Samples every 12 days for 15% of sites CV < 10% of samples > 3 Fg/m3 Part 5AccuracyTemperature Audit 2/yr " 2EC MPressure Audit 2/yr "10 mm Hg MBalance Audit 1/yr " 0.050 mg or manufacturers specs, whichever is tighter MSemi Annual Flow Rate Audit 2/yr " 4% of audit standard 

" 5% of design flow rate 

Part 5

Calibration & Check Standards - Field Thermometer 1/yr " 0.1E C resolution, " 0.5E C accuracy MethField Barometer 1/yr " 1 mm Hg resolution, " 5 mm Hg accuracy MethWorking Mass Stds. (compare to primary standards) 

1/3 mo. 0.025 mg Meth

Monitor MaintenanceImpactor (WINs) Very Sharp Cut Cyclone 

every 5 sampling events 

Every 30 days 

cleaned/changed M

Inlet/downtube Cleaning every 15 sampling events cleaned MFilter Chamber Cleaning 1/4 weeks cleaned M
QA Hand

Criteria Frequency Acceptable Range

Informati

Leak Check @ see Verification/CalibrationCirculating Fan Filter Cleaning 1/4 weeks cleaned/changed M

Manufacturer-Recommended Maintenance 

per manufacturers’ SOP per manufacturers’ SOP 

SYSTEMATIC CRITERIA -PM2.5 Filter Based Local Conditions 

Data Completeness quarterly > 75% Part 50, ApReporting Units all filters Fg/m3 at ambient temp/pressure (PM2.5) Rounding ConventionAnnual 3-yr average quarterly nearest 0.1 Fg/m3 (> 0.05 round up) Part 524-hour, 3-year average quarterly nearest 1 Fg/m3 (> 0.5 round up) Part 5Detection LimitLower DL all filters # 2 Fg/m3 Part Upper Conc. Limit all filters $ 200 Fg/m3 Part Verification/Calibration Standards Recertifications – All standards should have multi-point certifications against NIST Traceable standardsFlow Rate Transfer Std. 1/yr " 2% of NIST-traceable Std. Part 50, Field Thermometer 1/yr " 0.1E C resolution, " 0.5E C accuracy MField Barometer 1/yr " 1 mm Hg resolution, " 5 mm Hg accuracy MPrimary Mass Stds. (compare to NIST-traceable standards) 

1/yr 0.025 mg M

MicrobalanceReadability at purchase 1 Fg Part Repeatability 1/yr 1Fg Calibration & Check StandardsFlow Rate Transfer Std. 1/yr " 2% of NIST-traceable Std. Part 50, Verification/CalibrationClock/timer Verification 1/4 weeks 1 min/mo Part 5PrecisionSingle analyzer 1/3 mo. Coefficient of variation (CV) < 10% Single analyzer 1/ yr CV < 10% Primary Quality Assurance Org. Annual and 3 year estimates 90% CL of CV < 10% Part 5BiasPerformance Evaluation Program (PEP) 

5 audits for PQAOs with < 5 

sites 

8 audits for PQAOs with > 5 

sites 

"10% Part 58, A

1/ value must be flagged * SD= standard deviation CV= coefficient of variation @ = Scheduled to occur immediately after impactor cleaned/
QA Hand

NOTE: There may be a number of continuous monitors that may be designated as an FEM or an ARM. Thes

different measurement or sampling attributes that cannot be identified in this validation template. Monitoring review specific instrument operating manuals to augment this validation template as necessary. In general, 40 

and 40 CFR part 50 App L requirements apply to Continuous PM2.5 Continuous PM2.5 Local Conditions Validation Template 

Criteria Frequency Acceptable Range Information (

CRITICAL CRITERIA- PM2.5 Continuous, Local Conditions

Sampling Period  24 hour estimate

every sample period 1380-1500 minutes, or 

value if < 1380 and exceedance of NAAQS 1/

midnight to midnight 

Part 50 

Part 50, A

Hour estimate Every hour Instrument dependent See op

Sampling Instrument Average Flow Rate every 24 hours of op average within 5% of 16.67 liters/minute Part 50 Variability in Flow Rate every 24 hours of op CV # 2% Part 50, AVerification/CalibrationOne-point Flow Rate Verification 1/4 weeks " 4% of transfer standard Part 50, 

Part 58, Appen

Reference Membrane Verification (BAM) 

Hourly " 4% of ABS Value

OPERATIONAL CRITERIA- PM2.5 Continuous, Local Conditions

Verification/CalibrationLeak Check every 30 days Instrument dependent Part 50Temperature Calibration if multi-point failure " 2EC Part 50Temp M-point Verification on installation, then 1/yr " 2EC Part 50One-point Temp Check 1/4 weeks " 2EC Part 50Pressure Calibration on installation, then 1/yr " 10 mm Hg Part 50Pressure Verification 1/4 weeks " 10 mm Hg Part 50Other Monitor Calibrations per manufacturers’ op manual per manufacturers’ operating manual Flow Rate (FR) Calibration if multi-point verification 

failure 

" 2% Part 50

FR Multi-point Verification 1/yr " 2% Part 50Design Flow Rate Adjustment at one-point or multi-point " 2% of design flow rate Part 50, PrecisionCollocated Samples every 12 days for 15% of sites CV < 10% of samples > 3 Fg/m3 Part 58 
QA Hand

Criteria Frequency Acceptable Range Information (

AccuracyTemperature Audit 2/yr " 2EC Method Pressure Audit 2/yr "10 mm Hg Method Semi Annual Flow Rate Audit 2/yr " 4% of audit standard 

" 5% of design flow rate 

Method 

Calibration & Check Standards(working standards) 

Part 58, 

Field Thermometer 1/yr " 0.1E C resolution, " 0.5E C accuracy Method 2Field Barometer 1/yr " 1 mm Hg resolution, " 5 mm Hg accuracy Method 2Shelter Temperature Temperature range Daily 

(hourly values) 

20 to 30E C. (Hourly ave) 

or 

per manufacturers specifications if designated to a wider 

temperature range 

Generally the 20-3the most restrictive instruments in the guidance 

 Temperature Control Daily (hourly values) # " 2E C SD over 24 hours  Temperature Device Check 2/year " 2EC Monitor MaintenanceVirtual Impactor Very Sharp Cut Cyclone 

Every 30 days cleaned/changed Metho

Inlet Cleaning Every 30 days cleaned MethoFilter Chamber Cleaning 1/4 weeks cleaned MethoCirculating Fan Filter Cleaning 1/4 weeks cleaned/changed MethoManufacturer-Recommended  Maintenance 

per manufacturers’ SOP per manufacturers’ SOP 

SYSTEMATIC CRITERIA- PM2.5 Continuous, Local Conditions

Data Completeness quarterly > 75% Part 50, App. Reporting Units Fg/m3 at ambient temp/pressure (PM2.5) PRounding ConventionAnnual 3-yr average quarterly nearest 0.1 Fg/m3 (> 0.05 round up) Part 50, 24-hour, 3-year average quarterly nearest 1 Fg/m3 (> 0.5 round up) Part 50, Detection LimitLower DL all filters # 2 Fg/m3 Part 50Upper Conc. Limit all filters $ 200 Fg/m3 Part 50Verification/Calibration Standards Recertifications - All standards should have multi-point certifications against NIST Traceable standards
QA Hand

Criteria Frequency Acceptable Range Information (

Flow Rate Transfer Std. 1/yr " 2% of NIST-traceable Std. Part 50, AField Thermometer 1/yr " 0.1E C resolution, " 0.5E C accuracy Method Field Barometer 1/yr " 1 mm Hg resolution, " 5 mm Hg accuracy Method Calibration & Check StandardsFlow Rate Transfer Std. 1/yr " 2% of NIST-traceable Std. Part 50, APVerification/CalibrationClock/timer Verification 1/4 weeks 1 min/mo** Part 50PrecisionSingle analyzer 1/3 mo. Coefficient of variation (CV) < 10% Single analyzer 1/ yr CV < 10% Primary Quality Assurance Org. Annual and 3 year estimates 90% CL of CV < 10% Part 58, BiasPerformance Evaluation Program (PEP) 

5 audits for PQAOs with < 5 

sites 

8 audits for PQAOs with > 5 

sites 

"10% Part 58, Ap

1/ value must be flagged due to current implementation of BAM ( sampling 42 minute/hour) only 1008 minutes of sampling in 24 hour period 

*= not defined in CFR SD= standard deviation CV= coefficient of variation 

@ 

= Scheduled to occur immediately after impactor cleaned/changed.

** = need to ensure data system stamps appropriate time period with reported sample value 
QA Hand

NOTE: The following validation template was constructed for use of PM10 at local conditions where PM10 is us

the PM10-2.5 measurement or for objectives other than comparison to the PM10 NAAQS. Although the PM 10-2.5 

CFR Part 50 Appendix O, Appendix O references Appendix L (the PM2.5 Method) for the QC requirements li

Monitoring organizations using PM10 data for a NAAQS comparison purposes should refer to the PM10 valida

(standard temperature and pressure correction). 

PM10 Filter Based Local Conditions Validation Template 

Criteria Frequency Acceptable Range Information (C

CRITICAL CRITERIA- PM10 Filter Based Local Conditions

Filter Holding Times Sample Recovery all filters # 7 days 9 hours from sample end date Part 50 Post-sampling Weighing all filters # 10 days from sample end date if shipped at ambient 

temp, or 

# 30 days if shipped below ave ambient (or 4E C or 

below for ave sampling temps < 4E C ) from sample end 

date 

Part 50 

Sampling Period (including multiple power failures) 

all filters 1380-1500 minutes, or 

value if < 1380 and exceedance of NAAQS 1/

midnight to midnight 

Part 50 

Part 50, 

Sampling Instrument Average Flow Rate every 24 hours of op average within 5% of 16.67 liters/minute Part 50 Variability in Flow Rate every 24 hours of op CV # 2% Part 50, FilterVisual Defect Check (unexposed) all filters see reference Part 50Filter Conditioning Environment 

Equilibration all filters 24 hours minimum Part 50Temp. Range all filters 24-hr mean 20-23E C Part 50Temp.Control all filters " 2E C SD* over 24 hr Part 50Humidity Range all filters 24-hr mean 30% - 40% RH or 

# 5% sampling RH but > 20%RH 

Part 50

Humidity Control all filters " 5% SD* over 24 hr. Part 50Pre/post Sampling RH all filters difference in 24-hr means # " 5% RH Part 50, Balance all filters located in filter conditioning environment Part 50, 

Verification/Calibration
QA Hand

Criteria Frequency Acceptable Range Information (C

One-point Flow Rate Verification 1/4 weeks " 4% of transfer standard Part 50, 

Part 58, Appen

OPERATIONAL EVALUATIONS TABLE PM10 Filter Based Local Conditions

Filter Checks Lot Blanks 9 filters per lot less than 15 Fg change between weighings MethoExposure Lot Blanks 3 filters per lot less than 15 Fg change between weighings MethoFilter Integrity (exposed) each filter no visual defects MethoFilter Holding TimesPre-sampling all filters < 30 days before sampling Part 50Lab QC ChecksField Filter Blank 10% or 1 per weighing session " 30 Fg change between weighings Part 50Lab Filter Blank 10% or 1 per weighing session " 15 Fg change between weighings Part 50Balance Check beginning, 10th sample, end #3 Fg MeDuplicate Filter Weighing 1 per weighing session " 15 Fg change between weighings MetSampling InstrumentIndividual Flow Rates every 24 hours of op no flow rate excursions > "5% for > 5 min. 1/ Part 50, Filter Temp Sensor every 24 hours of op no excursions of > 5E C lasting longer than 30 min 1/ Part 50Verification/CalibrationRoutine Verifications External Leak Check every 5 sampling events < 80 mL/min Part 50Internal Leak Check every 5 sampling events < 80 mL/min Part 50One-point Temp Verification 1/4 weeks " 2EC Part 50Pressure Verification 1/4 weeks " 10 mm Hg Part 50Lab Temperature 1/6 months " 2EC MeLab Humidity 1/6 months " 2% MeAnnual Multi-point Verifications /Calibrations Temperature multi-point Verification/Calibration 

1/yr " 2EC Part 50

Pressure Verification/Calibration on installation, then 1/yr " 10 mm Hg Part 50Flow Rate Multi-point Verification/ Calibration 

1/yr " 2% of transfer standard Part 50
QA Hand

Criteria Frequency Acceptable Range Information (C

Design Flow Rate Adjustment at one-point or multi-point " 2% of design flow rate Part 50, Other Monitor Calibrations per manufacturers’ op manual per manufacturers’ operating manual Mirobalance Calibration 1/yr Manufacturer’s specification Part 50PrecisionCollocated Samples every 12 days for 15% of sites CV < 10% of samples > 3 Fg/m3 Part 58 AccuracyTemperature Audit 2/yr " 2EC MetPressure Audit 2/yr "10 mm Hg MetBalance Audit 1/yr " 0.050 mg or manufacturers specs, whichever is tighter MetSemi Annual Flow Rate Audit 2/yr " 4% of audit standard 

" 5% of design flow rate 

Part 58, 

Calibration & Check Standards(working standards) Field Thermometer 1/yr " 0.1E C resolution, " 0.5E C accuracy MethoField Barometer 1/yr " 1 mm Hg resolution, " 5 mm Hg accuracy MethoWorking Mass Stds. (compare to primary standards) 

1/3 mo. 0.025 mg Method 

Monitor MaintenanceInlet/downtube Cleaning every 15 sampling events cleaned MeFilter Chamber Cleaning 1/4 weeks cleaned MeLeak Check @ see Verification/CalibrationCirculating Fan Filter Cleaning 1/4 weeks cleaned/changed Me

Manufacturer-Recommended Maintenance 

per manufacturers’ SOP per manufacturers’ SOP 

SYSTEMATIC CRITERIA -PM10 Filter Based Local Conditions 

Data Completeness quarterly > 75% Part 50, Reporting Units all filters Fg/m3 at ambient temp/pressure (PM2.5) Rounding ConventionAnnual 3-yr average quarterly nearest 0.1 Fg/m3 (> 0.05 round up) Part 5024-hour, 3-year average quarterly nearest 1 Fg/m3 (> 0.5 round up) Part 50Detection LimitLower DL all filters # 2 Fg/m3 Part 50
QA Hand

Criteria Frequency Acceptable Range Information (C

Upper Conc. Limit all filters $ 200 Fg/m3 Part 50Verification/Calibration Standards Recertifications- All standards should have multi-point certifications against NIST Traceable standardsFlow Rate Transfer Std. 1/yr " 2% of NIST-traceable Std. Part 50, AField Thermometer 1/yr " 0.1E C resolution, " 0.5E C accuracy MetField Barometer 1/yr " 1 mm Hg resolution, " 5 mm Hg accuracy MetPrimary Mass Stds. (compare to NIST-traceable standards) 

1/yr 0.025 mg Met

MicrobalanceReadability at purchase 1 Fg Part 50Repeatability 1/yr 1Fg Calibration & Check StandardsFlow Rate Transfer Std. 1/yr " 2% of NIST-traceable Std. Part 50, AVerification/CalibrationClock/timer Verification 1/4 weeks 1 min/mo Part 50PrecisionSingle analyzer 1/3 mo. Coefficient of variation (CV) < 10% Single analyzer 1/ yr CV < 10% Primary Quality Assurance Org. Annual and 3 year estimates 90% CL of CV < 10% Part 58, BiasPerformance Evaluation Program (PEP) 

5 audits for PQAOs with < 5 

sites 

8 audits for PQAOs with > 5 

sites 

"10% Part 58, Ap

1/ value must be flagged 

SD= standard deviation CV= coefficient of variation 

@ 

= Scheduled to occur immediately after impactor cleaned/changed.
QA Hand

PM10 Filter Based Dichot STP Conditions Validation Template 

Criteria Frequency Acceptable Range Information (

CRITICAL CRITERIA- PM10 Filter Based Dichot 

Filter Holding Times Sample Recovery all filters ASAP Part 5Sampling Period all filters 1440 minutes + 60 minutes 

midnight to midnight 

Part 50 

Sampling Instrument Average Flow Rate every 24 hours of op average 16.67 liters/minute MethFilterVisual Defect Check (unexposed) all filters see reference MethCollection efficiency all filters 99 % Part 50Integrity all filters " 5 :g/m3 Part 50Alkalinity all filters < 25.0 microequivalents/gram Part 50Filter Conditioning Environment 

Equilibration all filters 24 hours minimum Part 5Temp. Range all filters 15-30E C Part 50Temp.Control all filters " 3E C SD* over 24 hr Part 50Humidity Range all filters 20% - 45% RH Part 50Humidity Control all filters " 5% SD* over 24 hr Part 50Pre/post Sampling RH all filters difference in 24-hr means # " 5% RH Part 50Balance all filters located in filter conditioning environment Part 50

