EPA Contract No. EP-D-11-006 

Work Assignment 5-09 

DRAFT 

Technical Support Document 

Optical Gas Imaging Protocol 

(40 CFR Part 60, Appendix K) 

Prepared for: 

Jason DeWees 

U.S. Environmental Protection Agency 

Office of Air Quality Planning Standards 

Air Quality Assessment Division 

Measurement Technology Group (E141-03) 

Research Triangle Park, NC 27711 

Prepared by: 

Tracey L. Footer 

Eastern Research Group, Inc. 

601 Keystone Park Drive, Suite 700 

Morrisville, NC 27560 

Revision No. 5 

August 11, 2015 
ii 

DISCLAIMER 

This document and related appendices are currently in draft format. Do not cite or quote. This 

document will continue to be developed based on the latest information. This draft report has 

been initially reviewed by the U.S. Environmental Protection Agency’s (EPA’s) Office of Air 

Quality Planning and Standards and has been approved in draft form. 

Mention of or referral to commercial products or services and/or links to non-EPA websites does 

not imply official EPA endorsement of or responsibility for opinions, ideas, data, or products 

presented at those locations, or guarantee the validity of the information provided. Mention of 

commercial products/services and non-EPA websites is provided solely as a reference to 

information on topics related to environmental protection that may be useful to EPA staff and the 

public. 
iii 

ABSTRACT 

This technical support document (TSD) provides background, technical analyses, experimental 

results, and other supplemental information to support regulatory development of an optical gas 

imaging (OGI) protocol. OGI technology can be used to detect fugitive emissions of compounds 

such as methane and volatile organic compounds from industrial sources, including those within 

the refinery, oil and gas, and chemical sectors. The potential use of OGI technology has been 

presented in two Federal Register notices (77 FR 76248, June 18, 2012 and 79 FR 36880, June 

30, 2014). A protocol for applying OGI technology will be codified at 40 CFR part 60, appendix 

K. This document presents a comprehensive regulatory history and results of a literature review 

on the technology development and observations of current application of OGI technology. The 

literature review identifies the technology, applications, and limitations of the current remote 

measurement and monitoring technologies. This TSD also contains the results from multiple 

efforts commissioned by the U.S. Environmental Protection Agency (EPA) for Eastern Research 

Group, Inc. (ERG) to perform laboratory studies, evaluate OGI technology, and research 

potential operations and procedures for detecting leaks using OGI technology. Laboratory studies 

include testing of the spectral limitations and gas sensitivity and determining the effect of various 

environmental factors on leak detection. Finally, the appendices of this document contain 

supplemental information to the laboratory studies. 

 
iv 

TABLE OF CONTENTS

Section Page No. 

ABSTRACT ............................................................................................................................. iii

I. BACKGROUND .............................................................................................................1

A. Leak Detection and Repair ..........................................................................................1

B. Purpose and Scope of this Document...........................................................................2

II. POLICY AND REGULATIONS .....................................................................................3

A. History of LDAR Based on the 1990 CAA Amendments ............................................3

B. Regulatory Status ........................................................................................................6

C. Costing Evaluations .................................................................................................. 11

III. LITERATURE REVIEW .............................................................................................. 12

A. Technology ............................................................................................................... 12

1. History ................................................................................................................. 12

2. Basis of OGI technology ...................................................................................... 13

3. Available Technology .......................................................................................... 16

B. Observations and Improvements ............................................................................... 17

1. Initial OGI Technology Performance Studies ....................................................... 17

2. API Follow-on Studies5,74,75 ................................................................................. 21

3. ETV Minimum Detection Limit Study ................................................................. 24

4. Attempts at Calibration and Performance Verification.......................................... 27

5. Studies to Compare OGI Technology to Method 21 ............................................. 35

6. Studies Comparing OGI Technology to “Bagging” Techniques............................ 36

C. Conclusion ................................................................................................................ 38

D. References and Reviewed Literature ......................................................................... 41

IV. ERG LABORATORY EVALUATIONS ....................................................................... 49

A. Feasibility and Detection Limit Study ....................................................................... 50

B. Spectral Limitations and Gas Sensitivity Studies ....................................................... 58

C. Assessment of Parameters that Influence Plume Characteristics/Detection ................ 66

D. Camera Field Operation ............................................................................................ 72

V. SUMMARY .................................................................................................................. 77

VI. LIST OF APPENDICES AND SUPPLEMENTAL DOCUMENTS ............................... 80
v 

LIST OF TABLES

Table 2-1. Timeline of Major Regulatory Milestones Leading to Current Status ..........................4

Table 2-2. Federal Regulations Requiring LDAR Programs with Method 21 Leak Monitoring22, 

119

 ...........................................................................................................................4

Table 3-1. Currently Commercially Available Handheld OGI Camera Systems ......................... 17

Table 3-2. Average Minimum Detection Level Mass Emission Rates (g/hr), Number of 

Measurements in Parentheses24 ............................................................................. 19

Table 3-3. Summary of Controlled Laboratory Testing Minimum Detection Limits (g/hr) at 

Various Wind Speeds74 ......................................................................................... 22

Table 3-4. Summary of Controlled Laboratory Minimum Detection Limits (g/hr) for Pure Gases 

at Various Wind Speeds74 ..................................................................................... 23

Table 3-5. Summary of Controlled Laboratory Minimum Detection Limits (g/hr) for Gases 

Diluted with N2 at Various Wind Speeds74 ............................................................ 23

Tables 3-6 and 3-7. MDLRs for Pure Compounds at Different Wind Speeds and Gas Mixtures at 

Different Wind Speeds5,75 ..................................................................................... 24

Table 3-8. Summary of MDLs and % Agreement with a M21 Monitoring Device during Lab 

Testing10,11 ............................................................................................................ 26

Table 3-9. Empirical Methane NECL Values for a FLIR GF320 OGI Camera88 ........................ 34

Table 3-10. Comparison of Field-Derived Values to Published Laboratory Detection Limits 

(g/hr)35 .................................................................................................................. 37

Table 3-11. Comparison Between FLIR GF320 and Opgal EyeCGas Specifications33,73 ............ 38

Table 3-12. Minimum Detected Leak Rates (MDLRs) for the FLIR GF320 per manufacturer33. 40

Table 4-1. Results from Feasibility Study at About 20,000 ppmV (2%) Total Hydrocarbons 

(50/50 Propane-Butane Mix) ................................................................................. 53

Table 4-2. Results from Feasibility Study at About 10,000 ppmV (1%) Total Hydrocarbons 

(50/50 Propane-Butane Mix) ................................................................................. 54

Table 4-3. Results from Feasibility Study at About 5,000 ppmV (0.5%) Total Hydrocarbons 

(50/50 Propane-Butane Mix) ................................................................................. 54

Table 4-4. Results from Feasibility Study at About 500 ppmV Total Hydrocarbons .................. 54

Table 4-5. Results from Feasibility Study Holding Mass Emission Rate Equal to 10 g/hr with 

OGI Camera Thermal Tuning on Auto (50/50 Propane-Butane Mix) ..................... 55

Table 4-6. Results from Feasibility Study at About 500 ppmV Total Hydrocarbons on High 

Sensitivity Mode (50/50 Propane-Butane Mix) ..................................................... 55

Table 4-7. Results from Feasibility Study at About 500 ppmV Total Hydrocarbons on High 

Sensitivity Mode, Rerun (50/50 Propane-Butane Mix) .......................................... 56

Table 4-8. Overall Results from the Feasibility Study Showing Both ∆T Conditions ................. 56

Table 4-9. OGI Cameras Evaluated for Spectral Limitations and Gas Sensitivity....................... 59

Table 4-10. FLIR GF320 Spectral Window Results ................................................................... 62

Table 4-11. Integrated Spectral Absorbance and Propane Relative Response Factors ................ 63
vi 

Table 4-12. Repeat Feasibility Study Run 1 (2% concentration) with FLIR and Opgal OGI 

Cameras ................................................................................................................ 66

Table 4-13. Repeat Feasibility Study Run 3 (5000 ppmV) with FLIR and Opgal OGI Cameras . 67

Table 4-14. Repeat Feasibility Study Run 4 (500 ppmV) with FLIR and Opgal OGI Cameras ... 67

Table 4-15. Repeat Feasibility Study Run 5 (10.2 g/hr held constant) with FLIR and Opgal OGI 

Cameras ................................................................................................................ 68

Table 4-16. Rerun of Repeat Feasibility Study Run 5 ................................................................ 68

Table 4-17. Repeat Feasibility Study Run 10 (500 ppmV on High Sensitivity/Enhanced Modes) 

with FLIR and Opgal OGI Cameras ...................................................................... 68

Table 4-18. Repeat of Feasibility Study Run 5 with FLIR and Opgal on High 

Sensitivity/Enhanced Mode ................................................................................... 69

Table 4-19. Horizontal Wind Shear, Normal/Auto Mode ........................................................... 69

Table 4-20. Horizontal Wind Shear, High Sensitivity/Enhanced Mode ...................................... 69

Table 4-21. Reynolds Number Study Results with 2” Orifice .................................................... 70

Table 4-22. Reynolds Number Study Results with 1” Orifice .................................................... 70

Table 4-23. Reynolds Number Study Results with 1/2” Orifice ................................................. 70

Table 4-24. Reynolds Number Study Results with 1/4” Orifice ................................................. 71

Table 4-25. Reynolds Number Study Results with 1/8” Orifice ................................................. 71

Table 4-26. Reynolds Number Study Results with 1/8” Orifice and High/Enhanced Sensitivity 

Modes ................................................................................................................... 71

Table 4-27. List of LSP Leaking Elements ................................................................................ 74

Table 4-28. Initial Experimental Matrix for Blind Surveys ........................................................ 74

Table 4-29. List of OGI Camera Operators and Experience Level ............................................. 75

Table 4-30. Overall Blind Survey Results for Leaks Released at 2% Concentration ................... 76
vii 

LIST OF FIGURES

Figure 2-1. Distribution of the Total Equipment Counts and Estimated Emissions by Screening 

Range1 ....................................................................................................................8

Figure 3-1. Basic Principle of IMSS Diffractive Optics45........................................................... 15

Figure 3-2. Correlation Between the Concentration Measurements Made by the FID Device as 

Compared to that Using the Sherlock® VOC47 ...................................................... 16

Figure 3-3. Field Survey Performance Summary of Infrared Cameras24 ..................................... 20

Figure 3-4. MDLRs Versus Standoff Distance for Three Lenses5 .............................................. 22

Figure 3-5. Calibration Chambered Vessel6 ............................................................................... 28

Figure 3-6. Gas Imaging IR Camera Verification and Calibration System131 ............................. 29

Figure 3-7. Quality Control Chart for IR Camera Daily Check131 .............................................. 29

Figure 3-8. Example of a Cluster of ΔI vs. ΔT Curves for Different PPM-M Levels of Benzene131

 ............................................................................................................................. 30

Figure 3-9. Example of a ΔI vs. Concentration-Path Length Curve131 ........................................ 30

Figure 3-10. Experimental Set Up of Gas Cells with Controlled Blackbody Sources7 ................ 31

Figure 3-11. Measurement of the Signal Attenuation from 2,000 ppm of Methane7 ................... 31

Figure 3-12. Signal Attenuation vs. Gas Concentration7 ............................................................ 32

Figure 3-13. NECL Measurement Set Up88 ............................................................................... 33

Figure 3-14. Signal Intensity as a Function of CL88 ................................................................... 33

Figure 4-1. CLGS Gas Blending Component Developed by ERG for Preliminary Performance 

Tests ..................................................................................................................... 51

Figure 4-2. Overview of CLGS in Place at ERG’s Laboratory ................................................... 52

Figure 4-3. Feasibility Study Results by Flow Rate and Mass Emission Rate for Measurements in 

Manual and Auto Modes ....................................................................................... 57

Figure 4-4. EPA ORD Custom-built Spectral Test Platform ...................................................... 58

Figure 4-5. Example Placement of Neutral Density Filters for Non-Thermometric IR Spectral 

Tests in the Visible (Left) and IR (Right) .............................................................. 59

Figure 4-6. A FLIR GasFindIR Mounted and Aligned to the Monochromator Exit Slit.............. 60

Figure 4-7. The Exit Slit of the Monochromator as Imaged by the FLIR GF320 ........................ 60

Figure 4-8. Average Spectral Window Curve for FLIR GF320 Cameras ................................... 61

Figure 4-9. Average FLIR GF320 Spectral Window Curve Illustrating POL Locations ............. 62

Figure 4-10. Example Gas Sensitivity Curve for 50/50 Propane-Butane Mixture ....................... 65

Figure 4-11. Overview of Reynolds Number Data ..................................................................... 72

Figure 4-12. Custom-built LSP by ERG from the Front (left) and Side (right) Showing Leak 

Locations .............................................................................................................. 73

Figure 5-1. Concept Diagram of OGI Camera Performance Envelope ....................................... 78

Figure 5-2. Concept Diagram of the OGI Camera Performance Envelope in the Presence of NonIdeal Conditions .................................................................................................... 79
viii 

LIST OF ACRONYMS 

Å Ångström (0.0001 μm) 

AIMM approved instrument monitoring method 

API American Petroleum Institute 

AQCC State of Colorado Air Quality Control Commission 

AWMA Air and Waste Management Association 

AWP Alternative Work Practice 

BAGI backscatter absorption gas imaging 

CAA Clean Air Act 

CAAA Clean Air Act Amendments of 1990 

C-H carbon-hydrogen 

CLGS custom controlled leak generation system 

DI&M directed inspection and maintenance 

DIAL/LIDAR differential absorption light detection and ranging systems 

ELP enhanced LDAR program 

EPA U.S. Environmental Protection Agency 

ERG Eastern Research Group, Inc. 

ETV Environmental Technology Verification program 

FID flame-ionization detector 

FIP federal implementation plan 

FTIR Fourier transform infrared spectroscopy 

FOV field-of-view 

FPA focal plan array 

ft feet 

GF GasFindIR 

g/hr grams per hour 

GHG greenhouse gas 

GIT Gas Imaging Technologies, LLC 

GWP global warming potential 

HAP hazardous air pollutant 

HC hydrocarbon 

HgCdTe mercury cadmium telluride 

IMSS image multi-spectral sensing 

InSb indium antimonide 

IR infrared 

lbs pounds 

LDAR leak detection and repair 

LSI Leak Surveys, Inc. 

LSP leak simulation platform 

MDL minimum detection limit 

MDLR minimum detected leak rate 

mK millikelvin 

NECL noise equivalent concentration length 

NEIC National Enforcement Investigations Center 

NESHAP national emission standards for hazardous air pollutants 
ix 

NETD noise equivalent temperature difference 

NSPS new source performance standards 

OGI optical gas imaging 

OP-FTIR open-path Fourier transform infrared spectroscopy 

OP-TDL open-path tunable diode laser 

ORD Office of Research and Development 

ORS optical remote sensing 

PAT Pacific Advanced Technology 

PIA pixel intensity analyzer 

PID photo-ionization detector 

POL point of limitation 

PNNL Pacific Northwest National Laboratory 

ppm parts per million 

ppm•m parts per million – meters 

ppmv parts per million by volume 

RPM radial plume mapping 

RRF relative response factor 

SF6 sulfur hexafluoride 

SIP state implementation plan 

SOCMI synthetic organic chemicals manufacturing industry 

TSD technical support document 

UV-DOAS ultraviolet differential optical absorption spectrometer 

VOC volatile organic compound 

μm micrometer 

 
1 

I. BACKGROUND 

Fugitive emissions are a significant source of air emissions in the United States. The U.S. 

Environmental Protection Agency (EPA) defines fugitive emissions as emissions that could not 

reasonably pass through a stack, chimney, vent, or other functionally-equivalent opening. 

Examples of fugitive emissions include methane or volatile organic compounds (VOCs) from 

chemical plants or oil refineries, particulate emissions from handling solid raw materials in 

chemical or other manufacturing, or evaporative emissions of VOCs from wastewater treatment. 

The magnitude of fugitive emissions can be significant for a source category. For example, at 

chemical processing plants, one study showed that about half of all hydrocarbon emissions 

typically stem from fugitive emissions from equipment.35 An emissions inventory of four natural 

gas processing plants showed that more than 80% of methane emissions resulted from fugitive 

equipment leaks.17 Emissions from the oil and gas industry, specifically from production, 

transmission, storage, and distribution, are currently among the largest anthropogenic sources of 

U.S. methane emissions.129 In 2013, methane emissions from natural gas systems and petroleum 

systemsa were 157.4 and 25.2 million metric tons of carbon dioxide equivalents, respectively, 

representing 69% of methane emissions from the energy sector. Fugitive methane emissions 

from compressors, including compressor seals, are the primary emission source from natural gas 

processing.49 In emission projections to 2018, fugitive emissions continue to be the largest 

emission source category for the oil and gas sector.49 For the purposes of this document, fugitive 

emissions are the unplanned losses of gaseous compounds from pipes, valves, flanges, and other 

types of industrial equipment. 

A. Leak Detection and Repair 

Leak detection and repair (LDAR) programs are standardized regulatory work practices that are 

designed to reduce fugitive emissions of air pollutants from industry by identifying leaking 

equipment for repair.119 Regulatory LDAR programs first appeared in EPA regulations in 1983 

and continue today. Regulatory LDAR programs typically involve several elements: an inventory 

of equipment that could be leaking; monitoring the equipment to determine if there is a leak (as 

defined by the applicable regulation) using sensory monitoring (i.e., audio, visual, olfactory) or 

EPA Method 21, and performing corrective action on equipment that is found to be leaking. EPA 

Method 21 (Determination of Volatile Organic Compound Leaks) is the most common method 

for identifying leaking equipment. Method 21 monitoring requires the use of a portable 

instrument to detect VOC leaks above a certain action level from equipment such as valves, 

flanges, pressure relief devices, pump seals, compressor seals, agitator seals, connectors, openended lines, sampling connections, and other common industrial connections at individual 

sources. 

In 2008, the EPA introduced the Alternative Work Practice (AWP) as an option to replace 

standard work practices that use only Method 21 monitoring. The AWP allows LDAR programs 

the flexibility to implement OGI techniques for screening in lieu of Method 21. Instead of using 

a portable instrument to detect and measure the concentration of VOC leaks using a 

 

a

 IPCC source category 1B2a (onshore and offshore crude oil production, transportation, and refining operations). 
2 

photoionization detector (PID) or flame ionization detector (FID), OGI technology utilizes an 

infrared (IR) camera to make equipment leaks visual by means of thermographic imaging. 

Because OGI technology continues to evolve and improve, the EPA is conducting research into 

the current state of OGI technology to help standardize its use for regulatory purposes. The 

potential use of OGI technology has been presented in two Federal Register notices (National 

Uniform Emission Standards for Storage Vessel and Transfer Operations, Equipment Leaks, and 

Closed Vent Systems and Control Devices at 77 FR 76248, June 18, 2012; and Petroleum 

Refinery Sector Risk and Technology Review and New Source Performance Standards at 79 FR 

36880, June 30, 2014). A protocol for applying OGI technology will be codified at 40 CFR part 

60, appendix K. 

B. Purpose and Scope of this Document 

The purpose of this document is to provide technical background information on OGI. 

