United States 

Environmental Protection 

Agency 

Research and 

Development 

METHANE EMISSIONS FROM THE 

NATURAL GAS INuUSTRY 

Volume 3: General Methodology 

Prepared for 

Energy Information Administration {U.S. DOE) 

Prepared by 

National Risk Management 

________ Research Laboratory 

Research Triangle Park, NC 27711 

GRI-94/ 0257.20 

EPA· 600/R-96·080c 

June 1996 

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FOREWORD 

The U.S. Environmental Protection Agency is charged by Congress with protecting the Nation's land, air* and water resources. Under a mandate of national 

enviro:rmentallaws, the Agency strives to formulate and implement actions leading to a compatible balance between human activities and the ability of natural 

systems to support and nurture life. 'Io meet this mandate, EPA's research 

program is providing data and technical support for solving environmental problems today and builcting .a science knowledge base necessary to manage our ecological resources wisely, understand how pollutants affect our health, and prevent or reduce environmental risks in the future. 

The National Risk Management Research Laboratory is the Agency1 s center for 

investigation of technological and management approaches for reductng risks 

from threats to human health and the environment. The focus of the Laboratory's 

research program is on methods for the prevention and control of pollution to air, 

land. water. and subsurface resources; protection of water quality in public water 

systems; remediation of contaminated sites and groundwater; and prevention and 

control of indoor air pollution. The goal of this research effort is to catalyze 

development and implementation of innovative, cost-effective enVironmental 

technologies; develop scientific and engineering information needed by EPA to 

support regulatory and policy decisions; and provide technical support and infOrmation transfer to ensure effective implementation of environmental regulations 

and strategies. 

This publication has been produced as part of the Laboratory's strategic longterm research plan. It is published and made available by EPA's Office of Research and Development to assist the user community and to link researchers 

with their clients. 

E. Timothy Oppelt. Director 

National Risk Management Research Laboratory 

EPA REVIEW NOTICE 

This report has been peer and administratively reviewed by the U.S. Environmental 

Protection Agency, and approved for publication. Mention of trade names or 

commercial products does not constitute endorsement or recommendation for use. 

This document is available to the public through the National T echnicallnfonnation 

Service, Springfield, Virginia 22161. 
METHANE EMISSIONS FROM 

EPA-600 IR-96-0BOc 

June 1996 

THE NATURAL GAS INDUSTRY, 

VOLUME 3: GENERAL METHODOLOGY 

FINAL REPORT 

Prepared by: 

Matthew R. Harrison 

Hugh J. Williamson 

Lisa M. Campbell 

Radian Corporation 

8501 N. M<ipac Blvd. 

P.O. Box 201088 

Austin, TX 78720-1088 

DCN: 95-263-081-13 

For 

GRI Project Manager: Robert A. Lott 

GAS RESEARCH INSTITUTE 

Contract No. 5091-251-2171 

8600 West Bryn Mawr Ave. 

Chicago, IL 60631 

and 

EPA Project Manager: David A. Kirchgessner 

U.S. ENVIRONMENTAL PROTECTION AGENCY 

Contract No. 68-D!-0031 

National Risk Management Research Laboratory 

Research Triangle Park, NC 27711 
DISCLAIMER 

LEGAL NOTICE: This report was prepared by Radian International LLC as an account of 

work sponsored by Gas Research Institute (GRJ) and the U.S. Envirotunental Protection 

Agency (EPA). Neither EPA, GRI, members of GRI, nor any person acting on behalf of 

either: 

a. Makes any warranty or represe!ltation, express or implied, with respect to the accuracy, 

completeness, or usefulness of the information contained in this report, or that the use 

of any apparatus, method, or process disclosed in this report may not infringe privately 

owned rights; or 

b. Assnmes any liability with respect to the use of, or for damages resulting from the use 

of, any information, apparatus, method, or process disclosed in this report. 

NOTE: EPA's Office of Research and Development qnality assurance/qnality control 

(QNQC) requirements are applicable to some of the count data generated by this project. 

Emission data and additional count data are from industry or literature sources, and are not 

subject to EPA/ORD's QA/QC policies. In all cases, data and results were reviewed by the 

panel of experts listed in Appendix D of Volume 2. 

ii 
Title 

Contractor 

Principal 

Investigator 

Report Period 

Objective 

Technical 

Perspective 

RESEARCH SUMMARY 

Methane Emissions from the Natural Gas Industry, 

Volume 3: General Methodology 

Final Report 

Radian International LLC 

GRI Contract Number 509I-25I-2I7I 

EPA Contract Number 68-DI-003I 

Matthew R. Harrison 

March I99I -June I996 

Final Report 

This report describes the methods used to quantifY the annnal methane 

emissions from the natural gas industry. The methods include the 

general methods used for emission factor measurement, activity factor 

quantification, and extrapolation. 

The increased use of natural gas has been suggested as a strategy for 

reducing the potential for global wanning. During combustion, natural 

gas generates less carhon dioxide (C02) per unit of energy produced than 

either coal or oil. On the basis of the amotmt of C02 emitted, the 

potential for global warming could be reduced by substituting natural gas 

for coal or oil. However, since natural gas is primarily methane, a potent 

greenhouse gas, losses of natural gas during production, processing, 

transmission, and distribution could reduce the inherent advantage of its 

lower C02 emissions. 

To investigate this, Gas Research Institute (GRI) and the U.S. 

Environmental Protection Agency's Office of Research and Development 

(EPNORD) cofunded a major study to quantifY methane emissions from 

U.S. natural gas operations for the I992 base year. The results of this 

study can be used to construct global methane budgets and to determine 

the relative impact of natural gas on global warming versus coal and oil. 

This report is Volume 3 of a multi-volume set of reports that fully 

describe the project. While general methodology is covered in this 

report, specific statistical methodology is covered in Volume 4, and 

detailed activity factor methodology is covered in Volume 5. 

UI 
Results 

Technical 

Approach 

Project 

Implications 

This report provides a brief summary of the methods used by the 

GRI/EP A project to estimate emissions from the natural gas industry. 

The methods have been extensively reviewed by industry experts and by 

project advisors throughout the duration of this multi·year project. The 

following is included: methods used to characterize the industry and to 

identify each emission source, the measurement teclmiques used to 

mell.Sure emissions, the procedures used for calculating emissions from 

sources that couldn't be measured, methods used to extrapolate perdevice emissions to national totals, and the sampling techniques and 

statistical methods used to detennine the accuracy of the emissions 

estimate. 

The national emissions for the base year are 314 ± 105 Bscf (± 33%), 

which is equivalent to 1.4 ± 0.5% of gross natural gas production. The 

program reached its accuracy goal and provides an accurate estimate of 

methane emissions that can be used to construct U.S. methane 

inventories and analyze fuel switching strategies. 

The techniques used to determine methane emissions were developed to 

be Representative of annual emissions from the natural gas industry. 

However, it is impractical to measme every source continuously for a 

year. Therefore, emission rates for various sources were determined by 

developing annual emission factors for sources in each industry segment 

and extrapolating these data based on activity factors to develop a 

national estimate, where the national emissions estimate is the product of 

the emission factor and activity factor. This report documents this 

overall technical approach. 

The development of specific emission factors and activity factors for 

each source category are presented in separate reports (Volumes 6 

through 15). 

For the 1992 base year the annual methane emissions estimate for the 

U.S. natural gas industry is 314 Bscf ± 105 Bscf (± 33 %). This is 

equivalent to 1.4% ± 0.5% of gross natural gas production. Results from 

this program were used to compare greenhouse gas emissions from the 

fuel cycle for natural gas, oil, and coal using the global warming 

potentials (GWPs) recently published by the Intergovernmental Panel on 

Climate Change (IPCC). The analysis showed that natural gas 

contributes less to global warming than coal or oil, which supports the 

fuel switching strategy suggested by IPCC and others. 

In addition, results from this study are being used by the natural gas 

industry to reduce operating costs while reducing emissions. Some 

companies are also participating in the Natural Gas-Star program, a 

iv 
voluntary program sponsored by EPA's Office of Air and Radiation in 

cooperation with the American Gas Association to implement 

cost-effective emission reductions and to report reductions to EPA. 

Since this program was begw1 after the 1992 baseline year, any 

reductions in methane emissions from this program are not reflected in 

this study's total emissions. 

Robert A. Lott 

Senior Project Manager, Environment and Safety 

v 
TABLE OF CONTENTS 

Page 

l.O SUMMARY ................................................. I 

2.0 INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 

3.0 METHOD USED TO CHARACTERIZE THE NATURAL GAS INDUSTRY ... 4 

3.1 Natural Gas Industry Defmition ............................... 

3.2 Production 

4 

Segment Defmition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 3.3 Gas Processing Segment Defmition ............................ 

3.4 Transmission 

9 

and Storage Segment Defmition .................... 

3.5 Distribution 

10 

Segment Defmition ............................. 13 

4.0 EMISSION ESTIMATION TECHNIQUES .......................... 15 

4.1 Measurement Techniques for Steady Emissions . . . . . . . . . . . . . . . . . . . 

4.2 Calculation 

15 

Approach for Unsteady Emissions . . . . . . . . . . . . . . . . . 17 

5.0 GENERAL EXTRAPOLATION METHODOLOGY .................... 19 

5.1 Emission Factors ....................................... 

5.2 Activity 

20 

Factors. . ....................................... 21 

6.0 SAMPLING AND STATISTICAL ACCURACY ...................... 45 

6.1 Sampling Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 

6.2 Screening 

47 

for Bias in Activity Factors . . . . . . . . . . . . . . . . . . . . . . . . . 

6.3 Screening 

53 

for Bias in Emission Factors ........................ 

6.4 Accuracy 

54 

Target ........................................ 6.5 Overall 57 Statistical Accuracy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61 

7.0 REFERENCES .............................................. 63 

APPENDIX A - Production Source Sheets ... · ....................... A-I 

APPENDIX B - Gas Processing Source Sheets . . . . . . . . . . . . . . . . . . . . . . . B-1 

APPENDIX C - Transmission/Storage Source Sheets . . . . . . . . . . . . . . . . . . . C-1 

APPENDIX D - Distribution Source Sheets ......................... D-1 

APPENDIX E- Conversion Table ................................ E-1 

VI 
LIST OF FIGURES 

Page 

3-1 Gas Industry Flow Chart . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 

3-2 Industry Boundaries ............................................ 7 

3-3 Gas Processing Plant . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 

34 Transmission and Storage Stations ................................. 12 

3-5 Distribution Segment Equipment .................................. 14 

5-1 Selected Production Regions ..................................... 29 

6-1 lllustration of Random and Bias Errors ...............•............. 46 

vii 
LIST OF TABLES 

Page 

5-l Well-Defined Activity Factors .................................... 23 

5-2 Examples of Developed Activity Factors ............................ 24 

5-3 Example Data Compilation of Sites in Region X ....................... 27 

5-4 Regional Differences in Production Rates and Well Counts . . . . . . . . . . . . . . . 30 

5-5 Production Sites Summary ...................................... 32 

5-6 Data for Offshore Production Sites . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 

5-7 Data for Gulf Coast Onshore Production Sites . . . . . . . . . . . . . . . . . . . . . . . . 34 

5-8 Data for Central Plains Production Sites . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35 

5-9 Data for Pacific/Mountain Production Sites . . . . . . . . . . . . . . . . . . . . . . . . . . . 36 

5-10 Data for Atlantic and Great Lakes Production Sites ..................... 37 

5-11 Gas Processing Plants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 

5-12 Transmission Compressor Stations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41 

5-13 Storage Compressor Stations ..................................... 43 

6-1 Estimated Methane Emissions from Distribution Metering and Pressure 

Regulating Stations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56 

6-2 Percentage of Error in Total Emissions ............................. 59 

viii 
1.0 SUMMARY 

Fuel switching has been suggested by the International Panel on Climate 

Change (IPCC), U.S. Environmental Protection Agency (EPA), and others as a strategy for 

reducing global warming. During the combustion process, natural gas generates less carbon 

dioxide (C02) per unit of energy generated than either coal or oiL On the basis of the 

amount of C02 generated, global wanning could be reduced by substituting natural gas for 

coal. However, since natural gas is primarily methane, a potent greenhouse gas, losses of 

natural gas during the production, transmission, and distribution of natural gas could reduce 

or even eliminate the inherent advantage of its lower carbon dioxide emissions during 

combustion. For this reason, Gas Research Institute (GRJ) and the U.S. Environmental 

Protection Agency Office of Research and Development (EPA-ORD) developed a jointly 

funded and managed program to better defme methane emissions from the U.S. natural gas 

industry. The objective of this comprehensive program is to quantify methane emissions 

from the gas industry, beginning at the wellhead and ending immediately downstream of the 

customer's meter, with an overall accuracy goal of 0.5% of natural gas production (± I 11 

Bscf) based on a 90% confidence level. 

This report provides a brief summary of the methods used by the GRJIEPA 

project to estimate emissions from the natural gas industry. The methods have been 

extensively reviewed by industry experts and by project advisors throughout the duration of 

this multi-year project. The methods include the following: the industry characterization 

that was used to identify each emission source, the measurement techniques used to directly 

measure emissions, the calculation approach used to estimate unmeasured emissions, the 

activity factor approach used to extrapolate per-device emissions to national totals, and the 

sampling techniques and statistical methods used to determine the accuracy of the emission 

estimate. These methods are more completely described in other volumes prepared as part 

of this project. 
2.0 INTRODUCTION 

The GRI/EPA project was conducted in three phases: seeping, methods 

development, and implementation. During the seeping study, methane emissions from each 

source in the gas industry were estimated c.n the basis of available data and engineering 

judgement. These initial estimates were used to set priorities for data collection according 

to the relative contribution to emissions or the uncertainty in emissions. 

In the second phase of the program, methods were developed to measure 

and/or calculate emissions from ail sources of methane emissions in the gas industry. 

These methods were validated through tests designed to quantify the accuracy in the 

measurement approach (i.e., proof of concept tests), and through industry review for the 

calculation approaches. However, emissions could not be measured or calculated from each 

individual source (e.g., glycol dehydrator, compressor engine) in the natural gas industry 

because of the vast number of sources. Therefore, part of the second phase was to develop 

defensible techniques for extrapolating limited data collected for sources in a specific 

source category to similar sources nationwide. 

The third phase of the program focused on collecting data needed to defme 

emissions from all sources and extrapolating these data to develop a national estimate. 

Data collection in this phase concentrated on high priority sources. An Advisory 

Committee consisting of industry representatives, project sponsors, and other interested 

parties from both the government and private sectors provided guidance and peer review for 

all phases of the program. In addition, an Industry Review Panel provided more detailed 

technical review of the project. 