Verification/CalibrationOne-point Flow Rate Verification 1/4 weeks " 7% of transfer standard and 10% from design Method 

OPERATIONAL EVALUATIONS TABLE PM10 Filter Based Dichot 

Lab QC ChecksBalance Check beginning, 10th sample, end #4 Fg of true zero

#2 Fg of 10 mg check weight 

Meth

“Standard” filter QC check 10% " 20 Fg change from original value Meth

From stand

“Routine” duplicate weighing 5-7 per weighing session " 20 Fg change from original value Meth

From 

Verification/CalibrationSystem Leak Check During precalibration check Vacuum of 10 to 15 in. with decline to 0 >60 seconds MethoFR Multi-point Verification/Calibration 

1/yr " 2% Part 50

Field Temp M-point Verification on installation, then 1/yr " 2EC Lab Temperature 1/6 months " 2EC recLab Humidity 1/6 months " 2% recMicrobalance Calibration 1/yr Manufacturer’s specification Precision
QA Hand

Criteria Frequency Acceptable Range Information (

Collocated Samples every 12 days for 15% of sites CV < 10% of samples > 3 Fg/m3 Part 58 Audits Filter Weighing 1/yr " 20 Fg change from original value Method Balance Audit 1/yr Observe weighing technique and check balance with 

ASTM Class 1 standard 

Method 2.10 

Semi Annual Flow Rate Audit 2/yr " 4% of audit standard 

" 5% of design flow rate 

Part 58

Monitor MaintenanceImpactor 1/3 mo cleaned/changed MethoInlet/downtube Cleaning 1/3 mo cleaned Metho

Vacuum pump 1/yr Replace diaphragm and flapper valves MethoManufacturer-Recommended Maintenance 

per manufacturers’ SOP per manufacturers’ SOP 

SYSTEMATIC CRITERIA - PM10 Filter Based Dichot 

Data Completeness quarterly > 75% Part 50 Reporting Units all filters Fg/m3 at standard temperature and pressure (STP) PaRounding Convention24-hour, 3-year average quarterly nearest 10 Fg/m3 (> 5 round up) Part Verification/Calibration Standards and Recertifications - All standards should have multi-point certifications against NIST Traceable standardsFlow Rate Transfer Std. 1/yr " 2% of NIST-traceable Std. Part 5Field Thermometer 1/yr " 0.1E C resolution, " 0.5E C accuracy Field Barometer 1/yr " 1 mm Hg resolution, " 5 mm Hg accuracy Primary Mass Stds. (compare to NIST-traceable standards) 

1/yr NIST traceable 

(e.g., ANSI/ASTM Class 1, 1.1 or 2) 

Met

MicrobalanceReadability at purchase 1 Fg MethRepeatability 1/yr 1Fg MethCalibration & Check StandardsFlow Rate Transfer Std. 1/yr " 2% of NIST-traceable Std. MetVerification/CalibrationClock/timer Verification 4/year 5 min/mo recPrecisionSingle analyzer 1/3 mo. Coefficient of variation (CV) < 10% recSingle analyzer 1/ yr CV < 10% recPrimary Quality Assurance Org. Annual and 3 year estimates 90% CL of CV < 10% Part 58

SD= standard deviation CV= coefficient of variation 
QA Hand

PM10 Filter Based High Volume (HV) STP Conditions Validation Template 

Criteria Frequency Acceptable Range Informatio

CRITICAL CRITERIA- PM10 Filter Based Hi-Vol

Filter Holding Times Sample Recovery all filters ASAP PSampling Period all filters 1440 minutes + 60 minutes 

midnight to midnight 

Pa

Sampling Instrument Average Flow Rate every 24 hours of op ~1.13 m3/min (varies with instrument) FilterVisual Defect Check (unexposed) all filters see reference MCollection efficiency all filters 99 % PaIntegrity all filters " 5 :g/m3 PaAlkalinity all filters < 25.0 microequivalents/gram PaFilter Conditioning Environment 

Equilibration all filters 24 hours minimum PTemp. Range all filters 15-30E C PaTemp.Control all filters " 3E C SD* over 24 hr PaHumidity Range all filters 20% - 45% RH PaHumidity Control all filters " 5% SD* over 24 hr PaPre/post Sampling RH all filters difference in 24-hr means # " 5% RH Balance all filters located in filter conditioning environment 

Verification/CalibrationOne-point Flow Rate Verification 1/3 mo " 7% of transfer standard and 10% from design Me

OPERATIONAL EVALUATIONS TABLE PM10 Filter Based Hi-Vol 

Lab QC ChecksBalance Check beginning, 10th sample, end + 0.5 mg of true zero and + 0.5 mg 1-5 g check weight M“Routine” duplicate weighing 5-7 per weighing session " 2.8 mg change from original value M

F

Verification/CalibrationSystem Leak Check During precalibration check Auditory inspection with faceplate blocked MFR Multi-point Verification/Calibration 

1/yr 3 of 4 cal points within + 10% of design M
QA Hand

Criteria Frequency Acceptable Range Informatio

Field Temp M-point Verification on installation, then 1/yr " 2EC Lab Temperature 1/6 months " 2EC Lab Humidity 1/6 months " 2% Microbalance Calibration 1/yr Manufacturer’s specification PrecisionCollocated Samples every 12 days for 15% of sites CV < 10% of samples > 15 Fg/m3 PaAudits Filter Weighing 1/yr " 5 mg change from original value MBalance Audit 1/yr Observe weighing technique and check balance with ASTM 

Class 1 standard 

M

Semi Annual Flow Rate Audit 2/yr " 10% of audit standard and design value ParMonitor MaintenanceInlet/downtube Cleaning 1/3 mo cleaned Motor/housing gaskets 1/3 mo Inspected replaced 

Blower motor brushes 600-1000 hours Replace Manufacturer-Recommended Maintenance 

per manufacturers’ SOP per manufacturers’ SOP 

SYSTEMATIC CRITERIA - PM10 Filter Based Hi-Vol 

Data Completeness quarterly > 75% PaReporting Units all filters Fg/m3 at standard temperature and pressure (STP) Rounding Convention24-hour, 3-year average quarterly nearest 10 Fg/m3 (> 5 round up) Verification/Calibration Standards and Recertifications - All standards should have multi-point certifications against NIST Traceable standardsFlow Rate Transfer Std. 1/yr " 2% of NIST-traceable Std. PField Thermometer 1/yr " 0.1E C resolution, " 0.5E C accuracy Field Barometer 1/yr " 1 mm Hg resolution, " 5 mm Hg accuracy Primary Mass Stds. (compare to NIST-traceable standards) 

1/yr NIST traceable 

(e.g., ANSI/ASTM Class 1, 1.1 or 2) 

MicrobalanceReadability at purchase 0.1 mg MRepeatability 1/yr 0.5 mg (HV) MCalibration & Check Standards
QA Hand

Criteria Frequency Acceptable Range Informatio

Flow Rate Transfer Std. 1/yr " 2% of NIST-traceable Std. Verification/CalibrationClock/timer Verification 4/year 5 min/mo PrecisionSingle analyzer 1/3 mo. Coefficient of variation (CV) < 10% Single analyzer 1/ yr CV < 10% Primary Quality Assurance Org. Annual and 3 year estimates 90% CL of CV < 10% Par

SD= standard deviation CV= coefficient of variation 
QA Hand

Continuous PM10 STP Conditions Validation Template NOTE: There are a number of continuous PM10 monitors that are designated as FEM. These monitors may 

measurement or sampling attributes that cannot be identified in this validation template. Monitoring organizaspecific instrument operating manuals to augment this validation template as necessary. In general, 40 CFR Pa

CFR part 50 App J requirements apply to Continuous PM10. Since a guidance document was never developed many of the requirements reflect a combination of manual and continuous PM2.5 requirements and are therefrecommendations. 

Criteria Frequency Acceptable Range Informatio

CRITICAL CRITERIA- PM10 Continuous

Sampling Period all filters 1440 minutes + 60 minutes 

midnight to midnight 

Pa

Sampling Instrument Average Flow Rate every 24 hours of op Average within + 5% of design Verification/CalibrationOne-point Flow Rate Verification 1/mo " 7% of transfer standard and 10% from design Par

OPERATIONAL EVALUATIONS TABLE PM10 Continuous 

Verification/CalibrationSystem Leak Check During precalibration check Auditory inspection with faceplate blocked MFR Multi-point Verification/Calibration 

1/yr 3 of 4 cal points within + 10% of design M

Audits Semi Annual Flow Rate Audit 1/6 mo " 10% of audit standard and design value ParMonitor MaintenanceInlet/downtube Cleaning 1/3 mo cleaned Motor/housing gaskets 1/3 mo Inspected replaced 

Blower motor brushes 600-1000 hours Replace Manufacturer-Recommended Maintenance 

per manufacturers’ SOP per manufacturers’ SOP 

SYSTEMATIC CRITERIA - PM10 Continuous 

Data Completeness quarterly > 75% PaReporting Units all filters Fg/m3 at standard temperature and pressure (STP) Rounding Convention
QA Hand

Criteria Frequency Acceptable Range Informatio

24-hour, 3-year average quarterly nearest 10 Fg/m3 (> 5 round up) Verification/Calibration Standards and Recertifications - All standards should have multi-point certifications against NIST Traceable standardsFlow Rate Transfer Std. 1/yr " 2% of NIST-traceable Std. PField Thermometer 1/yr " 0.1E C resolution, " 0.5E C accuracy Field Barometer 1/yr " 1 mm Hg resolution, " 5 mm Hg accuracy Calibration & Check StandardsFlow Rate Transfer Std. 1/yr " 2% of NIST-traceable Std. Verification/CalibrationClock/timer Verification 4/year 5 min/mo 
QA Hand

Pb High Volume (TSP) Validation Template Note: in 2008, the NAAQS was lowered for Pb and new monitoring rules were promulgated which allowed for the us

analytical methods and the use of PM10 sampling in certain circumstances. The following information is guidance ba

which is sampling by TSP and analysis by atomic absorption. Information is this table is derived from the TSP sampl

Part 50 App B, and QA Handbook Method 2.2 (1977). The analytical requirements/guidance is derived from 40 CFR 

QA Handbook Method 2.8 (1981). Monitoring for Pb based on the new NAAQS requirements will begin in calendar new guidance related to analytical FEM (ICP-MS, XRF, etc.) will be developed and included as additional guid

and/or additional Pb validation templates will be included in this section and posted on AMTIC.

Criteria Frequency Acceptable Range

Informatio

CRITICAL CRITERIA- Pb in TSP

Filter Holding Times Sample Recovery all filters ASAP Sampling Period all filters 1440 minutes + 60 minutes 

midnight to midnight 

Pa

Sampling Instrument Average Flow Rate every 24 hours of op 1.1-1.70 m3/min (varies with instrument) PFilter PVisual Defect Check (unexposed) all filters see reference PCollection Efficiency all filters 99 % PaPressure Drop Range all filters 42-54 mm Hg PapH all filters 6-10 PaPb Content all filters pre-sampling batch 

check 

<75 :g/filter Pa

M

Verification/CalibrationOne-point Flow Rate Verification 1/3 mo +7% from design transfer standard +10% from design Part 58 Calibration Reproducibility Checks Beginning, every 10 samples 

and end 

+ 5% of value predicted by calibration curve Pa

Reagent Blank Every analytical batch < LDL Daily Calibration Daily until good agreement is obtained among replicates M

OPERATIONAL EVALUATIONS TABLE Pb in TSP 

Verification/CalibrationSystem Leak Check During precalibration check Auditory inspection with faceplate blocked 
QA Hand

Criteria Frequency Acceptable Range

Informatio

FR Multi-point Verification/Calibration 

After receipt, after motor 

maintenance or failure of 1-

point check and 

1/yr 

5 points over range of 1.1 to 1.7 m3/min 

within + 5% limits of linearity 

PrecisionCollocated Samples 15% of each method code in 

PQAO 

Frequency - every 12 days 

CV < 20% of samples > 0.02 Fg/m3 (cutoff value) Pa

Audits Semi Annual Flow Rate Audit 2/yr " 10% of audit standard and design value ParLead Strip Analysis 6 strips/quarter 

3/conc. 

10% (percent difference) Par

Blanks Field Filter Blank 1/quarter < LDL Monitor MaintenanceInlet cleaning 1/3 mo cleaned Motor/housing gaskets ~400 hours Inspected replaced 

Blower motor brushes 400-500 Replace Manufacturer-Recommended Maintenance 

per manufacturers’ SOP per manufacturers’ SOP 

SYSTEMATIC CRITERIA - Pb Filter Based Hi-Vol 

Data Completeness quarterly three -month mean (i.e., the 3-month data capture rate) > 75% PReporting Units all filters Fg/m3 at local temperature and pressure. Rounding Convention3-month arithmetic mean quarterly Report data to 3 decimal places (data after 3 are truncated. Lower Detectable LimitAtomic Absorption 0.07 :g/m3 PVerification/Calibration Standards and Recertifications - All standards should have multi-point certifications against NIST Traceable standardsFlow Rate Transfer Std. 1/yr Resolution 0.02 m3/min 

" 2% reproducibility 

P

Field Thermometer 1/yr 2E C resolution PField Barometer 1/yr " 5 mm Hg resolution PAnalytical Standards
QA Hand

Criteria Frequency Acceptable Range

Informatio

Reagents (HNO3 and HCL) ACS reagent grade PPb nitrate Pb (NO3)2 ACS reagent grade (99.0% purity PVerification/CalibrationClock/timer Verification 4/year 5 min/mo PrecisionSingle analyzer 1/3 mo. Coefficient of variation (CV) < 20% Single analyzer 1/ yr CV < 20% Primary Quality Assurance Org. Annual and 3 year estimates 90% CL of CV < 20% ParBiasPerformance Evaluation Program (PEP) 

5 audits for PQAOs with < 5 

sites 

8 audits for PQAOs with > 5 

sites 

95% CL Absolute bias "15% Par

SD= standard deviation CV= coefficient of variation 
QA Handbook Volume II, Appendix E 

Revision No. 1 

Date:12/08 

Page 1 of 8 

Appendix E 

Characteristics of Spatial Scales Related to Each Pollutant 

The following tables provide information in order to match the spatial scale represented by the monitor 

with the monitoring objectives. 

NOTE: This information can also be found in 40 CFR Part 58, Appendix D and since there is a 

possibility that spatial scales have been updated, users should also review CFR. 
QA Handbook Volume II, Appendix E 

Revision No. 1 

Date:12/08 

Page 2 of 7 

Page intentionally left blank 
QA Ha

Pollutant Spatial Scale Characteristics NOTE: This information can also be found in 40 CFR Part 58, Appendix D a

possibility that spatial scales have been updated, users should also review CFR. 

NCore Urban 

Rural 

Generally located at urban or neighborhood scale to provide representative concentrations of exposure expected throu

however, a middle-scale site may be acceptable in cases where the site can represent many such locations throughout Rural NCore stations are to be located to the maximum extent practicable at a regional or larger scale away from any that they represent ambient concentrations over an extensive area.

PM10 Micro 

Middle Neighborhood 

This scale would typify areas such as downtown street canyons, traffic corridors, and fence line stationary source mon

general public could be exposed to maximum PM10 concentrations. Microscale particulate matter sites should be localocations where the general public can be expected to be exposed to the concentration measured. Emissions from statisecondary smelters, power plants, and other large industrial processes may, under certain plume conditions, likewise r

concentrations at the microscale. In the latter case, the microscale would represent an area impacted by the plume wit

approximately 100 meters. Data collected at microscale sites provide information for evaluating and developing hot spMuch of the short-term public exposure to coarse fraction particles (PM10) is on this scale and on the neighborhood s

downtown areas or living near major roadways or stationary sources, may encounter particulate pollution that would b

measurements of this spatial scale. Middle scale PM10 measurements can be appropriate for the evaluation of possiblhealth effects. In many situations, monitoring sites that are representative of micro-scale or middle-scale impacts are n

of many similar situations. This can occur along traffic corridors or other locations in a residential district. In this casea neighborhood of small scale sites and is appropriate for evaluation of long-term or chronic effects. This scale also inconcentrations for other areas with dimensions of a few hundred meters such as the parking lot and feeder streets asso

stadia, and office buildings. In the case of PM10, unpaved or seldomly swept parking lots associated with these sourc

Measurements in this category represent conditions throughout some reasonably homogeneous urban subregion with 

and of generally more regular shape than the middle scale. Homogeneity refers to the particulate matter concentrationsurface characteristics. In some cases, a location carefully chosen to provide neighborhood scale data would represent 

neighborhood but also neighborhoods of the same type in other parts of the city. Neighborhood scale PM10 sites prov

compliance with standards because they often represent conditions in areas where people commonly live and work foscale data could provide valuable information for developing, testing, and revising models that describe the largerscal

especially those models relying on spatially smoothed emission fields for inputs. The neighborhood scale measuremen

neighborhood comparisons within or between cities. 
QA Ha

Pollutant Spatial Scale Characteristics NOTE: This information can also be found in 40 CFR Part 58, Appendix D a

possibility that spatial scales have been updated, users should also review CFR. 