Information presented in this document will help the EPA in developing, evaluating, and 

promoting standardized prescriptive procedures for source characterization and compliance 

monitoring related to the use of OGI technology to detect fugitive gas emissions of VOCs, 

hazardous air pollutants (HAPs), and greenhouse gases (GHGs) (i.e., methane, sulfur 

hexafluoride) from industrial environments. 

Since the formation of the EPA in 1970, the issue of management and mitigation of the fugitive 

emissions from industrial activities to ambient air has received a lot of attention because of 

fugitive emissions’ direct effect on human health and the environment. This document reviews 

the evolution of federal regulations designed to control the amount of fugitive HAPs and VOCs 

released by leaking industrial equipment up to the current implementation of LDAR programs 

and the recent increase in use of OGI technology to assist these programs. The information 

presented in this document includes a review of publically available literature. This document 

focuses on the theory and performance of OGI technology application for LDAR programs and 

presents results from controlled laboratory studies aimed at characterizing the performance of 

OGI technology for leak detection. 

Following are the main organizational compartments of this document: 

• Section II – A summary of the regulatory history that covers regulatory and policy 

development up to today. 

• Section III – A technical literature review that discusses commercially available OGI 

technologies and associated studies. 

• Section IV – Research commissioned by the EPA for ERG to evaluate technology 

performance and methods related to the application of OGI for leak detection. 

• Section V – Summary and observations. 

• Section VI – Appendices and supporting documents. 
3 

II. POLICY AND REGULATIONS 

A. History of LDAR Based on the 1990 CAA Amendments 

Coincident with the formation of the EPA in 1970, Congress passed the Clean Air Act (CAA), 

which required the EPA to develop national ambient air quality standards (NAAQS) and 

establish measurement methods for criteria pollutants. Additionally, in response to the CAA’s 

directive to establish federal standards of performance for new sources within categories of 

sources contributing significantly to air pollution, the EPA launched the new source performance 

standards (NSPS) program. The intention of the NSPS program is to control emissions from new, 

modified, or reconstructed stationary sources by setting standards that limit emissions through 

the use of the best system of emission reduction, which takes into account the cost of achieving 

such reductions. Existing sources were regulated through state implementation plans (SIPs) or 

the federal implementation plan (FIP). 

Federal leak standards were first introduced when the NSPS for synthetic organic chemicals 

manufacturing industries (SOCMI) and petroleum refineries were promulgated in October 1983 

and May 1984, respectively. These actions required monitoring of specific types of equipment in 

VOC or HAP serviceb, depending on the regulation, using EPA Method 21 or other equivalent 

monitoring. The types of industrial equipment targeted in these actions included pumps, valves, 

compressors, pressure relief devices, sampling connection systems, open-ended lines, flanges, 

and other connector types.118 Along with the first leak standards, Method 21 was first

promulgated in 1983 at 40 CFR part 60, appendix A. 

During the first two decades after being founded, the EPA began to investigate the level of 

hazard associated with individual HAPs that were listed in the CAA and developed a list of 

stationary sources that emitted these HAPs. The EPA developed national emission standards for 

hazardous air pollutants (NESHAP) to reduce, by the maximum degree, the emissions of HAPs 

from these source categories. 

With the rise of new environmental issues getting public attention (e.g., inability to control HAP 

emissions from industrial sources, continued NAAQS non-attainment, increased emissions from 

automobiles, and acid rain), Congress passed the reauthorization of the CAA complete with over 

600 additional pages of amendments, known as the Clean Air Act Amendments of 1990 (1990 

CAAA).103 Following passage of the 1990 CAAA, the EPA developed a new strategy for 

addressing HAP issues that involved shifting the focus from individual HAPs to source 

categories that may emit multiple pollutants.102 This shift in regulatory approach resulted in the 

addition of source-specific NESHAPs based on Maximum Achievable Control Technology 

(MACT). MACT standards aim to reduce HAP emissions from stationary sources by requiring 

all sources to reduce their emissions to the levels of emissions achieved by the best performing 

sources in a source category. In 1990, with the introduction of the 1990 CAAA, Method 21 was 

revised to its current form. 

 

b

 In VOC or HAP service means that the equipment is expected to come into contact with and/or contain a liquid or 

gas with VOC or HAP, generally above a specific level (e.g., greater than 10% by weight). The definition of in 

VOC or HAP service varies by regulation. 
4 

The control of fugitive emissions (and, therefore, LDAR programs) is mostly implemented 

through these two major regulatory programs today: the NSPS and NESHAP programs. Table 2-

1 lists the major regulatory milestones that shaped current LDAR programs and requirements. 

Table 2-2 lists the federal regulations that require a formal LDAR program as of 2015. 

Table 2-1. Timeline of Major Regulatory Milestones Leading to Current Status 

Year Common Name Document 

1955 Air Pollution Control Act Public Law 84-159

1963 Clean Air Act (CAA) Public Law 88-206

1967 Air Quality Act Public Law 90-148

1970 National Environmental Policy Act (NEPA) Public Law 91-190

1970 Clean Air Act of 1970 (1970 CAA) Public Law 91-604

1983 NSPS LDAR and Method 21 Promulgation 48 FR 37598

1984 NESHAP (Part 61) LDAR Promulgation 49 FR 23513

1990 CAA amendments extend LDAR provisions to NESHAP 

MACT; (1990 Clean Air Act Amendments (CAAA)) 55 FR 25602, Public Law 101-549

2000 Consolidated Federal Air Rule (CAR) for Equipment Leaks 65 FR 78268

2008 Alternative Work Practice (AWP) Promulgation 73 FR 78199 (40 CFR 60.18, 

63.11, and 65.7) 

2008 Greenhouse Gas Reporting Rule 74 FR 56260

2011 Proposed Uniform Standards for Equipment Leaks 77 FR 36248 (40 CFR 65)

Table 2-2. Federal Regulations Requiring LDAR Programs with Method 21 Leak 

Monitoring22, 119

40 CFR 

Part and Subpart Regulation Title 

Part 60 Standards for Performance of New Stationary Sources (NSPS)

Subpart VV 

Standards of Performance for Equipment Leaks of VOC in the Synthetic Organic Chemicals 

Manufacturing Industry for which Construction, Reconstruction, or Modification 

Commenced After January 5, 1981, and on or Before November 7, 2006 

 VVa 

Standards of Performance for Equipment Leaks of VOC in the Synthetic Organic Chemicals 

Manufacturing Industry for Which Construction, Reconstruction, or Modification 

Commenced After November 7, 2006 

XX Standards of Performance for Bulk Gasoline Terminals

 DDD Standards of Performance for Volatile Organic Compound (VOC) Emissions from the 

Polymer Manufacturing Industry 

 GGG 

Standards of Performance for Equipment Leaks of VOC in Petroleum Refineries for which 

Construction, Reconstruction, or Modification Commenced After January 4, 1983, and on or 

Before November 7, 2006 

 GGGa Standards of Performance for Equipment Leaks of VOC in Petroleum Refineries for Which 

Construction, Reconstruction, or Modification Commenced After November 7, 2006 

 KKK 

Standards of Performance for Equipment Leaks of VOC From Onshore Natural Gas 

Processing Plants for Which Construction, Reconstruction, or Modification Commenced 

After January 20, 1984, and on or Before August 23, 2011 
5 

Table 2-2. Federal Regulations Requiring LDAR Programs with Method 21 Leak 

Monitoring22, 119

40 CFR 

Part and Subpart Regulation Title 

 QQQ Standards of Performance for VOC Emissions From Petroleum Refinery Wastewater 

Systems 

Part 61 National Emissions Standards for Hazardous Air Pollutants (NESHAP)

Subpart F National Emission Standard for Vinyl Chloride

J National Emission Standard for Equipment Leaks (Fugitive Emission Sources) of Benzene

L National Emission Standard for Benzene Emissions from Coke By-Product Recovery Plants

V National Emission Standard for Equipment Leaks (Fugitive Emission Sources)

BB National Emission Standard for Benzene Emissions From Benzene Transfer Operations

FF National Emission Standard for Benzene Waste Operations

Part 63 NESHAP for Source Categories – Maximum Achievable Control Technology (MACT)

Subpart H National Emission Standards for Organic Hazardous Air Pollutants for Equipment Leaks

 I National Emission Standards for Organic Hazardous Air Pollutants for Certain Processes 

Subject to the Negotiated Regulation for Equipment Leaks 

 J National Emission Standards for Organic Hazardous Air Pollutants for Polyvinyl Chloride 

and Copolymers Production 

 R National Emission Standards for Gasoline Distribution Facilities (Bulk Gasoline Terminals 

and Pipeline Breakout Stations) 

S National Emission Standards for Hazardous Air Pollutants from the Pulp and Paper Industry

 U National Emission Standards for Hazardous Air Pollutants Emissions: Group I Polymers and 

Resins 

 W National Emission Standards for Hazardous Air Pollutants for Epoxy Resins Production and 

Non-Nylon Polyamides Production 

Y National Emission Standards for Marine Tank Vessel Loading Operations

CC National Emission Standards for Hazardous Air Pollutants from Petroleum Refineries

 DD National Emission Standards for Hazardous Air Pollutants from Off-Site Waste and 

Recovery Operations 

GG National Emission Standards for Aerospace Manufacturing and Rework Facilities

 HH National Emission Standards for Hazardous Air Pollutants from Oil and Natural Gas 

Production Facilities 

OO National Emission Standards for Tanks – Level 1

PP National Emission Standards for Containers

QQ National Emission Standards for Surface Impoundments

 SS National Emission Standards for Closed Vent Systems, Control Devices, Recovery Devices,

and Routing to a Fuel Gas System or a Process 

TT National Emission Standards for Equipment Leaks – Control Level 1

UU National Emission Standards for Equipment Leaks – Control Level 2

WW National Emission Standards for Storage Vessels (Tanks) – Control Level 2

 XX National Emission Standards for Ethylene Manufacturing Process Units: Heat Exchange 

Systems and Waste Operations 

 YY National Emission Standards for Hazardous Air Pollutants for Source Categories: Generic 

Maximum Achievable Control Technology Standards 
6 

Table 2-2. Federal Regulations Requiring LDAR Programs with Method 21 Leak 

Monitoring22, 119

40 CFR 

Part and Subpart Regulation Title 

GGG National Emission Standards for Pharmaceuticals Production

 HHH National Emission Standards for Hazardous Air Pollutants from Natural Gas Transmission 

and Storage Facilities 

 III National Emission Standards for Hazardous Air Pollutants for Flexible Polyurethane Foam 

Production 

 JJJ National Emission Standards for Hazardous Air Pollutant Emissions: Group IV Polymers and

Resins 

 MMM National Emission Standards for Hazardous Air Pollutants for Pesticide Active Ingredient 

Production 

 OOO National Emission Standards for Hazardous Air Pollutant Emissions: Manufacture of 

Amino/Phenolic Resins 

 PPP National Emission Standards for Hazardous Air Pollutant Emissions for Polyether Polyols 

Production 

 VVV National Emission Standards for Hazardous Air Pollutants: Publicly Owned Treatment 

Works 

 EEEE National Emission Standards for Hazardous Air Pollutants: Organic Liquids Distribution 

(Non-Gasoline) 

 FFFF National Emission Standards for Hazardous Air Pollutants: Miscellaneous Organic Chemical 

Manufacturing 

BBBBB National Emission Standards for Hazardous Air Pollutants for Semiconductor Manufacturing

GGGGG National Emission Standards for Hazardous Air Pollutants: Site Remediation

 HHHHH National Emission Standards for Hazardous Air Pollutants: Miscellaneous Coating 

Manufacturing 

 BBBBBB National Emission Standards for Hazardous Air Pollutants for Source Category: Gasoline 

Distribution Bulk Terminals, Bulk Plants, and Pipeline Facilities 

VVVVVV Hazardous Air Pollutants for Chemical Manufacturing Area Sources

Part 65 Consolidated Federal Air Rule

Subpart F Equipment Leaks

Part 98 Mandatory Greenhouse Gas Reporting Program

Subpart W Petroleum and Natural Gas Systems

Part 264 Standards for Owners and Operators of Hazardous Waste Treatment, Storage, and Disposal 

Facilities 

Subpart BB Air Emission Standards for Equipment Leaks

Part 265 Interim Status Standards for Owners and Operators of Hazardous Waste Treatment, Storage, 

and Disposal Facilities 

BB Air Emission Standards for Equipment Leaks

B. Regulatory Status 

Both the EPA and industry encountered unexpected challenges in implementing LDAR 

programs with Method 21 following initial establishment of the LDAR programs listed in 
7 

Table 2-2. EPA Method 21 involves positioning an instrument probe near the source of a 

potential equipment leak and measuring the VOC concentration as the probe is judiciously (and 

slowly) scanned around the potential leak source. A formal LDAR program requires that the 

facility maintain an inventory of all equipment at the facility subject to the regulation, complete 

with unique equipment IDs, leak definition, monitoring frequency information, and previous 

screening and repair results. If the survey result for an individual piece of equipment is above the 

regulatory leak definition, then the equipment is considered to be leaking and must be repaired 

and rescreened within a prescribed time frame. With individual facilities easily having thousands 

of pieces of equipment to monitor, this process immediately becomes a heavy resource burden to 

industries seeking compliance. 

The following paragraphs present some of the challenges and findings of implementing LDAR 

programs using Method 21. 

1993. Methane is a potent GHG that is estimated to have 28-36 times more global warming 

potential (GWP) than carbon dioxide on a 100-year time frame.51 The overall threat of 

increasing GHG emissions to hasten global climate change compelled President Clinton to 

announce the Climate Change Action Plan of 1993. As a part of this plan, the EPA created 

the Natural Gas STAR program in 1993 to increase the awareness of methane emission 

sources and to serve as a platform for sharing emissions reduction innovations and best 

practices throughout the oil and natural gas industry.25 The primary goal of the Gas STAR 

program is to offer a voluntary, flexible, and cost-effective partnership between the 

government and the oil and natural gas industry. By volunteering to become a partner of the 

program, companies exchange information with the EPA and, in turn, the EPA provides 

news, updates, and regular transfer of information meetings to assist their facilities with 

emissions reduction in all areas of operations, including those that were not regulated. 

1995. Around this time, the term “Directed Inspection and Maintenance” (DI&M) started to 

appear in the literature relative to cost-effective strategies implemented by the facilities to 

proactively find and fix leaks. DI&M was one of the recommended practices introduced to 

industry in 1995 through the Gas STAR program. Industry began to realize that reducing 

fugitive emissions also meant reducing product loss and therefore could lead to improved 

economic performance. With a highly profitable product that was difficult to contain, the oil 

and natural gas industry was particularly interested in how to prevent methane product loss. 

However, not all companies willingly signed up for the Gas STAR program, and simply 

implementing the DI&M programs did not necessarily ensure that a facility using the practice 

was in compliance with all regulatory emissions control requirements. (DI&M does not 

satisfy the requirements for regulatory LDAR programs.)

1997. In 1997, the American Petroleum Institute (API) commissioned a study to investigate 

the possibility for conducting LDAR surveys in a more efficient manner.1 This study 

collected data from seven Los Angeles, California refineries over 5.5 years for a total of 11.5 

million refinery equipment measurements. Results showed that valve equipment in gas and 

light liquid service combined contributed an average of 68% of the total facility fugitive 

VOC emissions, while connectors in the same service contributed only 28% of the total 

facility fugitive VOC emissions, but were three times as abundant as valves by count of 

equipment monitored. A major discovery from this study was that 92% of the controllable 
8 

fugitive emissions (non-zero screening values) were attributed to just 0.13% of the total 

equipment monitored (as represented by Figure 2-1), and the study concluded that the current 

leak detection practice spends about 98% of the LDAR program’s effort monitoring nonleakers. The study went on to propose that a more cost effective method for LDAR program 

compliance should focus more on the high emission rate leakers and avoid performing EPA 

Method 21 monitoring on all equipment types during every survey. 

Figure 2-1. Distribution of the Total Equipment Counts and Estimated Emissions by 

Screening Range1

1997-1999. By 1999, it was obvious to the EPA that industry compliance reports were not 

matching up with results from comparison monitoring conducted by the EPA’s National 

Enforcement Investigations Center (NEIC).110 For example, 17 facilities were monitored 

during investigations by NEIC for several years, and while the average leak rate reported by 

facilities to the EPA was 1.3%, the NEIC found the average leak rate to be 5.0%. A potential 

explanation for this discrepancy appeared in a 1997 report by the Bay Area Air Quality 

Management District, whose findings showed that a one centimeter difference in analyzer 

position equated to a 57% chance of missing an actual leak.110 This amount of sensitivity to 

operator error while performing Method 21, and the resulting under-reporting of potentially 

80 million pounds of VOCs being emitted annually, fueled action by the EPA to find new 

ways to quickly and definitively identify significant leaks. 
9 

1999. Starting around 1999, to address poor performing LDAR programs, the Department of 

Justice teamed up with the EPA to issue civil penalties and consent decrees to industry 

LDAR programs that were found to be deficient. The consent decrees instructed the 

penalized facility to implement a stricter program of leak detection and repair monitoring 

called “Enhanced LDAR.”22,62 Enhanced LDAR programs (ELPs) go above and beyond 

regulatory LDAR requirements to systematically improve the performance of a facility’s 

LDAR program. ELPs include tighter restrictions and/or more activity in subsections such as: 

documentation, monitoring frequency, LDAR action levels, repairs, delay of repairs, 

equipment upgrades, training, LDAR audits, recordkeeping, and reporting.62 ELPs have 

resulted in considerable emissions reductions at individual facilities.97

2002-2005. Clearstone Engineering conducted two studies (in 200017 and 2004-200518) that 

evaluated the potential for methane emissions reduction and cost-saving opportunities at gas 

processing facilities. In both studies, Clearstone found that fugitive equipment leaks 

contributed the majority of methane and non-methane hydrocarbon emissions and that, of the 

fugitive equipment leak emission categories, equipment that is associated with vibrational 

and heat-cycle services contributed a large majority of the total fugitive emissions. A 

significant result of the 2002 Clearstone report was that an estimated 94.9% of total natural 

gas losses would be cost-effective to reduce. However, similar to findings of the 1997 API 

study1, both Clearstone studies found that only a small percentage (2.4% of all the equipment 

surveyed) under hydrocarbon service were determined to be leaking, in this case using a leak 

definition of 10,000 parts per million by volume (ppmv). The Clearstone studies also 

prompted the Gas Technology Institute (GTI, formerly known as the Gas Research Institute, 

GRI) to petition the EPA for acceptance of alternative work practices to Method 21 as early 

as 2000.17

The 2002 Clearstone study also indicated that using a HiFlowTM Sampler could provide more 

accurate estimates of actual leak rates versus Method 21. The HiFlowTM Sampler was developed 

by GTI as an economic means of estimating the emission rate from individual leaking equipment 

components with sufficient accuracy to allow an objective cost-benefit analysis of each repair 

opportunity. Leak source emission rate is the product of the measured pollutant concentration 

and the measured leak flow rate. Emission rates, as opposed to actual pollutant concentrations, 

provide an assessment of the severity of the leak in terms of air mass volume and time, which 

can in turn be used to determine long and short term exposure. In addition to tools such as the 

HiFlowTM Sampler, a more accurate way to determine the mass emission rate of fugitive gases 

from equipment leak sources is through “baggingc” or physical isolation techniques.116 However, 

this technique is estimated to cost roughly $500 per equipment component; and with facilities 

having as many as a million components, this technique is impractical and prohibitively 

expensive. 