This report briefly describes the methods used in all phases of the GRIIEPA 

methane emissions study. Section 3 presents the methods for characterizing the industry 

and identifying sources of emissions (part of Phase I of the program). Section 4 presents 

the measurement and calculation methods used to determine emissions from each source 

2 
type or category. Section 5 presents the methods used to extrapolate emissions from 

individual sources to a national total. Section 6 provides a brief summary of the sampling 

and statistical methods used to determine the accuracy of each emissions estimate. The 

appendices (A, B, C, D) present some of the data collected as part of the program and the 

worksheets for determining emissions and extrapolating national annual emissions for each 

source of methane emissions in the natural gas industry. 

3 
3.0 METHOD USED TO CHARACTERIZE THE NATURAL GAS 

INDUSTRY 

The first step for estimating methane emissions from the U.S. natural gas 

industry is to identify and characterize each emission source so that all significant sources 

are included. This section of the report characterizes the industry by outlining the segments 

of the industry as well as the types of equipment found within each segment. (This section 

is identical to Section 3 of Volume 5 on activity factors. 1

) 

While this section draws a general picture of the industry developed by the 

GRI/EPA methane emissions project, it is not intended to present a definitive picture of the 

industry regarding all typical operational parameters but only those that are necessary to 

identify all sources and causes of methane emissions. 

3.1 Natural Gas lndustn' Definition 

The natural gas industry produces and delivers natural gas to various 

residential, commercial, and industrial customers. The industry uses wells to produce 

natural gas existing in underground formations, then processes and compresses the gas and 

transports it to the customer. Transportation to the customer involves intra- and interstate 

pipeline transportation. storage. and finally distribution of the gas to the customer through 

local distribution pipeline networks. 

The generally accepted segments of the natural gas industry are 1) 

production, 2) gas processing, 3) transportation, 4) storage, and 5) distribution. Each of 

these segments is shovm in the overall flow chart for the industry in Figure 3-1. Each 

segment is described in more detail in the following subsections. 

BOlmdaries for the study were defmed to specify what equipment is included 

or excluded from the study. These boundaries were set using input from industry experts. 

4 
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PRODUCTION I 

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Surtace Facilities 

Liquids 

,_?. " 

I 

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PROCESSING I 

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Gas Plant I 

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Liquids I 

I 

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TRANSMISSION/ 

STORAGE 

Compressor 

Stations 

I 

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DISTRIBUTION 

Main and 

Service Pipelines 

Direct 1 

I 

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I 

.-~c~~-----L-4--~~~~~+-~--~M Pipelines I 

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I 

L-~c~-.~~~1~~~~~~~~+--4M 

Storage 

Underground 

Storage 

Reservoir 

Customer Meters 

0 Compressor 

@ Meter 

t;:::1o Pressure 

1*;1 Regulator 

Figure 3-1. Gas Industry Flow Cbart 
The guideline used for setting the boundaries was to exclude equipment in each segment 

not required for the marketing of narural gas. For example, certain oil production 

equipment is excluded from the production segment since it exists to produce oil and is not 

needed for gas production (see Figure 3-2). Similarly, in gas processing, equipment 

associated with the fractionation of propane, butane, and natural gas liquids is excluded. In 

distribution, all equipment up to and including the customer's meter are included. End user 

piping, combustion, and vented emissions are not included. 

3.2 Production Segment Definition 

Emissions of methane that result from oil production, or that occur naturally 

(non-anthropogenic) from formations, are excluded. Unmarketed natural gas, such as that 

produced by oil wells that vent some gas, are not considered part of the gas industry. 

The production segment is composed of gas wells, oil wells, and surface 

equipment. The well includes the holes drilled through subsurface rock that reach the 

producing formation and the subsurface equipment such as casing and tubing pipe. Gas and 

oil surface equipment can include separators, heaters, heater-treaters, tanks, dehydrators, 

compressors, pumps, and pipelines. 

However, the segment definition for gas industry production equipment 

excludes equipment associated with oil production. Figure 3-2 shows the general 

equipment found in the oil and gas production segment as well as the selected boundaries 

for gas industry equipment used by this study. Equipment outside the boundaries were not 

included in the activity factor estimates developed in this study. 

The rationale for defining the boundaries is that all equipment at a gas well 

site, except equipment used to collect and handle liquids that are marketed (oil or 

condensate), is part of the gas industry, but that all equipment at an oil we11 site is excluded 

unless it is used to collect, process or transport marketed natural gas (Figure 3-2). 

6 
-

0 

Wellhead 

OiiW~il t==l 

l._J 

' 

Oil Well 

Wellhead 

(producing 

gas} 

Metlw!eWen ""''"" 

Gas. Well 

Wellhead 

Coropn:ssor 

r---""'-~_.d_~_"'~'"-~;,,:a· ~ 

Salt Wall:!" and 

Oil Stocl< Tanb 

Gas I11dustry 

-

~ 

~ Vapor R~covery Compressor 

Dehydrator 

Figure 3~2. Industry Boundaries 

7 
Therefore, the definition excludes all oil tanks and equipment at all oil wells that do not 

market gas. In addition, it excludes much of the equipment at oil wells that do market gas. 

At oil wells that market gas, the gas production is secondary and usually generates lower 

revenue; the well exists primarily because it produces oil. Therefore, the wellhead, the 

separator, the pneumatic control valves, the well's chemical injection pumps, any field use 

gas lines, and all of the liquid piping are considered part of the oil industry and are 

excluded from the GRJ/EPA gas industry study. The gas industry equipment begins only 

on the gas line downstream of the separator, at the first piece of gas line equipment, such as 

the sales meter, compressor, or dehydrator. 

In general, an oil or oil and gas field may have centralized surface treatment 

facilities or each well site may have its own independent surface facilities. In centralized 

facilities, all of the separators, dehydrators, and compressors may be in one location, with 

gas flowing in from gathering pipelines connected to many wellheads. Decentralized 

facilities have all the necessary surface equipment (separators, compressor, dehydrator, etc.) 

at each individual well site. Centralized facilities can have lower equipment counts per 

well than decentralized facilities. Sometimes the facilities may be primarily decentralized 

but have a few centralized components. For example, separators may be at each well 

(decentralized), while compressors and dehydrators may be centralized. 

'Whatever the field configuratio~ ali gas wells have a wellhead and most 

have a gas meter. AJso independent of the field configuration, gas wells may or may not 

have a separator(s), dehydrator, or compressor. The use of the equipment depends upon 

the free liquid production, absorbed moisture content, and well pressure. For example, 

some sweet, dry gas wells can produce directly to a pipeline. However, most wells require 

separation for free-liquid products (salt water, hydrocarbon condensate, and oil) and some 

dehydration. 

Oil wells that market gas (the only oil wells included in this study) may also 

have centralized or individual well site facilities. They will always have a separator and a 

8 
meter. As with gas wells, they may or may not have a dehydrator or a compressor, 

depending upon the absorbed moisture content and the pressure. 

Oil wells that market gas may be either free-flowing or artificial-lift wells. 

Free-flowing wells often have absorbed or co-produced gas that is marketed. Therefore, 

some of the equipment at these free-flowing oil wells is considered part of the gas industry 

if it exists to market the gas. Artificial-lift oil wells are most often not part of the gas 

industry, but a few do produce gas and therefore are included in the gas industry definition. 

Artificial-lift oil wells that have downhole pumps or surface pump jacks 

usually do not produce or market any gas and therefore are not part of the gas industry. 

Artificial-gas lift oil wells push compressed gas downhole and inject the gas int? the tubing, 

thus using the gas to aerate the oil in the tubing string. This brings the oil back to the 

surface. Only the gas-lift wells that produce and market gas in excess of the amount 

injected are considered part of the natural gas industry. For gas-lift oil wells that market 

gas, the compressors associated with the gas-lift circulation are not considered to be part of 

the gas industry. 

3.3 Gas Processing Segment Definition 

Natural gas processing plants exist primarily to recover high value liquid 

products from the gas stream and to maintain the quality (content and heating value) of the 

gas stream. The liquid products include natural gasoline, butane, and propane. (Ethane is 

sometimes recovered as well.) The products are removed by compression and cooling or 

by absorption. Absorption processes use a fluid, such as lean oil, to absorb the liquid 

components from the gas stream in a tower; the rich oil is then heated to release the 

recovered products. A compression and cooling process uses a turboexpander or a 

refrigeration process to supercool the natural gas so that the products will condense. 

9 
A gas plant may have fractionation towers and stabilization towers to further 

purifY the individual compnnents of the product stream. The back end of the gas plan~ 

such as the fractionation train, is excluded from the gas industry defmition since it exists to 

purifY and market liquid products. The back end of the gas plant has negligible methane 

emissions since the liquids handled contain only trace amounts of methane. 

The front end of the gas plant often contains dehydration facilities, wet gas 

compression, and the absorption or compression and cooling process. All gas plants are 

considered part of the natural gas industry. Therefore, all methane emissions from natural 

gas processing plants are included in this study. Figure 3-3 shows a schematic diagram of 

a gas plant. 

3.4 Transmission and Storage Segment Definition 

The transmission segment moves the natural gas from the gas plant or 

directly from the field production to the local distribution companies (LDCs ). Gas is often 

moved across many states, such as from the Gulf Coast to the eastern seaboard of the 

United States. The segment consists of large diameter pipelines, compressor stations, and 

metering facilities. All of these facilities and all of the equipment they contain are 

considered part of the natural gas industry. 

Transmission compressor stations usually consist of piping manifolds, 

reciprocating or gas turbine (centrifugal) compressors, and generators. Dehydrators may be 

included but are not usually present because of upstream drying. The station may also 

include metering facilities. Figure 3-4 shows a schematic diagram of transmission and 

storage stations. 

Transmission companies also have metering and regulating stations where 

they exchange gas with other transmission companies or where they deliver gas to the 

LDCs. Storage facilities exist to store natural gas produced during off-peak times (summer) 

so that the gas can be produced and delivered during periods of peak demand in the winter. 

10 
c 

Dehydration 

Absorption or 

Compression 

& Cooling Process 

to 

Backend of the Plant 

,--------------

Liquids 

1 

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Figure 3-3. Gas Processing Plant 

II 

C' 2 

r-+C' 4 

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Natural I 

Gasolines I 
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-N 

Gas 

from 

Pipeline 

TRANSMISSION 

COMPRESSOR STATION 

Compressors 

c 1---, 

c 

c 1----1 

c 1---l 

c 1----' 

ABOVE GROUND STORAGE 

rr:lc Cooling ~ 

r-~l'af~ Process 1 ,. 

LNG 

Tank 

Gas 

from 

PipeHne 

Heaters 

----,lr--" 

Transmission Pipeline 

BELOW GROUND STORAGE 

\ 

Compressor 

Station 

Wells 

Dehydrator + + + Storage Field 

Figure 3-4. Transmission and Storage Stations 
Storage facilities are often located close to consumption centers so that a cross-country 

transmission pipeline does not have to be sized for peak Mnter demand. Storage facilities 

can be below or above ground. Above-ground facilities are liquefied natural gas (LNG) 

facilities that liquefy the gas by supercooling and then store the liquid-phase methane in 

above-ground, heavily insulated storage tanks. Below-ground facilities compress and store 

the gas (in vapor phase) in one of several fonnations: 1) spent gas production fields, 2) 

aquifers, or 3) salt caverns. Below-ground storage is the predominant means of gas storage. 

Most storage stations consist of a compressor station that is very similar to a 

transmission compression station (see Figure 3-4). Underground storage facilities also have 

storage field wells and often have dehydrators to remove the water absorbed by the gas 

while undergroWld. Except for emissions from underground leaks in storage formations, all 

storage equipment is included in the boundaries for the gas industty as defined by this 

project. 

3.5 Distribution Segment Definition 

The distribution segment receives high-pressure gas from the transmission 

pipelines, reduces the pressure, and delivers the gas to all of the residential, commercial, 

and industrial conslllTiers. The segment includes pipeline (mains and services), meter and 

regulation stations (city gates), and customer meters. All of these facilities are considered 

to be an integral part of the gas industry. Figure 3-5 shows a schematic of the distribution 

segment and associated equipment. 

13 
Meter and Pressure 

Regulating Pressure-Reducing (M&PR) Station Station 

Mains (Pipeline) 

~ 

@ 

v 

M 

Transmission @ 

Pipeline v Meter 

Pressure-Reducing 

Regulators 

Figure 3·5. Distribution Segment Equipment 

ervrces rna lp M 

S (S II p· e) 

li'l\ 

~ 

""' 

_r.'l\ 

~ 

M 

r.:.. 

""" 

~ M 

""" 

~ 

Customer Meters 

(Residential, 

Commercial, 

Industrial, 

Electric Utility} 
4.0 EMISSION ESTIMATION TECHNIQUES 

After all potential sources of methane emissions in the industry were identified 

and characterized, the emissions were quantified. The method selected to quantify the 

emissions from a source depended on the variability of emissions with time. The sources 

were ·divided into two categories: steady emitters and unsteady emitters. Emission sources 

with continuous bleed rates, or with reasonably steady bleed rates over a typical 

measurement time, are considered "steady" sources and can be more easily measured. 

Fugitive emissions are generally considered steady. Unsteady emitters are defined as sources 

with highly variable emissions, such as a pneumatic device on an isolation valve or a 

maintenance activity that requires blowdown. These emissions sources vary from company 

to company and site to site because of different maintenance practices and operat~g 

conditions. "Steady" is a relative term and is defined by the time period of data needed for 

the study. For this study, the annual value of methane emissions is needed. Because it 

would be impractical to measure emissions all year for every source, it is important that a 

single measurement is representative of the annual emissions. 

This section describes the measurement techniques used for steady emissions 

and the calculation approach used to estimate unsteady emissions. 

4.1 Measurement Techniques for Steady Emissions 

The techniques used in the study for measuring ·steady emissions is briefly 

described below. 

Fugitives Measurement Methods 

Emission factors for estimating fugitive emissions were determined based upon 

measurements of emissions from individual sealed surfaces (components) associated with the 

equipment, such as valve packing, flange gaskets, screwed fittings, and compressor/pump 

15 
seals. Emissions from a large number of components were measured and an average 

emission rate per component determined for each component type. Emissions from an 

equipment source, such as a compressor, or a facility, such as a compressor station, were 

then calculated by multiplying the number of components associated with that equipment or 

facility with the average emission rate per component.2 

Emissions from individual components were measured using one of several methods: 

• A high flow organic vapor analyzer captures the entire leak and 

measures the methane concentration and flow rate. The emissions rate 

is determined from the product of the concentration and flow rate. 

• A total enclosure technique called bagging. Unconuuninated air is 

blown through a plastic bag enclosing the component. The flow rate 

and outlet concentration is measured by an organic vapor analyzer, and 

the leak rate is determined from the product of the concentration and 

flow rate. 

• A screening technique where the methane concentration is measured at 

the point of the leak using a standard organic vapor analyzer. The 

concentration is related to an emission rate by a correlation equation 

that was developed in other srudies and that related bagged emissions to 

the concentration measured during the screening test. 