SO2 Micro/Middle 

Neighborhood 

Some data uses associated with microscale and middle scale measurements for SO2 include assessing the effects of c

reduce concentrations (especially for the 3-hour and 24-hour averaging times) and monitoring air pollution episodes. 

This scale applies where there is a need to collect air quality data as part of an ongoing SO2 stationary source impact 

might include suburban areas adjacent to SO2 stationary sources for example, or for determining background concent

population responses to exposure to SO2.

CO Micro 

Middle 

This scale applies when air quality measurements are to be used to represent distributions within street canyons, over roadways. In the case with carbon monoxide, microscale measurements in one location can often be considered as replocations in a city. Middle scale measurements are intended to represent areas with dimensions from 100 meters to 0.5 kilometer. In cert

measurements may apply to areas that have a total length of several kilometers, such as ‘‘line’’ emission source areas

areas would include air quality along a commercially developed street or shopping plaza, freeway corridors, parking l

O3 Neighborhood 

Urban Regional 

Measurements in this category represent conditions throughout some reasonably homogeneous urban subregion, with 

Homogeneity refers to pollutant concentrations. Neighborhood scale data will provide valuable information for develoconcepts and models that describe urban/regional concentration patterns. These data will be useful to the understandin

take periods of hours to occur and hence involve considerable mixing and transport. Under stagnation conditions, a si

scale may also experience peak concentration levels within a metropolitan area. Measurement in this scale will be used to estimate concentrations over large portions of an urban area with dimension

more kilometers. Such measurements will be used for determining trends, and designing area-wide control strategies. 

be used to measure high concentrations downwind of the area having the highest precursor emissions. 

This scale of measurement will be used to typify concentrations over large portions of a metropolitan area and even lamuch as hundreds of kilometers. Such measurements will be useful for assessing the O3 that is transported to and from background concentrations. In some situations, particularly when considering very large metropolitan areas with com

scale sites can be the maximum concentration location. 
QA Ha

Pollutant Spatial Scale Characteristics NOTE: This information can also be found in 40 CFR Part 58, Appendix D a

possibility that spatial scales have been updated, users should also review CFR. 

NO2 Middle 

Neighborhood Urban 

Dimensions from about 100 meters to 0.5 kilometer. These measurements would characterize the public exposure to N

Same as for O3

Same as for O3
QA Ha

Pollutant Spatial Scale Characteristics NOTE: This information can also be found in 40 CFR Part 58, Appendix D a

possibility that spatial scales have been updated, users should also review CFR. 

PM2.5 Microscale 

Middle Neighborhood Urban Regional 

Areas such as downtown street canyons and traffic corridors where the general public would be exposed to maximum 

sources. In some circumstances, the microscale is appropriate for particulate sites; community-oriented SLAMS sites 

should, however, be limited to urban sites that are representative of long-term human exposure and of many such mic

general, microscale particulate matter sites should be located near inhabited buildings or locations where the general p

exposed to the concentration measured. Emissions from stationary sources such as primary and secondary smelters, p

industrial processes may, under certain plume conditions, likewise result in high ground level concentrations at the m

microscale would represent an area impacted by the plume with dimensions extending up to approximately 100 metersites provide information for evaluating and developing hot spot control measures. People moving through downtown areas, or living near major roadways, encounter particle concentrations that would 

this spatial scale. Thus, measurements of this type would be appropriate for the evaluation of possible short-term expo

particulate matter pollution. In many situations, monitoring sites that are representative of microscale or middle-scale representative of many similar situations. This can occur along traffic corridors or other locations in a residential distr

representative of a number of small scale sites and is appropriate for evaluation of long-term or chronic effects. This s

characteristic concentrations for other areas with dimensions of a few hundred meters such as the parking lot and feedshopping centers, stadia, and office buildings. Measurements in this category would represent conditions throughout some reasonably homogeneous urban sub-regio

kilometers and of generally more regular shape than the middle scale. Homogeneity refers to the particulate matter co

use and land surface characteristics. Much of the PM2.5 exposures are expected to be associated with this scale of me

location carefully chosen to provide neighborhood scale data would represent the immediate neighborhood as well as 

other parts of the city. PM2.5 sites of this kind provide good information about trends and compliance with standards 

conditions in areas where people commonly live and work for periods comparable to those specified in the NAAQS. monitoring in urban areas should have this scale. This class of measurement would be used to characterize the particulate matter concentration over an entire metropolisize from 4 to 50 kilometers. Such measurements would be useful for assessing trends in area-wide air quality, and he

scale air pollution control strategies. Community-oriented PM2.5 sites may have this scale. These measurements would characterize conditions over areas with dimensions of as much as hundreds of kilometers

representative conditions for an area implies some degree of homogeneity in that area. For this reason, regional scale applicable to sparsely populated areas. Data characteristics of this scale would provide information about larger scale 
QA Ha

Pollutant Spatial Scale Characteristics NOTE: This information can also be found in 40 CFR Part 58, Appendix D a

possibility that spatial scales have been updated, users should also review CFR. 

Pb Micro 

Middle Neighborhood 

This scale would typify areas in close proximity to lead point sources. Emissions from point sources such as primary primary copper smelters may under fumigation conditions likewise result in high ground level concentrations at the m

microscale would represent an area impacted by the plume with dimensions extending up to approximately 100 metersites provide information for evaluating and developing ‘‘hot-spot’’ control measures. This scale generally represents Pb air quality levels in areas up to several city blocks in size with dimensions on the o

to 500 meters. The middle scale may for example, include schools and playgrounds in center city areas which are clos

monitors in such areas are desirable because of the higher sensitivity of children to exposures of elevated Pb concentr

appendix). Emissions from point sources frequently impact on areas at which single sites may be located to measure c

spatial scales. The neighborhood scale would characterize air quality conditions throughout some relatively uniform land use areas wkilometer range. Sites of this scale would provide monitoring data in areas representing conditions where children live 

areas is important since this segment of the population is more susceptible to the effects of Pb. Where a neighborhood 

immediate Pb sources, the site may be very useful in representing typical air quality values for a larger residential arepopulation exposure and trends analyses. 

PAMs Neighborhood 

Urban 

Would define conditions within some extended areas of the city that have a relatively uniform land use and range from 

neighborhood scale represent conditions throughout a homogeneous urban subregion. Precursor concentrations, on thbecome well mixed and can be used to assess exposure impacts and track emissions. Neighborhood data will provide to residential and local business districts. VOC sampling at Site #2 is characteristic of a neighborhood scale. Measur

ideally located just downwind of the edge of the urban core emission areas. Further definition of neighborhood and u

Appendix D of 40 CFR 58 and Reference 9. Would represent concentration distributions over a metropolitan area. Monitoring on this scale relates to precursor em

strategy plans for an MSA/CMSA. PAMS Sites #1, #3, and #4 are characteristic of the urban scale. 
QA Ha

Pollutant Spatial Scale Characteristics NOTE: This information can also be found in 40 CFR Part 58, Appendix D a

possibility that spatial scales have been updated, users should also review CFR. 

PM 10-2.5

Micro Middle Neighborhood 

The only required monitors for PM10-2.5 are those required at NCore Stations. Although microscale monitoring may be 

circumstances, middle and neighborhood scale measurements are the most important station classifications for PM10-2

This scale would typify relatively small areas immediately adjacent to: Industrial sources; locations experiencing ong

and soil disturbance; and heavily traveled roadways. Data collected at microscale stations would characterize exposur

extent and population exposure, and may provide information useful for evaluating and developing source oriented coPeople living or working near major roadways or industrial districts encounter particle concentrations that would be a

spatial scale. Thus, measurements of this type would be appropriate for the evaluation of public health effects of coarslocated in populated areas that are nearly adjacent to large industrial point sources of coarse particles provide suitable 

population exposure levels and identifying areas of potentially poor air quality. Similarly, monitors located in populatnetworks of heavily-traveled traffic are appropriate for assessing the impacts of resuspended road dust. This scale also 

concentrations for other areas with dimensions of a few hundred meters such as school grounds and parks that are neaand industrial point sources, locations exhibiting mixed residential and commercial development, and downtown area

shopping centers, and stadiums. Measurements in this category would represent conditions throughout some reasonably homogeneous urban sub-regio

kilometers and of generally more regular shape than the middle scale. Homogeneity refers to the particulate matter co

use and land surface characteristics. This category includes suburban neighborhoods dominated by residences that are 

roadways and industrial districts but still impacted by urban sources, and areas of diverse land use where residences a

and industrial neighborhoods. In some cases, a location carefully chosen to provide neighborhood scale data would reneighborhood as well as neighborhoods of the same type in other parts of the city. The comparison of data from middsites would provide valuable information for determining the variation of PM10–2.5 levels across urban areas and ass

elevated concentrations caused by major industrial point sources and heavily traveled roadways. Neighborhood scale data that are relevant to informing a large segment of the population of their exposure levels on a given day. 

PM 2.5

Speciation NA Each State shall continue to conduct chemical speciation monitoring and analyses at sites designated to be part of the 

Network (STN). The selection and modification of these STN sites must be approved by the Administrator. 
QA Handbook Volume II, Appendix F 

Revision No: 1 

Date: 12/08 

Page 1 of 13 

Appendix F 

Sample Manifold Design for Precursor Gas Monitoring 

The following information is extracted from the document titled: Version 4 of the Technical 

Assistance Document for Precursor Gas Measurements in the NCore Multi-pollutant Monitoring Network

which can be found on the AMTIC website at: http://www.epa.gov/ttn/amtic/pretecdoc.html
QA Handbook Volume II, Appendix F 

Revision No: 1 

Date: 12/08 

Page 2 of 13 

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QA Handbook Volume II, Appendix F 

Revision No: 1 

Date: 12/08 

Page 3 of 13 

Sample Manifold Design for Precursor Gas Monitoring 

Many important variables affect sampling manifold design for ambient precursor gas monitoring: 

residence time of sample gases, materials of construction, diameter, length, flow rate, and 

pressure drop. Considerations for these parameters are discussed below. 

Residence Time Determination: The residence time of air pollutants within the sampling system 

(defined as extending from the entrance of the sample inlet above the instrument shelter to the 

bulkhead of the precursor gas analyzer) is critical. Residence time is defined as the amount of 

time that it takes for a sample of air to travel through the sampling system. This issue is 

discussed in detail for NOy monitoring in Section 4.2, and recommendations in Section 4 for the 

arrangement of the molybdenum converter and inlet system should be followed. However, 

residence time is also an issue for other precursor gases, and should be considered in designing 

sample manifolds for those species. For example, Code of Federal Regulations (CFR), Title 40 

Part 58, Appendix E.9 states, “Ozone in the presence of NO will show significant losses even in 

the most inert probe material when the residence time exceeds 20 seconds. Other studies indicate 

that 10-second or less residence time is easily achievable.”1

 Although 20-second residence time 

is the maximum allowed as specified in 40 CFR 58, Appendix E, it is recommended that the 

residence time within the sampling system be less than 10 seconds. If the volume of the 

sampling system does not allow this to occur, then a blower motor or other device (such as a 

vacuum pump) can be used to increase flow rate and decrease the residence time. The residence 

time for a sample manifold system is determined in the following way. First the total volume of 

the cane (inlet), manifold, and sample lines must be determined using the following equation: 

Total Volume = Cv + Mv + Lv Equation 1

Where: 

Cv = Volume of the sample cane or inlet and extensions 

Mv = Volume of the sample manifold and moisture trap 

Lv = Volume of the instrument lines from the manifold to the instrument bulkhead

The volume of each component of the sampling system must be measured individually. To 

measure the volume of the components (assuming they are cylindrical in shape), use the 

following equation: 

V = π * (d/2)2

 * L Equation 2 

Where: 

V = volume of the component, cm3

π = 3.14 

L = Length of the component, cm 

d = inside diameter of the component, cm 
QA Handbook Volume II, Appendix F 

Revision No: 1 

Date: 12/08 

Page 4 of 13 

Once the total volume is determined, divide the total volume by the total sample flow rate of all 

instruments to calculate the residence time in the inlet. If the residence time is greater than 20 

seconds, attach a blower or vacuum pump to increase the flow rate and decrease the residence 

time. 

Laminar Flow Manifolds: In the past, vertical laminar flow manifolds were a popular design. 

By the proper selection of a large diameter vertical inlet probe and by maintaining a laminar flow 

throughout, it was assumed that the sample air would not react with the walls of the probe. 

Numerous materials such as glass, plastic, galvanized steel, and stainless steel were used for 

constructing the probe. Removable sample lines constructed of FEP or PTFE were placed to 

protrude into the manifold to provide each instrument with sample air. A laminar flow manifold 

could have a flow rate as high as 150 L/min, in order to minimize any losses, and large diameter 

tubing was used to minimize pressure drops. However, experience has shown that vertical 

laminar flow manifolds have demonstrated many disadvantages which are listed below: 

• Since the flow rates are so high, it is difficult to supply enough audit gas to provide an 

adequate independent assessment for the entire sampling system; 

• Long laminar flow manifolds may be difficult to clean due to size and length; 

• Temperature differentials may exist that could change the characteristics of the gases, e.g., if 

a laminar manifold’s inlet is on top of a building, the temperature at the bottom of the 

building may be much lower, thereby dropping the dew point and condensing water. 

• Construction of the manifold is frequently of an unapproved material. 

For these technical reasons, EPA strongly discourages the use of laminar flow manifolds in the 

national air monitoring network. It is recommended that agencies that utilize laminar manifolds 

migrate to conventional manifold designs that are described below. 

Sampling Lines as Inlet and Manifold: Often air monitoring agencies will place individual 

sample lines outside of their shelter for each instrument. If the sample lines are manufactured 

out of Polytetrafluoroethylene (PTFE) or Fluoroethylpropylene (FEP) Teflon®, this is 

acceptable to the EPA. The advantages to using single sample lines are: no breakage and ease 

of external auditing. In addition, rather than cleaning glass manifolds, some agencies just 

replace the sampling lines. However, please note the following caveats: 

1. PTFE and FEP lines can deteriorate when exposed to atmospheric conditions, particularly 

ultraviolet radiation from the sun. Therefore, it is recommended that sample lines be 

inspected and replaced regularly. 

2. Small insects and particles can accumulate inside of the tubing. It has been reported that 

small spiders build their webs inside of tubing. This can cause blockage and affect the 

response of the instruments. In addition, particles can collect inside the tubing, especially at 

the entrance, thus affecting precursor gas concentrations. Check the sampling lines and 

replace or clean the tubing on a regular basis. 

3. Since there is no central manifold, these configurations sometimes have a “three-way” tee, 

i.e., one flow path for supplying calibration mixtures and the other for the sampling of 

ambient air. If the three-way tee is not placed near the outermost limit of the sample inlet 
QA Handbook Volume II, Appendix F 

Revision No: 1 

Date: 12/08 

Page 5 of 13 

tubing, then the entire sampling system is not challenged by the provision of calibration gas. 

It is strongly recommended that at least on a periodic basis calibration gas be supplied so 

that it floods the entire sample line. This is best done by placing the three-way tee just 

below the sample inlet, so that calibration gas supplied there is drawn through the entire 

sampling line. 

4. The calibration gas must be delivered to the analyzers at near ambient pressure. Some 

instruments are very sensitive to pressure changes. If the calibration gas flow is excessive, 

the analyzer may sample the gas under pressure. If a pressure effect on calibration gas 

response is suspected, it is recommended that the gas be introduced at more than one place 

in the sampling line (by placement of the tee, as described in item #3 above). If the response 

to the calibration gas is the same regardless of delivery point, then there is likely no pressure 

effect. 

Conventional Manifold Design - A number of “conventional” manifold systems exist today. 

However, one manifold feature must be consistent: the probe and manifold must be constructed 

of borosilicate glass or Teflon® (PFA or PTFE). These are the only materials proven to be inert 

to gases. EPA will accept manifolds or inlets that are made from other materials, such as steel or 

aluminum, that are lined or coated with borosilicate glass or the Teflon® materials named above. 

However, all of the linings, joints and connectors that could possibly come into contact with the 

sample gases must be of glass or Teflon®. It is recommended that probes and manifolds be 

constructed in modular sections to enable frequent cleaning. It has been demonstrated that there 

are no significant losses of reactive gas concentrations in conventional 13 mm inside diameter 

(ID) sampling lines of glass or Teflon® if the sample residence time is 10 seconds or less. This is 

true even in sample lines up to 38 m in length. However, when the sample residence time 

exceeds 20 seconds, loss is detectable, and at 60 seconds the loss can be nearly complete. 

Therefore, EPA requires that residence times must be 20 seconds or less (except for NOy). 