 

c

 Bagging is a method to measure the emission rate from an equipment component by isolating the component from 

ambient air to collect any leaking compound(s). A tent (i.e., bag) made of material impermeable to the 

compound(s) of interest is constructed around the leak interface of the piece of equipment. More information on 

bagging can be found in Section 4 of the EPA’s Protocol for Equipment Leak Emission Estimates 

(http://www.epa.gov/ttn/chief/efdocs/equiplks.pdf). 
10 

EPA studies have correlated Method 21 concentration measurement values with a mass 

emissions rate from available bagging data as a way to estimate mass emissions rates for whole 

facilities.116 However, because current OGI technology cannot reliably measure gas 

concentration values, a more resource intensive method such as EPA Method 21, bagging, or 

radial plume mapping with Fourier Transform Infrared Spectroscopy/Tunable Diode Laser/ 

Differential Optical Absorption Spectrometer (FTIR/TDL/DOAS) would still be required to 

estimate facility emission rates.115 

Following the Clearstone report in 2002,17 Natural Gas STAR began to publish “Lessons 

Learned” documents as technical references. Natural Gas STAR industry partners evaluated 

the effectiveness of DI&M programs to cut total facility emissions while also reducing 

facility costs. The projected cost curves from the Clearstone 2002 study indicated the 

likelihood that industry could make choices that would result in financial improvement with 

the added benefit of reducing fugitive emissions to the atmosphere, which appealed to state 

and federal regulators. Since 2002, the Natural Gas STAR program has published 19 Lessons 

Learned, covering sources such as compressors, dehydrators, and pneumatics and controls. 

The Lessons Learned serve as comprehensive guides for implementing methane emission 

reduction technologies and practices and summarize cost and benefit information. 

2006-2007. Furry et al., 2006; Reese et al., 2007 and Trefiak, 2006 reported for industry on 

LDAR applications and technology challenges. These reports all agree that the 

implementation of Method 21 is timely and expensive, while advancing technologies offer 

promise to streamline and reduce the cost of routine monitoring.35,80,98 A paper by Robinson 

et al. in 2007 found that using OGI technology to assist the periodic screening procedures 

increases the survey rate of equipment dramatically from about 60 pieces of equipment per 

hour with Method 21 to over 2,000 pieces of equipment per hour with OGI technology and 

that OGI technology-assisted surveys identified 97% of the total mass emissions detected 

from leaking sources with Method 21.85 These studies provided evidence that using OGI 

technology to assist LDAR programs with their regular equipment surveys promises to be a 

quicker and more cost-effective method of identifying the largest sources of leaking 

emissions relative to Method 21 and will increase the amount of total facility fugitive 

emissions reduction because OGI technology can identify fugitive emissions from all 

equipment categories, regardless of whether that equipment is mandated for LDAR program 

compliance or not. 

Grievances from industry, in addition to information on the difficulties of using Method 21, led 

to the proposal and ultimate promulgation of the AWP in 2008. The AWP, also commonly 

known as “Smart LDAR,” gives LDAR programs the flexibility to implement OGI techniques 

for equipment screening in lieu of Method 21. Industry’s initial response to the proposal of the 

AWP was favorable and even enthusiastic.68,80,98 However, due to concerns raised during the 

proposal of the AWP about whether OGI technology could detect persistent low-leaking 

equipment, the EPA included an annual Method 21 survey requirement in the AWP, with a 

statement that this requirement would be revisited as people began to use the AWP and more 

information on OGI technology became available. This resulted in a lack of interest by industry 

to utilize the AWP in lieu of standard LDAR monitoring. Nonetheless, the promulgation of the 

AWP in 2008 was a catalyst for a flurry of studies and publications on its 

implementation.10,11,68,78 
11 

On March 26, 2012, the EPA proposed a set of emission standards for storage vessels and 

transfer operations, equipment leaks, and closed vent systems and control devices known as the 

“Uniform Standards” in an effort to ensure consistency and streamline recordkeeping and 

reporting requirements for facilities with sources subject to multiple regulations.48,127 The 

requirements proposed in the Uniform Standards would be applicable only when referenced by a 

specific NESHAP or NSPS. As part of the Uniform Standards, the EPA proposed to allow the 

use of OGI technology in lieu of Method 21, as long as use of OGI technology followed the 

requirements of the protocol for use of OGI technology in 40 CFR 60, Appendix K, which has 

not yet been developed. The EPA recognized the potential in OGI technology for streamlining 

compliance activities related to emissions control, but because there is a well-documented need 

for OGI technology performance and operational studies,94 the EPA still needed more data 

before concrete specifications could be outlined. The EPA received numerous comments on the 

proposal, but has not yet finalized the Uniform Standards.

States may opt to set emission standards that are more stringent than those required by the EPA. 

One such example is the enactment of Colorado’s Air Quality Control Commission (AQCC) 

Regulation Number 7 in 2014, which covers the oil and natural gas sectors. This rule allows 

owners or operators to use one of the Approved Instrument Monitoring Method (AIMM), such as 

Method 21, OGI technology or any other Division approved instrument based monitoring device 

or method.21 Some of the more progressive requirements included into Regulation 7 include: 

• Provisions to reduce methane emissions from oil and gas development (first state in the 

nation to address methane); 

• Increased control and inspection requirements for storage tanks (first standard in the U.S. 

to require tank emissions are captured and routed to control devices); 

• Added requirement for well production facilities to connect their gas streams to a pipeline 

or control device from the first date of production; 

• More stringent control requirements for glycol dehydrators; 

• Extended the LDAR program requirements to include open-ended valves and lines; and 

• Specifies the requirement of the use of best management practices (including increased 

use/allowance for OGI camera application and comprehensive recordkeeping and 

reporting) for well maintenance. 

Colorado’s Regulation 7 requirements prescribe LDAR program schedules according to 

threshold emission rates (in tons per year). This indicates that at least one LDAR screening 

survey is conducted via Method 21 or comparable quantification method. Thereafter, facilities 

are allowed to use AIMMs, such as OGI cameras, for LDAR surveys. 

C. Costing Evaluations 

[This section will discuss the results from studies performed on the financial burden and 

projected savings in relation to fugitive leak emissions reduction activities.] 
12 

III. LITERATURE REVIEW

ERG searched the literature to identify the technology, applications, and limitations of the 

current remote measurement and monitoring technologies. This section presents the findings of 

the literature search. 

A. Technology 

1. History 

Remote measurement and monitoring technologies have been available since the 1970s and 

extensive efforts have been made to make these technologies more widely acceptable to the 

monitoring community.4,15,65,86,108,124 In late 2011, the EPA published the Optical Remote 

Sensing (ORS) for Measurement and Monitoring of Emissions Flux handbook,71 which lists 

some of the more prominent technologies and applications, including: 

• Ultraviolet Differential Optical Absorption Spectrometer (UV-DOAS) 

• Open-Path Fourier Transform Infrared Spectroscopy (OP-FTIR) 

• Raman spectroscopy 

• Tunable Diode Laser (OP-TDL) 

• Differential Absorption Light Detection and Ranging Systems (DIAL/LIDAR) 

• OTM-10d/Radial Plume Mapping (RPM) 

• Eddy Covariance Flux 

• Optical Gas Imaging (OGI). 

The application of some of these technologies has been difficult, especially with respect to 

LDAR programs. Roadblocks include: high cost, complex measurement theory, need for highly 

specialized operators, difficulty-of-use, identification of leak location, and inconsistent units of 

measure for data output to the end-user (e.g., parts per million – meters (ppm·m), path-averaged 

concentration).124 

The scope of the literature search was broad initially, but ERG focused on leak detection 

technologies based on IR imaging (both active and passive) due to the potential for these 

technologies to reduce the time, labor, and cost of equipment monitoring for LDAR program 

compliance.129 Of these technologies, the EPA selected only OGI cameras for implementation 

for the AWP. Other technologies were not selected because of the reasons above, in addition to 

technical limitations and interferences.68 In-depth discussion on the different ORS technologies

and their strengths, weaknesses, and applications can be found in the EPA ORS handbook124 

 

d

 OTM-10 is “Other Test Method 10 – Optical Remote Sensing for Emission Characterization from Non-Point 

Sources” that contains various configurations of radial plume mapping or RPM. It is available from the EPA at 

http://www.epa.gov/ttn/emc/prelim.html. 
13 

2. Basis of OGI technology 

OGI cameras produce images of gaseous emissions using one of two different IR sensing 

approaches: active or passive IR imaging. Active IR imaging provides the IR light source via 

controlled laser output to the environment that is then reflected off the background and 

attenuated or absorbed as it encounters gas species along the optical path. Passive IR imaging 

uses available IR radiation (anything with a temperature—above 0 K—produces IR radiation) to 

detect differences in the IR intensity between background IR and gas plume IR radiation. The 

type of gas species that will be imaged is a function of the spectral transmission window in the 

camera design. For example, many common OGI cameras for VOC detection have a bandpass 

filter that allows transmission of the 3.2 to 3.4 micrometer (μm) spectral region to the detector. 

This spectral region is characteristic of the stretching vibrational energy between a carbonhydrogen (C-H) bond and is typically targeted when trying to detect or measure gases containing 

alkanes, alkenes, aromatics, and other hydrocarbons (such as methane, benzene, propane, butane 

and many others).92 OGI cameras with bandpass filters that allow the transmission of different 

spectral windows can target different gas types; such as 4.52 – 4.67 μm for carbon monoxide, 

10.3 – 10.7 μm for sulfur hexafluoride and anhydrous ammonia, and 8.0 – 8.6 μm for refrigerant 

gases.34

Active IR Imaging 

Backscatter Absorption Gas Imaging (BAGI) cameras produce a live image by illuminating the 

viewing area with infrared laser light and detecting the amount of reflected (or backscattered) 

laser light returned to the instrument’s detector. When the laser light of a specified wavelength is 

strongly absorbed by a gas, a shadowy cloud of that gas becomes visible as a darkened area in 

the live image.84 This method of hydrocarbon gas leak detection works independently of ambient 

conditions but is limited by the laser wavelength output specified. Active IR imagers that use 

carbon dioxide lasers for their light source are unable to illuminate some target hydrocarbons 

such as methane. Sandia National Laboratories has developed two BAGI cameras to address the 

laser wavelength limitations: one for petroleum refineries, and one for the natural gas industry 

(to detect methane). 

For the BAGI technology to image a leak there must be some sort of reflective surface close 

behind the leak.84,85 A leak cannot be imaged against the sky or a distant background because the 

camera detector will not receive sufficient backscattered light intensity. As of 2007, BAGI 

cameras from Sandia National Laboratories and Laser Imaging Systems weighed between 20 and 

30 pounds and could only run about 1 to 1.5 hours on battery power.84,85 Quantification is not yet 

available with this technology and eye-safety for surrounding personnel is a concern due to laser 

output. 

Passive IR Imaging 

Due to the power demands and optical complexity of using controlled light sources with active 

IR imaging, manufacturers of OGI cameras will more commonly turn to passive IR imaging 

techniques to develop a more market viable system. Passive IR imaging cameras typically 

comprise an IR-transmissive lens, a staring focal plane array (FPA) detector, a cooling system, 
14 

and a processing system.8,64 The selection of the FPA depends on the wavelength region of 

interest. 

For detection of hydrocarbons, the region of interest is typically 3 – 5 μm, for which a detector 

made of indium antimonide (InSb) is the FPA of choice. However, in order to generate an image 

of sufficient contrast between gas plumes and the apparent background, passive IR imagers need 

stricter controls on the spectral bandwidth of the image and a reduction of signal noise. To 

address noise reduction in OGI detectors, a cooling module (like a Stirling engine) is 

incorporated into the camera design to cool the detector. 

Recently there has been research and developments using microbolometer detectors which have 

resulted in products (such as Bertin Technologies’ Second Sight9) now being commercially 

available. Microbolometer detectors do not need to be cryo-cooled; however, the physics behind 

the thermal conductivity response mechanism of microbolometer-based devices renders them 

slower and less sensitive than cooled photo-detection devices, like InSb FPAs. 50

Two very different techniques have evolved to control the spectral bandwidth of passive IR 

imagers, band-pass filter and diffractive optics. Opgal and FLIR Systems, Inc. have each 

developed their own offering of an IR camera (the EyeCGas and GasFindIR 320 (GF320), 

respectively) based on OGI technology that restricts bandwidth to 3.2 – 3.4 μm. This bandwidth 

is spectrally harmonious with major absorption lines in the spectra of many target gases as 

mentioned above.26 Because of the lack of complexity with this type of camera design, it is 

smaller, easier to use, and more robust. 

Another way to control the spectral bandwidth is through methods called hyperspectral and 

multispectral imaging. Recent advances of this technology have increased the number of 

potential OGI instruments for leak detection applications since the start of this effort by the EPA 

to evaluate all commercially available OGI technology systems. Some of these upcoming 

instruments are not yet ready for commercial distribution and/or are so new that performance 

studies are either still underway or have yet to be planned. As this document is currently still in 

draft form, more analysis will be incorporated as newer OGI technology systems and relevant 

study data becomes available. 

Gas Imaging Technologies, LLC (GIT) has developed the Sherlock® VOC OGI camera, which 

uses diffractive optics and multispectral image processing to image, speciate, and quantify 

fugitive gas emissions. The Sherlock® VOC camera operates based on the principles of image 

multi-spectral sensing (IMSS). IMSS is a form of diffractive optics whereby the incident light 

being received through the camera lens is both imaged and dispersed using a combination of a 

diffractive imaging spectrometer and an adaptive tunable filter.40,42,43,44,45,46 Similar to a 

monochromator, where light is separated spectrally and the light that passes through the exit slit 

is scanned, with IMSS the light is spectrally dispersed using an optical lens that can be focused 

along the optical axis to produce images of narrow spectral bands that are measured sequentially 

in time on the FPA detector. See Figure 3-1 for an example of the basic concept of IMSS 

compared to a monochromator. 
15 

Figure 3-1. Basic Principle of IMSS Diffractive Optics45

The camera operator of a Sherlock® VOC has full control on the motion of the optical lens, 

allowing the operator to scan a series of wavelengths or dwell indefinitely on one wavelength.46

The result is a frame-by-frame imaging of different spectral wavelengths that can be selected and 

combined with visual images to show gas leaks as false color. By selecting to visualize different 

wavelengths, it is possible to distinguish between gas species with the Sherlock® VOC; however, 

the exact identification and quantification of gas concentration procedures utilized by the 

associated software has not yet been evaluated in this document because it is proprietary. 

Declaring that the Sherlock® VOC can quantify gas concentrations comes with a heavy caveat as 

verification studies by an external party has not yet been performed and QA evaluations on any 

measured gas concentrations produced by the Sherlock® VOC still need to be carefully studied.

US Patent # 668077846 for the Sherlock® “Gas Leak Detector” states this technology determines 

concentrations of the target chemical by calculating the absorption (or emission) of the target 

chemical at its absorption (or emission) wavelength through the gas plume and comparing this 

value to absorption amounts at the same wavelength measured simultaneously from a 

background (out-of-plume) region. In a presentation at the 99th annual meeting of the Air and 

Waste Management Association (AWMA), Hinnrichs et al.47 explained further that the log of the 

ratio of the signal intensity from the gas and the background is equal to the product of the 

absorption coefficient of the gas, the path length of the gas, and the concentration of the gas, as 

illustrated in the equation below. The plume depth (or path length) is determined by assuming 

the gas plume is symmetric and using the 2D pixel footprint of the image of the gas.47 

−  	



 = 	

The quantification of gas concentration by the Sherlock® VOC was compared with results from a 

FID at an oil and gas plant in Viggiano, Italy.47 The study did not find many leaking equipment 

detected by EPA Method 21, and so the comparison was limited to six measurements. Of these 

six measurements, three had concentrations higher than the FID saturation level, and one was 

taken during rain, which interfered with the FID detection. The study claimed that the two 

remaining measurements agreed well, providing Figure 3-2 as evidence of good correlation. 

Where the FID measured 3,300 ppm, the Sherlock® VOC measured 4,530 ppm. And where the 

FID measured 9,155 ppm, the Sherlock® VOC measured 9,060 ppm. These measurements equate 

Monochromator IMSS
16 

to a relative percent difference of 31% and 1%, respectively. Added in the conclusions of this 

study is a statement regarding the need for more testing to better understand the accuracy of the 

Sherlock® VOC’s gas concentration quantification performance.47 

Figure 3-2. Correlation Between the Concentration Measurements Made by the FID Device 

as Compared to that Using the Sherlock® VOC47

Gas-imaging devices based on OGI technology operate by visually representing the temperature 

profile in a field of view where a gas cloud has a different thermal signature than its apparent 

background. The difference between the temperature of a targeted gas cloud and the temperature 

of the apparent background for that gas cloud is known as “delta-T” (∆T). This is an important 

property to understand with respect to OGI technology because the greater the difference in 

temperature between the gas cloud and its apparent background (or the larger the absolute value 

of ∆T becomes), the higher the contrast between the two objects will appear in the OGI 

technology display and the more likely it will be for that leak to be detected by the OGI 

technology operator or automated display algorithm. 

3. Available Technology 

Both FLIR and GIT have long-wave IR options for imaging gases such as sulfur hexafluoride 

(SF6) and ammonia (NH3). As current LDAR activities focus principally on gases that absorb in 

the mid-wave IR (3 – 5 μm), so does this review. Commercially available OGI systems that 

operate in the mid-wave IR are displayed in Table 3-1 with estimated purchase costs, safety 

certifications, notes on the detector technology, and whether the manufacturer offers capability to 

quantify gas concentration (via software) or not. 
17 

Table 3-1. Currently Commercially Available Handheld OGI Camera Systems 

Model Make Est. Cost Intrinsically 

Safe? 

Detector 

Technology Quant? 

GF320 FLIR $85,000 No InSb No

EyeCGas Opgal $86,500 Yes HgCdTe No

Sherlock®

VOC 

Gas Imaging 

Technology $100,000 No Diffractive w/ InSb Yes* 

* The ability of the Sherlock® VOC to consistently provide a quantification value for gas concentration has not been 

sufficiently evaluated or verified.41 

The allowance for the application of OGI cameras in regulatory LDAR programs through the 

AWP was partly to help alleviate the time, labor, and financial cost of compliance for industry 

and partly to help improve the rule effectiveness of LDAR programs. In order for the technology 

to meet these objectives, it must be able to consistently visualize target compound leaks at 

concentrations equal to the leak definition as specified by the applicable regulation. It also must 

be field portable so that an LDAR inspector can comfortably use the OGI technology for the 

duration of the LDAR survey without interruption for power (battery life), data (space), or 

physical demands (not too heavy or bulky). Ideally, the technology would be easy to deploy with 

minimal training and staffing requirements, have a reasonable cost for initial purchase and 

maintenance, and not endanger the OGI operators (be intrinsically safe in hazardous 

environments). The technology must be rugged enough for routine field use and provide a near 

real-time response with the capability of identifying the exact source of the leak. 