Tracer Gas Method 

The tracer gas method of measuring methane emissions consists of releasing 

tracer gas (at a known constant rate) near the emission source and measuring the downwind 

concentrations of the tracer gas and methane. Assuming complete mixing of the methane and 

tracer gas and identical dispersion, the ratio of the downwind concentrations is equal to the 

ratio of the release rates. Based upon the downwind concentrations of methane and tracer 

gas and the known release rate of the tracer, the emission rate of methane can then be 

determined. This method was used primarily to measure emissions from meter and pressure 

regulating stations. 3 

16 
Leak Statistics Method 

The leak statistics method is used to quantify methane emissions from 

underground mains and services in distribution systems. Emission rates are measured for a 

large number of leaks to accurately determine the average emission rate per leak as a 

function of pipe material, age, pressure, and soil characteristics. The leak statistics program 

was conducted as a cooperative program between EPNGRI and industry. The industry 

participants used specially designed equipment to measure leakage rates from underground 

distribution mains and services. To perform the measurement, a pipe segment containing the 

leak is isolated, the isolated segment repressurized, and the volumetric flow required to 

maintain normal operating pressure in the isolated segment is measured. The leak statistics . method combines the measured leakage rate per leak with the historical leak records of the 

companies and national leak repair data to determine the number of leaks per mile for 

different pipe material. The emissions are determined by multiplying the leak rate per leak 

by the leaks per mile and number of miles of pipe.' 

Direct Flow Measurement 

The direct flow method was used to measure emissions from some pneumatic 

devices and leaks in some open ended lines. Since the gas consumption of certain pneumatic 

devices is emitted to the atmosphere, a flow measurement of the supply gas to the pneumatic 

device can be used to characterize the device emissions. Measurements used by this study 

involved a direct flow turbine meter that was installed in the supply gas lines. 5 Leaks from 

some open ended lines were measured by directly connecting a gas meter to the line. 

4.2 Calculation Approach for Unsteady Emissions 

Emissions that are intennitten; or unsteady have highly variable emission rates 

during a year. Because it would not be practical to collect data continuously for a year for 

each source, emissions from these sources were often calculated rather than measured. 

17 
For some sources, such as maintenance emissions, detailed company 

calculations are available for multiple years. 6 However, most sources of emissions are not 

tracked by companies and therefore must be calculated. 

Each unsteady source of emissions requires data gathering and a unique set of 

equations to quantify the average annual emissions. In general, all unsteady sources of 

emissions require the following infonnation to quantify annual emissions: 

• A detailed technical characterization of the source. identifying the 

important parameters affecting emissions. (This information was 

documented for individual source types in other Tier 3 reports on each 

major emission type. ·~ 

• Data gathered (from multiple sites) that would be needed to calculate 

emissions per event. 

• Sufficient data to define the frequency of events. 

An example of emissions calculated for an unsteady source is the estimate of 

emissions from a vessel blowdown for routine maintenance. In this case, the volume, 

pressure, and temperature of gas contained in the vessel before blowdown is "calcula~" to 

quantify the losses from the blowdown event. Additionally, an average frequency of these 

vessel blowdown events is necessary to determine the annual losses from this source of 

methane emissions. 

In some cases, measurement from other studies were used to establish the 

emissions per event. Therefore, these emissions data were combined with site data collected 

in this study to quantify the number of events per year in order to calculate the annual 

emissions from these sources. Examples of sources where data from other studies were used 

are: emissions from compressor exhaust, gas-operated pneumatic devices. glycol dehydrator 

regenerator overhead vents, and gas-operated chemical injection pumps by measuring the 

emissions per event. 

18 
5.0 GENERAL EXTRAPOLATION METHODOLOGY 

By necessity, data were collected on a relatively small percentage of sources 

within each source category. These data were extrapolated to obtain nationwide estimates for 

similar sources throughout the industry. The extrapolation techniques for creating nationwide 

emission estimates were developed so that the emissions for each source category could be 

estimated to meet a specified level of precision and negligible bias. 

The extrapolation approach is a method to scale-up the average emissions from 

a source, determined by a limited sampling effort, to represent the entire population of 

similar sources in the gas industry. The extrapolation approach uses the concept of emission 

and activity factors to estimate emissions based on the limited number of samples. These 

factors are defined in such a way that their product equals the total emissions from a source 

category. 

EF x AF = National Emissions (1) 

Typically, the emission factor is the average measured or calculated emissions 

from a large number of randomly selected sources in a source category and the activity factor 

is the total number of sources in the entire target population or source category. However, 

in applying this simplified approach to developing emission and activity factors it is 

imponant to ensure that there is no bias in the data. 

The extrapolation methodology involves more than just the scale-up of 

emissions data; it also includes the sampling approach which is fundamental to the accuracy 

of the emissions data. 

This section describes the two components for the extrapolation equationemission factors and activity factors. 

19 
5.1 Emission Factors 

The emission factor is generally defmed as the annual emissions per source. 

In many cases. the emission factor was calculated by simply summing the emissions data 

from each source and dividing by the number of sources sampled. The emissions data would 

be measurements or estimates for each source. In some cases, the variability of the 

emissions data from source to source is very large. For source types of this nature, it is 

often possible to reduce variability by redefining the emission factor or by stratification. 

Reducing the variability is important because it reduces the number of data points needed to 

achieve the accuracy target. 

Redefming the Emission Factor 

For a few types of sources, emissions can be more accurately estimated with 

fewer data points when the emission factor is defined not as a simple average for the source 

but in relation to key parameters that influence the emissions from the source. This is 

essentially the same as subdividing the source category into subsets. Since the variability is 

significantly reduced, fewer total data points are required to achieve an acceptable level of 

accuracy. 

For example, the internal combustion engines that drive compressors in the gas 

industry vary in size (i.e., horsepower rating). If data were collected on individual engines 

in the industry and an average emission rate per engine was established, the variability from 

engine to engine would be very large because of size differences. However, if the emission 

factor for the engines is defmed by horsepower of the engine (i.e., annual emissions per 

horsepower), then the variability from engine to engine and therefore the number of samples 

required to reach an acceptable accuracy are both significantly reduced. 

The number of data points required may also be reduced by stratifying on the 

basis of parameters that affect emissions. An example is quantification of the methane 

20 
emissions from underground distribution mains and services. Based on limited data, the 

variability in emission measurements for underground distribution lines was determined to be 

very large. By defming parameters that influence the emission rate from distribution lines 

and stratifying the emission factor and activity factor for this source by these parameters, the 

variability of emissions from source to source may be reduced. Data collection resources 

can be allocated to the parameters that contribute the most to the overall uncertainty of the 

estimate. Therefore, by subdividing a source into categories with differing emission 

characteristics and allocating data collection resources to the parameters that influence 

emissions the most, the overall number of samples required to meet the accuracy target can 

be reduced. 

5.2 Activity Factors 

This section on activity factors is an abbreviated version of the text presented 

in Volume 5. 1 The reader is referred to the activity factors report for specific details on 

particular activity fact~rs that cannot be found in Section 5 .2 or in the appendices to this 

report. 

In general, the activity factor is the total population of the source when the 

emission factor is defmed as the annual emissions per source. Exceptions to this general 

definition of an activity factor would only include sources that have an emission factor that 

can be more accurately represented by a parameter(s) that influences emissions (e.g., the 

emission factor for internal combustion engines is in tenns of emissions per horsepowerhour). For these exceptions, the activity factor would be the parameter that influences 

emissions (e.g., horsepower-hours/year). 

In some cases, existing programs track the total nationwide population of a 

source type, such as gas wells, miles of transmission and distribution pipelines, and total 

national production, within the natural gas industry, as shown in Table 5-1. However, in 

many cases, the total population of a source type within the gas industry is unknown. 

21 
Table 5-2 presents some of the activity factors that are not tracked nationally, but that were 

generated by this project. 

For sources that have an unknown population, site visits were conducted to 

determine the number of sources at each site and to scale-up the site data to represent the 

total population. These site visits to collect activity factor data are typically conducted in 

conjunction with the data collection efforts for the emission factor. The number of sites 

visited, gas produced or marketed, and equipment counts are presented in Section 6.1, 

Sampling Approach. These site count data are scaled by using population data that is known 

and is related to the source. For example, in the GRIIEPA study, no data were available on 

the nationwide population of production separators. To calculate this value, the number of 

production separators at a site, gathered as part of site visits, were divided by the number of 

wells at each site. Then, the average ratio of separators to wells from all site visit data were 

used to extrapolate nationally by multiplying by the national well count. However, when 

scaling the site visit data to represent the entire population, a check for bias is made. (Refer 

to Section 6.2, Screening for Bias in Activity Factors.) 

For sources that are not tracked nationally, individual company data or 

regional surveys (surveys by state agencies or trade organizations) were sometimes available. 

Metering/pressure regulating stations, glycol dehydrators, and compressor engines/gas 

turbines are tracked on a company wide basis or through regional surveys. For regional or 

company tracked activity factors, sufficient company/regional data had to be gathered to 

comprise a representative sample to extrapolate to a national population. In most cases. 

entire companies or regions could be represented by the data collected from one sample; 

therefore, few samples were required, in general, to represent the national population 

accurately. 

The extrapolation of equipment activity factors from individual site data within 

a stratum is usually handled by selecting an "extrapolation parameter" (EP) that is known for 

the site as well as regionally or nationally. Examples of extrapolation parameters are the 

22 
TABLE 5-1. WELL-DEFINED ACTIVITY FACTORS 

Segment 

Total Industry 

Production 

Processing 

Transmission and Storage 

DistributiOn 

Activity Factor Nru:ne 

Gross Gas Production (Tscf) 

No. of gas wells 

No. of oil wells 

No. of gas plants 

No. of AGR units 

Miles of transmission pipeline 

No. of storage facilities 

No. of wells 

Miles of mains 

No. of services 

23 

Number 

22.13 

276,000 

602,000 

726 

371 

284,500 

475 

18,000 

888,000 

43,714,000 

(Continued) 
TABLE 5-2. EXAMPLES OF DEVELOPED ACTIVITY FACTORS 

Segment ACtivity Factor Name Number 

Total Industry Reciprocating compressor drivers 44,130 

Turbine compressor drivers 1,543 

Number of glycol dehydrators 39,620 

Production No. of oil wells marketing gas 209,000 

No. of gas wells requiring unloading 114,100 

Compressor drivers 17,100 recips 

Engineer MMHp-hr 27,460 

Offshore platforms 1 ,114 

Glycol dehydrators 37,820 

Glycol dehydrator throughput (MMscfy) 12,400,000 

Separators 167,200 

In-line heaters 51,000 

Total production vessels 256,000 

Chemical injection pumps 16,970 

Pressure relief valves 529,400 

Gathering pipeline miles 340,000 

Pneumatic devices 249.100 

Processing Compressor drivers and installed HP 4,092 recips (4.19 MMHP) 

726 turbines (5.19 MMHP) 

Annual compressor operating hours (average) 6,626 (recips) 

6,345 (rurbines) 

Glycol dehydrator throughput (M:Mscfy) 8,630,000 

Acid gas recovery units 371 

(Continued) 

24 
TABLE S-2. EXAMPLES OF DEVELOPED ACTIVITY FACTORS (Continued) 

Segment ActiVity Factor Name 

Transmission and Storage Compressor drivers and installed HP 

Distribution 

Annual driver operating hours (average) 

- Transmission compressor drivers 

- Transmission generating drivers 

- Storage compressor drivers 

- Storage generating drivers 

Transmission compressor stations 

Glycol dehydrator (throughput (MMscfy) 

M&R stations 

- Farm taps 

- Interconnects 

- Direct industrial sales 

M&R stations 

Outdoor customer meters 

Leak frequency 

25 

Number 

7,715 recips (13.4 MMHP) 

817 turbines (5.1 MMHP) 

3,964 (recips) 

2,118 (turbines) 

I ,352 (recips) 

474 (turbines) 

3,707 (recips) 

2,917 (turbines) 

191 (recips) 

36 {turbines) 

I ,700 

3,086,000 

71,690 

2,533 

938 

!32,000 

40,049,000 

Various 
number of wells for production, number of plants for processing, and number of compressor 

stations for transmission. Populations of other equipment, such as the count of separators at 

the site, are then divided by that term, allowing the resulting ratio to be easily extrapolated 

to a regional or national total. 

where: 

However, the regional ratio of 

AF, = 

EP 

--"AF""·'-

EP 

activity factor (population) of equipment type 1 

extrapolation parameter. 

can be determined from 1) regional sums, or 2) by averaging the ratio from each site. The 

extrapolation plan must select one of these two methods based upon technical merit. These 

two methods can be described as: 1) weighting the site counts by the extrapolation activity 

factor, or 2) using an average count per site (not weighting). 

(2) 

For example, to determine the number of separators in a region, the 

production site count of separators and wells at a site could be extrapolated to the regional 

total by two methods: 1) summing the separators and dividing by the total well count (each 

site data is weighted by the total well counts), or 2) by averaging all of the site ratios of 

separators/well (thus treating each site as an equally representative sample). The decision on 

which method to use depended upon a technical analysis of whether that method would 

introduce bias. The method selected might vary from segment to segment, but was generally 

constant across most calculations within a segment. The first method, summing equipment 

from all sites and dividing by the sum of the extrapolation parameter. was used almost 

exclusively by this project. This is discussed in detail in Volume 4 on statistical 

methodology. 10 

26 
The following hypothetical example illustrates the two options for extrapolating 

activity factors. The following table (Table 5-3) and calculations give an example of the two 

methods for determining the number of separators in a region in the natural gas production 

segment. 

TABLE 5-3. EXAMPLE DATA COMPILATION OF SITES IN REGION X 

Sire Count of Site Count of Gas Site Ratio 

Site Separators Wells (separators/well) 

I 140 138 1.01 

2 324 321 1.01 

3 100 100 1.00 

4 5 15 0.33 

5 10 1000 0.01 

TOTAL 579 1574 

On a basis weighted by the total wells at a site, the regional ratio is 579/1574, 

which equals 0.37 separators/well. This number is heavily weighted by one of five sites that 

had a low separator per well count but a high number of wells (about ten times as many as 

any other site). If the second method is used, each site is treated as an equally representative 

sample and the average of the site ratios is used; the result is 0.67 separators/well. 

The first method was selected for all production activity factor extrapolations 

since there is a reason to believe that a randomly selected site that has many wells is 

representative of a larger portion of the population than a randomly selected site with only a 

few wells. Weighting by well count assumes that a larger number of wells at a site means 

that the site is representative of a larger population than a site with a smaller well count. 

Volume 5 on activity factors 1 provides additional details on this method. 

In addition, some equipment activity factors sources could be scaled up by 

several possible EPs. If a known physical/technical relationship existed between the source 

27 
population and one EP, then that parameter was selected. However, where the relationship 

between the source population and the other parameters is not obvious from a technical 

perspective, many approaches having technical merit were used, and either a) the average of 

the methods was used, or b) the resulting data from individual companies statistically 

analyzed to determine the appropriate extrapolation approach. 

For example, it was not clear from a technical perspective whether to scale-up 

the number of metering/pressure regulating stations by miles of main pipeline or system 

throughput, which were the only known population statistics. The station counts from 

individual companies were examined both from a per mile main and per system throughput 

basis. A linear regression analysis showed that if the data were preferentially extrapolated 

using a per mile main basis, the resulting national extrapolation would have lower variability. 