Please note that for particulate matter (PM) monitoring instruments, such as nephelometers, 

Tapered Element Oscillating Microbalance (TEOM) instruments, or Beta Gauges, the ambient 

precursor gas manifold is not recommended. Particle monitoring instruments should have 

separate intake probes that are as short and as straight as possible to avoid particulate losses due 

to impaction on the walls of the probe. 

T-Type Design: The most popular gas sampling system in use today consists of a vertical 

"candy cane" protruding through the roof of the shelter with a horizontal sampling manifold 

connected by a tee fitting to the vertical section (Figure 1). This type of manifold is 

commercially available. At the bottom of the tee is a bottle for collecting particles and moisture 

that cannot make the bend; this is known as the “drop out” or moisture trap bottle. Please note 

that a small blower at the exhaust end of the system (optional) is used to provide flow through 

the sampling system. There are several issues that must be mitigated with this design: 

• The probe and manifold may have a volume such that the total draw of the precursor gas 

analyzers cannot keep the residence time less than 20 seconds (except NOy), thereby 

requiring a blower motor. However, a blower motor may prevent calibration and audit 

gases from being supplied in sufficient quantity, because of the high flow rate in the 

manifold. To remedy this, the blower motor must be turned off for calibration. 
QA Handbook Volume II, Appendix F 

Revision No: 1 

Date: 12/08 

Page 6 of 13 

However, this may affect the response of the instruments since they are usually operated 

with the blower on. 

• Horizontal manifolds have been known to collect water, especially in humid climates. 

Standing water in the manifold can be pulled into the instrument lines. Since most 

monitoring shelters are maintained at 20-30 oC, condensation can occur when warm 

humid outside air enters the manifold and is cooled. Station operators must be aware of 

this issue and mitigate this situation if it occurs. Tilting the horizontal manifold slightly 

and possibly heating the manifold have been used to mitigate the condensation problem. 

Water traps should be emptied whenever there is standing water. 

Sample Cane

Blower Motor

Teflon Connectors -

 Bushing

Modular Manifold

Moisture Trap

roof line

Screw Type Opening 

"T" 

adaptor

Figure 1. Conventional T-Type Glass Manifold System 

California Air Resources Board “Octopus” Style: Another type of manifold that is being 

widely used is known as the California Air Resources Board (CARB) style or “Octopus” 

manifold, illustrated in Figure 2. This manifold has a reduced profile, i.e., there is less volume in 

the cane and manifold; therefore, there is less need for a blower motor. If the combined flow 

rates of the gas analyzers are high enough, then an additional blower is not required. 
QA Handbook Volume II, Appendix F 

Revision No: 1 

Date: 12/08 

Page 7 of 13 

roof line

Screw Type Opening 

Moisture Trap

Sample Cane

Teflon Connectors -

 Bushing

8-port "Octopus" 

 Manifold

Figure 2. CARB or “Octopus” Style Manifold 
QA Handbook Volume II, Appendix F 

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Page 8 of 13 

Placement of Tubing on the Manifold: If the manifold employed at the station has multiple 

ports (as in Figure 2) then the position of the instrument lines relative to the calibration input line 

can be crucial. If a CARB “Octopus” or similar manifold is used, it is suggested that sample 

connections for analyzers requiring lower flows be placed towards the bottom of the manifold. 

Also, the general rule of thumb states that the calibration gas delivery line (if used) should be in 

a location so that the calibration gas flows past the analyzer inlet points before the gas is 

evacuated out of the manifold. Figure 3 illustrates two potential locations for introduction of the 

calibration gas. One is located at the ports on the “Octopus” manifold, and the other is upstream 

near the air inlet point, using an audit or probe inlet stub. This stub is a tee fitting placed so that 

“Through-the-Probe” audit line or sampling system tests and calibrations can be conducted. 

roof line

Sample Cane

Audit and probe 

inlet stub

Instrument 

inlet lines

Calibration 

outlet line

Instrument 

inlet lines

Figure 3. Placement of Lines on the Manifold 
QA Handbook Volume II, Appendix F 

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Page 9 of 13 

3

14

2

8

1

4

15

13

12 12

9

11

7

6

16

5

Measurements and Features

1. Knurled Connector

2. O-ring

3. Threaded opening 

4. Top extension - 56 mm

5. Overall Length - 304 mm

6. Outside diameter - 24 mm

7. Top and bottom shoulder - 50 mm

8. Length of inlet tube - 30 mm

9. Distancebetween inlet tubes - 16 mm

10. Length of internal tube - 145 mm

11. Width of inlet tube OD - 6 mm

12. Distance from inner tube to wall - 18 mm

13. Inside width of outer tube 60 mm

14. Down tube length 76 mm

15. Width Down tube OD - 24 mm

16 Overall Width ~ 124 mm

10

7

Figure 4. Specifications for an ‘Octopus” Style Manifold 
QA Handbook Volume II, Appendix F 

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Date: 12/08 

Page 10 of 13 

Figure 4 illustrates the specifications of an Octopus style manifold. Please note that EPAOAQPS has used this style of manifold in its precursor gas analyzer testing program. This type 

of manifold is commercially available. 

Vertical Manifold Design: Figure 5 shows a schematic of the vertical manifold design. 

Commercially available vertical manifolds have been on the market for some time. The issues 

with this type of manifold are the same with other conventional manifolds, i.e., when sample air 

moves from a warm humid atmosphere into an air-conditioned shelter, condensation of moisture 

can occur on the walls of the manifold. Commercially available vertical manifolds have the 

option for heated insulation to mitigate this problem. Whether the manifold tubing is made of 

glass or Teflon®, the heated insulation prevents viewing of the tubing, so the interior must be 

inspected often. The same issues apply to this manifold style as with horizontal or “Octopus” 

style manifolds: additional blower motors should not be used if the residence time is less than 20 

seconds, and the calibration gas inlet should be placed upstream so that the calibration gas flows 

past the analyzer inlets before it exits the manifold. 

roof line

Support Pipe

Glass Manifold

Sample Ports

Blower Motor

Insulation

Heater Power Cord

Manifold Support

Exhaust Hose

Floor

"T" Connector

Figure 5. Example of Vertical Design Manifold 
QA Handbook Volume II, Appendix F 

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Page 11 of 13 

Manifold/Instrument Line Interface: A sampling system is an integral part of a monitoring 

station, however, it is only one part of the whole monitoring process. With the continuing 

integration of advanced electronics into monitoring stations, manifold design must be taken into 

consideration. Data Acquisition Systems (DASs) are able not only to collect serial and analog 

data from the analyzers, but also to control Mass Flow Calibration (MFC) equipment and solid 

state solenoid switches, communicate via modem or Ethernet, and monitor conditions such as 

shelter temperature and manifold pressure. As described in Chapter 6, commercially available 

DASs may implement these features in an electronic data logger, or via software installed on a 

personal computer. Utilization of these features allows the DAS and support equipment to 

perform automated calibrations (Autocals). In addition to performing these tasks, the DAS can 

flag data during calibration periods and allow the data to be stored in separate files that can be 

reviewed remotely. 

Figure 6 shows a schematic of the integrated monitoring system at EPA’s Burden Creek NCore 

monitoring station. Note that a series of solenoid switches are positioned between the ambient 

air inlet manifold and an additional “calibration” manifold. This configuration allows the DAS 

to control the route from which the analyzers draw their sample. At the beginning of an Autocal, 

the DAS signals the MFC unit to come out of standby mode and start producing zero or 

calibration gas. Once the MFC has stabilized, the DAS switches the analyzers’ inlet flow (via 

solenoids) from the ambient air manifold to the calibration manifold. The calibration gas is 

routed to the instruments, and the DAS monitors and averages the response, flagging the data 

appropriately as calibration data. When the Autocal has terminated, the DAS switches the 

analyzers’ inlet flow from the calibration manifold back to the ambient manifold, and the data 

system resets the data flag to the normal ambient mode. 

The integration of DAS, solenoid switches, and MFC into an automated configuration can bring 

an additional level of complexity to the monitoring station. Operators must be aware that this 

additional complexity can create situations where leaks can occur. For instance, if a solenoid 

switch fails to open, then the inlet flow of an analyzer may not be switched back to the ambient 

manifold, but instead will be sampling interior room air. When the calibrations occur, the 

instrument will span correctly, but will not return to ambient air sampling. In this case, the data 

collected must be invalidated. These problems are usually not discovered until there is an 

external “Through-the Probe” audit, but by then extensive data could be lost. It is recommended 

that the operator remove the calibration line from the calibration manifold on a routine basis and 

challenge the sampling system from the inlet probe. This test will discover any leak or switching 

problems within the entire sampling system. 
QA Handbook Volume II, Appendix F 

Revision No: 1 

Date: 12/08 

Page 12 of 13 

Figure 6. Example of a Manifold/Instrument Interface 

Figure 7 shows a close up of an ambient/calibration manifold, illustrating the calibration 

manifold – ambient manifold interface. This is the same interface used at EPA’s Burden’s Creek 

monitoring station. The interface consists of three distinct portions: the ambient manifold, the 

solenoid switching system and the calibration manifold. In this instance, the ambient manifold is 

a T-type design that is being utilized with a blower fan at the terminal. Teflon® tubing connects 

the manifold to the solenoid switching system. Two-way solenoids have two configurations. 

Either the solenoid is in its passive state, at which time the ports that are connected are the 

normally open (NO) and the common (COM). In the other state, when it is energized, the ports 

that are connected are the normally closed (NC) and the COM ports. Depending on whether the 

solenoid is ‘active’ or not, the solenoid routes the air from the calibration or ambient manifold to 

the instrument inlets. There are two configurations that can be instituted with this system. 

1. Ambient Mode: In this mode the solenoids are in “passive” state. The flow of air (under 

vacuum) is routed from the NO port through the solenoid to the COM port. 

2. Calibration Mode: In this mode, the solenoids are in the “active” state. An external 

switching device, usually the DAS, must supply direct current to the solenoid. This 

causes the solenoid to be energized so that the NO port is shut and the NC port is now 

connected to the COM port. As in all cases, the COM port is always selected. The 

switching of the solenoid is done in conjunction with the MFC unit becoming active; 

Burden's Creek Sampling Station - OAQPS/MQAG

Environics

9100 Cal Sys

TECO 42CY TL

NOx

TECO 43CTL

SO2

TECO 48CTL

CO

P

V V S

S S S

F

V

Other Monitor

(O3 etc)

C

C C C

NC

NC NC NC

NO

NO NO NO

External Moly

Sampling Cane Converter

Manifold Fan

Charcoal

Scrubber

4-ft

Notes:

S - Teflon 3-way Solenoid

P - Pump

F - Manifold Fan/Blower

V - Vent - Particulate Filter

Sample tubing lengths < 3-ft

Cal Standard

(triblend)

Temp/

Pressure/RH

Calibration Manifold

Ambient Sampling Manifold

UPS Power

Supply

Zero Air

Source

Cal

NOy

NO

Sample In

EnviDAS Data 

Acquisition System

Analog Inputs -

To Analyzers/

Sensors

Control Outputs

- To Environics

Cal Sys

Control Out- To Solenoids

Modem

Desktop System
QA Handbook Volume II, Appendix F 

Revision No: 1 

Date: 12/08 

Page 13 of 13 

generally, the MFC is controlled by the DAS. When the calibration sequences have 

finished, the DAS stops the direct current from being sent to the solenoid and switches 

automatically back to the NO to COM (inactive) port configuration. This allows the air 

to flow through the NO to COM port and the instrument is now back on ambient mode. 

Air Flow to the Analyzers

N O

N C

N O N O

N C N C

COM

Calibration 

Gas from the Mass 

Flow Calibrator Exhaust

Air Flow Air Flow

Air Flow 

to 

Exhaust 

Fan

Air Flow Air Flow Air Flow

Figure 7. Ambient – Calibration Manifold Interface 

Reference 

1. Code of Federal Regulations, Title 40, Part 58, Appendix E.9 
QA Handbook Vol II, Appendix G 

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Appendix G 

Example Procedure for Calibrating a Data Acquisition System 
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DAS Calibration Technique

The following is an example of a DAS calibration. The DAS owner’s manual should be 

followed. The calibration of a DAS is performed by inputting known voltages into the DAS and 

measuring the output of the DAS. 

1. The calibration begins by obtaining a voltage source and an ohm/voltmeter. 

2. Place a wire lead across the input of the DAS multiplexer. With this "shorted" out, the 

DAS should read zero. 

3. If the output does not read zero, adjust the output according to the owners manual. 

4. After the background zero has been determined, it is time to adjust the full scale of the 

system. Most DAS system work on a 1, 5 or 10 volt range, i.e., the full scale equals an 

output of voltage. In the case of a 0 - 1000 ppb range instrument, 1.00 volts equals 1000 

ppb. Accordingly, 500 ppb equals 0.5 volts (500 milivolts). To get the DAS to be linear 

throughout the range of the instrument being measured, the DAS must be tested for 

linearity. 

5. Attach the voltage source to a voltmeter. Adjust the voltage source to 1.000 volts (this is 

critical that the output be 1.000 volts). Attach the output of the voltage source the DAS 

multiplexer. The DAS should read 1000 ppb. Adjust the DAS voltage A/D card 

accordingly. Adjust the output of the voltage source to 0.250 volts. The DAS output 

should read 250 ppb. Adjust the A/D card in the DAS accordingly. Once you have 

adjusted in the lower range of the DAS, check the full scale point. With the voltage 

source at 1.000 volts, the output should be 1000 ppb. If it isn't, then adjust the DAS to 

allow the high and low points to be as close to the source voltage as possible. In some 

cases, the linearity of the DAS may be in question. If this occurs, the data collected may 

need to be adjusted using a linear regression equation. See Section 2.0.9 for details on 

data adjustment. The critical range for many instruments is in the lower 10 % of the 

scale. It is critical that this be linear. 

6. Every channel on a DAS should be calibrated. In some newer DAS systems, there is only 

one A/D card voltage adjustment which is carried throughout the multiplexer. This 

usually will adjust all channels. It is recommended that DAS be calibrated once per year. 
QA Handbook Volume II, Appendix H 

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Appendix H 

United States Environmental Protection Agency 

National Ambient Air Monitoring Technical System Audit Form 
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QA Handbook Volume II, Appendix H 

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Table of Contents 

1) General / Quality Management 

a) Program Organization 

b) Facilities 

c) Independent Quality Assurance and Quality Control 

d) Planning Documents (including QMP, QAPPs, & SOPs) 

e) General Documentation Policies 

f) Training 

g) Corrective Action 

h) Quality Improvement 

i) External Performance Audits 

2) Network Management / Field Operations 

a) Network Design 

b) Changes to the Network since the last audit 

c) Proposed changes to the Network 

d) Field Support 

i) SOPs 

ii) Instrument Acceptance 

iii) Calibration 

iv) Repair 

v) Site and Monitor Information Form 

3) Laboratory Operations 

a) Routine Operations 

b) Quality Control 

c) Laboratory Preventive Maintenance 

d) Laboratory Record Keeping 

e) Laboratory Data Acquisition and Handling 

f) Specific Pollutants: PM10,PM 2.5 and Lead 

 4) Data and Data Management 

a.) Data Handling 

b.) Software Documentation 

c.) Data Validation and Correction 

d.) Data Processing 

e.) Internal Reporting 

f.) External Reporting 
QA Handbook Volume II, Appendix H 

Revision No: 1 

Date: 12/08 

Page 4 of 46 

1) General / Quality Management 

 State/ Local / Tribal Agency Audited: 

 Address: 

 City, State, and Zip Code: 

 Date of Technical System Audit: 

 Auditor / Agency: 

a) Program Organization 

1) Key Individuals 

1.1) Agency Director: 

1.2) Ambient Air Monitoring (AAM) Network Manager: 

1.3) Quality Assurance Manager: 

1.4) QA Auditors: 

1.5) Field Operations Supervisor / Lead: 

1.6) Laboratory Supervisor: 

1.7) QA Laboratory Manager: 

1.8) Data Management Supervisor / Lead: 

Attach an Organizational Chart : 
QA Handbook Volume II, Appendix H 

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Page 5 of 46 

Flow Chart: 

Key position staffing. Number of personnel available to each of the following program areas: 

Program Area 

Number of 

People 

Primary 

Number of 

People 

Backup 

Vacancies Program Area 

Number 

of People 

Primary 

Number 

of People 

Backup 

Vacancies 

Network 

Design and 

Siting 

 Data and Data 

Management 

 

QC activities 

 Equipment 

repair and 

maintenance 

 

QA activities 

 Financial 

Management 

 

List available personnel by name and percentage of time spent on each task category

Name Network 

Design 

and siting 

QC 

activities 

QA 

activities 

Equipment repair 

 and maintenance 

Data and 

Data Management 

Financial 

Management 

 

Comment on the need for additional personnel, if applicable 

List personnel who have authority or are responsible for: 

Activity Name Title 

QA Training Field/Lab 

Grant Management 

Purchases greater than $500 

Equipment and Service Contract 

Management 

 Staff appointment 
QA Handbook Volume II, Appendix H 

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Page 6 of 46 

6 

b) Facilities

 Identify the principal facilities where the agency conducts work that is related to air monitoring. Do not include 

monitoring stations but do include facilities where work is performed by contractors or other organizations. 