Other potential units, such as Bertin Technologies’ Second Sight TC and Telops Hyper-Cam 

have been excluded from this list due to the impractical weight and size of the units for LDAR 

application.9,53,63 The Sherlock® VOC has also been determined impractical for LDAR 

applications by the EPA for similar reasons.127 However, the Environmental Technology 

Verification (ETV) program did perform similar performance assessments on the FLIR 

GasFindIRTM MW (the predecessor to the FLIR GF320) and Sherlock® VOC cameras which 

demonstrated that the minimum detection limits (MDLs) for the Sherlock® VOC were generally 

higher and that the FLIR GasFindIRTM MW performed better overall. Results from these ETV 

assessments are provided in Table 3-2 and described in the next section.10,11 

B. Observations and Improvements 

Because of the importance proper leak identification and repair ultimately has on human health, 

safety, and the environment, many studies have been conducted to try and delineate the expected 

technology performance, limitations, and best practices associated with performing leak 

detection surveys using OGI cameras. This section presents summaries of key efforts at 

evaluating detection limit performance, operational conditions, and emission rate estimates. 

1. Initial OGI Technology Performance Studies 

After an intensive air quality study in Texas in 2000 revealed a discrepancy between aerial 

measurements of chemical species concentrations in the atmosphere over the Houston-Galveston 

area and what investigators expected the chemical species concentrations to be based on 
18 

available VOC emission inventory estimates, the Texas Commission on Environmental Quality 

(TCEQ) focused its efforts on better characterizing fugitive emissions through the development 

of additional leak detection and evaluation methods and using these new methods and 

conventional methods to update emissions factors and correlation equations.24 The TCEQ funded 

studies to conduct evaluations of OGI technology to assist leak detection surveys at chemical and 

petroleum facilities. The ENVIRON International Corporation (Environ) was appointed by the 

Texas Council on Environmental Technology (TCET, which was later absorbed into TCEQ) in 

June 2003 to conduct the first of these studies. 

TCEQ/Environ Study24

The main objectives for Environ in this study were to conduct a laboratory evaluation on OGI 

technology and to conduct a field evaluation on OGI technology for the development of a 

monitoring protocol using OGI technology for leak detection and updated emission factors 

and/or correlation equations.24 Four OGI technology-based IR cameras were evaluated in the 

laboratory: 

• Pacific Advanced Technology’s (PAT) IMSS passive IR imaging camera (the 

predecessor to GIT’s Sherlock® VOC) 

• Laser Imaging Systems’ Long-wave BAGI active IR imaging camera 

• Sandia National Laboratory’s Mid-wave BAGI active IR imaging camera 

• Leak Survey, Inc.’s (LSI) Hawk passive IR imaging camera (the predecessor to FLIR’s 

GasFindIR and GF320 cameras). 

The tests were performed at the BP laboratory in Naperville, IL as detailed in the Environ report. 

The experimental set up that resulted from this effort was later used to conduct further OGI 

technology performance evaluations described later in this document. 5,10,11,74,75

Delta-T (∆T) 

The TCEQ/Environ study employed a copper plate background painted flat black to assess the 

ability for PAT’s IMSS and LSI’s Hawk OGI cameras to detect gases as the ∆T approaches zero. 

Under controlled laboratory conditions, they found that both cameras were able to detect 60 

grams per hour (g/hr) butane test gas with a ∆T as little as 0.5°C.24 This result prompted the 

investigators to conclude that the ∆T parameter was not crucial in OGI technology leak detection 

as the OGI technology instruments were sensitive enough to be able to visualize gas leaks with 

very small ∆T values. 

Laboratory Minimum Detection Limit Tests 

The TCEQ/Environ study evaluated the minimum detectable mass emission rates of the four 

OGI cameras under controlled laboratory conditions for the following gas species of interest: 

ethylene, 1,3-butadiene, 1-butene, and propylene. Butane gas was also tested where time and 

resources allowed. All four OGI cameras were able to detect all test gases at mass emission rates 

less than 60 g/hr except the Mid-wave BAGI camera could not detect 1,3-butadiene and butane 

test gas was not evaluated for the Long-wave BAGI OGI camera. Table 3-2 summarizes the 
19 

results for each OGI camera under low wind conditions with a concrete background at a distance 

of 10 feet (ft) from the leak source. 

Table 3-2. Average Minimum Detection Level Mass Emission Rates (g/hr), Number of 

Measurements in Parentheses24

OGI Camera Ethylene 1,3-Butadiene 1-Butene Propylene Butane 

PAT’s IMSS 36 (3) 27 (3) 18 (3) 25 (4) 15 (3)* 

Long-Wave 

BAGI 6 (5) 19 (3) 28 (3) 24 (3) Not Tested 

Mid-Wave 

BAGI 21 (3) Not Detected 

Below 60 g/hr 8 (3) 17 (4) 1 (3) 

LSI Hawk 14 (3) 18 (2) 5 (5) 7 (3) 5 (5) 

* Results are uncertain and expected to be biased high due to a leak in the gas delivery system that was discovered 

after testing. 

Other parameters expected to affect the leak detection capability of OGI cameras were tested 

during the TCEQ/Environ study. Two different backgrounds were employed to simulate various 

industrial conditions: concrete wall and metal gas cylinders (to represent metallic background 

equipment). Two different wind speeds were evaluated: low wind speeds (between 0 and 2 mph) 

and high wind speeds (between 3 and 5 mph). The leaking source was imaged at two distances 

(10 ft and 20 ft) to evaluate the impact distance from leak source had on leak detection 

capability. 

To investigate the impact of a reflective background, the TCEQ/Environ study used metal 

cylinders as an experimental background. The results indicate that the “darker” areas of the metal 

cylinders prevented plume detection in those areas, but did not impact the overall minimum 

detection limits for any of the OGI cameras tested as the movement of the test gas plume was 

still visible in the “lighter” areas of the metal cylinder background. However, preliminary study 

data indicate that there is an impact on the minimum detection limit capabilities for each OGI 

camera by the other conditions tested (namely, higher wind speeds and farther distances from the 

leak source). 

In February 2004, Environ carried out the field portion of a study on the performance of different 

OGI camera technologies.24 This field study found that none of the four OGI camera

technologies tested or Method 21, alone or in combination, detected all gas leaks. A total of 66 

leaks were found at two study locations, representing normal industrial conditions for leaks of 

ethylene, propylene, butenes, 1,3-butadiene, and hexanes. The four OGI cameras found 31 of the 

66 leaks (47%), and Method 21 found 49 of the 66 leaks (74%). Nonetheless, OGI camera 

surveys detected 533.9 g/hr of the overall 595.4 g/hr mass emissions found by Method 21 and 

measured by bagging, or about 90%, and indicate that the OGI cameras captured the majority of 

the larger leaks. Figure 3-3 is a graphical representation of the leaks seen or unseen by each OGI 

technology over the measured mass emission rate determined by bagging.24 
20 

Figure 3-3. Field Survey Performance Summary of Infrared Cameras24 

The y-axis in Figure 3-3 is unitless, the black X data points represent the leak rates of leaks 

discovered via Method 21 but not detected by the OGI cameras, and the hollow data points 

represent a bagged leak that was not detected by the camera. Of the OGI camera technologies 

tested, passive IR (the LSI Hawk, predecessor to the FLIR and Opgal OGI cameras) detected the 

lowest mass emission leak (1.4 g/hr), detected the most leaks, detected all leaks above the 

Method 21 equivalency leak ratee of 60 g/hr, and detected all leaks larger than 21 g/hr.24 The 

other camera technologies tested missed leaks either near or above the Method 21 equivalency 

leak rate of 60 g/hr. The IMSS camera (i.e., Sherlock® VOC) detected leaks that could not be 

verified with Method 21, these were labeled as “False Positives” and are depicted on the left side 

of Figure 3-3 in the zero region.24 According to this study—based on the OGI camera 

technologies available at the time of the study and the compounds detected—cameras designed 

with passive IR OGI technology are the most practicable and reliable for leak detection surveys. 

Because LDAR applicable OGI cameras alone are not yet able to quantify the concentration or 

mass emission rates of fugitive gas emissions, and because there is still some concern remaining 

over OGI detection of very small leaks, other detection technologies may be useful when 

combined with AWP surveys. For example, a PID is a highly sensitive hand held device that can 

be extremely useful when coupled into an AWP program.90 However, a PID will measure only 

gas concentrations and not direct mass emission rates, thereby, still requiring the application of 

correlation equations to calculate whole facility leak mass emission rates as with the current 

 

e

 Common Method 21 leak definitions of 500, 1,000, and 10,000 ppmv are employed by various LDAR program 

regulations to ensure a specific level of environmental protection from fugitive emissions. Monte Carlo analysis 

has been extensively studied as a way to determine the leak rate level that would result in an equivalent level of 

environmental protection when OGI technology is used in lieu of Method 21. For the purposes of AWP 

implementation, the EPA approved an equivalency leak rate of 60 g/hr when monitoring is performed on a bimonthly frequency.109
21 

work practice of Method 21. However, at the time of publication, the results of the TCEQ study 

gained OGI technology favorable attention from industry for its cost, size, weight, portability, 

performance, user-friendliness, and value as a potential tool to assist AWP leak detection 

surveys.74

2. API Follow-on Studies5,74,75

One year after the TCEQ/Environ study, the API sponsored continuation studies using the same 

laboratory facility in Naperville, IL to evaluate two newer OGI cameras: the FLIR GasFindIR, 

and the PAT Sherlock. Studies by Panek74,75 and Benson5 report on the results from these followon efforts. 

Operational conditions such as lens focal length, gas temperature, background composition, 

steam presence, wind speed, and gas mixture versus pure compound were evaluated as possible 

convoluting factors when establishing new detection limits for FLIR GF-series OGI 

cameras.5,74,75 

• The focal length of the lens did affect the detection capability of the camera. Using the 

same lens but increasing the distance to the target resulted in increased detection limits. 

Conversely, higher focal length lenses had better detection limits compared to shorter 

focal length lenses at the same distance.5,75 Minimum detected leak rates (MDLRs) were 

plotted versus standoff distance in Figure 3-4 to illustrate this effect. 

• Adding to the efforts of the earlier TCEQ study, Panek75 found that an increase in the gas 

temperature increased the visible contrast of the gas plume against a uniform background 

(by increasing the temperature differential between the gas and the background) and lead 

to a reduction of detection limits.75

• The detection limits for imaging gas against a background of metal cylinders were higher 

than those with a uniform concrete background. It is assumed that this is because of a 

lack of thermal contrast between the gas and the cylinder background.75

• The Panek75 study did not detect steam that was generated by a pump. However, when 

steam was produced using a hot vapor generator, the plume was easily visible.75

• MDLRs are presented for 20 compounds at three different wind speeds in Tables 3-3 

through 3-5. These tables illustrate that higher wind speeds and measuring mixtures of 

the pollutants versus pure chemical both resulted in higher MDLRs.5
22 

Figure 3-4. MDLRs Versus Standoff Distance for Three Lenses5 

Table 3-3. Summary of Controlled Laboratory Testing Minimum Detection Limits (g/hr) at 

Various Wind Speeds74

OGI Camera Sherlock GasFindIR 

Compound 0 mph 2 mph 5 mph 0 mph 2 mph 5 mph 

Benzene 34.72 >66* ND >70.1* >70.1* >70.1*

Ethylbenzene 20.6 48.9 ND 7.6 53.2 >75.9*

Heptane 13.55 28.8 >51.4* 3 21 48

Hexane 4.4 18.25 52.1 2.9 37.6 57.8

Isoprene 28.8 >51.4* ND 32.8 59.6 >59.6*

Methanol 23.5 55.4 >153.9* 16.7 41.7 69.3

MEK 32.15 61.1 ND 5.3 60 >70.5*

MIBK 11.1 60.4 ND 7.01 24.6 70.1

Octane 11.1 31.7 ND 4.36 18.7 62.2

Pentane Not tested Not tested Not tested 13.8 25.4 45.8

1-Pentene 9.85 >25.2* ND 14 30.9 47.7

Toluene 34.3 >65.2* ND 22.6 >75.3* >75.3*

Xylene 30.75 64.9 ND 15.1 52.8 >75.3*

* The values in this table with a greater than sign indicate where the gas was imaged at a leak rate above that which 

the laboratory design was to quantify. This represents that the gas is able to be detected, but the MDLR could not 

be determined using the available equipment. ND = Not Detected. 
23 

Table 3-4. Summary of Controlled Laboratory Minimum Detection Limits (g/hr) for Pure 

Gases at Various Wind Speeds74 

OGI Camera Sherlock GasFindIR 

Compound 0 mph 2 mph 5 mph 0 mph 2 mph 5 mph 

Butane Not tested 2.85 24.25 0.72 5.8 15.9

Ethane Not tested 22.5 41.2 0.97 5.2 17.8

Methane Not tested 32 80 3.96 20.8 49

Propane Not tested 7.14 29.1 0.76 9.8 19.1

Ethylene Not tested Not tested Not tested 13.9 53.7 104

Propylene Not tested Not tested Not tested 4.37 15.6 59.8

Table 3-5. Summary of Controlled Laboratory Minimum Detection Limits (g/hr) for Gases 

Diluted with N2 at Various Wind Speeds74

OGI Camera Sherlock GasFindIR 

Compound 0 mph 2 mph 5 mph 0 mph 2 mph 5 mph 

Butane Not tested 12.8 24.25 7.9 15.9 21.6

Ethane Not tested 37.5 63.7 5.94 14.5 20.4

Methane Not tested 68 159 19.8 45.6 65.4

Propane Not tested 27.5 53.9 7.08 16.3 21.8

Ethylene Not tested Not tested Not tested 90.1 >90.1* >90.1*

Propylene Not tested Not tested Not tested 24.7 47 62.4

* The values in this table with a greater than sign indicate where the gas was imaged at a leak rate above that which 

the laboratory design was to quantify. This represents that the gas is able to be detected, but the MDLR could not

be determined using the available equipment.

FLIR developed a second generation GasFindIR and submitted this OGI technology update for 

testing later that same year on the same experimental apparatus at the Naperville, IL facility. The 

second generation FLIR GasFindIR camera achieved lower MDLRs for all gases tested and even 

challenged the lower release rate capabilities of the experimental apparatus. A summary of the 

MDLR values for the second generation FLIR GasFindIR is presented in Tables 3-6 and 3-7 for 

all gases and conditions tested. The values in Tables 3-6 and 3-7 for 0 mph wind speed 

conditions and pure gas are currently used by FLIR to describe the gas detection limits of their 

next generation GasFindIR OGI camera, the FLIR GF320.33

In a report prepared for FLIR on both GasFindIR studies, Panek

75 confirmed the conclusions 

resulting from the study conducted earlier that year, and reiterated that: 

• The focal length of the lens did impact the detection capability of the camera; 

• The temperature of the gas relative to that of the background (the ∆T) can potentially 

have large impacts on the MDLR for this OGI technology; and, 

• The uniformity of the background does influence the MDLR for this OGI technology. 
24 

The report by Panek75 reintroduced the importance of temperature differences and thermal tuning 

when operating OGI technology.75 

Tables 3-6 and 3-7. MDLRs for Pure Compounds at Different Wind Speeds and Gas 

Mixtures at Different Wind Speeds5,75 

* It is assumed that the cement board background was used (instead of the metal cylinder background) for this part 

of the study because the authors did not specify the exact background used. 

* A hot nitrogen gas stream was flowed through a custom organic vapor generator system in order to generate the 

gases for the compounds listed in the table on the left, which are normally liquid at room temperature. To make 

direct comparisons between these MDLRs and those of the compounds from the table on the right (species that 

are gases at room temperature), the pure gases from the table on the right were diluted with nitrogen at a flow rate 

similar to that used for the vapor generator (about 3 L/min).

3. ETV Minimum Detection Limit Study 

The EPA Environmental Technology Verification program conducted OGI technology 

verification studies on the second generation FLIR GasFindIR and the GIT (formerly PAT) 

Sherlock®

 VOC cameras in both laboratory (Naperville, IL facility) and field conditions in 2008. 

For the ETV MDL study, gaseous compounds were released from a 1 inch outlet valve under 

carefully controlled laboratory conditions for each of the compounds listed in Table 3-8 using the 

same Naperville, IL experimental apparatus discussed above. Three observers were used to 

confirm OGI camera detection. Starting at release rates in g/hr resulting from the Panek74,75 and 

Benson5 studies previously discussed as the limit of detection for each compound, the mass rate 
25 

was incrementally decreased if all three observers identified the leak. Once a leak rate that was 

not identifiable by all three observers was reached, the release rate was then increased until all 

three observers could again identify the leak with the OGI camera. This procedure was repeated 

under different test conditions, such as: stand-off distance, wind speed, and background material 

as performed initially during the TCEQ study. The minimum and maximum MDLs presented in 

Table 3-8 represent the range of MDLs measured over all test conditions.10,11 

The ETV study also compared relative OGI camera agreement with an approved Method 21 

monitoring device during laboratory testing. Once a detection level using the OGI camera was 

found for each test condition, gas concentrations were measured according to Method 21 using a 

PID and a leak definition concentration of 500 ppmv. For situations where the OGI camera MDL 

was above the highest reliable flow rate of the chemical delivery system, the OGI camera was 

noted as not being able to detect the compound under the specific test conditions. Similarly, if 

the Method 21 monitoring device produced a response equal to zero, then the monitoring device 

was considered unable to detect the chemical gas leak under the specific test conditions.10,11 

If both the OGI camera and the Method 21 monitoring device proved capable of detecting the 

gas leak, then both units were considered to have agreed under the specific test conditions. 

Likewise, if either unit proved incapable of detecting the gas leak under the specified test 

conditions, then the units were considered to have disagreed. The relative agreement between 

OGI camera leak detection and a Method 21 acceptable monitoring device is listed by camera for 

each chemical compound tested in Table 3-8. Percent agreement was calculated where A was the 

number of tests that both units agree and T was the total number of tests in: 

	 = 	 

 

!	 × 100

 
26 

Table 3-8. Summary of MDLs and % Agreement with a M21 Monitoring Device during 

Lab Testing10,11

FLIR GasFindIRTM MW Camera

Compound 

Method Detection Limit (g/hr) Agreement with Method 21 Device 

Minimum Maximum Total No. of Tests 

Performed Percent Agreement

1,3-butadiene 1.3 2.7 4 100%

Acetic acid ≤ 0.02 ≤ 4.6 (b), (c) 11 100%

Acrylic acid 0.92 1.2 4 100%

Benzene 0.35 35 (c) 12 100%

Methylene chloride 4.9 > 70 (c) No data (d)

Ethylene 0.35 278 (c) 8 100%

Methanol 0.28 22 (c) No data (d)

Pentane ≤ 0.28 28 (c) 16 100%

Propane ≤ 0.44 13 (c) No data (d)

Styrene 0.35 0.70 3 100%

Sherlock® VOC

Compound 

Method Detection Limit (g/hr) Agreement with Method 21 Device 

Minimum Maximum Total No. of Tests 

Performed Percent Agreement

1,3-butadiene 8.0 27 4 100%

Acetic acid 1.7 81 11 100%

Acrylic acid 0.92 7.4 4 100%

Benzene 3.2 ≥ 70 (b), (c) 10 40%

Methylene chloride ≥ 70 (b) ≥ 70 (b) No data (d)

Ethylene 3.3 ≥ 278 (b) 6 33%

Methanol 2.1 ≥ 69 (c) No data (d)

Pentane 0.83 ≥ 55 (b), (c) 12 75%

Propane 0.88 235 (b) No data (d)

Styrene 15 25 4 100%

(a) Minimum and maximum method detection limits were measured at a 0-mph wind speed unless otherwise noted. 