In production, the number of separators appears to be technically related to both well count 

and throughput. Therefore, separator count was extrapolated by both methods, and the 

average of the two national estimates was used. 

Activity Factors Developed for Production Sources 

Most production activity factors were extrapolated by ratio to known EPs. 

The extrapolations were done on a regional basis, since regional biases were known to exist 

aod each of the well-known EPs (i.e., well count and production throughput) were also 

known on a regional basis. Six regions were selected based upon an analysis of the 

production and well population centers in· the United States .• as well as based upon known 

differences in practices in various regions. The regions are: I) Gulf Coast Onshore, 2) Gulf 

Coast Offshore, 3) Central Plains (onshore), 4) Atlantic & Great Lakes (onshore), 5) Pacific 

and Mountain (onshore), and 6) Pacific Offshore. Figure 5-l shows the regions selected and 

which states are included. 

The differences in the regions justify their selection and can be seen in Table 

5-4. Specifically, Table 5-4 shows the regional biases that exist in production versus well 

28 
P.M. Offshore 

G.C. Offshore 

Figure 5-1. Selected Production Regions 
w 

0 

TABLE 5-4- REGIONAL DIFFERENCES IN PRODUCTION RATES AND WELL COUNTS 

Stitk:l ID Rqioll fbi •re 

R<Pul Grotapbgs >SDibtUyr 

Gulr Coast Region Total TX,LA,FL 

GC Offshore' 

GC Onshore 

Central Plains {onshore) OK,AR,CO,MO,NM,WY ,KS 

Pacific and Mountain Tohl:l UT,CA,AK 

PM Offshore• 

PM Onshore 

Atlantic and Great Lakes PA,MI,OH,WV 

(onshore) 

TOl'AL U.S. 

• Table 3-17, Gas Facts 11 

b Natural Gas Annual 12 

c Table 3-10, Gas Facts 11 

1992 ProdKbr: Gu 

W""' 

Ptr«Rf Gf 

Coul Totol 

63667 lJ.I 

4021 

S9ti46 ,,. '·' 

80924 293 

2266 .. 

65 0.0 

2201 03 

129157 46.8 

276014 IOO.Oo/e 

•m Prodvdac oo Wdll" 

Pttu.t of 

cout Tolol .. . 

217567 36.1 

5140 0.9 

212427 353 

19!1103 JJ.I 

46722 7.8 

2040 0.3 

44682 7.4 

138805 ll.O 

602197 100.0 

1992 Marl:ded tmGma ........... Pn:MI.c:tio•' 

hrud or l"ft't"t:ft 

.. 

- """""" """' ofGrost Total 

Tobl 

11514 61.5 12272 55.4 

sooo 26.7 5045 22.8 

6514 34.8 7227 32.6 

5424 29.0 5672 25.6 

'" 5.3 JJ9l 15.3 

186 1.0 279 1.3 

798 4.3 Jill 14.1 

790 4.2 796 3.6 

18712 100.0% 622132 100.0"/., 
count. Each region has a unique oil well versus gas well split and a unique production rate 

per well. Two offshore regions exist to account for the known differences in practices 

between onshore and offshore production operations. The well and production demographics 

also support this split, since the offshore regions account for a small portion of the wells 

(1.5% of the gas wells, 1.2 % of the oil wells), but produce 26.1 %of the U.S. marketed 

gas production. 

As shown in Table 5-4, the majority of natural gas produced in the United 

States (more than 64% of total production) occurs is in the Gulf Coast region. Other regions 

only account for 36% of the production, and the majority of that occurs in the Central Plains 

region. However, the split on well count is completely different. The Atlantic and Great 

Lakes region, which accounts for only 3.8% of the gross national gas production, has the 

largest portion of gas wells (46% of the national total) as well as a large fraction of oil wells 

(24%). 

If the source being evaluated is wells or equipment associated with wells (such 

as separators and chemical injection pumps), then bias would potentially be introduced if 

only wells in the Gulf Coast region were sampled, where most of the gas is produced. The 

sources should be combined regionally, and the regional averages then added in the same 

proportion that they are distributed in the actual population. 

The site data used to develop production activity factors are presented in 

Tables 5-5 through 5-10. 

Activity Factors Developed for Processing Sources 

Activity factors in gas processing are significantly simpler than in gas 

production, since the segment consists of one type of facility: gas processing plants. Major 

activity factors were limited to the count of gas plants (and gas plant type), the count of 

dehydrators, the count of acid gas recovery units (AGRs), and compressor data. All of these 

31 
w 

N 

Site 

Survey Type 

- Site Visit 

- Phone Survey 

- Star Site Visit* 

TABLE 5-5. PRODUCTION SITE SUMMARY 

6 

4 

I 

5 

0 

9 

7 

9 

0 

0 

7 

7 

3 

4 

0 

9 

4 

9 

0 

0 

!9 50 sites* 

!0 32 companies 

2 24 site visits 

5 14 phone 

12 surveys 

12 star sites* 

*This does not include all sites visited by Star or other fugitive emissions contractors. Only the sites used for activity 

factor data collection are included. 
TABLE 5-6- DATA FOR OFFSHORE DATA PRODUCTION SITES 

Tolal Equipmen!l Equipment/ Equip./Mkt. Gas Equfp.Prod. Gas 

Region cc-orr ec.orr Gc-orr cc-orr PM-orr PM-orr Off$hore Tolab Total Wells Gas Wells (l/MMdd) (1/MMc!d) 

Site 1 2 3 4 s 6 

Company I 

' 2 ' 3 4 6SJtf.!l. I GC Sw:vey Type v p p p . p p 4 Companies PM GC PM GC PM GC PM GC PM 

Gas Marketed {MMcfd) 0.365 12.5 440 4 17.5 16{) 456.9 177.5 1.66 5.22 

Gas Produced (MMcfd) OS 12.5 440 4 11.5 160 457.0 177.5 1.66 5.22 

Equipment Counts: 

Gas Wells 

Oil Wells 

2 0 80 0 0 12 82 12 

+Oil wells 

3 ISO 0 40 22 0 193 22 

Separators 

that market gas 3 ISO 0 40 22 0 193 22 

4 0 24 0 0 1 28 I 0.10 O.oJ 0.34 0.08 0.06 O.QI 0.06 O.QI 

In-line Heaters 0 0 0 0 2 0 2 0.00 0.06 0.00 0.00 0.00 0.01 0.00 0.01 

Pneumatic Devices 3 0 32 0 0 0 35 0 0.13 0.00 0.43 0.00 0.08 0.00 0.08 0.00 

Chern lnj Pumps 0 0 0 0 0 0 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 

Compressors• 0 . - . 2 0 2 0.00 0.17 0.00 0.17 0.00 0.01 0.00 0.01 

Dehydrators I 0 8 I 2 3 10 5 0.04 0.15 0.11 0.25 0.02 0.03 0.02 0.03 

+Dchy with 3 pH Flash I 

+ Dehy with Vent Control 

I 0 

0 

+ Dehy w/Kimray 

0 0 

Pumps I 

+ Dchy w/Stripping 

I 0 

Gas 0 

Miles of Galhering 

0 0 

Pipeline . . - - . 

Fugitive Component 'ount y N N N N N 

Vented (Site Blow & Purge Dala) y y y y y y 

N01es: I) Survey Type V = Site Visit (Radian); P = Phone Survey; S = Site Visit (Star) 

2) • = Gas lift compre~sors not included. 

3) Y =Yes, N =No;"-"= No Data: 

4) Region Key: GC = Gulf Caast, PM = Pacific Mounlain; CP = Central Plains; A = Atlantic & Great Lakes 
TABLE 5-7. DATA FOR GULF COAST ONSHORE PRODUCTION SITES 

Region GC GC GC GC GC GC .. Gc GC GC TotalGC 

Site 7 8 • 10 II !2 13 14 15 

Compauy s 6 

Equip./ Equip./ 

7 8 • 10 II II 11 !J Sites 

Totili Survey Type v v v v v v v v v Equlp.! Equip .I Mkt. Gas Prod. Ga! 7 Companies Total We!Js Gas Wdls (1/MMcfd) (I/MMc£d) 

Gas Marketed (MMcfd) 23.1 25.5 124 54 28 250 1.9 7 130 643.4 0.54 

Gas Produced {MMcfd) 23.1 25.5 124 

" 28 250 1.9 7 130 643.4 0.54 

F..quipment Counts: 

Gas Wells 

Oil Wells 

13 80 18 130 26 300 0 10 31 608 

so 0 3 3 0 300 "' +Oil wells 

127 0 638 

Separators 

that market gas so 0 3 3 0 300 ISS 68 0 579 

In-line Heaters 

38 

2 56 

80 42 71 26 300 0 II 31 S99 0.50 0.99 0.93 0.93 

Pneumatic Devices 68 

17 23 26 0 0 12 0 136 OJI 0.22 0.21 0.21 

170 0 68 109 

"' Chern lnj Pumps 10 

0 11 31 682 0.57 1.12 1.06 106 

' Compressors• 12 4 2 

0 5 0 0 0 0 0 20 002 0.03 0.03 0.03 

37 0 0 0 

" Dehydrators 7 2 2 

10 80 0.07 0.13 0.12 0.12 

+ Dehy with 3 pH Flash 0 0 

12 26 2 0 4 26 81 0.07 0.13 0.13 0.13 

+Deily with 

2 2 0 0 0 4 0 8 

+ 

Vent Control 4 0 2 0 0 0 0 0 0 6 

+ Dehy 

Dehy 

w/Stripping 

w/!Gmray Pumps 7 I I 6 26 2 0 0 26 69 

Miles 

Gas 0 0 0 0 0 0 0 0 0 0 

of Gathering Pipeline . 46.3 26.4 40 8 . . . . 

Fugitive Component count y y y y y y . . . 

Vented (Site Blow & Purge Data) y y y y y y y y y 

Notes; I) Survey Type V =Site Visit (Radian); P = Phone Survey; S =Site Visit (Star) 

2) • "" Gas lift compressors not included. 

3) Y =Yes, N =No;"-"= No Data; 

4) Region Key: GC = Gulf Coast, PM ~ Pacific Mountain; CP = Central Plains; A .., Atlantic & Great Lakes 
TABLE 5-8. DATA FOR CENTRAL PLAINS PRODUCTION SITES 

RegiOn CP CP CP CP CP CP CP TotaiCP 

Site 16 l7 18 19 

" " " EquJp./ Equip.! 

Company 12 13 14 

" . 16 17 18 7Sft~ Equip./ Equip./ Mkt. Gas Prod. Gas 

Survey Type v v v p p p p 7 CompanieS Total Total Wells Gas Wells (1/MMcfd) (J/MM'cfd) 

Gas Marketed (MMcfd) 42.7 180 196 7 0.2 19.8 2 447.7 0.22 

Gas Produced (MMcfd) 42.7 180 196 7 0.2 20 2.1 448.0 0.22 

Equipmem Counts; 

Gas Wells 138 321 1000 400 I 100 

" Oil Wells 

. 1975 

" +Oil wells 

II 0 0 0 0 4 70 

thai market gas 

" Separators 

II 0 0 0 0 4 70 

130 321 7 400 I 100 I 960 0.47 0.49 2.14 2.14 

In-line Heaters 138 321 0 400 0 0 0 859 0.42 0.43 1.92 1.92 

Pneumatic Devices 449 963 667 100 0 2179 1.33 us 4.95 4.94 

Chern lnj Pumps 28 273 0 13 0 0 0 ll4 0.15 0.16 0.70 0.70 

Compressors• 31 50 64 I 146 0.09 0.10 0.35 0.35 

Dehydra!Ors !6 220 0 400 0 

" I 662 0.32 0.34 1.48 1.48 

+Dehy 

+ Dehy 

with 

with 

Vent 

J pH 

Control 

Flash 0 0 0 0 - 0 

0 0 0 

+Dehy w/Kimray 

- - 0 

Pumps 16 220 0 

" + Dehy w/Stripping Gas 

0 261 

0 0 0 

Miles of Gathering 

- 0 

Pipeline 5.2 - 600 - - - -

Fugitive Component count y y y - -

Vented (Silo Bklw & Purge Data) y y y - -

Notes: I) Survey Type V "" Site Visit (Radian); P "' Phone Survey; S "' Site Visit (Star) 

2) ~ "' Gas lift compressors not included. 

3) Y"' Yes, N "'No; •-· =No Data; 

4) Region Key: GC "' Gulf Coast, PM = Pacific Mountain; CP = Cemra! Plains; A = Arlantic & Great Lakes 
TABLE 5-9. DATA FOR PACIFIC/MOUNTAIN PRODUCTION SITES 

Region PM PM PM PM PM PM PM PM PM Total PM 

Site 23 24 25 ,. 27 28 

" 30 31 

COmpany ,. Equip./ Equip./ 

" 2l 2l 2l ll 

" Survey 'l)pe v v v v 

2l 2l 9 Sites Equip./ Rqulp.l Mkt. Gas Prod, Gas 

v v v v v 4 Companies Total Total Wells Gas WeDs (t!MMcfd) (l/MMrfd) 

Gas Marketed {MMcfd) 4 104 0.138 O.o3 O.o2 0.035 0.8 O.I 11.082 120.2 0.12 

Gas Produced {MMcfd) 4 307 0.138 O.oJ o.oz 0.035 0.8 O.I 11.082 323.2 0.32 

Equipment Counts: 

Gas Wells 

" 0 0 0 0 0 0 0 0 

" Oil Wells 0 m I8 8 10 I5 20 7 728 1719 

+Oil wells that market gas 0 137 I8 8 10 IS 20 7 728 943 

Separators 

In-line He~ters 

4S 0 0 0 0 0 0 0 4S 0.17 0.85 0.41 0.14 

" s ' 2 0 0 0 0 

Pneumatic Devices 

63 0.24 1.00 0.58 0.20 

Chern Inj Pumps 

80 0 0 0 0 0 0 0 0 80 0.011 1.51 0.67 0.25 

Compressors"' 

36 0 0 0 0 0 0 0 0 36 0.04 0.68 0.30 0.11 

I7 I9 0 0 0 0 I I 

Dehydrators 

38 0.14 0.32 0.35 0.12 

s 0 0 0 0 0 I 0 • + Dehy with 3 pH Flash 

0.02 0,09 0.05 0.02 

0 0 0 0 

+Dehy with Vent Comrol 0 0 0 0 

+ Dehy w/Kimray Pumps s 0 I 6 

+ Dehy w/Stripping Gas 0 0 0 0 

Miles of Gathering Pipeline - - - - - - - Fugitive Component count y y N N N N N N N 

Vented (Site Blow & Purge Data) y y N N N N N N N 

Notes; I) Survey Type V = Site Visit {R3dian): P = Phone SUrvey; S = Site Visit (Star) 

2) • = Gas lift compressors not included. 