Facility AAM Function Offices responsible for 

ensuring adequacy 

Location Adequate Y/N 

To be completed by auditor 

Instrument repair 

Certification of Standards e.g. 

gases, flow transfers, MFC 

 

PM filter weighing 

 

Data verification and processing 

 

General office space 

 

Storage space, short and long 

term 

 

Air Toxics (Carbonyls, VOC s, 

Metals): 

 

Indicate any facilities that should be upgraded. Identify by function and any suggested improvements or 

recommendations 

Are facilities adequate concerning safety? Yes / No Please explain if answer is no any suggested 

improvements or recommendations 

Are there any significant changes which are likely to be implemented to agency facilities within the next one to two 

years? Comment on agency’s needs for additional physical space (laboratory, office, storage, etc.).

Facility Function Proposed Change - Date 

 
QA Handbook Volume II, Appendix H 

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Page 7 of 46 

7 

c) Independent Quality Assurance and Quality Control 

1. Status of Quality Assurance Program

Question Yes No Comment

Does the agency perform QA activities with 

internal personnel? If no go to Section d.

 

Does the agency maintain a separate 

laboratory to support quality assurance 

activities? 

 

Has the agency documented and 

implemented specific audit procedures 

separate from monitoring procedures? 

 

Are there two levels of management 

separation between QA and QC operations? 

Please explain: 

 

Does the agency have identifiable auditing 

equipment and standards (specifically 

intended for sole use) for audits? 

 

 

 2. Internal Performance Audits 

Question Yes No Comment 

Does the agency have separate facilities to 

support audits and calibrations? 

 

If the agency has in place contracts or similar agreements either with another agency or contractor to perform 

audits or calibrations, please name the organization and briefly describe the type of agreement. 

If the agency does not have a performance audit SOP (included as an attachment), please describe performance 

audit procedure for each type of pollutant. 

Does the agency maintain independence of audit 

standards and personnel? 

 

Please provide information on certification of audit standards currently being used. Include information on 

vendor and internal or external certification of standards. 

Does the agency have a certified source of zero 

air for performance audits? 

 

Does the agency have procedures for auditing 

and/or validating performance of 

Meteorological monitoring? 

 

Please provide a list of the agency’s audit equipment and age of audit equipment. 
QA Handbook Volume II, Appendix H 

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Page 8 of 46 

8 

Is audit equipment ever used to support routine 

calibration and QC checks required for 

monitoring network operations? 

 

If yes, please describe.

Are standard operating procedures (SOPs) for 

air monitoring available to all field personnel?

 

 Has the agency established and has it 

documented criteria to define agency-acceptable 

audit results?

 

 

Please complete the table below with the pollutant, monitor and acceptance criteria. 

Pollutant How is performance tracked (e.g., control 

charts) Audit Result Acceptance 

Criteria 

CO 

O3

NO2

SO2

PM10

PM2.5

Pb 

VOCs 

Carbonlys 

PM2.5 speciation

PM10-2.5 speciation

PM10-2.5 FRM Mass 

Continuous PM2.5

Trace Levels (CO) 

Trace Levels (SO2) 

Trace Levels (NO) 

Trace Levels (NOy) 

Surface 

Meteorology 

Others 

 

 
QA Handbook Volume II, Appendix H 

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9 

Question Yes No Comment

Were these audit criteria based on, or derived from, the 

guidance found in Volume II of the QA Handbook for 

Air Pollution Measurement System, Section 2.0.12? 

If no, please explain. 

If yes, please explain any changes or 

assumptions made in the derivation. 

 What corrective action may be taken if criteria are exceeded? If possible, indicate two examples of corrective 

actions, taken within the period since the previous systems audit which are based directly on the criteria discussed 

above. 

 

Corrective Action # 1 

Corrective Action #2 
QA Handbook Volume II, Appendix H 

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10 

d) Planning Documents including QMP, QAPP, &SOP

QMP questions Yes No 

 Does the agency have an EPA-approved 

quality management plan? 

 

 If yes, have changes to the plan been 

approved by the EPA? 

 

Has the QMP been approved by EPA 

within the last five years? 

 

 Please provide: Date of Original Approval Date of Last Revision: Date of Latest Approval: 

QAPP questions Yes No Comment

Does the agency have an EPA-approved 

quality assurance project plan? 

If yes, have changes to the plan been 

approved by the EPA? 

 

Has the QAPP been reviewed by EPA 

annually? 

Please provide: Date of Original Approval Date of Last Revision Date of Latest 

Approval 

Does the agency have any revisions to your 

QA project plan still pending? 

How does the agency verify the QA project 

plan is fully implemented? 

How are the updates distributed? 

What personnel regularly receive updates? 

SOP questions 

 

Has the agency prepared and implemented 

standard operating procedures (SOPs) for 

all facets of agency operation? 

 

Do the SOPs adequately address 

ANSI/ASQC E-4 quality system required 

by 40 CFR 58, Appendix A? 

 

Are copies of the SOP or pertinent sections 

available to agency personnel? 

 

How does the agency verify that the SOPs 

are implemented as provided? 

How are the updates distributed? 
QA Handbook Volume II, Appendix H 

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Page 11 of 46 

11 

e) General Documentation Policies 

Question Yes No Comment

Does the agency have a documented records management 

plan? 

Does the agency have a list of files considered official records 

and their media type I.E. paper, electronic? 

Does the agency have a schedule for retention and disposition 

of records? 

Are records for at least three years? 

 Who is responsible for the storage and retrieval of records? 

What security measures are utilized to protect records? 

Where/when does the agency rely on electronic files as 

primary records? 

What is the system for the storage, retrieval and backup of 

these files? 
QA Handbook Volume II, Appendix H 

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12 

f) Training 

Question Yes No Comment

 Does the agency have a training program and training plan? 

 

 Where is it documented? 

Does it make use of seminars, courses, EPA sponsored 

college level courses? 

 

Are personnel cross-trained for other ambient air monitoring 

duties? 

 

Are training funds specifically designated in the annual 

budget? 

 

Does the training plan include: Yes No Comment

Training requirements by position 

Frequency of training 

Training for contract personnel 

A list of core QA related courses 

Indicate below the three most recent training events and identify the personnel participating in them. 

Event Dates Participant(s) 
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13 

g) Corrective Action 

Question Yes No Comment

Does the agency have a comprehensive corrective 

action program in place and operational? 

Have the procedures been documented? 

As a part of the QA project plan? 

As a separate standard operating procedure? 

 

Does the agency have established and documented 

corrective limits for QA and QC activities? 

 

Are procedures implemented for corrective actions 

based on results of the following which fall outside 

the established limits: 

 

 Performance evaluations 

 

 Precision goals 

 

 Bias goals 

 

 NPAP audits 

 

 PEP audits 

 

 

Oversight of Contractors and Suppliers 

Question Contractors Yes No Comment

Who is responsible for oversight of contract personnel?

What steps are taken to ensure contract personnel meet 

training and experience criteria? 

How often are contracts reviewed and /or renewed? 

Question Suppliers

 

Have criteria and specification been established for 

consumable supplies and for equipment? 

 

What supplies and equipment have established 

specifications? 

Is equipment from suppliers open for bid? 

 
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14 

Question Yes No Comment

 Validation of one point QC check goals 

 Completeness goals 

 

 Data audits 

 

 Calibrations and zero span checks 

 Technical Systems Audit 

 

Have the procedures been documented? 

 

How is responsibility for implementing corrective actions assigned? Briefly discuss. 

How does the agency follow up on implemented corrective actions? 

Briefly describe recent examples of the ways in which the above corrective action system was employed to remove 

problems. 
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15 

h) Quality Improvement 

Question Yes No Comment

What actions were taken to improve the quality system 

since the last TSA? 

Since the last TSA do your control charts indicate that the 

overall data quality for each pollutant steady or 

improving? 

 

For areas where data quality appears to be declining has a 

cause been determined? 

 

Have all deficiencies indicted on the previous TSA been 

corrected? 

 If not explain. 

Are there pending plans for quality improvement such as 

purchase of new or improved equipment, standards, or 

instruments? 

 
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16 

i) External Performance Audits 

Question Yes No Comment 

Does your agency participate in NPAP, PM2.5 PEP, and 

Other performance audits performed by an external party 

and/or using external standards. 

 

If the agency does not participate, please explain why not: 

Are NPAP audits performed by QA staff, site operators, 

calibration staff, and/or another group? 

 

 National Performance Audit Program (NPAP) and Additional Audits 

Does the agency participate in the National Performance Audit Program (NPAP) as required 

under 40 CFR 58, Appendix A? If so, identify the individual with primary responsibility for the 

required participation in the National Performance Audit Program. 

 Name: Program function: 

 

Please complete the table below:

 Parameter Audited Date of Last NPAP Audit 

CO 

O3

SO2

NO2

PM10

PM2.5

Pb 

VOCs 

Carbonlys 
QA Handbook Volume II, Appendix H 

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17 

2) Network Management/Field Operations 

State/Local/Tribal Agency Audited: 

 Address: 

 City, State, and Zip Code: 

 Auditor / Agency: 

Key Individuals 

Ambient Air Monitoring Network Manager: 

Quality Assurance Manager: 

Field Operations Supervisor/Lead: 

Field Operations Staff involved in the TSA: 
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18 

*NCore - National Core monitoring stations; SLAMS - state and local air monitoring stations; SPM - special 

purpose monitors; PAMS - photochemical assessment monitoring stations 

Indicate by Site ID # any non-conformance with the requirements of 40 CFR 58, Appendices D and E, along with any waivers granted 

by the Regional Office (provide waiver documentation)

Monitor Site ID Reason for Non-Conformance

SO2

O3

CO

NO2

PM10

PM2.5

Pb

a) Network Design 

Complete the table below for each of the pollutants monitored as part of your air monitoring network. (Record applicable count by 

category.) Also indicate seasonal monitoring with an S for a Parameter/Category as appropriate. Provide the most recent annual 

monitoring network plan, including date of approval and AQS quicklook or if not available, network description and other similar 

summary of site data, including SLAMS, Other and Toxics 

Category* SO2 NO2 CO O3 PM10 PM2.5 Pb Other 

(type) 

Other 

(type) 

NCore 

SLAMS 

SPM 

PAMS 

Total 

Question Yes No Comment

What is the date of the most current Monitoring Network Plan?

 I. Is it available for public inspection

II. Does it include the information required for each site?

AQS Site ID #

Street address and geographic coordinates 

Sampling and Analysis Method(s)

Operating Schedule

Monitoring Objective and Scale of Representativeness

Site suitable/not suitable for comparison to annual PM2.5 

NAAQS? 

MSA, CBSA or CSA indicated as required? 
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19 

b) Changes to the Network since the last audit 

 What is the date of the most recent network assessment? (Provide copy) Are all SLAMS parameters included? Any 

 Others?

 Please provide information on any site changes since the last audit 

Pollutant Site ID Site Address Site 

Added/Deleted/

Relocated

Reason (Assessment, lost lease, etc. 

Provide documentation of reason 

for each site change.) 

Question Yes No Comment

Are hard copy site information files retained by the agency for all 

air monitoring stations within the network?

Does each station have the required information including:

AQS Site ID Number?

Photographs/slides to the four cardinal compass points?

Startup and shutdown dates?

Documentation of instrumentation?

Who has custody of the current network documents Name: 

Title:

Does the current level of monitoring effort, station placement, 

instrumentation, etc., meet requirements imposed by current grant 

conditions?

How often is the network siting reviewed? Frequency: 

Date of last review:

 Are there any issues 

Do any sites vary from the required frequency in 40 CFR 58.12? 

 Does the number of collocated monitoring stations meet the 

requirements of 40 CFR 58 Appendix A? 
QA Handbook Volume II, Appendix H 

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20 

d) Field Support

Question Yes No Comment

On average, how often are most of your stations visited by a field 

operator? 

 ______ per _______ 

 Is this visit frequency consistent for all reporting organizations within 

your agency? 

On average, how many stations does a single operator have responsibility 

for? 

How many of the stations of your SLAMS/NCORE network are equipped 

with sampling manifolds? 

Do the sample inlets and manifolds meet the requirements for through the 

probe audits? 

I. Briefly describe most common manifold type 

II. Are Manifolds cleaned periodically How often? 

III. If the manifold is cleaned, what is used to perform cleaning 

IV. Are manifold(s) equipped with a blower 

V. Is there sufficient air flow through the manifold at all times? Approximate air flow: 

VI. How is the air flow through the manifold monitored? 

VII. Is there a conditioning period for the manifold after cleaning? Length of time: 

VIII. What is the residence time? 

 Sampling lines: 1) What material is used for instrument sampling lines? 

 2) How often are lines changed? 

Do you utilize uninterruptable power supplies or backup power sources at 

your sites? 

 

What instruments or devices are protected? 

c) Proposed changes to the Network 

 Are future network changes proposed?

 Please provide information on proposed site changes, including documentation of the need for the change and any required 

approvals 

Pollutant Site ID Site Address Site to be 

Added/Deleted/

Relocated

Reason (Assessment, lost lease, etc. 

Provide documentation of reason 

for each site change.) 
QA Handbook Volume II, Appendix H 

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21 

i). SOPs

Please complete the following table: 

Pollutant Monitored Date of Last SOP Review Date of Last SOP Revision 

SO2

 

NO2

 

CO 

 

O3 

 

PM10

 

PM2.5 FRM mass 

 

Pb 

 

PM2.5 speciation 

 

PM10-2.5 FRM mass 

PM10-2.5speciation 

Continuous PM2.5 mass 

Trace levels (CO) 

Trace levels (SO2) 

Trace levels (NO) 

Trace levels (NOy) 

Total reactive nitrogen 

 

Surface Meteorology 

Wind speed and direction, temperature, RH, 

precipitation and solar radiation 

 

Others 

Question Yes No Comment

 Is the documentation of monitoring SOPs complete? 

 Are any new monitoring SOPs needed? 

 

 Are such procedures available to all field operations personnel? 

 Are SOPs that detail operations during episode monitoring 

prepared and available to field personnel? 

 

 Are SOPs based on the framework contained in Guidance for 

Preparing Standard Operating Procedures EPA QA/G-6? 
QA Handbook Volume II, Appendix H 

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22 

ii). Instrument Acceptance

Has your agency obtained necessary waiver provisions to operate equipment which does not meet the effective 

reference and equivalency requirements? List all waivers. 

Please list instruments in your inventory 

Pollutant Number Make and Models Reference or Equivalent number 

SO2

 

NO2

 

CO 

 

O3 

PM10

 

PM2.5

 

Pb 

 

Multi gas calibrator 

 

PM2.5 speciation 

 

PM10-2.5 speciation 

 

PM10-2.5 FRM mass 

 

Continuous PM2.5 mass 

 

Trace levels (CO) 

 

Trace levels (SO2) 

 

Trace levels (NO) 

 

Trace levels (NOy) 

 

Surface Meteorology 

 

Others 

 

Please comment briefly and prioritize your currently identified instrument needs. 

Question Yes No Comment

Are criteria established for field QC equipment? 

Are criteria established for field QC gas standards? 

 
QA Handbook Volume II, Appendix H 

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23 

iii) Calibration 

 Please indicate the frequency of multi point calibrations. 

Pollutant Frequency Name of Calibration Method 

Question Yes No Comment

 Are field calibration procedures included in the document? SOPs? Location (site, lab etc.): 

Are calibrations performed in keeping with the guidance in 

 section Vol II of the QA Handbook for Air Pollution 

 Measurement Systems? 

If no, why not? 

Are calibration procedures consistent with the operational 

requirements of Appendices to 40 CFR 50 or to analyzer 

operation/instruction manuals? 

If no, why not? 

 Have changes been made to calibration methods based on 

manufacturer’s suggestions for a particular instrument? 

Do standard materials used for calibrations meet the requirements 

of appendices to 40 CFR 50 (EPA reference methods) and 

Appendix A to 40 CFR 58 (traceability of materials to NISTSRMs or CRMs)? 

Comment on deviations 

 Are all flow-measurement devices checked and certified? 

Additional comments: 

 Please list the authoritative standards used for each type of flow measurement, indicate the certification frequency of standards 

to maintain field material/device credibility. 

Flow Device Primary Standard Frequency of Certification 

HiVol orifice 

Streamline 

TriCal 

BIOS 

 

DeltaCal 

 

Gilibrators

 

Where do field operations personnel obtain gaseous standards? 

Are those standards certified by: 
QA Handbook Volume II, Appendix H 

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24 

Question Yes No Comment

The agency laboratory? 