(b) Measured at a 2.5-mph wind speed. 

(c) Measured at a 5-mph wind speed. 

(d) Percent agreement was not evaluated for methylene chloride, methanol, and propane because these compounds 

have an ionization potential greater than the energy that could be supplied by the Industrial Scientific IBRID 

MX6 with PID sensor. 
27 

The ETV assessment tests did find these same operational results for both cameras: 

• Increased stand-off distance led to increased MDLs 

• Increased wind speed led to increased MDLs 

• The units were both easy to set up and ready to deploy in 10 minutes. 

However, the GasFindIRTM MW was significantly lighter in weight (4.6 pounds (lbs)) versus the 

Sherlock® VOC (19 lbs), and optional lenses that are interchangeable with the GasFindIRTM MW 

offset the increase in MDL with distance from target. The Sherlock® VOC does not have this 

capability. 

4. Attempts at Calibration and Performance Verification

Challenges to acceptance of OGI technology as a standalone technique for LDAR surveys 

include a lack of detailed information on standardized procedures to be followed, requirements 

for formal training of OGI technology operators, and conditions under which LDAR surveys 

with OGI technology should be performed.68 Calibration verification is a quality assurance 

procedure typically implemented through prescriptive methods and/or standard operating 

procedures that objectively measures the performance of OGI technology prior to field 

deployment to ensure data of known quality. Calibration equipment and techniques are currently 

being discussed and refined, but in general include: the detection of a reference cell as compared 

to a cell filled with gas (see Figures 3-5 and 3-6) or an added calibration component to be 

attached to the OGI camera. 

In the first calibration option, shown in Figure 3-5, a chambered vessel is filled with different 

gases of known concentrations and mounted onto the lens of the OGI camera. A video overlay 

allows the user to adjust camera settings to align the gain and level amounts to match with the 

desired gas at the desired concentration allowing the camera to be calibrated.6 
28 

Figure 3-5. Calibration Chambered Vessel6 

Alternatively, the raw pixel intensity from the OGI camera’s detector can be used in a laboratory 

set up (shown in Figure 3-6) developed with a gas cell and a reference cell against a temperature 

controlled background. In this pixel intensity approach, the OGI camera images are processed 

with a pixel intensity analyzer (PIA)—or software algorithm that gathers and evaluates the raw 

pixel data from the detector—and are used to construct a quality control chart that defines the 

quality control criteria.131 The following paragraphs discuss this calibration verification concept 

further; the use of a PIA to develop a quantitative OGI method will be discussed later in this 

document. 

Using the set up illustrated in Figure 3-6, researchers131 were able to develop theoretical 

relationships between the difference in pixel intensity measurements between the gas cell and the 

reference cell (ΔI) and the difference between the gas cell temperature and the background board 

temperature. Using a gas cell filled with a known gas at a known concentration and varying the 

temperature of the background board, a calibration verification quality control chart, such as the 

one calculated in Figure 3-7, can be developed as part of a daily OGI calibration check routine, 

complete with bound compliance criteria windows.131 
29 

Figure 3-6. Gas Imaging IR Camera Verification and Calibration System131 

Figure 3-7. Quality Control Chart for IR Camera Daily Check131 

Repeating this experiment with many different gases at many different concentrations yields a 

library of response clusters, such as the one in Figure 3-8. Therefore, being able to know the 

temperature difference (ΔT) between the target gas and the background—and if imaging a pure 

component or a specific mixture of components for which a cluster has been developed—allows 

the operator to determine the concentration-path length. For example, if the ΔT was 9°C (as 
30 

shown in Figure 3-8 with a dotted blue vertical line), then the camera operator should be able to 

determine the concentration-path length using a plot of the ΔI of the target plume and the 

background as demonstrated in Figure 3-9.131 

Figure 3-8. Example of a Cluster of ΔI vs. ΔT Curves for Different PPM-M Levels of 

Benzene131 

Figure 3-9. Example of a ΔI vs. Concentration-Path Length Curve131 
31 

A Benson et al. study7 from 2008, which looked for camera signal intensity with gas reference 

cells (set up is shown in Figure 3-10), used the change in signal intensity (Figure 3-11) to 

develop OGI camera sensitivity functions. Plotting the amount of signal attenuation versus 

concentration in Figure 3-12 showed a way to predict OGI camera minimum detectible leak 

rates, and also illustrated the effect of maximum optical attenuation, the phenomenon by which 

an increase in gas concentration will no longer result in a larger signal because the optical signal 

has reached maximum attenuation. This is illustrated in Figure 3-12 as the point where the 

signal-to-noise ratio (S/N Ratio) begins to level off. 

Figure 3-10. Experimental Set Up of Gas Cells with Controlled Blackbody Sources7 

Figure 3-11. Measurement of the Signal Attenuation from 2,000 ppm of Methane7 
32 

Figure 3-12. Signal Attenuation vs. Gas Concentration7

Recently, Sandsten et al. took this concept a step further and defined the noise equivalent 

concentration length (NECL) derived from OGI camera gas absorption curves as a promising 

metric for establishing OGI camera performance.88 Similar to the way in which the noise 

equivalent temperature difference (NETD) is used to characterize the performance of 

thermometric instruments by defining the smallest amount of temperature difference that can be 

definitively measured above noise levels (like the limit of detection in analytical chemistry), the 

NECL describes the performance limitations for OGI cameras in terms of the lowest ppm•m that 

can be detected above the baseline noise. As a measure of the sensitivity of an OGI camera to a 

specific gas, the NECL value depends on ∆T, the concentration of the target gas, and the depth 

of the gas plume along the optical axis of the OGI camera. Their studies, presented in 2015, used 

a similar design to those mentioned above where a test cell of specified gas concentration (at 

ambient temperature) is placed between the OGI camera and a blackbody background able to 

maintain a stable temperature at 30°C (about 10°C above ambient), as illustrated in Figure 3-13. 

The gas concentration is varied by pre-filling gas cuvettes with different gas concentrations and 

placing them inside the holder (small white box in Figure 3-13) located 1.0 m away from the lens 

of the OGI camera. 
33 

Figure 3-13. NECL Measurement Set Up88

 

A proxy measurement of the signal intensity is recorded from the set up in Figure 3-13 as 

apparent temperature of the black body background through the test gas and plotted over the 

path-integrated concentration length (CL, in ppm•m) in Figure 3-14. During these measurements, 

the ∆T was recorded by monitoring the temperature difference between the black body radiator 

and the test gas. 

Figure 3-14. Signal Intensity as a Function of CL88

 

By developing a derivation of the Beer-Lambert law to integrate the signal over the OGI cameras 

spectral range of operation, Sandsten et al. calculated a line of best fit (green dashed line in 

Figure 3-14) through the experimental data obtained during their study (blue circles in Figure 3-
34 

14) and extrapolated the line function to CL = 0 to find the NECL. The fit-function of the line in 

Figure 3-14 can be described by the following relationship: 

%&', ) ∝



+ + '

Where the radiative signal (S) for a given ∆T (T) and CL received by the OGI camera through a 

plume of pollutant are proportional to line fit factors A and B and the CL. In this way, Sandsten 

et al. determined the NECL of methane for the FLIR GF320 to be 13 ppm•m. Sandsten et al. 

verified this NECL result by simulating a theoretical value through calculations with spectral 

compound data from the HiTran database. These calculations are displayed in Table 3-9 where 

the empirical results are shown for different ∆T amounts with a measure of the instrumental error 

and the simulated results for comparison in parentheses.

88

 

Table 3-9. Empirical Methane NECL Values for a FLIR GF320 OGI Camera88

CL ( ppm•m) ∆T = 2 °C ∆T = 5 °C ∆T = 10 °C 

0 75 ± 4 (76) 28 ± 1 (28) 13 ± 1 (13) 

10 76 ± 4 (77) 29 ± 1 (29) 13 ± 1 (13) 

100 87 ± 4 (90) 33 ± 1 (34) 15 ± 1 (15) 

1000 235 ± 3 (239) 88 ± 1 (90) 40 ± 1 (40) 

In order to develop a standardized metric that objectively describes the performance of an OGI 

camera, Sandsten et al. proposed measurement conditions (highlighted in green in Table 3-9) that 

should remain constant so that the NECL results for multiple cameras of different types can be 

compared. These conditions are: 

• ∆T = 10°C 

• The OGI camera to be tested is set up 1.0 m from the gas cell 

• After the line of best fit is optimized (through the A and B factors), the NECL is 

evaluated at a CL = 0 ppm•m. 

Also, this metric can be applied to describing potential field performance. For example, a NECL 

of 13 ppm•m for methane with a gas plume that is 10 cm in optical depth translates to the OGI 

camera being technically capable of detecting the plume if it has a concentration greater than 130 

ppm (13 ppm•m / 0.1 m). This limit of detection will increase, however, in a manner 

commiserate with field conditions at the time of detection (e.g., wind speed, leak exit velocity, 

background temperature and uniformity, distance from targeted equipment). 
35 

5. Studies to Compare OGI Technology to Method 21 

Many studies have been conducted to evaluate the ability of OGI technology to perform 

comprehensive LDAR leak surveys and compare the results between OGI technology monitoring 

and Method 21 monitoring. 

Robinson and Luke-Boone84,85 performed a study that tested the capabilities of the active IR 

imaging BAGI camera at ethylene chemical plants and refineries. It was shown that the OGI 

camera was able to consistently detect unsaturated (gas feedstock has a higher percentage of 

olefinic—or unsaturated—chemical compounds) gas plant leaks at 20 g/hr or above as 

determined by bagging; however, a modified background (something to reflect the IR output, 

such as brightly reflecting Styrofoam) was needed to consistently image leaks at lower rates. The 

BAGI camera only missed 3 out of a total 27 leaks detected where all 3 of the missed leaks were 

measured to have a mass emission rate of 5 g/hr or less. However, it was observed during the 

surveys that multiple LDAR leak identification tags resulting from Method 21 surveys were 

actually misidentifications due to the lack of visual confirmation. Additionally, operators 

conducting LDAR surveys using Method 21 only were able to screen between 500 and 700 

equipment components per day, whereas the OGI technology-assisted surveys increased that rate 

to 2,100 equipment components per hour. The study showed that the potential cost savings was 

outstanding based on the rate at which LDAR operators could perform the survey.84

The same screening rate inequality was found in a different study by Picard et al.78 at a gas 

fractionation plant, where the implementation of OGI technology increased the screening speed 

nearly 10-fold.78 For a two person team using Method 21, a rate of 240 components per hour was 

a reasonable pace. A two person team using OGI increases that rate to 2,300 components per 

hour.81 Of the top 10 biggest leakers found during this study, operators only found 5 while using 

Method 21, but found 8 while using OGI technology (the other 2 leaks having sufficient mass 

emission rates to be detected by the camera, but were missed by the operatorf). While the study 

emphasized the detection performance for the top 10 leaks, there was no comparison of 

performance over the entire size range of leaks. Additionally, this study found that as compared 

to Method 21, OGI technology had the following advantages and disadvantages.78 

Advantages Disadvantages 

Able to visualize difficult and hard-to-reach 

leak locations. 

Is not recommended for use during rain, fog, 

or in extreme cold. Also may not be as 

effective during overcast conditions. 

Can clearly “see” the source of the leak. Needs a knowledgeable operator. 

Reduces equipment operator exposure to 

vapors. 

Unable to quantify emissions. 

 

f

 Operator sensitivity to contrast differences varies widely from person to person and depends on multiple factors 

such as pupil dilation. For more on the capabilities of the human eye, see Optical Modulation Transfer Functions 

of the Human Eye.55
36 

During a study by Reese et al., 2006, it was determined that only two people were required for 

2 days to do an OGI technology-assisted facility survey versus four people for 4 days using 

Method 21.80 In this study, the authors allowed some leaks that were less than the regulation 

definition of 10,000 ppm to go unrepaired to evaluate the concern over the potential for leaks at 

lower mass emission rates to become bigger over time. These equipment leaks were re-surveyed 

three months after the initial Method 21 survey. Although some leak rates increased over that 

time, an equivalent amount of leaks decreased, resulting in no net change over time and resulting 

in the authors unable to find any correlation between leak rate and length of time. 

Reese et al. reported that, during the last comparison survey conducted for this study, only one 

leak was detected with OGI technology and nine leaks were detected with Method 21 

independently. In this example, although the Method 21 survey found more leaks, the maximum 

leak concentration detected by Method 21 was 5,817 ppm. In comparison, the one leak found by 

OGI technology measured 210,000 ppm; this was the largest leak of the study, and it was not 

detected via Method 21. Therefore, lower whole-facility emissions can result from the 

implementation of OGI technology-assisted leak surveys due to the greater probability of a large 

leak being detected with OGI versus Method 21 only. Reese et al.80 reached this conclusion after 

observing that OGI consistently found the larger leaks, although some leaks were missed starting 

around 6,000 ppm (according to EPA Method 21 measurements) and less.80 In the study, the 

authors applied the EPA correlation curves106 to Method 21 screening values and the API 

leak/no-leak emission factors2,3,59,60 to come up with whole facility emission rates of 9,099 

pounds per year (lbs/yr) for Method 21 and 7,774 lbs/yr for OGI. This was a difference of about 

15%, which was acceptable to the authors.80 The study authors concluded that the use of OGI 

technology to assist LDAR surveys results in lower whole-facility emissions versus Method 21 

alone and that the amount of emissions released by smaller leaks possibly missed by OGI 

technology-assisted surveys are offset by the faster identification (and repair) of larger leaks 

when surveys are conducted on a more frequent basis. 

6. Studies Comparing OGI Technology to “Bagging” Techniques 

While the fugitive emissions from individual equipment may be small, the large number of 

leaking equipment that can be found in typical refinery or petrochemical processing plants 

results in the total amount of emissions from this source category being about 50% of the total 

facility hydrocarbon emissions.35 Developed in response to the 1997 API study,1 which showed 

that a very small fraction of equipment leaks contribute a large majority of the controllable 

fugitive emissions, Smart LDAR programs target these larger leakers. OGI technology has the 

potential to assist LDAR programs by increasing the efficiency and cost effectiveness of leak 

detection surveys, but data on the applicability of OGI technology still needs to be collected in 

order to confirm the leak detection capabilities of this developing technology. The studies 

conducted by Furry et al., 200635 and Thoma, 2009122 compared results between OGI technology 

and bagging techniques to add to the body of knowledge on OGI technology leak detection 

capabilities. 

Furry et al., 2006 tried to validate the laboratory controlled minimum detection leak rates 

(MDLRs) for OGI technology previously developed by Panek et al.74 and Benson et al.5 by 

comparing these earlier published values with field data collected using Method 21 and bagging 

techniques from targeted chemical plant process unit areas.

35 The study team quantitatively 
37 

validated the OGI technology leak detections made in the field with a FLIR GasFindIR by 

obtaining a screening value for the leaks using a Method 21-approved PID/FID analyzer and 

“bagging” some of the leak emissions for laboratory gas concentration analysis and emission rate 

measurements. The results of this effort are illustrated in Table 3-10 where the MDLRs at 

various wind speeds determined from the Panek and Benson studies are compared to the results 

from the field study conducted for this effort.35 The Panek and Benson results are discussed in 

detail in Section III.B.2 of this document, and it is worth noting that the range of MDLR values 

presented by Furry et al. in Table 3-10 for the Panek et al. study is for the first generation FLIR 

GasFindIR OGI camera. Therefore, evaluating Table 3-10 with respect to the range of MDLR 

values from the Benson et al. study, which were conducted on the second generation FLIR 

GasFindIR OGI camera, may be more useful, although it is unknown which generation FLIR 

GasFindIR OGI camera was used for conducting the field tests. 

Table 3-10. Comparison of Field-Derived Values to Published Laboratory Detection Limits 

(g/hr)35 

Chemical Field Test Panek et al., 200674 Benson et al., 20065 

Methane 3.7 3.96 – 49 0.8 – 11

Propane 4.7 0.76 – 19.1 0.4 – 9.3

Butane 10.6 0.72 – 15.9 0.4 – 13

Propylene 23.8 4.37 – 59.8 2.9 – 35

Toluene 50.2 22.6 – 75.3 3.8 – 14.3

Xylene 17.8 15.1 – 75.3 1.9 – 18.9

In Furry’s study, the monitoring team was able to screen at a rate of 3,600 components per hour 

and were able to confirm the applicability of lab-derived detection limits as predictive values for 

field operation. This study also showed that leaks were successfully detected against many 

different backgrounds representing various reflectivities, as long as there was a sufficient ∆T. It 

is worthwhile to note that wind speed, optical resolution, plume motion, and viewing angle are 

all parameters that will influence detection sensitivity, and so the comparison between the fieldderived detection limits and the MDLRs determined under ideal laboratory conditions are 

expected to be different.35 However, evaluating the field-derived MDLRs with respect to both 

published MDLR ranges in Table 3-10 shows that the laboratory results are able to provide 

predictive performance ranges for field applications of OGI technology. 

In 2008, multiple interested parties collaborated on a study investigating fugitive emissions from 

petrochemical barges using OTM-10, OGI technology, and “bagging” techniques.122 The 

activities included using the LSI Hawk (FLIR GasFindIR) to image barges from a helicopter, 

from the ground standing on the edge of the lock as vessels passed through channel locks, and 

from the ground on the barges themselves. The “bagging” technique was used to quantify 

emission rates visualized from the aerial survey, and OTM-10 with OP-FTIR was used to 

quantify emission rates from barge vessels as they moved through the channel locks. The 

following general conclusions were made from this study:122 
38 

• Aerial IR images from OGI technology identified barges, and even barge equipment, with 

big leaks, whereas ground-based and onboard IR images from OGI technology detected 

leaks at lower emission rates in addition to the larger leaks. 

• OGI IR equipment was found to be robust, easy-to-use, and possessing sufficient 

detection sensitivity for all applications in this study. 

• OGI technology detection was easier to perform during mid-day to late afternoon time 

periods because of more favorable background conditions during those hours. The higher 

sun position during those hours heated the background scenery (the barges) to effectively 

raise the ∆T while also reducing the interference caused by shadows. 

• Onboard OGI technology detection was less sensitive to ambient conditions as compared 

to aerial observations. 

• OGI technology measurements were able to detect leaks from barges in the lock that 

ranged from 169 to 12,204 g/hr alkane mixture as measured by OTM-10. 

• Aerial images were identifying leaks that were quantified by bagging as being in the 

range of 252 to 20,772 g/hr for individual components, relating to total barge leak rates of 

4,068 to 22,464 g/hr. 

• In all, there were seven instances where leaks were detected from passing barges in the 

lock by OGI technology, but the plumes never crossed the optical path of the OTM-10, 

thereby missing the leak quantification via OTM-10. 

C. Conclusion 

Two commercially-viable cameras are on the market today and available for leak detection work: 

the FLIR GF320 and the Opgal EyeCGas provided by Guardian Compliance. These two units are 

extremely similar and operate based on the same passive IR OGI technology imaging principles. 