3) Y =Yes, N =No:"-"= No Data; 

4) Region Key: GC = Gulf Coast. PM = Pacific Mountain; CP = Central Plains; A = Atlantic & Great Lakes 
TABLE 5-10. DATA FOR ATLANTIC & GREAT LAKES PRODUCTION SITES 

Region AGL AGL AGL AGL AGL AGL AGL AGL AGL 

Site J2 

" 34 35 36 37 38 39 40 

Company 23 24 

" " 27 28 

" 30 30 

SuntcyType v p p v p p p s s 

Gas Marketed (MMcfd) 24 6 15 17 12 16 81 0.18 0.18 

Gas Tllruughpul (MMcfd) 24 6 15 17 12 20 81 0.19 0.19 

Oil Throughput(!OOO BID) 0 

Equipment Counts: 

Gas Wells 801) 250 IOOU 520 450 1582 4034 II II 

Oil Wells 0 0 0 0 163 418 0 0 0 

+Oil wells that market gas 0 0 0 163 418 0 0 0 

Separators 151 250 500 520 450 1582 3227 2 

ln-llne Heaters 0 

0 

Pneumatic Devices 

Chern Inj Pumps 

76 0 10 520 450 1582 1294 

0 0 0 12 0 8 25 y 0 

Compressors"' I 

0 

Dehydrators 0 

' + Dehy with 3 pH Flash 

30 0 0 41 

0 0 0 0 

+Dehy with Vent Control 

5 

0 3 

+ Dehy w/K.imray Pumps 

2 

0 2 30 8 0 

'"" + Dehy w!Stfipping Gas 0 

21 0 _, Miles of Gathering Pipeline 

Fugitive Component count y N N N y y y 

Vented 

y 

(Site Blow & Purge Data) y y 

Notes: 

,, 

I) Survey Type V = Site Visit (Radian); P = Phone Survey; S = Site Visit {Star) 

• = Gas lift compressors not included. 

3) y = Yes, N = No;"-" = No Data; 

(Continued) 

4) Region Key: GC "' Gulf Coast, PM "' Pacific Mountain; CP = Central Plains; A = Atlantic & Great Lakes 
TABLE 5-l 0. (Continued) 

Region AGL AGL AGL AGL AGL AGL AGL AGL AGL AGL TotaiAGL 

Site 41 42 43 44 45 46 47 48 49 so Company 30 31 

Equip.! EquJp.l 

Survey Type s s s s s 

31 31 31 31 31 31 31 31 19 Sites Total Equ1p./ Equip./ Mkt. Ga! -Prod. Gas 

s s s s s 10 Companies (SUes 32-50) Total Wells Ga~ Wdb (IIMMtrd) (1/MMdd} 

Gas Marketed (MMcfd) 0.17 0.39 0.37 0.37 0.18 0.23 0.30 0.35 0.13 0.35 173.6 

Gas Throughput (MMcfd) 0.17 0.39 0.37 0.37 0.19 0.23 0.30 0.35 0.13 0.35 178.0 

Oil Throughput (1000 BID) 

Equipment Counts: 

Gas Wells 

Oil Wells 

10 23 22 22 II 14 18 21 8 21 8828 

0 0 0 0 0 0 0 0 0 0 581 

+Oil wells that market gas 0 0 0 0 0 0 0 0 0 0 581 

Separators 0 10 7 8· ' 3 IS 17 ' In-line Heaters 0 0 0 

7 6766 0.72 0.77 38.97 38.01 

0 I I 0 0 0 0 

Pneumatic Devices . . . . 2 0.00 0.00 O.o7 om . . . . . . . 

Chern lnj Pumps 0 0 0 

3932 0.43 0.46 23.07 22.50 

Compressors"' 0 0 0 

0 0 0 0 0 0 0 45 0.00 0.01 0.26 0.25 

0 0 0 0 0 0 0 

Dehydrators . - . . . I 0.00 0.00 0.04 0.04 . . . . . 

+ Dchy with 3 pH Plash 

74 0.01 0.61 0.43 0.42 

' +Dehy with Vent Control 

' + Dehy w/Kimr:ay Pumps 41 

+Dehy w!Stripping Gas 

Mites 

21 

of Gathering Pipeline . . . . . . . . . . 

Fugitive Component count y y y y y y y y y y 

Vented (Sire Blow & Purge Data) . . . . . . . 

Nores: I) Survey Type V = Site Visit (Radian); P = Phone Survey; S "" Site Visit (Star) 

2) • = Gas lift compressors no! included. 

3) Y =Yes, N =No;·-· =No Data; 

4) Region Key: GC = Gulf Coast, PM = Pacific Mountain; CP =Central Plains: A = Atlantic & Great Lakes 
activity factors were either published and well-defined or were developed through other 

studies such as the report by Wright Killen & CoY or Volume 11 on compressor driver 

exhaust. 14 The site data used to developed processing activity factors are presented in Table 

5-11. 

Activity Factors Developed for Transmission Sources 

Activity factors for the transmission segment were simpler than production 

segment factors. The transmission segment is defmitely more homogeneous than the 

production segment. Transmission facilities are either surface compressor stations, surface 

metering and regulating stations, buried pipelines, or underground storage. Most 

transmission pipelines are one of two types: interstate (cross-country) or intrastate (strictly 

regional). Therefore, transmission company data can be extrapolated by using pipeline 

miles, station count, or storage facility count. 

The total number of compressor stations was extrapolated from data on major 

transmission companies listed in Gas Facrs. 11 The total miles of transmission pipeline and 

the number of storage facilities and storage wells is also published. Counts of transmission 

metering stations by type were produced by extrapolating data from Radian's company 

surveys of several transmission companies. Other transmission activity factors were 

developed from Radian site visits to transmission facilities. The site data used to develop the 

transmission activity factors is presented in Tables 5-12 and 5-13. 

Activity Factors Developed for Distribution Sources 

In the d~stribution segment, activity factors were developed for total number of 

leaks in underground mains and services. These activity factors were desegregated by pipe 

service (i.e., mains versus services) and pipe material (i.e., cast iron, cathodically protected 

steel, unprotected steel, plastic, and copper). The estimates of total leaks for each company 

39 
TABLE 5-11. GAS PROCESSING PLANTS 

~ " it"~ ··~··"·· .. 

I 2 3 

Type Cryo Cryo Cryo Lean Oil Cryo Cryo Lean Oil 

Abs., 

Cryo 

Capacity 100 75 70 850 900 

Current Throughput 49 60 56 350 750 140 

. Uni" 7 4 6" 9 I o•u 

- Turb. Eng 0 0 0 2 I I 

- Recip. Eng 7 4 6" 7 0 0 

-Total HP 11000 3700 1 674o" 43300 27000 20000 

Dehys 0 _I 2 3 0 0 

Dehys w/Kimray I 0 0 

Pumps 

Pneum Onll"s 2 3 0 25 25 17 

Vented Data 

- Site y y y y - y 

- - - - - - y 

cc 639 357 799 1458 - -

* Count only of compressor BD OELs, site OELs, and Compressor PRVs. 

** Gas lift compressors not counted in the totals for this site with gas lift for oil recovery. 

*** I turbine drives 2 propane compressors. No NG compressors. 

"Y" =Yes 

Abs. 

40 

40 

4.4** 

0 

4.4'' 

I 

0 

0 

-

6831 

~flU~ 5 5 6 

companies 

Refrig. Refrig. Refrig./ 

Lean Oil 

Abs. 

130 130 140 

130 130 70 

1.4** J.4H 20 19 72 

0 0 5 2 10 

1.4" 1.4" 15 17 62 

1 6267" 59600 

I I I 10 

0 0 I 

0 ()- 0 72 

y y 

- - - -

5902 5902 - y• 
TABLE 5-12. TRANSMISSION COMPRESSOR STATIONS 

~' --- --~ -~ 

.... ,.,.I> .. ·Xh2 . .·:; ~~ ~~er~ ~~'~ ··+ ".: -- " ... :. 

Company Number I I I 2 2 2 3 3 4 4 4 

Compr. Units 13 2 2 6 7 13 12 13 2 10 6 

- Turb_. ~g 0 2 2 0 0 0 2 I 2  3 2 

- Rodp. Eng J3 0 0 6 7 J3 10 12 0 7 4•**  

-Total HP 32650 6900 6900 16900 10400 24800 14560 17570 40000 - -

r 0 0 0 0 I - 0 0 6 0 0 

- Flash Tanks I 6 

- 1 Pumps 0 6 

- Stripping Gas 0 0 

- Vapor Recovery 0 0 

- Vent Flash Gas 

Pneum 48 12 - 8 - 20 75 40 68 83 50 

Wells Not 

Fugitive CC 741** 22Jh 165** - - - 3038 3949 1730 1467 956 

Site B.D Practices y y - y y - - - y y y 

Co. BID No's - - - y y y - - - - -

(Continued) 
t-3 

.. 

. Slto N~n1~•r > • ·.· iii ·.:.::·: .1 ... \>lJ >· 

Company Number 5 6 

Compr. Units 18 2 

- Turb. Eng 0 2 

- Recip. Eng 18 0 

- Total HP 21000 

Dehydrators 0 

-Flash Tanks 

- Kimray Pumps 0 

- Stripping Gas 0 

- Vapor Recovery 0 

- Vent Flash Gas 

Pneum 3 

Wells 

Fugitive CC 1123 134 

Site B.D Practices y 

Co. BID No's 

Fug cc does not include connections or tubing 

* = Elec driven compressors 

** = Not including hydraulic valves 

*** = Recip Engine w/Centrifugal Compressor 

TARLE 5·12. (Continued) 

.•i!i ' ' --- '·: ~ ' : . • 

- .• ----" •- " is - - --·· ·•>~>tJ·• ~- '-'-' ,- --... 

6 7 8 8 

2 26 5 3 

2 0 

0 25 4 3 

0 0 0 0 

Not Applicable 

284 1706 345 12 

y 

**"'* = Docs not include third turbine that was permanently out-of-service 

"_- means no data available, "Y" = Yes 

)11 '• ·:·:;·:o,\~:2(},'~:;_:;_?\i 

·-·-·-PI ·-~r-·-- >.;11 $1\W :::.:. 

9 9 10 10 10 Co's 

7 13 7 2 171 

0 3 0 2 25 

6 10 7 0 145 

191,680 

0 0 8 

38 0 

508 792 

y y y 
Companies 2 3 4 5 6 7 7 7 Co's 

UG UG UG UG LNG UG UG UG 

. Units 3 2 2 4 5' 18 9 9 

- Turb. 

52 

- Recip. Eng 

0 0 0 2' 0 4 0 0 6 

3 2 2 2 0 14 9 9 

-Total HP 

41 

6250 2200 9400 7000 10300' 48510 9000 11600 104260 

4 8 0 

- Flash Tanks 8 

0 0 0 

i Ga. 0 0 

- Vapor 0 0 

- Vent Flash Gas 0 0 

Pneumatics 18 68 127 4 217 

... Wells ? 50 22 83 0 64 219 

w 

cc 1750 1113 8326 1679 887 

Vented Data: 

13700 

- Site 

-Company 

y y y y y y y 

y y 

Fug cc does not include connections or tubing 

• = Elec driven compressors 

'* = Not including hydraulic valves 

*'" = Recip Engine w/Centrifugal Compressor 

"-" means no data available, "Y" =Yes 

UG .., Underground Storage Station 

LNG = Above ground, Liquefied Natural Gas Station 
were based on historical leak records and the average leak per mile (or per service) 

extrapolated by the total national mileage (or number of services). 

For metering/pressure regulating stations, the number of stations was 

collected from each company and extrapolated by the total miles of distribution mains. 

Other activity factors used in the distribution segment were based on weli-defmed activity 

data, such as total mileage of mains/services and throughput. 

44 
6.0 SAMPLING AND STATISTICAL ACCURACY 

A key part of this project was the estimation of the accuracy of the overall 

emission rate. This section explains the techniques used during sampling to maximize 

precision and eliminate bias. The general approach used for statistical accuracy calculations 

is also discussed. 

Accuracy is made up of precision and bias. Precision can be calculated from 

a set of replicate measurements. Bias cannot be calculated, and must be discovered and 

eliminated where possible. Figure 6-1 illustrates the role of random and bias errors in the 

estimation process. In each of the four illustrations in this figure, the center of the 

concentric circles represents the correct answer. In the upper left, there is a significant 

amount of random scatter in the points. The term ''precision" refers to random variability 

alone; in this case, the precision is poor. Additionally, the points are predominantly below 

and to the right of the target. The systematic difference between the points and correct 

answer is a bias. The tenn "accuracy" refers to the total error, including random and bias 

errors. Because of the large bias and the poor precision, the accuracy is also poor. 

In the upper right of Figure 6-!, the points are randomly scattered about the 

correct answer; there is little or no bias in this case, but the precision and accuracy are both 

poor. In the lower left, there is good precision, but there is again a large bias; thus, the 

accuracy is poor. In the lower right, the bias is small and the precision is also good. Thus, 

the accuracy is good in this case. 

The following subsections discuss the approaches used in sampling to handle 

precision, bias, accuracy targets, and overall accuracy calculations. 

45 
• • • 

High Bias+ Low Precision 

= Low Accuracy 

High Bias+ Hlgh Precision 

= Low Accuracy 

• 

• • • • 

• 

0. • 

• • 

Low Bias +Low Precision 

= Low Accuracy 

Low Bias + High Precision 

= High Accuracy 

Figure 6-1. Illustration of Random and Bias Errors 

46 
6.1 Samplin2 Approach 

In general, a sampling program should gather enough replicate samples to 

meet the precision target. If the sample-to·sample variability is high, then more samples 

may need to be taken to reach the desired precision target. Even if the overall precision of 

an estimate is acceptable because the variability in the data is relatively low, the overall 

accuracy may still be poor if the data are biased. 

Sampling bias occurs if the methodology is flawed in a manner that leads to 

a systematic under-representation of parts of the population and a systematic overrepresentation of other parts. Bias, in a statistical sense, can be explained as follows. 

Suppose it was possible to repeat the sampling and measurement process infinite times, and 

that each time the process was repeated, an independent estimate of a given emission factor 

was obtained. If the average of the entire infinite set of emission factor estimates equalled 

the true value, then bias would not exist. If the average of these estimates differed from the 

true value, then the process would be wrong in a systematic sense, and bias would be said 

to exist. The point here is that averaging an infinite set of independent estimates of the 

emission factor would remove random error altogether, leaving only bias error, if any. 

While it is clearly impossible to obtain an infinite set of estimates of an emission factor, the 

example given serves to illustrate the meaning of bias. 

Even if there was no bias, the actual estimate of an emission factor would be 

expected to differ from the true value. First, the estimate is based on less than the total 

number of sources. Random differences bet.veen the set of sampled sources and the 

population of sources introduce a sampling error. Second, physical measurements have 

uncertainties. As is indicated above, the term "accuracy" refers to the closeness of an 

estimate of a quantity to the true value. Accuracy is a measure of random error plus bias 

error. The tenn "precision" refers to random error alone. 