EPA/NERL standards laboratory? 

A laboratory separate from this agency’s but part of the 

same reporting organization? 

The vendor? 

Other (describe). 

How are the gas standards verified after receipt? 

How are flow measurement devices certified? 

 Please provide copies of certifications of all standards currently in 

use from your master and/or satellite standard certification 

logbooks (i.e., chemical standards, ozone standards, flow 

standards, and zero air standards) . 

 What equipment is used to perform calibrations (e.g., dilution 

devices) and how is the performance of this equipment verified? 

Does the documentation include expiration date of certification? 

Reference to primary standard used? 

What traceability is used? 

Please attach an example of recent documentation of 

 traceability 

 Is calibration equipment maintained at each station? 

 

How is the functional integrity of this equipment documented? 

Who has responsibility for maintaining field calibration standards? 

Please list the authoritative standards and frequency of each type of dilution, permeation and ozone calibrator and indicate the 

certification frequency... 

Calibrator Primary Standard Frequency of 

CalibrationCertification 

Permeation calibrator flow controller 

Permeation calibrator temperature 

Dilution calibrator air and gas flow controllers 

Field/working standard photometer 

 

Ozone generator 
QA Handbook Volume II, Appendix H 

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Date: 12/08 

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25 

o) Please identify station standards for gaseous pollutants at representative air monitoring stations (attach additional sheets as 

appropriate): 

Parameter Station(s) Identification of Standard(s) Recertification Date(s) 

CO 

NO2

SO2

O3

iv) Repair

a) Who is responsible for performing preventive maintenance? 

b) Is special training provided them for performing preventive maintenance? Briefly comment on background or courses. 

c) Is this training routinely reinforced? Yes No 

 If no, why not? 

d) What is your preventive maintenance schedule for each type of field instrumentation? 

e) If preventive maintenance is MINOR, it is performed at (check one or more): field station , headquarters facilities , 

equipment is sent to manufacturer 

f) If preventive maintenance is MAJOR, it is performed at (check one or more): field station , headquarters facilities , 

equipment is sent to manufacturer 

g) Does the agency have service contracts or agreements in place with instrument manufacturers? Indicate below or attach 

additional pages to show which instrumentation is covered? 

h) Comment briefly on the adequacy and availability of the supply of spare parts, tools and manuals available to the field operator 

to perform any necessary maintenance activities. Do you feel that this is adequate to prevent any significant data loss? 

i) Is the agency currently experiencing any recurring problem with equipment or manufacturer(s)? If so, please identify the 

equipment or manufacturer, and comment on steps taken to remedy the problem. 

j) Have you lost any data due to repairs in the last 2 years? 

 More than 24 hours? 

 More than 48 hours? 

 More than a week? 

k) Explain any situations where instrument down time was due to lack of preventive maintenance of unavailability of parts. 
QA Handbook Volume II, Appendix H 

Revision No: 1 

Date: 12/08 

Page 26 of 46 

26 

RECORD KEEPING 

Question Yes No Comment

What type of station logbooks are maintained at each 

monitoring station? (maintenance logs, calibration logs, 

personal logs, etc.) 

What information is included in the station logbooks? 

Who reviews and verifies the logbooks for adequacy of station 

performance? 

 How is control of logbook maintained? 

Where is the completed logbook archived? 

What other records are used? 

 Zero span record? 

 Gas usage log? 

 Maintenance log? 

 Log of precision checks? 

 Control charts? 

 A record of audits? 

Please describe the use and storage of these documents. 

Are calibration records or at least calibration constants available 

to field operators? 

 

Please attach an example field calibration record sheet to this questionnaire. 
QA Handbook Volume II, Appendix H 

Revision No: 1 

Date: 12/08 

Page 27 of 46 

27 

V) Site/Monitor Information Form 

PQAO_______________________________________________________ 

AQS Site Name _______________________________________________ 

AQS Site Number______________________________________________ 

Agency Site Name/No.__________________________________________ 

(if different than AQS Site Name/Number) 

Site Address __________________________________________________ 

City & County ________________________________________________ 

Site Coordinates _______________________________________________ 

(specify lat/long or UTM) 

Site Elevation (m)______________________________________________ 

Criteria Pollutants Monitored _____________________________________ 

____________________________________________________________ 

Other Parameters ______________________________________________ 

Nearst Meterological Site ________________________________________ 

(‘on site’ is met tower present at this site) 

Photographs to and from each cardinal direction attached? ______________ 

(Yes or No) 

Name(s) of Report Preparer(s) ____________________________________ 

Name(s) of Auditors ____________________________________________ 

Date ________________________________________________________ 

Phone Number ________________________________________________ 
QA Handbook Volume II, Appendix H 

Revision No: 1 

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Page 28 of 46 

28 

Site Map

Draw map of site and surrounding terrain and features, up to 100 meters. 

Map notes
QA Handbook Volume II, Appendix H 

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29 

Monitor Information

 Pollutants 

 

Manufacturer Model 

Serial number 

Scale of representation 

MICro, MIDdle, Neighborhood, Urban 

Objective (Population, Max concentration, 

Background, Transport) 

Height of probe above ground(m) Distance from obstruction (m) 

Type of obstruction (Wall, Tree, etc) 

Distance from roadway (m) 

Unrestricted airflow (Yes, No) 

Designation (NCore, SLAMS,etc) 

Siting Criteria Met (Yes, No) 

 

Manufacturer Model 

Serial number 

Scale of representation 

MICro, MIDdle, Neighborhood, Urban 

Averaging time 1-, 8-, 24-hour Objective (Population, Max concentration, 

Background, Transport) 

Height of probe above ground(m) Distance from obstruction (m) 

Type of obstruction (Wall, Tree, etc) 

Distance from roadway (m) 

Unrestricted airflow (Yes, No) 

Designation (NCore, SLAMS,etc) 

Siting Criteria Met (Yes, No) 

Insert additional copies of table as needed
QA Handbook Volume II, Appendix H 

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30 

Area Information

Street Name 

Traffic Count 

(Vehicles/day) 

 

Direction Predominant Land Use (Industry, Residential, Commercial 

or Agriculture) 

North 

East 

South 

West 

Direction Obstructions Height (m) Distance (m) 

North 

East 

South 

West 

Note: This table is for large obstructions that affect the entire site, such as large clusters of trees 

or entire buildings. Individual obstructions, such as walls, single trees, other monitors, etc, 

should be entered in the Monitor Information table. 

Direction Topographic Features 

(hills, valleys, rivers, etc.)

General Terrain 

(flat, rolling, rough) 

North 

East 

South 

West 

Comments
QA Handbook Volume II, Appendix H 

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Date: 12/08 

Page 31 of 46 

31 

3) LABORATORY OPERATIONS 

State/Local/Tribal Agency Audited: 

City, State, and Zip Code: 

Date of Technical System Audit: 

Auditor / Agency: 

Key Individuals 

Laboratory Manager: 

Laboratory Supervisor: 

Quality Assurance Manager: 

Laboratory Staff involved in the TSA: 
QA Handbook Volume II, Appendix H 

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32 

a) Routine Operations

What analytical methods are employed in support of your air monitoring network? 

 Analysis Name or Description of Method

 PM10

 PM2.5

 Pb 

 

 Others (list by pollutant) 

Please describe areas where there have been difficulties meeting the regulatory requirements for 

any of the above analytical methods. 

In the table below, please identify the current versions of written methods, supplements, and 

guidelines that are used in your agency. 

Analysis Documentation of Method

PM10

PM2.5

Pb 

Others (list by 

pollutant) 

 

Question Yes No Comment

Were procedures for the methods listed above included in 

the agency=s QA Project Plan or SOP=s and were reviewed 

by EPA? Also, are SOP’s easily/readily accessible for use 

and reference? 

Does you lab have sufficient instrumentation to conduct 

analyses? 

d) Please describe needs for laboratory instrumentation. 
QA Handbook Volume II, Appendix H 

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33 

b) Laboratory Quality Control

Please identify laboratory standards used in support of the air monitoring program, including standards which may 

be kept in an analytical laboratory and standards which may be kept in a field support area or quality assurance 

laboratory that is dedicated to the air monitoring program (attach additional sheets if appropriate): 

Parameter Location of 

Standards 

Laboratory 

Standard 

Recertification 

Date 

Primary Standard* 

CO 

NO2

SO2

O3

Weights 

Temperature 

Moisture 

Barometric Pressure 

Flow 

Other Flow Standard 

Lead 

Other 

*Standards to which the laboratory standards can be traced. 

Question Yes No Comment

Are all chemicals and solutions clearly marked with an 

indication of shelf life? 

Are chemicals removed and properly disposed of when shelf 

life expires? 

Are only ACS grade chemicals used by the laboratory? 

e) Comment on the traceability of chemicals used in the preparation of calibration standards 
QA Handbook Volume II, Appendix H 

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34 

Question Yes No Comment

Does the laboratory purchase standard solutions such 

as those for use with lead or other metals analysis? 

Are all calibration procedures documented? 

 If answer “yes” to (f), please describe the following: 

(1) Title of the document: 

(2) Revision number: 

(3) Where the document is: 

Are at least one duplicate, one blank, and one 

standard or spike included with a given analytical 

batch? 

Briefly describe the laboratory=s use of data derived from blank analyses. 

Are criteria established to determine whether a 

blank data are acceptable?

 

How frequently and at what concentration ranges does the lab perform duplicate analysis? What constitutes an acceptable agreement? Please comment in the space below. 

Please describe how the lab use data obtained from spiked samples, including the acceptance criteria (e.g., 

acceptable percent recovery). 

Question Yes No Comment

Does the laboratory routinely include samples of 

reference material within an analytical batch? 

If yes, indicate frequency, level, and material used. 

Are mid-range standards included in analytical 

batches? 

Please describe the frequency, level and compound used in the space provided below. 
QA Handbook Volume II, Appendix H 

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35 

Question Yes No Comment

Are criteria for real time quality control 

established that are based on the results obtained 

for the mid-range standards discussed above? 

If yes, briefly discuss them below or indicate the document in which they can be found. 

Are appropriate acceptance criteria for each type 

of analysis documented ?

c) Laboratory Preventive Maintenance

Question Yes No Comment

For laboratory equipment, who has the responsibility for performing preventive maintenance? 

Is most maintenance performed in the lab? 

Is a maintenance log maintained for each major laboratory 

instrument? 

Are service contracts in place for major analytical 

instruments? 
QA Handbook Volume II, Appendix H 

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Date: 12/08 

Page 36 of 46 

36 

d) Laboratory Record Keeping 

Question Yes No Comment

Are all samples that are received by the laboratory 

logged in? 

Discuss sample routing and special needs for analysis (or attach a copy of the latest SOP which covers this). Attach a flow chart 

if possible. 

Are log books kept for all analytical laboratory 

instruments? 

Are there log books or other records that indicate 

the checks made on materials and instruments such 

as weights, humidity indicators, balances, and 

thermometers? 

Identify type of record, acceptable/non-acceptable 

Are log books maintained to track the preparation 

of filters for the field? 

 

Are they current? 

Do they indicate proper use of conditioning? 

Weighings? 

Stamping and numbering? 

Are log books kept which track filters returning 

from the field for analysis? 

How are data records from the laboratory archived? 

 Where? 

 Who has the responsibility? Person 

 Title 

 How long are records kept? Years 

Does a chain-of-custody procedure exist for 

laboratory samples? 

. 

If yes, indicate date, title and revision number where it can be found 
QA Handbook Volume II, Appendix H 

Revision No: 1 

Date: 12/08 

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37 

e) Laboratory Data Acquisition and Handling

Question Yes No Comment

Identify those laboratory instruments which make use of computer interfaces directly to record data. Which ones use strip charts? 

Integrators? 

Are QC data readily available to the analyst during 

a given analytical run? 

What is the laboratory=s capability with regard to data recovery? In case of problems, can they recapture data or are they 

dependent on computer operations? Discuss briefly. 

Has a user=s manual been prepared for the 

automated data acquisition instrumentation? 

Please provide below a data flow diagram which establishes, by a short summary flow chart: transcriptions, validations, and 

reporting format changes the data goes through before being released by the laboratory. 
QA Handbook Volume II, Appendix H 

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38 

f) Specific Pollutants: PM10, PM2.5 and Lead

Question Yes No Comment

PM10 and PM2.5

Does the agency use filters supplied by EPA? 

Do filters meet the specifications in 40 CFR 50? 

Are filters visually inspected via strong light from a 

view box for pinholes and other imperfections? 

Where does the laboratory keep records of the serial numbers of filters? 

Are unexposed filters equilibrated in controlled 

conditioning environment which meets or exceeds 

the requirements of 40 CFR 50? 

Are the temperature and relative humidity of the 

conditioning environment monitored? 

Are the temperature and humidity monitors 

calibrated? 

Are balances checked with Class S or Class M 

weights each day when they are used? 

Is the balance check information placed in QC log 

book? 

To what sensitivity are filter weights recorded? 

Are filter serial numbers and tare weights recorded 

in a bound notebook? 

Are filters packaged for protection while 

transporting to and from the monitoring stations? 

How often are filter samples collected? (Indicate the average elapsed time in hours between end of sampling and laboratory 

receipt.) 

In what medium are field measurements recorded (e.g., in a log book, on a filter folder, or on standard forms)? 

Are exposed filters reconditioned for at least 24 hrs 

in the same conditioning environment as for 

unexposed filters? 

Briefly describe how exposed filters are prepared for conditioning. 

Briefly describe how exposed filters are stored after being weighed. 

 
QA Handbook Volume II, Appendix H 

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39 

Question Yes No Comment

Are blank filters reweighed? 

Are chemical analyses performed on filters? 

LEAD

Is analysis for lead being conducted using atomic 

absorption spectrometry with air acetylene flame? 

If not, has the agency received an equivalency 

designation of their procedure? 

Is either the hot acid or ultrasonic extraction 

procedure being followed precisely? 

Which? 

Is Class A borosilicate glassware used throughout 

the analysis? 

Is all glassware cleaned with detergent, soaked and 

rinsed three times with distilled or deionized water? 

If extracted samples are stored, are linear 

polyethylene bottles used? 

Are all batches of glass fiber filters tested for 

background lead content? 

At a rate of 20 to 30 random filters per batch of 

500 or greater? Indicate rate. 

Are ACS reagent grade HNO3 and HCl used in the 

analysis? 

Is a calibration curve available having 

concentrations that cover the linear absorption 

range of the atomic absorption instrumentation? 

 Is the stability of the calibration curve checked by 

alternately remeasuring every 10th sample a 

concentration # 1Fg Pb/ml; # 10 Fg Pb/ml? 

 
QA Handbook Volume II, Appendix H 

Revision No: 1 

Date: 12/08 

Page 40 of 46 

40 

4) DATA AND DATA MANAGEMENT

State/Local/Tribal Agency Audited: 

City, State, and Zip Code: 

Date of Technical System Audit: 

Auditor / Agency: 

Key Individuals 

Data Manager: 

Data Supervisor: 

Quality Assurance Manager: 
QA Handbook Volume II, Appendix H 

Revision No: 1 

Date: 12/08 

Page 41 of 46 

41 

a) Data Handling

Question Yes No Comment

Is there a procedure, description, or a chart which shows a 

complete data sequence from point of acquisition to point of 

submission of data to EPA? 

Please provide below a data flow diagram indicating both the data flow within the reporting organization. 

Are procedures for data handling (e.g., data reduction, review, 

etc.) documented? 

In what media (e.g., diskette, data cartridge, or telemetry) and formats do data arrive at the data processing location? Please list 

below. 

Category of Data (by Pollutant) Data Media and Formats 

How often are data received at the processing location from the field sites and laboratory? 

Is there documentation accompanying the data regarding any 

media changes, transcriptions, or flags which have been placed 

into the data before data are released to agency internal data 

processing? 

. 

 

Describe the type of documentation 

How data are actually entered to the computer system (e.g., computerized transcription (copy from disk or data transfer device), 

manual entry, digitization of strip charts, or other)? 

For manual data, is a double-key entry system used? 
QA Handbook Volume II, Appendix H 

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Date: 12/08 

Page 42 of 46 

42 

b) Software Documentation

Question Yes No Comment

Does your agency use any AQS Manual? 

Does your agency use any Air Now Manual? 

If yes, list the title of manual used including the , version number and date published 

Does the agency have information on the reporting of precision and 

accuracy data available? 

What are the origins of the software used to prepare air monitoring data for release into the AQS and AirNow database? Please 

list the documentation for the software currently in use for data processing, including the names of the software packages, 

vendor or author, revision numbers, and the revision dates of the software.

What is the recovery capability in the event of a significant computer problem ( i.e., how much time and data would be lost)? 

Has your agency tested the data processing software to ensure its 

performance of the intended function are consistent with the QA 

Handbook, Volume II, and Section 14.0? 