There are several key differences in the design and functionality of the camera systems (as 

shown in Table 3-11), including the type of FPA detector used and the ability to measure 

temperature as well as image the gas. In addition to the differences noted below, the EyeCGas is 

intrinsically safe whereas the GF320 is not. 

Table 3-11. Comparison Between FLIR GF320 and Opgal EyeCGas Specifications33,73

Specification FLIR GF320 Opgal EyeCGas 

Field-of-View/minimum 

focus distance 24° x 18° / 0.3 m (1.0 ft) 18.2° x 13.6° / 0.5 m (1.6 ft) 

Lens F-number 1.5 1.1 

Thermal Sensitivity/NETD <15 millikelvin @ 30°C <12 millikelvin @ 25°C 
39 

Table 3-11. Comparison Between FLIR GF320 and Opgal EyeCGas Specifications33,73

Specification FLIR GF320 Opgal EyeCGas 

Focus Modes Auto or manual Manual 

Zoom 1-8x continuous, digital 2x, 4x, digital 

Focal Plane Array InSb (3.2 – 3.4 μm) HgCdTe (3 – 4 μm) 

Spectral Filter 3.2 – 3.4 μm cold bandpass 3.2 – 3.4 μm hot bandpass 

IR Resolution 320 x 240 pixels 320 x 240 pixels 

Sensor Cooling Stirling 

Microcooler FLIR MC-3 Ricor K563 

Full Frame Rate 60 Hz 30 Hz 

Display Built-in, 4.3” LCD, 800 x 480 

pixels 

Built-in, 3.5” LCD, 640 x 480 

pixels 

Viewfinder Built-in, 800 x 480 pixels None 

Automatic image 

adjustment 

Continuous/manual; linear or 

histogram based 

Automatic. Manual for 

Enhanced Mode adjustment 

Manual image adjustment Level/span Enhanced Mode 

(depth/background) 

Image modes IR-image, visual image, High 

Sensitivity Mode (HSM) 

IR-image, visual image, 

Enhanced Mode (Enh) 

Temperature measurement 

range 

-40 to +350°C None (does not perform 

temperature measurements) 

Temperature measurement 

accuracy 

± 1°C for temp range 0 to 

100°C, or ±2% of reading for 

temp range >+100°C 

None (does not perform 

temperature measurements) 

Meta data recording GPS Audio via Head Set 

Video output 

Removable SD (plus other 

connections) 

Visual image can be 

associated with video 

recording 

SD not removable (USB 

connection) 

Visual image can be recorded 

in the same footage with the 

IR video image 

Battery operating time > 3 hrs @ 25 °C, typical use > 4 hrs @ 25°C, typical use 

Start-up time < 5 min @ 25°C < 8 min @ 25°C 

Operating temperature 

range 

-20 to +50°C -20 to +50°C 
40 

Table 3-11. Comparison Between FLIR GF320 and Opgal EyeCGas Specifications33,73

Specification FLIR GF320 Opgal EyeCGas 

Weight incl. lens and battery 2.48 kg (5.47 lbs) 2.68 kg (5.9 lbs) 

Size incl. lens (LxWxH) 12.0 x 6.7 x 6.3 in. 9 x 5.1 x 4.3 in. 

Accessory lenses (mid-wave 

band) 

24°, f = 23 mm 

14.5°, f = 38 mm 

6°, f = 92 mm 

18.2°, f = 30 mm 

7.3°, f = 75mm 

Table 3-12 presents the MDLRs claimed by the manufacturer for the FLIR GF320 as reported by 

Panek for the FLIR GF320 predecessor, the second generation FLIR GasFindIR.75 There have 

not been any MDLR studies performed on the EyeCGas to date. Given the lack of studies 

involving the EyeCGas and, as a result, the lack of information available on its performance, it 

seems worthwhile to include the EyeCGas camera in future studies for model performance intercomparisons, such as the laboratory studies described in Section IV of this document. 

Table 3-12. Minimum Detected Leak Rates (MDLRs) for the FLIR GF320 per 

manufacturer33 

Gas MDLR 

(g/hr) Gas MDLR (g/hr) Gas MDLR (g/hr) 

1-Pentene 5.6 Heptane 1.8 Octane 1.2 

Benzene 3.5 Hexane 1.7 Pentane 3.0 

Butane 0.4 Isoprene 8.1 Propane 0.4 

Ethane 0.6 MEK 3.5 Propylene 2.9 

Ethanol 0.7 Methane 0.8 Toluene 3.8 

Ethylbenzene 1.5 Methanol 3.8 Xylene 1.9 

Ethylene 4.4 MIBK 2.1 

* MDLR values for zero wind conditions from report by Panek, 2005.75
41 

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47 

100. Tremblay, P. S. Savary, M. Rolland, A. Villemaire, M. Chamberland, V. Farley, L. Brault, J. Giroux, J-L. 

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48 

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49 

IV. ERG LABORATORY EVALUATIONS 

This section summarizes the experimental laboratory studies conducted by ERG under EPA 

contracts EP-D-11-006 and EP-W-09-033 to evaluate the performance and application of OGI 

technology for leak detection. OGI has the potential to accurately identify leaking equipment and 

streamline the surveying process for LDAR programs. However, in order to fully understand the 

capabilities of OGI so that it can be implemented as a standalone monitoring technique, 

substantial technology performance testing needs to be conducted to better quantify and qualify 

the applicability, issues, and operation of OGI cameras for LDAR activities. In the work 

conducted for the EPA to date, ERG evaluated the following parameters (with more studies 

currently ongoing): 

• Technology Feasibility Study – Initial demonstration of laboratory equipment and 

procedure used to determine the detection capabilities of an OGI camera at different gas 

concentrations and flow rates under controlled settings. 

• Spectral Limitation Study – Documented the spectral operating window for multiple OGI 

cameras to define a predictable window-of-operation with known variability between 

same and different OGI camera makes and models. 

• Gas Sensitivity Threshold Study – Evaluated the response of multiple OGI cameras to 

various test gases at different concentrations to develop a response curve with gas 

threshold detection levels. To be used for calculating OGI camera response factors 

relative to propane. 

• Repeat Feasibility Study – Observed side-by-side comparisons of OGI camera operation 

and leak display with cameras from two different manufacturers. 

• Horizontal Wind Shear Study – Observed the impact of various wind speeds 

perpendicular to the leak axis on OGI leak detection when all other parameters are 

controlled. 

• Reynolds Number Study – Observed the impact of leak source exit face velocity (or gas 

leak exit pressure) by changing the size of the exit leak orifice and varying the mass 

emission rate. 

• Temperature Differential Study – Investigated the impact of various temperature 

differentials (∆Ts) between the gas plume and the background scenery on OGI camera 

leak detection when the background is warmer and colder than the gas. 

• Sky Background Data Collection – Observed the impact of different sky background 

conditions on OGI gas leak detection. 

NOTE: All concentrations seen throughout this section represent the actual concentration of 

the gas before it is released as a simulated leak. Unless otherwise noted, the gas used for this 

study is nominally a 50/50 blend of propane and butane. The concentration of the gas should 

not be directly related to a Method 21 response without consideration of method specific 
50 

conditions (e.g., calibration gas, response factors, analyzer precision, environmental factors, 

leak geometry). 

Similar to how regular cameras produce images using the visible light region (about 0.40 to 0.75 

μm) of the electromagnetic spectrum, OGI cameras produce thermal images (called 

thermograms) from the infrared (IR) region (about 1.0 to 14.0 μm) of the electromagnetic 

spectrum. OGI cameras are a type of thermographic imager where a special optical component—

called a band-pass filter—filters the incoming radiation to a very specific region. In the case of 

OGI cameras that target hydrocarbons (HCs), the region that is allowed to pass through to the 

camera’s detector to make the image is from about 3.2 to 3.4 μm, which corresponds to the 

bandwidth of the energy absorbed by many compounds containing carbon-hydrogen (C-H) 

bonds. Therefore, the OGI camera produces a thermogram of the heat distribution in the field-ofview (FOV) where the presence of a plume of HC gas is represented by a change in heat. Like 

the way a shadow blocks incident light in the visible range, a plume of HC gas “blocks” the heat 

signature from the background thermal profile from being imaged in the IR, whether that 

background is hotter or colder than the gas plume. When the apparent background is hotter than 

the gas plume, the C-H bonds will absorb the heat signature and block the background thermal 

profile with a “cold” shadow. When the apparent background is colder, the C-H bonds will emit 

a hotter heat signature and block the background thermal profile with a “hot” shadow. Because 

OGI camera technology is based on thermal properties, some OGI cameras are developed with 

the ability to measure the apparent temperature of objects in the FOV; this capability is referred 

to as “thermometric” in this document. 

The Stephan-Boltzmann Law explains the relationship where a change in the temperature of an 

object is proportional to the radiation output of that object; for example, an increase in the 

object’s temperature results in an increase in the amount of IR radiation being emitted by that 

object. The total amount of radiation detected by the camera from an object is equal to the sum 

total of the amount of radiation emitted by the object, the amount of radiation transmitted by the 

object (unless the object is opaque) and the amount of radiation reflected by the object. Some 

OGI camera developers have created temperature calibration curves in the camera’s firmware 

where, if the user inputs an accurate emissivity value (or ratio that describes the object’s ability 

to emit radiation relative to a perfect blackbody emitter) and is able to view the object without 

transmissive or reflective interference, the intensity of the radiation received by the camera’s 

detector is an accurate measure of the object’s “apparent temperature.” In the presence of an HC 

gas plume, an object’s perceived radiation intensity will be partially occluded by HC gas 

absorption and the resulting apparent temperature of the object as measured by an OGI camera 

will change proportionally with the amount of gas between the object and the camera. Therefore, 

many of the studies presented in this section utilize measurements of apparent temperatures from 

FLIR GF320 cameras to objectively evaluate camera performance.

A. Feasibility and Detection Limit Study 

ERG designed a custom controlled leak generation system (CLGS) to allow the observation of 

OGI technology leak detection performance under carefully controlled laboratory settings. The 

objective for the CLGS was to allow precise blending of pollutant gas with diluent gas so that a 

leak of known concentration, flow rate, and mass emission rate is released out a 2” opening in 

front of a background with a known temperature that is stable, controllable, and different from 
51 

the gas temperature. The blending system design is illustrated as a schematic in Figure 4-1 and 

the whole CLGS system is shown in Figure 4-2. Figure 4-2 also shows the equipment used to 

monitor the temperature of the gas, the temperature of the background plate, the temperature of 

the hood space, the relative humidity of the hood space, and the wind speed generated from the 

hood system ventilation (the last 3 conditions monitored by the “Met Sensors” labeled in Figure 

4-2). The experimental gas plume is delivered from a 2” PVC pipe in front of a temperature 

controlled custom-built cold plate painted with Krylon #51602 Ultra Flat Black spray paint to 

reduce thermal reflection. See Appendix C.1 of this document for more detail on the CLGS 

design. 

Figure 4-1. CLGS Gas Blending Component Developed by ERG for Preliminary 

Performance Tests 
52 

Figure 4-2. Overview of CLGS in Place at ERG’s Laboratory 

The first task conducted was a feasibility study using the CLGS, a 2% total hydrocarbon test gas 

blend of propane and butane, and a tripod mounted FLIR GF320 OGI camera. This initial study 

had two objectives: (1) to see if the CLGS design worked and was appropriate for FLIR GF320 

camera performance testing; and (2) to determine at what concentration level and mass emission 

rate the FLIR GF320 camera lost detection when imaging leaks of various concentrations and 

mass rates. The settings on the OGI camera were held constant throughout the testing unless 

otherwise noted. More detail on the experimental design can be found in Appendix A.1: Test 

Plan. 

For the purposes of this feasibility study, the leak had to be easily noticeable within 5 seconds of 

viewing the FLIR GF320 camera output displayed on a 40” flat screen TV (to assist with the 

execution of the tests by one analyst and verified by observing the FLIR GF320 camera LCD 

screen when leak detection was marginal). Lacking prior experience with the magnitude of the 

impact ∆T has on leak detection, the first attempt to execute this study did not find much success 

determining limits of detection at a ∆T = 15 to 16° C, as all concentrations and mass rates were 

detected. The results shown in Tables 4-1 through 4-5 were collected later, with the effective ∆T 

lowered to 2 to 3°C. Using manual thermal tuning, the level and span of these tests at the lower 

∆T where held equal to those of the higher ∆T tests for comparison and to challenge the 

observer. 

NOTE: OGI camera software typically contains an automated display algorithm that defines 

the thermal tuning (grayscale profile) of an image based on establishing the range of 

temperatures in the FOV (“span”) and calculating the midpoint of the span (“level”). Both 

the GF320 and Opgal have a setting (“auto mode”) that allows the cameras to automatically 
53 

adjust the “span” and “level” so that all objects in the FOV are viewable. Additionally, the 

FLIR GF320 camera allows manual tuning, a process where the user can manually adjust the 

display thermal tuning (the “span” and “level”), thereby enabling us to perform a comparison 

between images produced by the two different ∆T conditions of our feasibility study while 

keeping all other conditions the same. The manual thermal tuning settings are not important 

when imaging in high sensitivity or enhanced modes due to the self-subtracting nature of the 

display algorithm. In other words, to increase OGI camera display sensitivity to a gas plume, 

camera developers designed an algorithm that subtracts the elements of the current frame 

from those of the previous frame (or average of a predetermined number of frames) to isolate 

(and, therefore, amplify) the difference between the frames due to the movement of the gas 

plume. In this way, the thermal tuning becomes less important, as the image is being 

constructed from differences in raw pixel intensity information from the detector. 

A look into the increase in detection capabilities through the use of high sensitivity or enhanced 

modes was performed at the lowest concentration level (500 ppmv), and the results are shown in 

Tables 4-6 and 4-7. This test was repeated (Table 4-7 displays the results of the second run) to 

validate the results due to the challenging nature of trying to image a leak at a low concentration. 

Table 4-8 shows an overview of the total results, including the earlier test runs with ∆T ≈ 15°C. 

The green shading in the following tables indicates conditions where easy/definitive detection 

was lost. 

Table 4-1. Results from Feasibility Study at About 20,000 ppmV (2%) Total Hydrocarbons 

(50/50 Propane-Butane Mix) 

Run ID Test Date Total HC Conc. 

(ppmV) 

Total Flow 

Rate (L/min) 

Mass Release 

Rate (g/hr) ∆T (°C) Detected? 

1A 2/7/2013 20220 100 255 2.4 Y

1B 2/7/2013 20220 90 229 2.6 Y

1C 2/7/2013 20220 80 204 2.8 Y

1D 2/7/2013 20220 70 178 2.7 Y

1E 2/7/2013 20220 60 153 2.6 Y

1F 2/7/2013 20220 50 128 2.7 Y

1G 2/7/2013 20220 40 102 2.9 Y

1H 2/7/2013 20220 30 77 2.7 Y

1I 2/7/2013 20220 20 51 2.8 Y

1J 2/7/2013 20220 10 26 2.8 Y

1K 2/7/2013 20220 5 13 2.7 N

1L 2/7/2013 20220 10 26 2.7 Y

1K 2/7/2013 20220 5 13 3.0 N

* Reversing the camera’s polarity and adjusting the thermal tuning allowed the 13 g/hr leak (1K) to be detected after 

this test run. 
54 

Table 4-2. Results from Feasibility Study at About 10,000 ppmV (1%) Total Hydrocarbons 

(50/50 Propane-Butane Mix) 

Run ID Test Date Total HC 

Conc. (ppmV)

Total Flow 

Rate (L/min) 

Mass Release 

Rate (g/hr) ∆T (°C) Detected? 

2A 2/7/2013 10110 100 128 3.1 Y

2B 2/7/2013 10110 90 115 3.1 Y

2C 2/7/2013 10110 80 102 3.1 Y

2D 2/7/2013 10110 70 89 3.2 Y

2E 2/7/2013 10110 60 77 3.0 Y

2F 2/7/2013 10110 50 64 3.1 Y

2G 2/7/2013 10110 40 51 3.1 Y

2H 2/7/2013 10110 30 38 3.0 Y

2I 2/7/2013 10110 20 26 2.9 Y

2J 2/7/2013 10110 10 13 3.2 Y

2K 2/7/2013 10110 5 6 2.8 N

2L 2/7/2013 10110 10 13 2.9 Y

Table 4-3. Results from Feasibility Study at About 5,000 ppmV (0.5%) Total Hydrocarbons 

(50/50 Propane-Butane Mix) 

Run ID Test Date Total HC 

Conc. (ppmV)

Total Flow 

Rate (L/min) 

Mass Release 

Rate (g/hr) ∆T (°C) Detected? 

3A 2/8/2013 5055 100 64 2.6 Y

3B 2/8/2013 5055 90 57 2.7 Y

3C 2/8/2013 5055 80 51 2.6 Y

3D 2/8/2013 5055 70 45 2.7 Y

3E 2/8/2013 5055 60 38 2.6 Y

3F 2/8/2013 5055 50 32 2.5 Y

3G 2/8/2013 5055 40 26 2.7 Y

3H 2/8/2013 5055 30 19 2.5 Y

3I 2/8/2013 5055 20 13 2.3 N

3O 2/8/2013 5055 25 16 2.6 Y

3P 2/8/2013 5055 30 19 2.5 Y

Table 4-4. Results from Feasibility Study at About 500 ppmV Total Hydrocarbons 

Run ID Test Date Total HC 

Conc. (ppmV)

Total Flow 

Rate (L/min) 

Mass Release 

Rate (g/hr) ∆T (°C) Detected? 

4A 2/8/2013 506 100 6 2.9 N

* Detection at this concentration level and flow rate was not achieved; therefore, further tests were not attempted 

according to original work plan. 
55 

Table 4-5. Results from Feasibility Study Holding Mass Emission Rate Equal to 10 g/hr 

with OGI Camera Thermal Tuning on Auto (50/50 Propane-Butane Mix) 

Run ID Test Date Total HC 

Conc. (ppmV)

Total Flow 

Rate (L/min) 

Mass Release 

Rate (g/hr) ∆T (°C) Detected? 

5A 2/21/2013 809 100 10 2.0 N

5B 2/21/2013 1011 80 10 2.1 Y

5C 2/21/2013 1348 60 10 2.2 Y

5D 2/21/2013 2022 40 10 2.3 Y

5E 2/21/2013 2696 30 10 2.3 Y

5F 2/21/2013 4044 20 10 2.0 Y

Table 4-6. Results from Feasibility Study at About 500 ppmV Total Hydrocarbons on High 

Sensitivity Mode (50/50 Propane-Butane Mix) 

Run ID Test Date Total HC 

Conc. (ppmV)

Total Flow 

Rate (L/min) 

Mass Release 

Rate (g/hr) ∆T (°C) Detected? 