47 
An estimate is precise if it has a small random error, regardless of the bias. 

Suppose, for example, that sources had been selected only from the Gulf Coast, but that a 

very large number of sources had been sampled. The averaging of a large number of 

emission measurements would lead to an emission factor estimate that had a small random 

error. Unless Gulf Coast sources were representative of the source type for the entire 

nation, however, the estimate could have a large bias because the sample of sources did not 

represent the general population. Bias in this example is avoided by sampling in a variety 

of regions of the country. More subtle potential sources of sampling bias and methods for 

avoiding them are discussed in this subsection. 

Several sampling approaches can be applied to avoid bias. 

Random Sampling 

In random sampling, each source in the population has an equal probability 

of being selected. A random sample is expected to "match" the industry population because 

no biases are introduced in selecting the sample sites. The number of data points required 

in a random sample depends on the target accuracy of the final emissions estimate, the 

confidence with which this accuracy is to be met, and the underlying variability among the 

emissions rates of the complete set of sources. 

Random sampling is not a guarantee of accurate results. It is possible, for 

example, that by pure chance random sampling would produce a disproportionately large 

number of sources from the Gulf Coast and an under-representation of sources from the 

West Coast. While such an outcome is unlikely if the sample size is sufficiently large, this 

particular problem can be avoided altogether by selecting an acceptable number of sources 

from each of a set of regions. (See the discussion of stratified random sampling below.) 

There are two major reasons why truly random sampling was not possible in 

the GRl/EPA program. First, a complete list of sources did not exist and still does not 

48 
exist. It was possible, for example, to list all compressor stations whose owners were GRI 

members. 'While this might account for 90% of the compressor stations, the list was not 

complete. Another example is the production segment, where it was not possible to 

produce a list of all the individual well owners for random selection. The second point is 

that the owners of the randomly selected sources could not be required to participate in the 

study. For this reason, there is no guarantee that a truly random sample of the available list 

could be tested. 

Stratified Random Sampling 

In stratified random sampling, the population of interest is divided into 

subsets, or strata. Then random samples are drawn from each stratum. For example, the 

sources of interest in this program could be stratified by geographical region, and random 

sampling could be applied within each region. 

Stratified random sampling can be performed proportiollately or 

disproportionately. In proportionate stratified random sampling, the number of sources 

sampled in. a stratum is in proportion to the total number of sources in that stratum. For 

example, if Region A had twice as many sources as Region B, then the sample would 

include twice as many sources from Region A as from Region B. From an intuitive point 

of view, then, a proportionate stratified random sample "matches11 the population, at least 

with respect to the criteria used to specify the stratification. 

Proportionate stratified random sampling can be used to address the issue of 

regional differences, but only if applied properly. In the paragraph above, it is suggested 

that sources could be sampled in proportion to the total number of sources by regio~. 

Alternatively, proportionality could be achieved on the basis of gas production, rather than 

on the basis of the number of sources. The variable or variables used to achieve 

proportionality must be closely related to emissions or proportionate random sampling could 

lead to biased results. 

49 
It is common in practice, however, to sample in such a way that the sample 

size for a strattun is not in proportion to the total number of sources in the stratum (and the 

throughput of the sampled sources is not proportional to total throughput in the stratum). 

This type of sample is called a "disproportionate stratified random sample." This type of 

sample does not "match" the population in the sense described above. As long as the 

disproportionality is accounted for in computing the fma1 statistics (e.g., mean emission rate 

by source or total emissions), disproportionate sampling will not cause bias in the final 

results. 

Stratified sampling can lead to increased accuracy for the total sample size if 

there is less variability within any given stratum than there is in the total population. 

Similarly, a smaller sample size might suffice to meet the target accuracy if stratified 

random sampling were used rather than random sampling. 

Neither type of stratified random sampling was feasible in this study. The 

obstacles to random sampling, discussed earlier in this section, were also obstacles to 

random sampling within strata. 

Further, at the outset of the program, it was not known which variables were 

related to emissions; thus, it was not known which variables should be used as a basis for 

stratification. If stratification had been performed on the basis of all variables that could 

possibly have an influence on emissions, the munber of strata ( detennined by the number of 

variables and the number of categories for each variable) could have become unreasonably 

large. For example, for leakage from lUldergrOlmd distribution mains and services, a 

number of parameters were identified that potentially influence emissions: pipe material, 

age, operating pressure, diameter, soil type, and parameters characterizing the leak detection 

and repair practices of the company. The required sample size can become large because 

of the total number of strata, especially if proportional stratified random sampling is used. 

One company has embarked upon an independent program to quantify leakage from 

underground mains and services using a proportional sampling approach. Even within this 

50 
single company, hWidreds of samples were required to produce a proportionate stratified 

random sample for underground pipelines. 

Additionally, stratified sampling is of no use unless there are activity factors 

that can be used to estimate the emission rate for the population. Complete information for 

all variables of potential interest does not exist. For example, the age of a dehydrator, in 

most cases, is not even known by the o'Wller of the equipment. It would be pointless to 

stratify dehydrator emission factors with respect to age if the necessary activity factors 

cannot be obtained. 

Sampling Approach Selected for This Program 

Thus, because of various practical limitations, neither random sampling nor 

stratified random sampling was perfectly feasible in this study. For this reason, an alternate 

approach was used. While this approach is not a textbook sampling method, it is believed 

to be very effective for the specific needs of this project. This approach is very similar to 

disproportionate stratified random sampling, with certain differences. 

Initially, some data were collected to determine if a given source was a major 

contributor to methane emissions. For each source category, an initial estimate of the 

munber of sources to be sampled was calculated based on an estimate of the accuracy target 

and the estimated standard deviation for the source category. The accuracy targets are 

based on the need ultimately to estimate the national emission rate to within 0.5% of the 

national production rate based on a 90% confidence limit. Sites were selected in a random 

fashion from known lists of facilities, such as GRI or American Gas Association (A.G.A.) 

member companies. However, the companies contacted were not required to participate, 

and a complete list of all sources in the United States was generally not available. 

Therefore, the final set of companies selected for sampling was not truly random. Each 

company that agreed to participate in the program was asked to select representative sites 

for sampling, rather than one-of-a-kind facilities. 

51 
After a limited set of data was collected, the data were screened for bias by 

evaluating the relationship between emission rate and parameters that may affect emissions. 

The topic of screening for bias is discussed further in Sectio115 6.2 and 6.3. If a 

relationship between emissions and a parameter was found, then the population, or the 

nwnber of sources in the industry, was stratified by that parameter. For example, station 

type was found to influence the emission rates from metering and pressure regulating 

stations, so the nwnber of stations under each station type in the nation was determined. 

To stratify the population of sources by a parameter, data were collected from companies 

on the distribution of sources in each stratum and an average over all companies sampled 

was detennined. 

It is important to realize that just because a parameter or set of strata is 

identified that has a large effect on the emissions from a given source category. it does not 

mean that there is bias in the data. A second condition is necessary. The condition is that 

the sampling procedure would have to produce a disproportionate number of samples in the 

strata. To determine whether this has occurred, information is needed on the ratio of the 

number of sources in a given stratum to the total number of sources for both the data set 

and at the national level. If this known national ratio is different from the ratio for the 

sample data set, then there may be bias. But this bias can be eliminated by applying the 

correct emission factors and activity factors for the different strata 

Once the strata were identified, the precision of the emission rate extrapolated 

to a national basis was evaluated and compared to the accuracy target. (Note: The 

accuracy target is a function of the magnitude of the emissions from the source.) Where 

necessary, additional data were collected in various strata to improve the precision of the 

national estimate of emissions from the source. The number of additional data points 

needed to meet the newly calculated accuracy target is computed based on the standard 

deviation and a 90% confidence interval. 

52 
6.2 Screening For Bias in Activity Factors 

It is impossible to teclmica11y prove that there is no bias in any dataset. 

While tests can be designed that are capable of revealing some bias, there are no tests nor 

group of tests that would reveal all possible biases. Assuming that any dataset has no bias, 

even after extensive testing, is only a theory. Such theories can be disproved, but not 

proved. The following examples in this section show some of the many bias tests used in 

this project. 

The sample sets were tested for bias by continuous technical and industry 

review. Numerous individual reviews and project ad visor's meetings were used to review 

the project data \V:ith knowledgeable industry experts, so that systematic errors could be 

discovered and eliminated. When possible biases in the activity factor sampling plan or 

extrapolation method were theorized, the project was altered to test for that bias and 

eliminate it if it existed. All provable biases were corrected. 

One example of the success of this bias review process includes the 

identification of regional differences in production practices. These differences were 

brought up by the advisor's meeting review process. The differences were then accounted 

for by stratifying the production data into two offshore and four onshore regions, sampling 

within each region, and extrapolating by region. 

J\nother example of activity factor screening bias includes extrapolation by 

two methods that validate each other. If both methods are technically sound and 

independent, and if they deliver the same result for national totals, then this indicates that 

there is no bias in the data set related to either variable. If a data set existed that was the 

perfect microcosm of the gas industry, one could extrapolate equipment counts from the 

data set to national totals by any variable in the data set. Any extrapolation from the 

perfect microcosm would deliver the right answer, even technically unrelated data such as 

extrapolating separator cotmt by nwnber of employees at the site. 

53 
Therefore, for an imperfect data se~ which all data sets are, extrapolation by 

two variables allows for a cross check. For example, production activity factors could be 

extrapolated by two nationally known extrapolation parameters: well count and production 

rate. It was possible that the extrapolated variable is actually technically related to one 

variable more than the other, or that the sample set had some bias related to one or both 

variables. Nevertheless, if the extrapolation by well coWit produces the same value as the 

extrapolation by production rate, then the methods tend to validate one another. This also 

indicates that there is no bias made in selecting the extrapolation technique, nor between the 

relations of the two extrapolation variables in the data set. 

If the two methods produced results which differed widely, that might 

indicate that one or the other method has a bias. In fact, as mentioned in Volume 5 on 

activity factors, 1 there was a tendency for the well method to be high-biased and for the 

production method to be low-biased. Therefore, the average of the two techniques should 

minimize the bias. 

6.3 Screening for Bias in Emissions Factors 

Screening for bias can be accomplished by identifying design, operational, 

and regional parameters that may cause differences in emissions across a source type and 

then analyzing the data to determine whether there is an established relationship between 

those parameters and the emission rate. Usually, these parameters are chosen on the basis 

of industry expertise and/or engineering judgement. If these parameters are determined to 

exhibit statistically different emission characteristics, then the population of sources is 

stratified into distinct categories by these design, operational, or regional parameters. 

Emission factors and activity factors are determined for each category within the source 

type to uniquely characterize emissions. 

Metering/pressure regulating stations provide an example where the process 

of screening for bias was beneficial. Table 6-1 shows the aVerage measured emission factor 

54 
for metering/pressure regulating stations, in Wlits of scf/station-hour, based on 86 

measurements which were performed in 19 cities in the United States. The activity factor 

was also derived from data provided by the distribution companies participating in the 

study, which was scaled to a national estimate of metering/pressure regulating stations. 

Assuming that the sample selection was random or representative, the extrapolated 

emissions are I 04.1 Bscf, based on the average of all measurements to estimate the 

emission factor. However, if the data is subdivided, or stratified, by station type (i.e., 

metering/pressure regulating versus pressure regulating), then the estimated emissions from 

this source type decrease to 73.7 Bscf. Furthermore, if this source type is further 

subdivided into discrete operating pressure ranges and by enclosure status, the emissions 

decrease to 27 3 Bscf. As illustrated, the bias, which was caused by testing a 

disproportionate number of high pressure stations, can be minimized by stratifying the 

emission and activity factors. 

The previous example also illustrates that it is equally as important to 

accurately stratifY the activity factor samples as the emission factor samples. In some 

cases, the activity f8.ctor can only be stratified to the necessary level of disaggregation by 

gathering data from industry. 

Even if a process does not produce a bias in the statistical sense described 

above, it is possible for a given segment of the population to be seriously under represented 

and another segment to be over represented by random chance (i.e., by an anomaly in the 

random selection of sources). The error that results is a larger than expected random error; 

an error from a correct sampling and measurement process is not a bias. 

55 
TABLE 6-l. ESTIMATED METHANE EMISSIONS FROM DISTRIBUTION 

METERING AND PRESSURE REGULATING STATIONS 

:: 

Location ' ActivityFactor 

(vault or Emission Factor (number of Emissions 

Category above-ground) (sc£istation-hr) stations) (Bscf) 

All Stations 90.2 131,799 104.1 

M&R Stations 154.1 23,922 32.3 

Reg. Stations 43.7 108,048 41.4 

Total 131,970 73.7 

M&R Stations 

>300 psig A-G 179.8 3,460 5.45 

100-300 psig A-G 95.6 13,335 11.2 

40-100 psig A-G 4.31 7,127 0.269 

<40 psig A-G 0 0 

Reg. Stations 

>300 psig A-G !61.9 3,995 5.67 

>300 psig Vault 1.30 2,346 0.0266 

100-300 psig A-G 40.5 12,273 4.35 

I 00-300 psig Vault 0.180 5,514 0.0087 

40-100 psig A-G 1.04 36,328 0.332 

40-100 psig Vault 0.0865 32,215 0.0244 

<40 psig Vault 0.133 15,377 0.0179 

Total 131,970 27.3 

The screening process serves to identify variables that are related to emission 

characteristics. Then it is possible to determine whether sources are disproJXJrtionately 

sampled in the different strata of these variables. Such a disproportionality need not lead to 

a bias in the fmal estimate of emissions, if this condition is identified and accounted for 

56 
properly. Moreover, the screening process has been carried out during the course of the 

study. Thus, additional sampling to correct a disproportionality, if present, is possible. 

Note that the screening process would identify unrepresentativeness in the 

sample, whether the problem resulted from an inadvertent bias in the sampling process or a 

purely random effect. The protection against both bias and anomalies in the random 

selection of sources is considered to be a significant benefit of the method used in this 

study. 

6.4 Accuracy Target 

The target uncertainty in the emission estimate is 0.5% of the national 

methane emissions, on the basis of a 90% confidence limit for the emissions estimate. 

Practical considerations allow sampling only a small percentage of the large num~er (tens 

of thousands) of sources that exist nationwide. Moreover, there is typically a large amount 

of variability among the sources in a given category. In view of these considerations, 

meeting the accuracy target may seem insunnountable. Despite these facts, the target 

precision for the industry emission rate was achieved. The purpose of this section is to 

illustrate, through hypothetical calculations, how large errors in emissions estimates for 

individual source strata can combine to allow this to occur. 

As is discussed in the preceding sections, bias is minimized by randomly 

selecting sites (although from a limited list), analyzing the data, and creating strata in a 

systematic way. The estimate of total emissions is the sum of the emissions for all the 

strata. An essential point is that the uncertainties are not additive; the uncertainty of a sum 

is related to the sum of squares of the individual uncertainties. If the errors in a sum vary 

independently, then they tend to "average out"; as a result, the relative uncertainty in a sum 

of terms (with equal means and variances) is smaller than the relative uncertainty in the 

individual terms. (Several statistical points made in this paragraph are discussed in further 

detail later in this subsection.) 