Does your agency document software tests? 

. 

If yes, provide the documentation 
QA Handbook Volume II, Appendix H 

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43 

c) Data Validation and Correction

Question Yes No Comment

Have your agency established and document the validation 

criteria ? 

If yes, indicate document where such 

criteria can be found (title, revision date). 

Does documentation exist on the identification and applicability 

of flags (i.e., identification of suspect values) within the data as 

recorded with the data in the computer files? 

Does your agency document the data validation criteria 

including limits for values such as flow rates, calibration 

results, or range tests for ambient measurements? 

(i) If yes, please describe what action the data validator will take if he/she find data with limits exceeded 

(e.g., flags, modifies, or delete, etc.) . 

 (ii) If yes, give examples to illustrate actions taken when limits were exceeded. 

Please describe how changes made to data that were submitted to AQS and AirNow are documented. 

Who has signature authority for approving corrections? 

Name Program function _____________________________ 

What criteria are used to determine a data point be deleted? Discuss briefly. 

What criteria are used to determine if data need to be reprocessed? Discuss. 

Are corrected data resubmitted to the issuing group for 

cross-checking prior to release? 
QA Handbook Volume II, Appendix H 

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44 

d) Data Processing

Question Yes No Comment

Does the agency generate data summary reports? 

Please list at least three reports routinely generated, including the information requested below. 

Report Title Distribution Period Covered 

Question Yes No Comment

How often are data submitted to AQS and AirNow? 

Briefly comment on difficulties the agency may have encountered in coding and submitting data following the guidance of the 

AQS guidelines? 

Does the agency routinely request a hard copy printout on 

submitted data from AQS? 

Are records kept for at least 3 years by the agency in an orderly, 

accessible form? 

. 

If yes, does this include raw data , calculation , QC data , and reports ? If no, please comment 

Has your agency submitted data along with the appropriate 

calibration equations used to the processing center? 

Are concentrations of pollutants other than PM2.5 corrected to 

EPA standard temperature and pressure conditions 

(i.e.,298EK, 760 mm Hg) before input to AQS, and 

concentrations of PM2.5 reported to AQS under actual 

(volumetric) conditions? 

: 

Are audits on data reduction procedure performed on a routine 

basis? 

 If yes, at what frequency? 

Are data precision and accuracy checked each time they are 

calculated, recorded, or transcribed to ensure that incorrect 

values are not submitted to EPA? 
QA Handbook Volume II, Appendix H 

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Page 45 of 46 

45 

e) Internal Reporting

What internal reports are prepared and submitted as a result of the audits required under 40 CFR 58, Appendix A? 

Report Title Frequency 

What internal reports are prepared and submitted as a result of precision checks also required under 40 CFR 58, Appendix A? 

Report Title Frequency 

Question Yes No Comment

 Do either the audit or precision check reports 

indicated include a discussion of corrective actions 

initiated based on audit or precision check results? 

Who has the responsibility for the calculation and preparation of data summaries? To whom are such summaries delivered? 

Name Title Type of Report Recipient 
QA Handbook Volume II, Appendix H 

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Date: 12/08 

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46 

f) External Reporting

For the current calendar year or portion thereof which ended at least 90 calendar days prior to the receipt of this 

questionnaire, please provide the following percentages for required data submitted on time. 

 Percent Submitted on Time* Period Covered: 

Monitoring Qtr. SO2 CO O3 NO2 PM10 PM2.5 Pb 

1 (Jan 1 - March 31) 

2 (Apr 1 - June 30) 

3 (July 1 - Sept. 30) 

4 (Oct.1 - Dec. 31) 

*"On time" = within 90 calendar days after the end of the quarter in which the data were collected. 

For the same period, what fraction of the stations (by pollutant) reported less than 75% of the data (adjusted for seasonal monitoring and site start-ups and terminations)? 

 Percent of Stations <75% Data Recovery Period Covered: 

Monitoring Qtr. SO2 CO O3 NO2 PM10 PM2.5 Pb 

1 (Jan 1 - March 31) 

2 (Apr 1 - June 30) 

3 (July 1 - Sept. 30) 

4 (Oct.1 - Dec. 31) 

Identify the individual within the agency with the responsibility for reviewing and releasing the data. 

Name Program function 

 

Question Yes No Comment

Does your agency report the Pollutant Standard Index? 

Has your agency submitted its annual data summary report 

(as required in 40 CFR 58.26)? 

If yes, did your agency=s annual report include the 

following: 

 Data summary required in Appendix F? 

 Annual precision and accuracy information described in 

 Section 5.2 of Appendix A? 

 Location, date, pollution source and duration of all 

 episodes reaching the significant harm levels? 

Is Data Certification signed by a senior officer of your 

agency? 
QA Handbook Volume II, Appendix I 

Revision No. 1 

Date:12/08 

Page 1of 25

Appendix I 

Examples of Reports to Management 

The following example of an annual quality assurance report consist of a number of sections that 

describe the quality objectives for selected sets of measurement data and how those objectives 

have been met. Sections include: 

• Executive Summary, 

• Introduction, and 

• Quality information for each ambient air pollutant monitoring program. 

The report is titled "Acme Reporting Organization, Annual Quality Assurance Report for 2000". 
QA Handbook Volume II, Appendix I 

Revision No. 1t 

Date:12/08 

Page 2 of 25 

ACME REPORTING ORGANIZATION

ANNUAL QUALITY ASSURANCE REPORT FOR 2000

Prepared by 

Quality Assurance Department 

Acme Reporting Organization 

110 Generic Office Building 

Townone XX, 00001 

April 2001
QA Handbook Volume II, Appendix I 

Revision No. 1 

Date:12/08 

Page 3of 25

ACME REPORTING ORGANIZATION 

ANNUAL QUALITY ASSURANCE REPORT FOR 2000 

TABLE OF CONTENTS 

EXECUTIVE SUMMARY

INTRODUCTION

<Data quality 

<Quality assurance procedures

GASEOUS CRITERIA POLLUTANTS

<Program update 

<Quality objectives for measurement data 

<Data quality assessment 

PARTICULATE CRITERIA POLLUTANTS

<Program update 

<Quality objectives for measurement data 

<Data quality assessment 

TOTAL AND SPECIATED VOLATILE ORGANIC COMPOUNDS

<Program update 

<Quality objectives for measurement data 

<Data quality assessment 

AIR TOXIC COMPOUNDS

<Program update 

<Quality objectives for measurement data 

<Data quality assessment 
QA Handbook Volume II, Appendix I 

Revision No. 1 

Date:12/08 

Page 4 of 25

ACME REPORTING ORGANIZATION

ANNUAL QUALITY ASSURANCE REPORT FOR 2000 

 EXECUTIVE SUMMARY 

This summary describes the Acme Reporting Organization's (ARO's) success in meeting its quality 

objectives for ambient air pollution monitoring data. ARO's attainment of quantitative objectives, such as 

promptness, completeness, precision, and bias, are shown in Table 1, below. ARO met these objectives 

for all pollutants, with the exception of nitrogen dioxide. The failure to meet completeness and timeliness 

goals for nitrogen dioxide was due to the breakdown of several older analyzers. Replacement parts were 

installed and the analyzers are now providing data that meet ARO's quality objectives. 

Table 1. Attainment of Quantitative Quality Objectives for Ambient Air Monitoring Data

Program met objectives for 

Measurement Promptness Completeness Precision Bias 

Air Toxics Yes Yes Yes Yes 

Carbon Monoxide Yes Yes Yes Yes 

Lead Yes Yes Yes Yes 

Nitrogen Dioxide No No Yes Yes 

Ozone Yes Yes Yes Yes 

Sulfur Dioxide Yes Yes Yes Yes 

PM10 Yes Yes Yes Yes 

PM2.5 Yes Yes Yes Yes 

Volatile Organic 

Compounds (VOCs) 

Yes Yes Yes Yes

Other quality objectives (for example those concerning siting, recordkeeping, etc.) were assessed via 

laboratory and field system audits. The results of these audits indicate compliance with ARO's standard 

operating procedures except for the following: 

• The Towntwo site was shadowed by a 20 story office building which was recently completed. 

This site was closed in July 2000. 

• The Townfour site had problems with vandalism. A new, more secure, fence was installed in 

April and the sheriff's department increased patrols in the area to prevent reoccurrences. 

• Newly acquired laboratory analytical instruments did not have maintenance logs. New logs were 

obtained and personnel were instructed on their use. A spot check, approximately one month 

later, indicated the new logs were in use. 

A review of equipment inventories identified three older sulfur dioxide ambient air monitors that, based 

on our past experience, are likely to experience problems. Cost information and a schedule for 

replacement has been prepared and submitted to management for funding. Based on this schedule, the 

new monitors will be installed before the end of 2001. 
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INTRODUCTION

The Acme Reporting Organization (ARO) conducts ambient air monitoring programs for the State Bureau 

of Environmental Quality and local air quality management districts. These programs involve: 

• monitoring of criteria pollutants to determine the National Ambient Air Quality Standards 

(NAAQS) attainment status of state and local air quality. This monitoring is conducted as part of 

the State and Local Air Monitoring Stations (SLAMS) and National Air Monitoring Stations 

(NAMS) networks. 

• monitoring compounds (volatile organic compounds and nitrogen oxides), referred to as ozone 

precursors, that can produce the criteria pollutant ozone. This monitoring is conducted as part of 

the Photochemical Assessment Monitoring Stations (PAMS) network. 

• monitoring toxic air pollutants. 

The purpose of this report is to summarize the results of quality assurance activities performed by ARO to 

ensure that the data meets its quality objectives. This report is organized by ambient air pollutant 

category (e.g., gaseous criteria pollutants, air toxics). The following are discussed for each pollutant 

category: 

<program overview and update 

<quality objectives for measurement data 

<data quality assessment 

DATA QUALITY

Data quality is related to the need of users for data of sufficient quality for decision making. Each user 

specifies their needed data quality in the form of their data quality objectives (DQOs). Quality objectives 

for measurement data are designed to ensure that the end user's DQOs are met. Measurement quality 

objectives are concerned with both with quantitative objectives (such as representativeness, completeness, 

promptness, accuracy, precision and detection level) and qualitative objectives (such as site placement, 

operator training, and sample handling techniques).

QUALITY ASSURANCE PROCEDURES

Quality assurance is a general term for the procedures used to ensure that a particular measurement meets 

the quality requirements for its intended use. In addition to performing tests to determine bias and 

precision, additional quality indicators (such as sensitivity, representativeness, completeness, timeliness, 

documentation quality, and sample custody control) are also evaluated. Quality assurance procedures fall 

under two categories: 

• quality control - procedures built into the daily sampling and analysis methodologies to ensure 

data quality, and 

• quality assessment - which refers to periodic outside evaluations of data quality. 

Some ambient air monitoring is performed by automated equipment located at field sites, while other 

measurements are made by taking samples from the field to the laboratory for analysis. For this reason, 

we will divide quality assurance procedures into two parts – field and laboratory quality assurance.
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Field Quality Assurance

Quality control of automated analyzers and samplers consists of calibration and precision checks. The 

overall precision of sampling methods is measured using collocated samplers. Quality assurance is 

evaluated by periodic performance and system audits. 

Calibration - Automated analyzers (except ozone) are calibrated by comparing the instrument's response 

when sampling a cylinder gas standard mixture to the cylinder's known concentration level. The analyzer 

is then adjusted to produce the correct response. Ozone analyzers are calibrated by on-site generation of 

ozone whose concentration is determined by a separate analyzer which has its calibration traceable to the 

U.S. Environmental Protection Agency. The site's analyzer is then adjusted to produce the same measured 

concentration as the traceable analyzer. Manual samplers are calibrated by comparing their volumetric 

flow rate at one or more flow rates to the flow measured by a flow rate transfer standard. Calibrations are 

performed when an instrument is first installed and at semi-annual intervals thereafter. Calibrations are 

also performed after instrument repairs or when quality control charts indicate a drift in response to 

quality control check standards. 

Precision - Precision is a measure of the variability of an instrument. The precision of automated 

analyzers is evaluated by comparing the sample's known concentration against the instrument's response. 

The precision of manual samplers is determined by collocated sampling – the simultaneous operation of 

two identical samplers placed side by side. The difference in the results of the two samplers is used to 

estimate the precision of the entire measurement process (i.e., both field and laboratory precision). 

Performance Audits - The bias of automated methods is assessed through field performance audits. 

Performance audits are conducted by sampling a blind sample (i.e., a sample whose concentration is 

known, but not to the operator). Bias is evaluated by comparing the measured response to the known 

value. Typically, performance audits are performed annually using blind samples of several different 

concentrations. 

System Audits - System audits indicate how well a sampling site conforms to the standard operating 

procedures as well as how well the site is located with respect to its mission (e.g., urban or rural sampling, 

special purpose sampling site, etc.). System audits involve sending a trained observer (QA Auditor) to the 

site to review the site compliance with standard operating procedures. Some areas reviewed include: site 

location (possible obstruction, presence of nearby pollutant sources), site security, site characteristics 

(urban versus suburban or rural), site maintenance, physical facilities (maintenance, type and operational 

quality of equipment, buildings, etc.), recordkeeping, sample handling, storage and transport. 

Laboratory Quality Assurance

Laboratory quality control includes calibration of analytical instrumentation, analysis of blank samples to 

check for contamination, and analysis of duplicate samples to evaluate precision. Quality assurance is 

accomplished through laboratory performance and system audits. 

 

Calibration - Laboratory analytical instruments are calibrated by comparing the instrument's response 

when sampling standards of known concentration level. The difference between the measured and known 

concentrations is then used to adjust the instrument to produce the correct response. 

Blank Analysis - A blank sample is one that has intentionally not been exposed to the pollutant of interest. 
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Analysis of blank samples reveals possible contamination in the laboratory or during field handling or 

transportation. 

Duplicate Analysis - Duplicate analyses of the same sample are performed to monitor the precision of the 

analytical method. 

Performance Audits - Regular performance audits are conducted by having the laboratory analyze 

samples whose physical or chemical properties have been certified by an external laboratory or standards 

organization. The difference between the laboratory's reported value and the certified values is used to 

evaluate the analytical method's accuracy. 

System Audits - System audits indicate how well the laboratory conforms to its standard operating 

procedures. System audits involve sending a trained observer (QA Auditor) to the laboratory to review 

compliance with standard operating conditions. Areas examined include: record keeping, sample 

custody, equipment maintenance, personnel training and qualifications, and a general review of facilities 

and equipment. 
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GASEOUS CRITERIA POLLUTANTS

The Acme Reporting Organization monitors the ambient concentrations of the gaseous criteria pollutants 

carbon monoxide (CO), nitrogen dioxide (NO2), ozone (O3), and sulfur dioxide (SO2) to determine 

attainment of Federal (NAAQS) and State ambient air quality standards. Monitoring of these pollutants is 

conducted continuously by a network of automated stations. 

PROGRAM UPDATE

At the beginning of 2000, the Acme Reporting Organization operated 38 ambient air monitoring stations 

that measured gaseous criteria pollutants. On March 1, 2000, a station was opened at Townone to monitor 

CO, NO2, O3, and SO2 . The station at Towntwo, which monitored NO2, O3, and SO2, was closed in April 

2000. 

QUALITY OBJECTIVES FOR MEASUREMENT DATA

The Quality Objectives for the Acme Reporting Organization's ambient air monitoring of gaseous criteria 

pollutants are shown in Table 2, below. 

Table 2. Quality Objectives for Gaseous Criteria 

Pollutants

Data Quality Indicator Objective

Precision "10% 

Bias "15% 

Completeness 75% 

Promptness 100% 

DATA QUALITY ASSESSMENT

Summary

Assessment of the data quality for ARO gaseous criteria pollutants showed that all instruments met goals 

for accuracy, precision, completeness, and promptness. System audits showed siting problems at three 

sites, two of these were corrected promptly, while the third site had to be closed due to the construction of 

a nearby large office building. 
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Promptness and Completeness

At least 75 percent of scheduled monitoring data must be reported for purposes of determining attainment 

of NAAQS. All data must be submitted within 90 days after the end of the reporting quarter. Table 3 

summarizes promptness and completeness for gaseous criteria pollutant data. 

Table 3. Data Quality Assessment for Promptness 

and Completeness

Pollutant Promptness Completeness

Carbon monoxide 100% 95% 

Nitrogen dioxide 100% 97% 

Ozone 100% 94% 

Sulfur dioxide 100% 96% 

Precision

At least once every two weeks, precision is determined by sampling a gas of known concentration. Table 

4 summarizes the precision checks for gaseous criteria pollutants. 