10A 2/21/2013 506 100 6.4 2.4 Y

10B 2/21/2013 494 90 5.6 2.5 Y

10C 2/21/2013 506 80 5.1 2.5 Y

10D 2/21/2013 491 70 4.3 2.4 Y

10E 2/21/2013 506 60 3.8 2.4 Y

10F 2/21/2013 485 50 3.1 2.7 N

10G 2/21/2013 506 40 2.6 2.4 N

10H 2/21/2013 539 30 2.0 2.3 N

10I 2/21/2013 506 20 1.3 2.6 N

10T 2/21/2013 485 50 3.1 2.2 N

10U 2/21/2013 478 55 3.3 2.4 N

10V 2/21/2013 515 55 3.6 2.5 Y

* Video files were not recovered from this test run. Test run was repeated due to video recording error. Results for 

rerun are shown in Table 4-7. 
56 

Table 4-7. Results from Feasibility Study at About 500 ppmV Total Hydrocarbons on High 

Sensitivity Mode, Rerun (50/50 Propane-Butane Mix) 

Run ID Test Date Total HC 

Conc. (ppmV)

Total Flow 

Rate (L/min) 

Mass Release 

Rate (g/hr) ∆T (°C) Detected? 

10A 3/12/2013 506 100 6.4 1.9 Y

10B 3/12/2013 494 90 5.6 2.1 Y

10C 3/12/2013 506 80 5.1 2.2 Y

10D 3/12/2013 491 70 4.3 2.1 Y

10E 3/12/2013 506 60 3.8 2.1 Y

10F 3/12/2013 485 50 3.1 2.1 Y

10G 3/12/2013 506 40 2.6 2.0 N

10H 3/12/2013 539 30 2.0 1.9 N

10I 3/12/2013 506 20 1.3 2.0 N

10T 3/12/2013 485 50 3.1 2.1 Y

10U 3/12/2013 478 55 3.3 2.0 Y

10V 3/12/2013 515 55 3.6 2.1 Y

Table 4-8. Overall Results from the Feasibility Study Showing Both ∆T Conditions 

Test Conditions Detection 

Limit 

Mass Emission 

(g/hr) 

Concentration 

(ppmV) 

Total Flow 

Rate (L/min) 

∆T ≈ 15°C 

Manual Mode 

Run 1 None reached - - -

Run 2 None reached - - -

Run 3 None reached - - -

Run 4 4O 1.5 485 25

High Sensitivity Mode Run 10 None reached - - -

∆T ≈ 2 – 3°C 

Manual Mode 

Run 1 1K 12.8 20220 5

Run 2 2K 6.4 10110 5

Run 3 3I 12.8 5055 20

Run 4 4A 6.4 506 100

Auto Mode Run 5* 5B 10.2 1011 80

High Sensitivity Mode Run 10 10G 2.6 506 40

* Due to the nature of this test run, this is the maximum total flow rate for detection at the 10.2 g/hr rate of 

emission. 

The results shown in Table 4-8 indicate that the FLIR GF320 camera should be able to detect a 

propane/butane gas mixture mass emission rate of 10.7 g/hr (average of runs 1 through 3) or 

greater under controlled laboratory conditions, with less-than-optimal manual thermal tuning, 

and with a ∆T ≈ 2°C. Using the FLIR GF320 camera’s High Sensitivity Mode, the camera could 

potentially achieve a limit of detection down to 2.6 g/hr under controlled laboratory conditions. 

The controlled laboratory conditions that were present during this study but that would generally 

not be found in the field were: 
57 

• Tripod-mounted camera 

• Consistently low and calm winds produced by the hood face velocity 

• Homogenous and non-reflective thermal background 

• Knowledge of the leak source 

• No thermal interference from the surrounding infrastructure. 

Other parameters contribute to a leak being detected by an OGI camera beside just mass 

emission rate, such as the speed at which the gas is exiting. A leak with a high flow rate will be 

harder to detect due to the more diffuse nature of the turbulent plume, and, conversely, a very 

slow leak will be harder to detect because it will appear smaller in volume, will be found closer 

to the leaking equipment, and will sometimes be intermittent depending on the wind conditions. 

By plotting the flow rate data from the feasibility study by the mass emission rate and 

highlighting the limits of detection (Figure 4-3), it is obvious that leak detection at the extremes 

of gas flow rate will be more challenging in addition to leaks with low mass emission rates. 

Figure 4-3. Feasibility Study Results by Flow Rate and Mass Emission Rate for 

Measurements in Manual and Auto Modes 

0

20

40

60

80

100

120

0 50 100 150 200 250 300

Flow Rate (L/min)

Mass Emission Rate (g/hr)

 Detects

 Non-Detects
58 

B. Spectral Limitations and Gas Sensitivity Studies 

The performance capabilities of an OGI camera are a direct result of the spectral properties of the 

IR optics used to construct the camera. The Office of Research and Development (ORD) of the 

EPA designed the custom-built spectral test platform shown in Figure 4-4 to specifically evaluate 

the spectral limitations of OGI cameras. One side of the spectral test platform (the left side in 

Figure 4-4) had a monochromator capable of emitting an IR source from 0.105 to 4.00 μm at a 

resolution of 1 Å (or 0.0001 μm), which was used to measure the spectral intensity curve of nine 

OGI cameras. The other side of the spectral test platform (the right side in Figure 4-4) had 

optical test cells with internal temperature and pressure sensors placed in front of a temperature 

controlled hot plate background. ERG integrated the precise gas dilution system from the CLGS 

described in Section IV-A of this document to deliver test gas to the cells on the spectral test 

platform at known concentrations. This was designed such that the spectral sensitivity of OGI 

cameras to different test gases at various concentrations could be evaluated. 

Figure 4-4. EPA ORD Custom-built Spectral Test Platform 

ERG conducted spectral evaluations on seven FLIR GF320 cameras, one Opgal EyeCGas 

camera, and one older model FLIR GasFindIR camera (predecessor to the FLIR GF320 camera). 

The details for the OGI IR cameras used for these evaluations are presented in Table 4-9. The 

experimental design for these evaluations was initially based on the thermometric function (or 

ability to provide measurements of apparent temperature) available with the FLIR GF320 camera 

model. The addition of non-thermometric cameras (Opgal EyeCGas and FLIR GasFindIR) into 

the study required an augmentation to the study design for these cameras. Grayscale intensity 

from IR images recorded by these OGI cameras is used as a proxy for optical intensity. By 

adding neutral density filters of known optical densities into the field of view during the gas cell 
59 

tests, a grayscale calibration curve can be developed and used to evaluate the grayscale values 

measured from the optical test cells at different concentrations. A curve of the normalized 

grayscale intensity from the monochromator exit image is currently in process for both nonthermometric OGI cameras. An example of this techniqueg

 is provided in Figure 4-5 in the 

visible and the IR. As the preparation of the data collected from non-thermometric cameras is 

ongoing, the results presented at this time are from only the FLIR GF320 cameras evaluated. 

Table 4-9. OGI Cameras Evaluated for Spectral Limitations and Gas Sensitivity 

Make Model Serial Number Owner/Location 

FLIR GF320 44401313 ERG 

FLIR GF320 44400966 EPA OECA 

FLIR GF320 44400816 EPA R8 

FLIR GF320 44401085 EPA OECA 

FLIR GF320 44401204 Southern Ute 

FLIR GF320 44401135 EPA R3 

Opgal EyeCGas* TCG1005011* Guardian Compliance 

FLIR GF320 44400819 EPA NEIC 

FLIR GasFindIR* BH0115* EPA R6 

* These OGI camera models do not have thermometric capabilities. Therefore, the data collected from these 

cameras are still being processed. 

Figure 4-5. Example Placement of Neutral Density Filters for Non-Thermometric IR 

Spectral Tests in the Visible (Left) and IR (Right) 

Each FLIR GF320 camera was mounted onto the spectral testing platform facing the 

monochromator and optimized such that the camera’s cooled internal components contributed 

 

g

 The data from the two non-thermometric OGI cameras using this technique are currently being processed under 

EPA Contract No. EP-D-11-006 Work Assignment 5-09. 
60 

minimal thermal interference (examples shown in Figures 4-6 and 4-7). After allowing the 

monochromator to thermally equilibrate, the optical intensity (as apparent temperature in °C) for 

each FLIR GF320 camera was measured from 3.00 to 3.65 μm in increments of 0.01 μm twice; 

once ascending from 3.00 to 3.65 μm, and then repeated descending from 3.65 to 3.00 μm for 

verification purposes. Each spectral curve was normalized to the maximum apparent temperature 

measured for that curve before being averaged over the entire collection of spectral curves for all 

FLIR GF320 cameras tested and plotted with 1σ standard deviation error bars by wavelength (in 

μm) in Figure 4-8. The error bars in Figure 4-8 highlight how the FLIR GF320 cameras all 

respond nearly identically, demonstrating the consistency of performance for the same make and 

model camera (the FLIR GF320), regardless of the original date of manufacture. 

Figure 4-6. A FLIR GasFindIR Mounted and Aligned to the Monochromator Exit Slit 

Figure 4-7. The Exit Slit of the Monochromator as Imaged by the FLIR GF320 
61 

Figure 4-8. Average Spectral Window Curve for FLIR GF320 Cameras 

In order to clearly define the spectral limitations of the OGI camera’s optical system (called the 

“spectral window”), a feature of the spectral curve, termed the “point of limitation” (or POL) 

was defined as an increase in the optical intensity greater than 30% of the baseline value 

(evaluated beyond the fringe of the spectral window). The two locations on the spectral curve 

where this occurs are called the POL1-low and POL1-high. A case can be made that only the 

peak area of optical transmission (the plateau at the top of the spectral curve in Figure 4-8) 

should be considered as the camera’s spectral window. Therefore, Category 2 POLs were 

calculated to be the region within which the optical intensity measurements stay within 5% of the 

maximum apparent temperature. Table 4-10 lists the results for all FLIR GF320 cameras tested 

and shows that POLs for Category 1 range from about 3.1 to 3.6 um and the POLs of Category 2 

range from about 3.2 to 3.4 μm. Figure 4-9 shows a graphical representation of the spectral 

window POL locations for the FLIR GF320 cameras. The Category 2 POLs seem to correspond 

to the operating range of 3.2 to 3.4 um advertised by the camera manufacturer. 
62 

Table 4-10. FLIR GF320 Spectral Window Results 

Camera ID Camera Make 

and Model Camera Owner Tmax

 (°C)

POL 1 (Å) POL 2 (Å) 

Low High Low High 

44401313 FLIR GF320 ERG 229 30900 35800 32400 33900

44400816 FLIR GF320 EPA OECA 231 30900 35700 32300 33800

44400966 FLIR GF320 EPA Region 8 236 30800 35600 32400 33900

44401085 FLIR GF320 EPA OECA 232 30900 35700 32400 33800

44401204 FLIR GF320 Southern Ute 228 31000 35700 32400 33800

44401135 FLIR GF320 EPA Region 3 228 30800 35500 32400 33800

44400819 FLIR GF320 EPA NEIC 236 30800 35700 32400 33800

Average 30900 35700 32400 33800

Figure 4-9. Average FLIR GF320 Spectral Window Curve Illustrating POL Locations 
63 

By developing an average OGI camera spectral performance curve, ERG was able to calculate 

response factors for various gases relative to propane (propane relative response factors). 

Spectral data from the Pacific Northwest National Laboratory (PNNL) were obtained and 

analyzed for each of the compounds listed in Table 4-11. The absorbance spectrum for each 

compound in the range of 3.00 to 3.70 μm was individually scaled by the average OGI camera 

spectral performance curve and then integrated to calculate the total integrated absorbance value 

presented in Table 4-11. These values were then divided by the total absorbance integrated value 

for propane in order to determine theoretical response factors relative to propane (propane 

relative response factors or propane RRFs). 

Table 4-11. Integrated Spectral Absorbance and Propane Relative Response Factors 

Compound Total Integrated Absorbance Propane Relative Response 

Factors 

1,3-butadiene 0.009 0.26

1,3,5-trimethylbenzene 0.034 0.95

Acetic Acid 0.003 0.08

Acetaldehyde 0.004 0.12

Acetone 0.007 0.21

Acetylene 0.000 0.01

Acrylic Acid* 0.002 0.05

Benzene 0.013 0.36

Butane 0.043 1.21

Butene 0.025 0.70

Carbon tetrachloride 0.000 0.00

Dimethylformamide 0.019 0.53

ETBE 0.048 1.35

Ethylbenzene 0.030 0.84

Ethylene 0.006 0.17

Formaldehyde 0.007 0.18

Heptane 0.064 1.80

Hexane 0.057 1.61

Isoprene 0.016 0.45

MEK 0.017 0.47

Methane 0.011 0.30

Methanol 0.016 0.44

Methyl chloride 0.006 0.15

Methylene chloride 0.001 0.03

MTBE 0.045 1.25

m-Xylene 0.027 0.76

Octane 0.051 2.00

o-Xylene 0.024 0.76

Pentane 0.051 1.43
64 

Table 4-11. Integrated Spectral Absorbance and Propane Relative Response Factors 

Compound Total Integrated Absorbance Propane Relative Response 

Factors 

Pentene 0.024 0.68

Propane 0.036 1.00

Propene 0.015 0.42

p-Xylene 0.029 0.80

Styrene 0.015 0.42

Toluene 0.020 0.56

Vinyl chloride 0.001 0.03

Water 0.000 0.00

Propane+Butane 0.039 1.10

* The spectra for Acrylic Acid was available from PNNL at only 50°C, versus 25°C as with all other gas spectra 

listed here. 

Changes in the method for calculating the propane RRFs (such as range of integration and 

saturation as a function of optical depth) will alter the resulting propane RRF values. Therefore, 

to determine the most accurate method of integration, the theoretical propane RRF values in 

Table 4-11 need to be empirically validated. ERG is currently evaluating gas sensitivity 

assessments as a way to empirically validate the theoretical propane RRFs that we calculated. 

The spectral testing platform shown in Figure 4-4 has two optically transmissive, air-tight, gas 

cells in front of a temperature controlled hot plate. By integrating the CLGS gas delivery 

component to the test cells of the spectral testing platform, we are able to carefully control the 

concentration of test gas delivered to the test cells. As discussed earlier in this section, the 

apparent temperature as measured by the FLIR GF320 camera provides a proxy for optical 

intensity received by the camera when the background apparent temperature is held constant. An 

example gas sensitivity curve is provided in Figure 4-10, where each blue asterisk represents the 

individual measurement for each of the seven FLIR GF320 tested at various concentration levels 

and the red circle is the average of all camera responses with black error bars representing 1σ

standard deviation. The dashed line indicates a polynomial Classical Least Squares line of best 

fit through the averaged data. By extrapolating the equation for this line of best fit, we can 

calculate the temperature differential of the OGI camera response at a pre-determined 

concentration level for all test gases and develop a ratio of temperature differential responses for 

each gas to propane and compare this ratio to our theoretical propane RRFs. This work is 

currently ongoing. 
65 

Figure 4-10. Example Gas Sensitivity Curve for 50/50 Propane-Butane Mixture 

According to the Beer-Lambert law, which describes the relationship between the intensity of 

light signal as it passes through a media and the properties of that media, the IR signal detected 

by an OGI camera will be attenuated exponentially with increasing concentration. It is 

hypothesized that the curve at the top end of the line of best fit in Figure 4-10 indicates the 

beginning of that exponential attenuation towards optical saturation. This will be investigated 

further and any influence this may have on the calculated propane RRFs will be evaluated. 

-0.5

0.5

1.5

2.5

3.5

4.5

5.5

-2000 3000 8000 13000 18000 23000

Bias-Corrected Temperature Differential 

(Control – Test, °C)

Concentration (ppmV)

Propane-Butane Mixture

 All Cameras

 Average

Poly. ( Average)
66 

C. Assessment of Parameters that Influence Plume Characteristics/Detection 

It is common knowledge that parameters beyond the camera’s technical design will influence 

leak detection success. When attempting to characterize the performance and application of a 

technology (especially if used for method development purposes), the proper identification and 

quantification of the impact that various parameters will have on data quality is paramount. As 

directed by the EPA, ERG evaluated the influence from parameters that potentially impact OGI 

camera leak detection capability by isolating these parameters in carefully designed laboratory 

experiments. Some of the parameters tested to date are: 

• Different manufacturers – a visual comparison 

• Horizontal wind shear 

• Reynolds number or leak face velocity 

• Hot vs. cold ∆T. 

The side-by-side visual comparison, horizontal wind shear, and Reynolds number parameters 

were investigated as part of Work Assignment 3-08 on EPA contract # EP-D-11-006. 

The results from these studies are presented in Tables 4-12 through 4-26. For images results from 

both OGI cameras, see Appendix C.2 of this document. Each OGI camera was set to Auto mode 

unless otherwise specified. The green shading in the following tables indicates conditions where 

easy/definitive detection was lost, and the orange shading indicates a discrepancy in results 

between the two cameras. Due to camera design and equipment restraints during these tests, it is 

reasonable to expect a difference of results between the two cameras when investigating the 

limits of detection. 

Table 4-12. Repeat Feasibility Study Run 1 (2% concentration) with FLIR and Opgal OGI 

Cameras 

Run ID Conc. (ppmV) Total Flow Rate 

(L/min) 

Mass Release 

Rate (g/hr) ∆T (°C) Detected by FLIR? 

Detected by 

Opgal? 

1A 20297 100 255 1.3 Y Y

1B 20297 90 229 1.4 Y Y

1C 20297 80 204 1.8 Y Y

1D 20297 70 178 1.8 Y Y

1E 20297 60 153 1.7 Y Y

1F 20297 50 127 1.9 Y Y

1G 20297 40 102 2.0 Y Y

1H 20297 30 76 1.6 Y Y

1I 20297 20 51 1.8 Y Y

1J 20297 10 26 1.7 Y Y

1K 20297 5 13 1.6 Y Y
67 

Table 4-13. Repeat Feasibility Study Run 3 (5000 ppmV) with FLIR and Opgal OGI 

Cameras 

Run ID Conc. (ppmV) Total Flow Rate 

(L/min) 

Mass Release 

Rate (g/hr) ∆T (°C) Detected by FLIR? 

Detected by 

Opgal? 

2A 5074 100 64 1.6 Y Y

2B 5074 90 57 1.7 Y Y

2C 5074 80 51 1.8 Y Y

2D 5074 70 45 1.5 Y Y

2E 5074 60 38 1.9 Y Y

2F 5074 50 32 1.9 Y Y

2G 5074 40 26 1.7 Y Y

2H 5074 30 19 1.7 Y Y

2I 5074 20 13 1.7 Y Y

2J 5074 10 6.4 1.7 Y Y

2K 5074 5 3.2 1.6 N N

2L 5074 10 6.4 1.4 Y Y

Table 4-14. Repeat Feasibility Study Run 4 (500 ppmV) with FLIR and Opgal OGI 

Cameras 

Run ID Conc. (ppmV) Total Flow Rate 

(L/min) 

Mass Release 

Rate (g/hr) ∆T (°C) Detected by FLIR? 

Detected by 

Opgal? 

3A 507 100 6.4 2.1 N N

3B 507 90 5.7 1.8 N N

3C 507 80 5.1 1.6 N N

3D 507 70 4.5 2.0 N N

3E 507 60 3.8 2.1 N N

3F 507 50 3.2 1.8 N N

3G 507 40 2.5 2.1 N N

3H 507 30 1.9 2.0 N N

3I 507 20 1.3 1.8 N N

3J 507 10 0.64 2.0 N N

3K 507 5 0.32 2.0 N N
68 

Table 4-15. Repeat Feasibility Study Run 5 (10.2 g/hr held constant) with FLIR and Opgal 

OGI Cameras 

Run ID Conc. (ppmV) Total Flow Rate 

(L/min) 

Mass Release 

Rate (g/hr) ∆T (°C) Detected by FLIR? 