57 
The steady emission sources have been split into five major segments. Each 

segment has two to seven significant source categories, and each source category is divided 

into 10 to 40 strata. In total, steady sources have been divided into nearly 100 strata. 

Unsteady or vented sources have been divided into approximately 40 strata. Thus, in all 

there are approximately 140 s'Tata. 

Hypothetical calculations are presented that illustrate the effect of summing 

the errors in the different strata. For the purposes of the hypothetical calculations, it has 

been assumed that there are "n11 strata with equal emissions and equal uncertainties based 

on random errors. While it is recognized that both the emission rate and the variability 

change from strattun to stratum, in actuality, the simplifying assumptions facilitate a 

calculation that illustrates the effect of summing the emission estimates from a large 

number of strata. 

Also, it has been assumed that undiscovered bias, if any, varies 

"independently" from stratum to stratum. This type of error would exist if the sources 

within a stratum were sampled in an unrepresentative manner, resulting in a bias error. 

Clearly, a systematic bias that was common to a large number of strata would have a more 

serious effect on the fmal result. The processes described earlier for screening for bias 

provide a protection against this (or any type of) bias error. Additionally, given the large 

munber and diversity of strata, it is reasonable to believe that any undetected bias will 

exhibit a high degree of "independence" among the strata. 

Table 6-2 presents the results of the calculations. The random error was 

chosen to be as large as plus or minus 100% of the emissions for each stratum, based on a 

90% confidence interval. This is equivalent to assuming a coefficient of variation of 

approximately 0.6. 

58 
TABLE 6-2. PERCENTAGE OF ERROR IN TOTAL EMISSIONS 

Bias·· Number of Strata .. 

(Percent of 

20 Strata 40 Strata Emissions) !00 Strata 

0% 0.40 0.29 0.18 

15% 0.41 0.29 0.18 

30% 0.43 0.31 0.19 

(Percent random error in a given stratum based upon a 900/o confidence interval = 130%) 

The bias error is represented as the stratum-to-stratum standard deviation of 

the biases in the emission estimates; this quantity is presented as a percent of the emissions 

for a stratum. In the calculations, three values have been considered for the bias: 0%, 

15%, and 30%. In view of the methods used for screening for bias, 30% is considered to 

be a high estimate. 

As previously mentioned, the total number of strata is approximately 140. It 

has been assumed that there are approximately I 00 strata with nearly equal emissions that 

represent the major part of the industry emissions. Some of the strata (such as distribution 

pipe type) have been aggregated in the final summary table that is presented in Volume 4 

on statistical methodology. 10 The summary table includes 86 source categories. 

Further calculations were performed assuming 40 and 20 strata, in addition to 

the case with 100 strata. Given that the parameters discussed above of the random and bias 

errors are fixed, the relative uncertainty in the frnal result decreases as the number of strata 

increases. Tills is because the "error averaging effect" is greater if a larger number of 

independent estimated quantities are summed. This does not mean that artificially 

increasing the number of strata would improve the accuracy. There would be fewer data 

points per stratmn, and the uncertainty of the emission estimate for each stratum would 

increase. 

59 
Table 6-2 presents the percentage of uncertainty in the fugitive emissions as a 

fraction of the national production rate. The uncertainty is expressed in terms of a 90% 

confidence interval. Since bias errors were considered as well as random errors, the 

numbers in Table 6-2 represent accuracy, not just precision. 

The accuracy target is met if the percentage error is no greater than 0.5%. 

Under all scenarios modelled, the uncertainty is less than 0.5%. This is true even in the 

case in which there are only 20 strata with approximately equal emissions, and the bias is 

30%. These calculations, while hypothetical, illustrate the way in which errors combine in 

a sum and show that meeting the accuracy target is feasible, even in the presence of large 

percentage random errors in the individual strata and an assumed large Wldetectable bias 

error. 

It must be remembered that the random and bias errors were expressed as a 

fraction of the emissions in the strata. For these test calculations, the national emissions 

were assumed to be approximately 307 Bscf. The accuracy target is expressed as a 

percentage (0.5%) of the national gas production per year, which is 22,132 Bscf. 

It is stated earlier in this subsection that the uncertainty of a smn is related to 

the sum of squares of the individual uncertainties. The uncertainty of the industry annual 

emissions have been calculated as the square root of the sum of the squares of the 

uncertainties of the emission rates by category. Tbis method is strictly valid if the errors in 

the different terms are uncorrelated. Two terms would have uncorrelated errors if there 

were no common source of error. The method would still be valid if the correlations were 

negligible. 

A method recommended in the Quality Control Handbook" by Juran, Gryna, 

and Bingham was used for quantifying the uncertainty of a sum (on the basis of assumed 

uncorrelated errors). The different terms being summed do not have to have the same 

statistical distribution. In fact, Juran, et al., illustrate the method with an example in which 

60 
three terms are summed, no two of which have estimated values that are the same within 

Wlcertainty. Also, no two of the terms have the same uncertainty. This method is based on 

a theorem that is proved by Mood, Graybill, and Bees in Introduction to the Theory of 

Statistics16 (p. 178). The methods used for analyzing error propagation, as well as 

alternative schemes, are discussed in much further detail in a separate project report 

documenting the statistical methods 10 used in this study. 

It has been pointed out that there may be correlations between the errors in 

the emission rates for different source categories. For example, in some instances, the same 

activity factor applies to more than one category. Also, there are instances in which data 

for more than one source category were collected from the same field. If inspection and 

maintenance practices at that field were better than the industry average, for example, this 

fact could have a common effect on the data for all categories sampled at that field. An 

assessment of the effect of correlated errors among categories has been performed. The 

results are discussed in Volume 4 on statistical methodology. 10 

6.5 Overall Statistical Accura:ey 

The precision is computed by rigorously calculating errors for average values 

produced from replicate measmements, and then by propagating error from each individual 

group of measurements into the national numbers. Tb.is section provides a brief discussion 

of the statistical methods used for the overall methane emissions project. Volume 5 on 

activity factors 1 summarizes the general statistical propagation techniques used, and 

Volume 410 provides the full details of the various statistical teclmiques, tests, and 

considerations involved with this project. 

During 1992, this project used a statistical analysis to apportion resources to 

reflne the categories with the highest emission rates and/or the poorest accuracies. This 

method allowed for additional measurements or calculations that quickly refined and 

tightened the precision of the estimate. The 1992 plan also set an absolute accuracy target 

61 
of± 0.5% of gross production for the 90% upper confidence bolllld of the annual national 

emission rate. This is equivalent to an absolute accuracy target of approximately ± 111 

Bscf. For the estimate of 307 Bscf, this means that the annual national estimate must have 

an upper confidence interval (at 90% confidence) that all possible answers will fall within ± 

35% (1 06/307) of the actual estimate. Any one source category within the sum of all 

sources may have a much larger confidence interval than ± 35%, since error bands are not 

additive directly, but are added as the square-root of a sum of squares. Consequently, it is 

possible for a sum to have a smaller relative uncertainty than do the individual terms 

(although the absolute uncertainty of the sum is larger than that of any individual term). 

The project progress was tested in 1993 after significant data had been 

collected. The test showed that the precision target had already been reached, so additional 

tests were not needed to improve the precision. However, accuracy is made of precision 

and bias, and data collection continued throughout 1993 and early 1994 in order to reduce 

and eliminate bias. Precision can be calculated and improved by additional measurements, 

but bias must be eliminated through proper testing design, proper extrapolation, bias tests, 

and detailed data analysis and review. Testing design is a key factor in eliminating bias 

since sources cannot really be randomly selected for a number of practical reasons. 

Another potential source of bias can be eliminated by subdividing the data on an 

appropriate basis (such as grouping metering and regulating stations into various pressure 

categories), and reanalyzing the data. Stratifying, or subdividing, the data is beneficial if 

there are differences in the means and variances within these strata. 

62 
7.0 

!. 

2. 

3. 

4. 

5. 

6. 

7. 

8. 

REFERENCES 

Stapper, B.E. Methane Emissions from the Natural Gas Industry, Volume 5: 

Activity Factors, Final Report, GRJ-94/0257.22 and EPA-600/R-96-080e. Gas 

Research Institute and U.S. Environmental Protection Agency, June 1996. 

Hummel, KE., LM. Campbell, and M.R. Harrison. Methane Emissions from 

the Natural Gas Industry, Volume 8: Equipment Leaks, Final Report, GRJ94/0257.25 and EPA-600/R-96-080h. Gas Research Institute and U.S. 

Environmental Protection Agency, June 1996. 

Campbell, L.M. and B.E. Stapper. Methane Emissions from the Natural Gas 

Industry, Volume 10: Metering and Pressure Regulating Stations in Natural 

Gas Transmission and Distribution, Final Report, GRJ-94/0257.27 and EPA600/R-96-080j. Gas Research Institute and U.S. Environmental Protection 

Agency, June !996. 

Campbell, L.M., M.V. Campbell, and D.L. Epperson . Methane Emissions 

from the Natural Gas Industry, Volume 9: Underground Pipelines, Final 

Report, GRJ-94/0257.26 and EPA-600/R-96-080i. Gas Research Institute and 

U.S. Environmental Protection Agency, June 1996. 

Shires, T.M. and M.R. Harrison. Methane Emissions from the Natural Gas 

Industry. Volume I2: Pneumatic Devices, Final Report, GRJ-94/0257.29 and 

EPA-600/R-96-0801. Gas Research Institute and U.S. Environmental 

Protection Agency, June !996. 

Shires, T.M. and M.R. Harrison. Methane Emissions from the Natural Gas 

Industry, Volume 7: Blow and Purge Activities, Final Report, GRJ-94/0257 .24 

and EPA-600/R-96-080g. Gas Research Institute and U.S. Environmental 

Protection Agency, June 1996. 

Shires, T.M. Methane Emissions from the Natural Gas Industry, Volume 13: 

Chemical Injection Pumps, Final Report, GRJ-94/0257.30 and EPA-600/R-96-

0&0m. Gas Research Institute and U.S. Environmental Protection Agency, 

June !996. 

Myers, D.B. and M.R. Harrison. Methane Emissions from the Natural Gas 

Industry, Volume I5: Gas-Assisted Glycol Pumps, Final Report, GRJ94/0257.33 and EPA-600/R-96-080o. Gas Research Institute and U.S. 

Environmental Protection Agency, June 1996. 

63 
9. 

10. 

II. 

12. 

13. 

14. 

15. 

16. 

Glycol 

Myers, D.B. Methane Emissions from the Natural Gas Industry, Volume 14: 

Dehydrators, Final Report, GRl-94/0257.31 and EPA-600/R-96-080n. 

Gas Research Institute and U.S. Environmental Protection Agency, June 

!996. 

Natural 

Williamson, H.J., M.B. Hall, and M.R. Harrison. Methane Emissions from the 

Gas Industry, Volume 4: Statistical t.:ethodology, Final Report, GRJ94/0257.21 and EPA-600/R-96-080d. Gas Research Institute and U.S. 

Environmental Protection Agency, June 1996. 

American Gas Association. Gas Facts, 1992 Data, Arlington, VA, !993. 

Annual, 

U.S. Department of Energy/Energy Infonnation Administration. Natural Gas 

1992. DOEIEIA-0131(92), Washington, DC, Sept. 1992. 

Report. 

Wright Killen & Co. Natural Gas Dehydration: Status and Trends, Final 

GRJ-94/0099, Gas Research Institute, Chicago, IL, January 1994. 

Compressor 

Stapper, C.J. Methane Emissions from the Natural Gas Industry, Volume 11: 

Driver Exhaust, Final Report, GRJ-94/0257.28 and EPA-600/R96-0SOk. Gas Research Institute and U.S. Environmental Protection Agency, 

Jnne 1996. 

Juran, J.M., F.M. Gryna, Jr., and RS. Bingham, Jr. Quality Control 

Handbook, Third edition, McGraw-Hill Book Company, New York, NY, 

1974, p. 178. 

Mood, A.M., F.A. Graybill, and D.C. Boes. Introduction to the Theory of 

Statistics, Third edition, McGraw-Hill Book Company, New York, NY, 1974. 

64 
APPENDIX A 

Production Source Sheets 

A-I 
SOURCE SPECIFIC EMISSION ESTIMATES 

This appendix presents the source specific emission estimates derived from 

emission factors and activity factors for the sources of emissions within the narural gas 

industry. Each significant source of emissions has a "source sheet" that gives a synopsis of 

the basis of the estimate. These estimates are presented in a format which documents the 

approach for extrapolation of data to a national estimate. The emission factor and activity 

factor presented represent the fmal estimates from the program. 

Each source sheet is divided into two sections, each one describing the basis 

for the emission factor and activity factor, respectively. The approach used to determine the 

accuracy of the emission and activity factor was discussed in Section 6.0, unless otherwise 

stated. 

A-2 
P-1-

P-2-

P-3-

P-4-

P-5 -

P-6-

P-7-

P-8-

P-9-

P-10-

P-11-

APPENDIX A 

Production Source Sheets 

Page 

Compressor Exhaust ............................ A-5 

Fugitive Emissions ............................. A-10 

Gathering Pipeline Leaks ......................... A-17 

Pneumatic Devices ............................. A-22 

Chemical Injection Pumps ......................... A-25 

Glycol Dehydrator Vents ......................... A-28 

Glycol Pumps ................................ A-32 

Maintenance Venting ............................ A-35 

Upsets ..................................... A-38 

Pipeline Dig-ins ............................... A-41 

Well Completion and Workovers .................... A-42 

A-3 
PRODUCTION SOURCE SHEETS 

This section contains the specific source sheets for the production segment of the natural gas 

industry. The following table serves as a guide for finding sheets in this section. The cells 

in the table give the sheet number (P-1, P-2, etc.) of the source sheet. The rows defme the 

equipment covered. while the columns defme the operating mode and emission type. A 

category with no sheet number means that the emissions from that area were determined to 

be negligibly small. The label for each source sheet is shown at the top of the cover page 

for that sheet. 