Table 4. Data Quality Assessment for Precision

Pollutant

Precision checks 

completed

Percentage within 

limits

Carbon monoxide (CO) 98% 98% 

Nitrogen dioxide (NO2) 100% 97% 

Ozone (O3) 97% 98% 

Sulfur dioxide (SO2) 100% 98% 

Bias

The results of annual performance audits conducted by ARO personnel are shown in Figure 1, below. The 

center line for each pollutant represents the average bias across all analyzers (i.e., with all analyzers 

weighted equally). The lower and upper probability limits represent the boundaries within which 95 

percent of the individual bias values are expected to be distributed. 
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Figure 2 shows the results of external performance audits performed with the National Performance Audit 

Program (NPAP), administered by the U.S. EPA. 
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System Audits

Systems audits were performed at approximately 25 percent of the sites during the calendar year 

2000. These audits evaluated areas such as siting criteria, analyzer operation and maintenance, 

operator training, recordkeeping, and serve as a general review of site operations. No significant 

problems were observed, except for the following: 

• The Towntwo site was shadowed by a 20 story office building which was recently 

completed. This site was closed in July 2000. 

• The Townfour site had problems with repeated vandalism. A new, more secure, fence 

was installed in April and the sheriff's department increased patrols in the area to prevent 

reoccurrences. 

• The Townsix site had vegetation which had grown too close to the analyzer inlet probes. 

The vegetation was removed within one week after the problem was reported. Personnel 

from the County Parks and Recreation Department provided assistance removing the 

vegitation. 
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 PARTICULATE CRITERIA POLLUTANTS

The Acme Reporting Organization monitors the ambient concentrations of three particulate criteria 

pollutants: 

• Lead; 

• PM10 (particles with an aerodynamic diameter less than or equal to a nominal 10 micrometers; 

and 

• PM2.5 (particles with an aerodynamic diameter less than or equal to a nominal 2.5 micrometers) 

This monitoring is used to determine attainment of Federal (NAAQS) and State ambient air quality 

standards. Monitoring of these pollutants is conducted by sampling for 24 hours every six days by a 

network of manually operated samplers. 

PROGRAM UPDATE

At the beginning of 2000, the Acme Reporting Organization operated 22 ambient air monitoring stations 

that measured particulate criteria pollutants. On March 1, 2000, a station was opened at Townone to 

monitor PM10, PM2.5, and lead. The station at Towntwo, which monitored PM10, PM2.5, and lead, was 

closed in April 2000. 

QUALITY OBJECTIVES FOR MEASUREMENT DATA

The Quality Objectives for the Acme Reporting Organization's ambient air monitoring of particulate 

criteria pollutants are shown in Table 5, below. 

Table 5. Quality Objectives for Particulate Criteria 

Pollutants

Data Quality Indicator Objective

Precision "7% 

Bias "10% 

Completeness 75% 

Promptness 100% 

DATA QUALITY ASSESSMENT

Summary

Assessment of the data quality for ARO particulate criteria pollutants showed that all samplers 

met goals for accuracy, precision, completeness, and promptness. System audits showed siting 

problems at three sites. Two of these were corrected promptly, while the third site had to be 

closed due to the construction of a large office building, nearby. 
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Promptness and Completeness

At least 75 percent of scheduled monitoring data must be reported for purposes of determining attainment 

of NAAQS. All data must be submitted within 90 days after the end of the reporting quarter. Table 6 

summarizes promptness and completeness data for particulate criteria pollutants. 

Table 6. Data Quality Assessment for Promptness and 

Completeness

Pollutant Promptness Completeness

Lead 100% 93% 

PM10 100% 95% 

PM2.5 100% 92% 

Precision

Precision is determined by operating collocated samplers (i.e., two identical samplers operated in the 

identical manner). Due to the anticipated poor precision for very low levels of pollutants, only collocated 

measurements above a minimum level (0.15 Fg/m3

 for lead, 20 Fg/m3 for PM10, and 6 Fg/m3 for PM2.5) 

are used to evaluate precision. Table 7 summarizes the results of collocated measurements made during 

the calendar year 2000. 

Table 7. Data Quality Assessment for Precision

Pollutant

Collocated precision 

measurements completed

Collocated 

measurements within 

limits

Lead 98% 98% 

PM10 100% 97% 

PM2.5 97% 98% 
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Flow rate precision 

A flow rate precision check is conducted at least every two weeks for PM10 and PM2.5 samplers. The flow 

should be within "10% of the specified value. Results are shown in Table 8. 

Table 8. Flow Rate Precision Checks for Particulate Criteria Pollutants

Pollutant

Precision Checks 

completed

Precision Checks 

within limits

Lead 98% 98% 

PM10 100% 97% 

PM2.5 97% 98% 

Flow rate bias

Results of the annual flow rate audits conducted by ARO personnel are shown in Figure 3, below. The 

center line for each pollutant represents the average bias across all sampler (i.e., with all sampler 

weighted equally). The lower and upper probability limits represent the boundaries within which 95 

percent of the individual bias values are expected to be distributed. 

Figure 4 shows the results of external flow rate audits for PM10 and lead samplers performed with the 

National Performance Audit Program (NPAP) which is administered by the U.S. EPA. Currently NPAP 

audits of PM2.5 samplers involve sampler collocation rather than flow rate checks 
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Measurement Bias

Measurement bias is evaluated for PM2.5 analyzers by collocated sampling using an audit sampler. For 

internal audits, the collocated measurements provide an estimate of bias resulting from sampler 

operations. For external NPAP audits, the collocated measurements provide an estimate of bias resulting 

from both sampler and laboratory operations. Measurement bias for lead is evaluated by use of standard 

lead test samples. This provides an estimate of the bias resulting from laboratory operations. The results 

of the annual performance audits of PM2.5 and lead conducted by ARO personnel are shown in Figure 5, 

below. 
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Figure 6 shows the results of external performance audits for PM10 and lead performed with the National 

Performance Audit Program (NPAP) which is administered by the U.S. EPA. 

System Audits

Systems audits were performed at approximately one fourth of the sites and at the central analytical 

laboratory during calendar year 2000. These audits evaluated areas such as siting criteria, equipment 

operation and maintenance, operator training, recordkeeping, and served as a general review of site 

operations. No significant problems were observed, except for the following: 

• The Towntwo site was shadowed by a 20 story office building which was recently completed. 

This site was closed in July 2000. 

• The Townfour site had problems with repeated vandalism. A new, more secure, fence was 

installed in April and the sheriff's department increased patrols in the area to prevent 

reoccurrences. 

No significant problems were found in the laboratory audits, except for failure to keep maintenance logs 

on several newly acquired analytical instruments. New logs were obtained and personnel instructed on 

their use. A spot check, approximately one month later, indicated the logs were in use. 
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TOTAL AND SPECIATED VOLATILE ORGANIC COMPOUNDS (PAMS)

The Acme Reporting Organization monitors the ambient concentrations of ozone precursors (volatile 

organic compounds [VOCs], carbonyls, and nitrogen oxides that can produce the criteria pollutant ozone). 

This monitoring is conducted as part of the Photochemical Assessment Monitoring Stations (PAMS) 

network. Nitrogen dioxide (one of the nitrogen oxides measured in PAMS) is also a criteria pollutant and 

its measurement is described under the gaseous criteria pollutant section, above. Total nitrogen oxides 

(NOx) measurements are obtained continuously by a network of automated stations. Volatile organic 

compounds (VOCs), excluding carbonyls, are measured by continuous analyzers (on-line gas 

chromatographs) at selected sites. The remaining sites use automated samplers to collect VOC canister 

samplers which are then transported to the laboratory for analysis. Carbonyls are collected in adsorbent 

sampling tubes, which are transported to the laboratory for analysis. 

PROGRAM UPDATE

At the beginning of 2000, the Acme Reporting Organization operated 5 ambient air monitoring stations 

that measured ozone precursors. On March 1, 2000, a station was opened at Townone to monitor VOCs, 

carbonyls, and NOx. 

QUALITY OBJECTIVES FOR MEASUREMENT DATA

The Quality Objectives for the Acme Reporting Organization's ambient air monitoring of ozone 

precursors are shown in Table 9, below. 

Table 9. Quality Objectives for Ozone Precursors

Data Quality Indicator Objective

Precision (NOx) "10% 

Precision (VOC, Carbonyls) "25% 

Bias (NOx) "15% 

Bias (VOC, Carbonyls) "20% 

Completeness 75% 

Promptness 100% 

DATA QUALITY ASSESSMENT

Summary

Assessment of the data quality for ozone precursors showed that all instruments met goals for accuracy, 

precision, completeness, and promptness. System audits showed siting problems at two sites, both of 

these were corrected promptly. 
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Promptness and Completeness 

At least 75 percent of scheduled monitoring data must be reported. All data must be submitted within six 

months after the end of the reporting quarter. Table 10 summarizes promptness and completeness data 

for ozone precursors. 

Table 10. Data Quality Assessment for Promptness and Completeness

Ozone precursor Promptness Completeness

Carbonyls 100% 80% 

Nitrogen Oxides (NOx) 100% 96% 

Total VOCs (Total nonmethane hydrocarbons) 

100% 87% 

Speciated VOCs 100% 83% 

Precision

At least once every two weeks, precision for nitrogen oxides (NOx) and automated VOC analysis were 

determined by sampling a gas of known concentration. Precision for manual VOC sampling and carbonyl 

sampling is obtained by analysis of duplicate samples. Duplicates are taken at a frequency of one 

duplicate for every 10 samples. Table 11 summarizes the precision check results for 2000. 

Table 11. Data Quality Assessment for Precision

Ozone precursor 

Precision checks 

completed

Precision checks 

within limits

Carbonyls 91% 90% 

Nitrogen Oxides (NOx) 98% 97% 

Total VOCs (Total nonmethane hydrocarbons) 

90% 91% 

Speciated VOCs 95% 80% 

Bias

 The results of the annual performance audits conducted by ARO personnel are shown in 

Figure 7, below. For NOx and the automated VOC analyzers, the center line represents the 

average bias across all sites (i.e., with all sites weighted equally). For the carbonyl and manual 

VOC analyses, the center line represents the average of all audit samples for the central 

analytical laboratory. The lower and upper probability limits represent the boundaries within 

which 95 percent of the individual bias values are expected to be distributed. Carbonyl and Total VOC 

measurements represent the average of all audit species. 
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Figure 8 shows the results of the external performance audits performed with the National Performance 

Audit Program (NPAP) which is administered by the U.S. EPA. 

System Audits

Systems audits were performed at two sites during calendar year 2000. These audits evaluated 

areas such as siting criteria, analyzer and sampler operation and maintenance, operator training, 

recordkeeping, and serve as a general review of site operations. In general both sites were 

performing well except for the following: 
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• The Townsix site had vegetation which had grown too close to the analyzer inlet probes. The 

vegetation was removed within one week, with assistance from the County Parks and Recreation 

Department. 

A systems audit was also performed at the central analytical laboratory. Results were good with only 

minor items noted for improvements. 
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AIR TOXICS

The Acme Reporting Organization monitors the ambient concentrations of air toxic compounds. Three 

different methods are used, depending on the class of air toxic compound. Volatile organic compounds 

(VOCs), excluding carbonyls, are measured by continuous analyzers (on-line gas chromatographs) at 

selected sites. The remaining sites use automated samplers to collect VOC cannister samplers which are 

then transported to the laboratory for analysis. Carbonyls are collected with adsorbent sampling tubes, 

which are transported to the laboratory for analysis. Inorganic compounds are collected on PM2.5 filters 

(as part of particulate criteria pollutant monitoring) and analyzed (after weighing for PM2.5 mass) by 

inductively coupled plasma mass spectrometry (ICP MS). This monitoring is conducted as part of the Air 

Toxics monitoring network. 

PROGRAM UPDATE

At the beginning of 2000, the Acme Reporting Organization operated five ambient air monitoring stations 

that measured ambient air toxics. On March 1, 2000, a station was opened at Townone to monitor air 

toxics. 

QUALITY OBJECTIVES FOR MEASUREMENT DATA

The Quality Objectives for the Acme Reporting Organization's ambient air monitoring of ambient air 

toxics are shown in Table 12, below. 

Table 12. Quality Objectives for Air Toxics

Data Quality Indicator Objective

Precision "25% 

Bias "25% 

Completeness 75% 

Promptness 100% 

DATA QUALITY ASSESSMENT

Summary

Assessment of the data quality for ambient air toxics showed that all instruments met goals for accuracy, 

precision, completeness, and promptness. System audits showed siting problems at two sites, both of 

these were corrected promptly. 
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Promptness and Completeness

At least 75 percent of scheduled monitoring data must be reported. All data must be submitted within six 

months after the end of the reporting quarter. Table 13 summarizes promptness and completeness for 

ambient air toxics monitoring data. 

Table 13. Data Quality Assessment for Promptness and Completeness

Pollutant Promptness Completeness

Carbonyls 100% 78% 

Volatile organic 

compounds 

100% 84% 

Inorganic compounds 100% 87% 

Precision

At least once every two weeks, precision for automated VOC analysis is determined by sampling a gas of 

known concentration. Precision for manual VOC sampling, carbonyl sampling, and inorganic sampling is 

obtained by analysis of duplicate samples. Duplicates are taken at a frequency of one duplicate for every 

10 samples. Table 14 summarizes the precision check results for 2000. 

Table 14. Data Quality Assessment for Precision

Pollutant

Precision checks 

completed

Precision checks 

within limits

Carbonyls 91% 90% 

Volatile organic 

compounds 

98% 97% 

Inorganic compounds 90% 91% 

Bias

The results of the annual performance audits conducted by ARO personnel are shown in Figure 9, below. 

For the automated VOC analyzers, the center line represents the average bias across all sites (i.e., with all 

sites weighted equally). For the carbonyl, manual VOC, and inorganic analyses, the center line represents 

the average of all audit samples for the central analytical laboratory. The lower and upper probability 

limits represent the boundaries within which 95 percent of the individual bias values are expected to be 

distributed. All measurements represent the average of all audit species. 
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Figure 10 shows the results of the external performance audits performed with the National 

Performance Audit Program (NPAP) which is administered by the U.S. EPA. 
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System Audits

Systems audits were performed at two sites during the calendar year 2000. These audits 

evaluated areas such as siting criteria, analyzer and sampler operation and maintenance, operator 

training, recordkeeping, and serve as a general review of site operations. No significant 

problems were found, except for the following: 

< The Townsix site had vegetation which had grown too close to the analyzer inlet probes. The 

vegetation was removed within one week, with assistance from the County Parks and 

Recreation Department. 

A systems audit was also performed at the central analytical laboratory. No significant problems 

were found. 

Example of Corrective Action Form

A corrective action request should be made whenever anyone in the reporting organization notes 

a problem that demands either immediate or long-term action to correct a safety defect, a 

operational problem, or a failure to comply with procedures. A typical corrective action request 

form, with example information entered, is shown below. A separate form should be used for 

each problem identified. 

The corrective action report form is designed as a closed-loop system. First it identifies the 

originator, that person who reports and identifies the problem, states the problem, and may 

suggest a solution. The form then directs the request to a specific person (or persons), i.e., the 

recipient, who would be best qualified to "fix" the problem. Finally, the form closes the loop by 

requiring that the recipient state how the problem was resolved and the effectiveness of the 

solution. The form is signed and a copy is returned to the originator and other copies are sent to 

the supervisor and the applicable files for the record. 
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 ARO - Corrective Action Request 

 

Part A - To be completed by requestor

To: John S. Visor

Organization Responsible for Action ARO Ambient Air Monitoring Section

 

Urgency:

9 Emergency (failure to take action immediately may result in injury or property damage) 

9 Immediate (4 hours) : Urgent (24 hours) 9 Routine (7 days) 

9 As resources allow 9 For Information only 

 

From: William Operator phone: (000) 555 - 1000

 fax: (000) 555 - 1001 e-mail: billo@localhost

Copies to: 

(Always send a copy to the ARO Site Coordinator at 115 Generic Office Building, Townone XX, 00001)

 

Problem Identification 

 Site(Location): Townsix site

 System: sample inlet

 Date problem identified: Aug. 1, 2000

 Nature of problem: Glass sample inlet and dropout trap broken during removal

 of weeds from site

 

 Recommended Action: Replace broken parts

 Signature: William Operator Date: Aug. 1, 2000

 

Part B - to be completed by responsible organization

Problem Resolution 

 Date corrective action taken: August 4, 2000

 Summary of Corrective Action: Replacement parts were ordered and received. The new 

parts were installed within three days of the request. Data from the days with a cracked sample inlet will 

be flagged as questionable.

 

 Effectiveness of corrective action: Sample inlet restored to new condition.

Signature: John Visor Date: Aug. 4, 2000

Phone: (000) 555 - 2000 Fax: (000) 555 - 2001

e-mail: jsv@localhost

Send copies of the completed form to the requestor and the ARO Site Coordinator at 115 Generic Office Building, Townone 

XX, 00001)

ARO form CAR-1 , May 1, 1999 
United States 

Environmental Protection Agency 

Office of Air Quality Planning and Standards 

Air Quality Assessment Division 

Research Triangle Park, NC 

Publication N