Detected by 

Opgal? 

4A 812 100 10.2 2.3 N N

4B 1015 80 10.2 2.2 N N

4C 1353 60 10.2 2.0 Y N*

4D 2030 40 10.2 1.8 Y Y

4E 2706 30 10.2 1.6 Y Y

4F 4059 20 10.2 2.2 Y Y

4G 8119 10 10.2 1.9 Y Y

* The viewing set up during these tests for the Opgal was not identical to that for the FLIR. The display TV was 

smaller and the video output had to be converted from analog to digital before being displayed. These 

discrepancies at the margins of detection are not anticipated to be representative of actual in-field performance. 

Table 4-16. Rerun of Repeat Feasibility Study Run 5 

Run ID Conc. (ppmV) Total Flow Rate 

(L/min) 

Mass Release 

Rate (g/hr) ∆T (°C) Detected by FLIR? 

Detected by 

Opgal? 

4A 812 100 10.2 1.5 N N

4B 1015 80 10.2 1.5 N N

4C 1353 60 10.2 1.5 N N

4D 2030 40 10.2 1.6 N N

4E 2706 30 10.2 1.5 N N

4F 4059 20 10.2 1.4 Y Y

4G 8119 10 10.2 1.3 Y Y

Table 4-17. Repeat Feasibility Study Run 10 (500 ppmV on High Sensitivity/Enhanced 

Modes) with FLIR and Opgal OGI Cameras 

Run ID Conc. (ppmV) Total Flow Rate 

(L/min) 

Mass Release 

Rate (g/hr) ∆T (°C) Detected by FLIR? 

Detected by 

Opgal? 

5A 507 100 6.4 1.5 N N

5B 507 90 5.7 1.7 N N

5C 507 80 5.1 1.5 N N

5D 507 70 4.5 1.5 N N

5E 507 60 3.8 1.8 N N

5F 507 50 3.2 1.8 N N

5G 507 40 2.5 1.6 N N

5H 507 30 1.9 1.9 N N
69 

Table 4-18. Repeat of Feasibility Study Run 5 with FLIR and Opgal on High 

Sensitivity/Enhanced Mode 

Run ID Conc. (ppmV) Total Flow Rate 

(L/min) 

Mass Release 

Rate (g/hr) ∆T (°C) Detected by FLIR? 

Detected by 

Opgal? 

6A 812 100 10.2 1.6 Y N*

6B 1015 80 10.2 2.1 Y Y

6C 1353 60 10.2 1.5 Y Y

6D 2030 40 10.2 1.9 Y Y

6E 2706 30 10.2 1.7 Y Y

6F 4059 20 10.2 1.9 Y Y

6G 8119 10 10.2 1.8 Y Y

* The viewing set up during these tests for the Opgal was not identical to that for the FLIR. The display TV was 

smaller and the video output had to be converted from analog to digital before being displayed. These 

discrepancies at the margins of detection are not anticipated to be representative of actual in-field performance. 

Table 4-19. Horizontal Wind Shear, Normal/Auto Mode 

Run ID 

Conc. (ppmV) 

Total Flow Rate (L/min) 

Mass Release Rate (g/hr) 

Horizontal Wind 

Velocity (m/s) ∆T (°C) Detected by FLIR? 

Detected by 

Opgal? 

2-1 20297, 50, 127 1.0 1.8 Y Y

2-2 20297, 50, 127 2.0 1.9 Y Y

2-3 20297, 50, 127 5.0 2.1 N N

2-4 20297, 50, 127 9.0 2.1 N N

2-5 20297, 50, 127 12 2.0 N N

Table 4-20. Horizontal Wind Shear, High Sensitivity/Enhanced Mode

Run ID 

Conc. (ppmV)

Total Flow Rate (L/min) 

Mass Release Rate (g/hr) 

Horizontal Wind 

Velocity (m/s) ∆T (°C) Detected by FLIR? 

Detected by 

Opgal? 

2-3 20297, 50, 127 5.0 2.0 Y Y

2-4 20297, 50, 127 9.0 2.1 N N

2-5 20297, 50, 127 12.0 2.1 N N
70 

Table 4-21. Reynolds Number Study Results with 2” Orifice 

Run ID Conc. 

(ppmV) 

Total Flow 

Rate (L/min) 

Mass Release 

Rate (g/hr) 

Reynolds 

Number 

∆T 

(°C) 

Detected by 

FLIR? 

Detected by 

Opgal? 

3-1A 20297 10 26 244 1.8 Y Y

3-1B 20297 20 51 488 1.8 Y Y

3-1C 20297 30 76 732 1.8 Y Y

3-1D 20297 40 102 977 1.6 Y Y

3-1E 20297 50 127 1221 1.9 Y Y

3-1F 20297 60 153 1465 1.8 Y Y

3-1G 20297 70 178 1709 1.8 Y Y

3-1H 20297 80 204 1953 2.1 Y Y

Table 4-22. Reynolds Number Study Results with 1” Orifice 

Run ID Conc. 

(ppmV) 

Total Flow 

Rate (L/min) 

Mass Release 

Rate (g/hr) 

Reynolds 

Number 

∆T 

(°C) 

Detected by 

FLIR? 

Detected by 

Opgal? 

3-2A 20297 10 26 475 1.7 Y Y

3-2B 20297 20 51 950 1.9 Y Y

3-2C 20297 30 76 1425 2.0 Y Y

3-2D 20297 40 102 1900 1.8 Y Y

3-2E 20297 50 127 2375 2.0 Y Y

3-2F 20297 60 153 2850 1.8 Y Y

3-2G 20297 70 178 3325 1.8 Y Y

3-2H 20297 80 204 3800 1.9 Y Y

Table 4-23. Reynolds Number Study Results with 1/2” Orifice 

Run ID Conc. 

(ppmV) 

Total Flow 

Rate (L/min) 

Mass Release 

Rate (g/hr) 

Reynolds 

Number 

∆T 

(°C) 

Detected by 

FLIR? 

Detected by 

Opgal? 

3-3A 20297 10 26 1009 1.9 Y Y

3-3B 20297 20 51 2018 2.2 Y Y

3-3C 20297 30 76 3027 2.1 Y Y

3-3D 20297 40 102 4035 2.1 Y Y

3-3E 20297 50 127 5044 2.1 Y Y

3-3F 20297 60 153 6053 2.2 Y Y

3-3G 20297 70 178 7062 2.0 Y Y

3-3H 20297 80 204 8071 2.3 Y Y
71 

Table 4-24. Reynolds Number Study Results with 1/4” Orifice 

Run ID Conc. 

(ppmV) 

Total Flow 

Rate (L/min) 

Mass Release 

Rate (g/hr) 

Reynolds 

Number 

∆T 

(°C) 

Detected by 

FLIR? 

Detected by 

Opgal? 

3-4A 20297 10 26 1992 1.9 N N

3-4B 20297 20 51 3984 1.9 Y Y

3-4C 20297 30 76 5976 2.1 Y Y

3-4D 20297 40 102 7968 1.8 Y Y

3-4E 20297 50 127 9960 2.0 N N

3-4F 20297 60 153 11952 1.9 N N

3-4G 20297 70 178 13944 1.9 N N

3-4H 20297 80 204 15937 2.0 N N

Table 4-25. Reynolds Number Study Results with 1/8” Orifice 

Run ID Conc. 

(ppmV) 

Total Flow 

Rate (L/min) 

Mass Release 

Rate (g/hr) 

Reynolds 

Number 

∆T 

(°C) 

Detected by 

FLIR? 

Detected by 

Opgal? 

3-5A 20297 10 26 3979 2.0 N N

3-5B 20297 20 51 7958 2.0 N N

3-5C 20297 30 76 11936 1.8 N N

3-5D 20297 40 102 15915 1.8 N N

3-5E 20297 50 127 19894 1.7 N N

3-5F 20297 60 153 23873 1.9 N N

3-5G 20297 70 178 27852 1.6 N N

3-5H 20297 80 204 31830 1.6 N N

Table 4-26. Reynolds Number Study Results with 1/8” Orifice and High/Enhanced 

Sensitivity Modes 

Run ID Conc. 

(ppmV) 

Total Flow 

Rate (L/min) 

Mass Release 

Rate (g/hr) 

Reynolds 

Number 

∆T 

(°C) 

Detected by 

FLIR? 

Detected by 

Opgal? 

3-5A 20297 10 26 3979 1.2 Y Y

3-5B 20297 20 51 7958 1.1 Y Y

3-5C 20297 30 76 11936 1.4 Y N*

3-5D 20297 40 102 15915 1.1 N N

3-5E 20297 50 127 19894 1.3 N N

3-5F 20297 60 153 23873 1.0 N N

3-5G 20297 70 178 27852 0.9 N N

3-5H 20297 80 204 31830 0.7 N N

* The viewing set up during these tests for the Opgal was not identical to that for the FLIR. The TV display was 

smaller and the video output had to be converted from analog to digital before being displayed. These 

discrepancies at the margins of detection are not anticipated to be representative of actual in-field performance. 

Two observations were made after plotting the Reynolds number data in a scatter plot (as shown 

in Figure 4-11). First, it appears detection becomes more challenging around a Reynolds number 

of 8000. Also, the lower mass emission rate values appear to be more difficult to visualize. 

However, due to the limited dimensions of this chart, it is not readily apparent that the mass 

emission rates from this test also correspond to flow rates. And, as observed with the initial 
72 

feasibility study data, the leaks that are being emitted at the lower flow rates (and, therefore, 

mass rates) will be harder to detect. 

Figure 4-11. Overview of Reynolds Number Data 

D. Camera Field Operation 

Laboratory studies are good for isolating specific parameters and making observations under 

carefully controlled conditions. However, the types of conditions experienced in the laboratory 

are rarely ever encountered in the field. ERG designed and constructed the leak simulation 

platform (LSP, shown in Figure 4-12) to evaluate the operation of OGI cameras for leak 

detection in the field. Three flow meters allow for up to three leak simulations to be flowing at 

one time. This allows the evaluation of detecting multiple leaks in close proximity. 

Volunteers of all experience levels ranging from never having used an OGI camera before to 

hundreds of hours of OGI camera use in the field and representing the EPA, industrial 

contractors, and camera vendors participated in a blind leak survey study using the LSP. Table 4-

27 lists all possible leak simulations with the LSP, and Table 4-28 shows the experimental matrix 

that was adopted partway through the testing (changes were made due to time and resource 

constraints). Table 4-29 lists each test participant and their experience level prior to running the 

blind test, and Table 4-30 represents an overview of the results. 
73 

Figure 4-12. Custom-built LSP by ERG from the Front (left) and Side (right) Showing Leak Locations
74 

Table 4-27. List of LSP Leaking Elements 

Leak Identifier Leak Description 

A1 Hatch – Gasket

A2 Hatch – Closure

B Flange – Gasket

C Flange – Attachment

D Ball Valve – Thru-valve leak

E Pop-off pressure release valve

F Gate Valve – Thru-stem leak

G Quick Disconnect – Leak from deformation

H Quick Disconnect – Gasket leak

I Pump – Head gasket

Table 4-28. Initial Experimental Matrix for Blind Surveys 

Run ID 

Leak 1 Leak 2 Survey 

Duration 

(seconds) 

Survey 

Leak ID Conc. Flow Rate Zone 

(L/min) Leak ID Conc. Flow Rate (L/min) 

1 E 2% 40 D 0.2%* 60 15 Point

2 B 2% 60 G 0.2%* 60 15 Point

3 C 2% 20 F 2% 60 300 Free

4 I 2% 60 B 2% 40 300 Free

5 I 2% 60 A1 2% 60 300 Free

6 C 2% 40 -- -- -- 300 Free

7 H 2% 20 F 2% 20 300 Free

8 E 2% 60 D 0.2%* 60 15 Point

9 A2 0.2%* 60 -- -- -- 15 Point

10 G 2% 60 D 0.2%* 60 300 Free

11 E 2% 60 D 0.2%* 60 300 Free

* It was later determined that the 0.2 % (2000 ppmv) concentration level was not detectable due to the conditions 

encountered during testing. 
75 

Table 4-29. List of OGI Camera Operators and Experience Level

Operator Experience Level Description 

A 3. Advanced 

Laboratory Scientist – Designed Study *

Operator had > 100 hours of camera operation experience in the past 

year. None of which was in a field setting. 

B 1. Novice 

Environmental Engineer

Operator had < 10 hours of camera operation experience. None of which 

was in a field setting. 

C 4. Expert 

LDAR Survey and Training Director

Operator had > 300 hours of camera operation experience in the past 2 

years. Almost all of which was in a field setting. 

D 3. Advanced 

LDAR Survey Technician

Operator had ~ 40 hours of camera experience in 2013, with a total of 

about 150 camera hours over entire career. Almost all of which was in a 

field setting. 

E 3. Advanced 

EPA Compliance Engineer

Operator had 90 hours of camera operational experience in 3 years. 

Hours were a mix of laboratory and field settings. 

F 3. Advanced 

Camera Vendor Technical Design Engineer/Scientist

Operator had > 400 hours of camera operation experience strictly in 

controlled/laboratory conditions. 

G 2. Intermediate 

Camera Vendor Salesman

Operator had ~ 40 hours of camera operation experience in 2013, 

typically in an office or laboratory setting. 

H 1. Novice 

EPA Policy Scientist †

Operator had < 10 hours of camera operation experience. None of which 

was in a field setting. 

* This participant was the designer of the study and was therefore biased. 

† This participant was a part of the EPA review team and therefore saw example footage of the leaking equipment

prior to the test day. 
76 

Table 4-30. Overall Blind Survey Results for Leaks Released at 2% Concentration 

Leak ID/Type

Operator/Camera 

A/1 B/1 C/1 C/2 D/1 D/2 E/1 E/2 F/2 G/2 H/1

A1 Hatch - Gasket Y N N - Y - Y - - - - 

B Flange - Gasket Y N N - Y Y N Y Y Y N 

C Flange - Attachment N Y N N Y - Y - - - - 

E Pop-off Y Y N Y Y Y Y Y Y N Y 

F Stem Valve Y Y N Y Y Y Y Y Y Y N 

G QD - Deform Y Y - Y Y Y Y Y Y Y Y 

H QD - Gasket Y N - Y N N N N Y N N 

I Pump Y Y Y - N Y Y N Y Y N 

1 = FLIR GF320, 2 = Opgal EyeCGas 

Green = Leak was detected at least 1 time, Red = Leak was not detected, Gray = Not tested due to time and resource 

constraints. See Appendix C.3 for more information. 

The efforts from this study resulted in the following observations: 

• Some leaks were harder to visualize than others. 

• Although level of experience generally predicted operator performance, it was not 

the rule in all cases. 

• There was no real discernible difference between the two camera types, although 

% detected by camera type (see Appendix C.3 of this document) indicates that the 

Opgal camera or users of the Opgal camera may have been more successful at 

identifying leaks. 

• The 2,000 ppmv (0.2%) test gas was not detectable under non-ideal conditions. 

• Capturing video footage is imperative for reviewing and qualifying leak detection.

• The presence of a heat/steam source during the cold, rainy conditions resulted in 

interference in leak identification.
77 

V. SUMMARY 

Through our evaluations and literature research, we identified a number of parameters that 

impact the detection capability of the OGI cameras. The parameters that have been evaluated by 

ERG and have an impact on the detection capability are: 

• ∆T – The temperature differential between the gas plume and the apparent background 

• Gas matrix of the plume or leak (speciation and concentration) 

• Mass rate of the leak 

• Camera configuration (both equipment and software parameters) 

• Operator ability 

• Wind speed 

• Reynolds number of the leak. 

Other parameters that were evaluated but are not deemed to substantially impact the detection 

capability are intra-model variability and performance degradation over lifespan of camera. 

Other potential parameters that have been identified in the literature research as potentially 

impacting the detection capabilities of the OGI cameras but that have not been evaluated by ERG 

to date are the line of sight, ratio of FOV to the plume size and the standoff distance, and thermal 

interferences (e.g., steam, glint). 

Despite the numerous parameters that may affect the detection capabilities of the OGI camera, 

the empirical testing in the lab and under proper field conditions with the LSP showed the ability 

of the FLIR GF320 and Opgal EyeCGas to detect leaks of 60 g/hr propane at a level of 10,000 

ppmv with a knowledgeable camera operator. 

While our testing focused on each parameter in isolation, it is important to remember that all 

these parameters can work in concert to affect the detection capability of the OGI camera. Figure 

5-1 shows an example concept of an OGI performance envelope for a camera operating during 

normal conditions. Once developed, all the points within the highlighted pentagon would define 

the conditions necessary for valid operation of the OGI camera in order to detect any fugitive 

emissions that are present. As the point of operation gets closer to the middle of the envelope, the 

conditions for use of the camera become more optimal, allowing for easier detection of fugitive 

emissions using the OGI camera. As the point of operation moves toward the outer boundaries of 

the highlighted pentagon, the conditions for use of the camera become less optimal, presenting 

more challenges to detection of fugitive emissions using the OGI camera. 
78 

Figure 5-1. Concept Diagram of OGI Camera Performance Envelope 

If there are parameters beyond the operator’s control (e.g., wind speed) that cause the point of 

operation to be outside of the normal performance envelope, there may be a need to develop 

alternative envelopes to deal with these parameters. For example, requiring a higher ∆T or higher 

concentration can compensate for higher wind speeds to allow for a similar mass rate detection. 

Examples of these adjusted performance envelopes for higher wind speed and higher ∆T and for 

higher wind speed and higher concentration as compared to the normal performance envelope 

are shown in Figure 5-2. This concept of maintaining the performance capabilities of the camera 

by requiring one parameter to move inward in order to compensate for another parameter that 

falls outside the performance envelope would be applicable to any of the parameter that define 

the performance envelope. 
79 

Figure 5-2. Concept Diagram of the OGI Camera Performance Envelope in the Presence of 

Non-Ideal Conditions 

NOTE: The performance envelopes presented in Figures 5-1 and 5-2 represent only a draft 

concept OGI performance envelope for a FLIR GF320 or Opgal EyeCGas. Only after further 

empirical tests of the parameters have been completed and robust empirical correlations have 

been derived can a final envelope be determined. Also, these draft concept performance 

envelopes may not represent all potential parameters that will impact the detection capability. 

With the possibility for a variety of technological advances of OGI cameras in the future, the 

development of these performance envelopes may be specific to camera models, camera modes, 

certain standards, and specific leak profiles such that parameters like the gas composition of the 

leak and the overall concentration of the leak affect the performance envelope while certain 

parameters such as wind have a consistent impact across all types of cameras. 
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VI. LIST OF APPENDICES AND SUPPLEMENTAL DOCUMENTS 

Appendix A: Feasibility Study (WA 2-09) 

1. Test Plan 

2. Final Report 

Appendix B: Spectral Testing (TD-19) 

1. Spectral Testing QAPP 

2. Final Report 

Appendix C: Parameters that Influence Detection (WA 3-08) 

1. Parameter Testing QAPP 

2. Final Report 

3. Blind Study Report 

Appendix D: BIC® Lighter Study Report 

Appendix E: SOP for FLIR Temperature Calibration Verification