TABLE OF OPERATING MODE, 

CONTENTS EMISSION TYPE (Fugitive, Vented, or Combusted) 

Start Up Norn:al Operations Maintenance Upsets M1shaps 

EQUIPMENT: v c F v c v c v c v 

Wellheads P-2 P-4, P-8, P-9 

P-5 P-11 

Heaters P-2 P-4 P-8 P-9 

Separators P-2 P-4 P-8 P-9 

Dehydrators P-2 P-4, P-8 P-9 

P-6, 

P-7 

Compressors P-2 P-4 P-1 P-8 P-9 

Metering P-2 P-8 P-9 

Pipelines P-3 P-8 P-9 P-10 

A-4 
SOURCES' 

OPERATING MODE' 

EMISSION TYPE' 

ANNUAL EMISSIONS' 

BACKGROUND' 

P-1 

ALL-SEGMENT SOURCE SHEET 

Compressors, Generators 

Normal Operation 

Unsteady, Combusted (Compressor Driver Exhaust) 

24.4 Bscf ± 64% 

Compressors are used to move gas through the system. They are located in production fields, processing 

plants, gas storage fields, and along transmlssion lines. Methane emissions are found in compressor driver 

exhaust 

as 

{reciprocating engines and gas rurbines} because of the incomplete combustion of the natural gas burned 

fueL 

EMISSION FACTOR: (0.240 ± 5% scflhpilr, engines and 0.0057 ± 30% scf/hp-hr, turbines) 

TR.ANSDAT 

An average emission rate was calculated for each model of compressor engine and turbine in the GRl 

Emissions Database (l), which is based on compressor tests conducted by Southwest Research 

Institute (SwRl). The emission rates were calculated from the reponed methane emissions per unit of fuel and 

the reported fuel use rate (FUR) for each compressor model, as follows: 

where: · ERxml = average emission rate for model, m (scf/hr) 

EP(Dl) = average emission parameter for model, m (scf CHJscf fuel) 

FUR(m) = average fuel use rate for model, m (scf fuel/hr) 

The following equation was used to determine the total emissions for the 86 turbines and 775 reciprocating 

engines in the Emissions Database. 

where: 1E = total emissions for database, (set) 

~ =o annual operating hours for compressor i, (hr/yr) 

K = number of unique compressor models 

M = number of compressors of model, m 

A-5 

(1) 

(2) 
The emission factors, for engines and turbines, were then calculated using the following equation. 

Emission Factor "' TE I [ E 

i "' 1 

where: HP = average operating horsepower during HR., (hp) 

HR = annual operating hours, (brJyr) 

N = number of compressors 

(3) 

base 

This equation considers that some models could be operated at a higher percentage of the time because they are 

loaded compressors. The average emission factors for the compressor drivers in the Emissions Database 

are 0.240 scf/hp·hr for reciprocating engines and 0.0057 scflhpilr for turbines. 

EF DATA SOURCESo 

l. "National Estimate of Methane Emissions from Compressors in the U.S. Natural Gas 

Industry" (2). 

EF ACCURACY: ± 5%, engines and ± 30%, turbines 

Basis: 

The accuracy for the EF is estimated based on propagation of error from the spread of samples in the 

database. However, engineering judgement was used to assign accuracy for two of the individual terms 

in the equation, as follows: 

l. Hydrocarbon analysis was estimated to be ± 10%, based on the generally accepted accuracy 

of gas chromatographs (flame ionization detector). 

2. Likewise, fuel flow measurements were estimated to be ± 2.5%. 

ACTIVITY FACTORS: (horsepower-hour) 

Horsepower· hour data were available for the prOduction industry segmtnt activity factor calculation. Two 

pieces of information are needed to calculate the activity factor, which is expressed as horsepower· hours (hpilr) 

for each type of driver in each of the remaining industry segments. These are the installed horsepower and the 

both 

average operating hours. The following table presents these parameters and the resulting activity factors for 

engines and turbines in each segment of the industry. The sources and methods for calculating all the 

values presented in the table below are given in the next section: AF Data Sources. 

It is estimated that about 94% of the emissions in compressor and generator driver exhaust are from 

reciprocating engines used in production, processing, and transmission, with about 5% attributable to 

reciprocating engines used in storage. All other categories are negligible in comparison. Therefore, it is more 

important to accurately determine the activity factors for reciprocating engines in production, processing, and 

transmission. 

A-6 
COMPRESSOR DRIVER ACTIVI'IY FACTORS FOR EACH INDUSI'RY SEGMENT 

......... ·- ._, """"" """"'"' - Tin-bine H""" Ho= 

-· Turbine 

Enike 

"''"""' MMbp' MMhp' TUrinne MMHp·hr MMBpm 

Production NA NA NA NA 27,460 ± 200% 0 

Processing 4.19 ± 132%" 5.19 ± 99.4%" 6626 ± 11.5% 634S ± 48.4% 27,760 ± 133% 32.910 ± 121% 

Transmission 

Compressor D!'ivers 10.2 ± 10.0% 4.55 ± 10.0% 3964 ± 13.8% 2Il8 ± 31.3% 40.380± 17.1% 9635 ± 33.0% 

Generator Drivers !.45 ± 23.3% 0.045 ± 166% 1352 ± 38.0% 474 ± 620% 1962 ± 45.4% 21.2 ± 1215% 

Storage 

Compressor Drivers 1.33 ± 13.5% 0.59 ± 13.5% 3707 ± 23.1% 2917 ± 620% 4922 ± 26.9% 1729 ± 626% 

Generator Drivers 0.085 ± 126% 0.057 ± 184% 191 ± 377'10 36 = 620% 16.3 ± 621% 2.05 ± 1312% 

• Does n01 include horsepower associated with gas lift for oil recovery or wilb electric drivers. 

• Average of two estimation methods. 

AF DATA SOURCES: 

l. The production segment horsepower is based on the total installed horsepower-hours for data 

provided by one company for 516 compressor drivers (all reciprocating engines). The 

horsepower· hours for the company was divided by their production before scaling to a national 

estimate. National horsepower·hou: was calculated using the 1992 marketed production for the 

U.S. [Natural Gas Annual 1992, (3)]. 

2. The processing segment horsepower was determined by taking the average of two methods. 

Each of the methods uses site data for the lO gas plants visited. The first method scales to a 

national estimate by multiplying the total U.S. gas plant throughput as of January l, 1993 

[46,510.7 MMcfd, Oil & Gas Journal (4)} by the total site visit horsepower per throughput 

(47.8 hp/MMcfd, engines and 59.2 hp/MMcfd, turbines). The second method scales to a 

national estimate by multiplying the total number of gas plants in the U.S. [726, Oil & Gas 

Journal (4)J by the total site visit horsepower per number of gas plants visited (10), which is a 

scale-up ratio of about 73. The annual operating hours are based on the 10 sites plus data 

from two companies for an additional 18 gas plants. An average of the average operating 

hours per site was calculated to get !he processing segment operating hours (203 engines and 9 

turbines). 

3. The transmission segment compressor station horsepower for each compressor driver type is 

based on the GRI TRANSDAT database. Installed horsepower was taken from the Industry 

Database module of GRI TRANSDAT. The annual operating hours are based on information 

reported on FERC Form No. 2. FERC data does not distinguish between driver type. The 

PERC data were split between engines and turbines based on data in GRI TRA.NSDAT and 

data provided by one transmission ccmpany (524 engines and 89 turbines). 

4. The storage segment horsepower came from Gas Fads (5) data for 1992 (1,920,441 hp). The 

split between engines and rurbines was assumed to be the same as the engine and turbine splits 

found in GRI TRANSDAT (69.1 %, engines and 30.9%, turbines). The annual operating 

hours are based on 11 storage stations (50 engines and 6 turbines). An average of the average 

operating hours per station was calculated to get the storage segment operating hours. 

A-7 
5. The generator driver horsepower (compressor stations) is based on the total installed 

horsepower for 7 of the transmission sites visited and company data for 34 transmission 

compressor stations. To scale to a national estimate, the total horsepower per station was 

multiplied by the total number of transmission compressor stations [1'700, FERC Form No.2 

(6)J in the U.S. The annual operating hours are also based on data from the site visits and 

company data. An average of the average generator operating hours per station was calculated 

to get generator operating hours (87 engines and 1 turbine). 

6. The generator driver horsepower (storage fields) is based on the total installed horsepower for 

9 storage fields (one company). To scale to a national estimate, the total horsepower per field 

was multiplied by the total number of storage fields [475, Gas Facts (5)1 in the United States. 

The annual operating hours are also based on the company data. An average of the average 

generator operating hours per field was calculated to get generator operating hours (3 engines 

and 1 turbine). 

AF ACCURACY' 

Basis: 

Errors were propagated from each of the following terms: 

l. Production Hp·hr: The production Hp·hr accuracy is based upon an engineering analysis and 

set at ± 200%. 

2. Transmission Hp·hr: The transmission Hp·hr accuracy is based upon an assigned estimated 

error of± IO% for the horsepower data in the GRI TRANSDAT database and error 

propagation from the FERC operating hours. 

3. Other segment Hpilr: The accuracy of the site visit data for horsepower and operating hours 

was also propagated using the spread of the data, but from much smaller data sets. The 

accuracy of the horsepower-hour activity factors for each industry segment are calculated 

statistically using the individual terms for horsepower and operating hours. 

ANNUAL METIIANE EMISSIONS: (24.57 ± 65.1% Bscf, engines+ 0.256 ± 97.8% Bscf, turbines) 

The annual emissions were determined by multiplying an emission factor by the horsepower· hour activity factor 

for reciprocating engines and turbines and summing these values for each segment. The following table shows 

the resulting emissions for each industry segment and the overall national estimate. 

ANNUAL COMPRESSOR EMISSIONS FOR THE NATURAL GAS INDUSTRY BY SEGMENT 

Compressor Production 

-..... Tl'llDSlllk'$ioD Storage Gene~tors TOTAL 

Engines, Bscf 6.58±200% 6.65±133% 9.68±17.9% l.i8±26.9% 0.474±45.6% 24.57±65.1% 

Turbines. Bscf 0.00 0.186±129% 0.0546±45.7% 0.00979±654% 0.000132± 1!63% 0.256±97.8% 

REFERENCES 

I. Biederman, N. GRI TRANSDAT Database: Compressor Module. (prepared for Gas Research 

Institute) npb Associates with Tom Jcyce and Associates, Chicago, IL, August 1991. 

2. Jones, 

Methane 

D.L., L.M. Campbell, C.E. Burklin, M. Gundappa, and R.A. Lott, ''National Estimate of 

Emissions from Compressors in the U.S. Natural Gas Industry." Radian Corporation and 

Gas Research Institute, Air & Waste Management Association Conference Proceedings, Paper # 92· 

142.02, Kansas City, MO, 1992. 

A-8 
3. U.S. Department of Energy/Energy Infonnation Administration. Natural Gas Annual, 1992. 

DOE/EIA-0131 (92), Washington, DC, September 1992. 

4. Oil & Gas Journal. 1992 Worldwide Gas Processing Survey Database, 1993. 

5. American Gas Association, Gas Facts: 1992 Data, Arlington, VA, 1993. 

6. Federal Energy Regulatory Commission (FER C) Form No. 2: Annual Report of Major Natural Gas 

Companies, !992 database. 

A-9 
SOURCEs, 

OPERATING MODE' 

EMISSION TYPE' 

ANNUAL EMISSIONS' 

BACKGROUND' 

P-2 

PRODUCTION SOURCE SHEET 

All Production Equipment (See Below) 

Normal Operation 

Steady, Fugitive 

17.4 Bscf ± 41% 

Equipment leaks are typically low-level, wrintentionallosses of process fluid (gas or liquid) from the sealed 

surfaces of above-ground process equipment. Equipment components that tend to leak include valves, flanges 

and other connectors, pump seals, compressor seals, pressure relief valves, open-ended lines, and sampling 

wear 

connections. These components represent mechanical joints, seals, and rotating surfaces, which in time tend to 

and develop leaks. 

EMISSION FACTOR: (scf/equipment-yr, see below) 

In the component method for estimating emissions from equipment leaks, an average emission factor is 

determined for each of tlle basic components, such as valves, flanges, seals, and other connectors that comprise 

a facility. The average emission factor for each type of component is determined by measuring the emission 

rate from a large number Of randomly selected components from similar types of facilities throughout the 

country. An average estimate of the emissions per equipment or facility are determined as the product of the 

average emission factor per component type (i.e., the component emission factor) and the average number of 

components associated with the major equipnent or facility: 

where: 

N, = average count of components of type x per plant, and 

EF, = average methane emission rate per component of type x. 

Component emission factors for fugitive equipment leaks in gas production were estimated separately for 

onshore and offshore production due to differences in operational characteristics. Regional differences were 

Western 

found to 

U.S. 

exist between onshore production in the Eastern U.S. (i.e., Atlantic and Grear Lakes region) and the 

(i.e., rest of the country. excluding the Atlantic and Great Lakes region) and between offshore 

production in the Gulf of Mexico and the Pacific Outer Continental Shelf (OCS). Separate measurement 

programs were conducted to account for these regional differences. 

of 

Onshore Production in the Eastern U.S. Region. Gas production in the Eastern U.S. accounts for only 4.2% 

gross national gas production, but includes 47% of the total gas wells in the country. Component emission 

GRI/Star 

factors for onshore production in the Eastern U.S. were based on a measurement program conducted by 

Environmental (1) of 192 individual well sites at 12 eastern gas production facilities. Component 

were 

counts for gas wellheads, separators, meters and the associated above-ground piping, and gathering compressors 

based on information collected as pan of the Eastern U.S. prOduction measurement program. Site visits 

and phone surveys of 7 additional sites provided data used for determining the number of heaters and 

dehydrators in the Eastern U.S. region. Component counts for heaters and dehydrators were assumed to be 

identical to those derived from data collected in the Western U.S. The following table presents the component 

Eastern 

emission 

U.S. 

factors, average component counts, and average equipment emissions for onshore gas production in the 

region. 

A-10 
Average Equipment Emissions for Onshore Production in the Eastern U .. S 

Equipment Type Component Type Component Average Average Equipment 

Emission Factor, Component Emissions,a 

Mscf/component-yr Count scf/equipment-yr 

Gas Wellheads Valve 0.184 8 2,595 (27%) 

Connection 0.024 38 

Open-Ended Line 0.42 0.5 

Separators Valve 0.184 1 328 (27%) 

Connection 0.024 6 

Heaters Valve 0.184 14 5,188 (43%) 

Connection 0.024 65 

Open-Ended Line 0.42 2 

Pressure Relief 0279 1 

Valve 

Glycol Valve 0.184 24 7,938 (35%) 

Dehydrators 

Connection 0.024 90 

Open-Ended Line 0.42 2 

Pressure Relief 0.279 2 

Valve 

Meters/Piping Valve 0.184 12 3,289 (30%) 

Connection 0.024 45 

Gathering Valve 0.184 12 4,417 (27%) 

Compressors 

Connection 0.024 57 

Open-Ended Line 0.42 2 

• Values in parentheses represent the 90% confidence interval. 

Onshore Production in the Western U.S. Region. Component emission factors for onshore production in the 

Western U.S. were based on a comprehensive fugitive emissions measurement program conducted by API/GRI 

(2) at 12 oil and gas production sites. In this program, measurement data were collected from 83 gas wells at 4 

gas production sites in the Pacific, Mountain, Central, and Gulf regions. The average component counts for 

each piece of major process equipment associated with gas production in the Western U.S. were based on data 

collected during the APIIGRI study and additional data collected for GRI during 13 site visits to gas production 

fields. The following table presents the component emlssion factors, average component counts, and average 

equipment emissions for onshore gas production in the Western U.S. region. 

A-ll 
Average Equipment Emissions for Onshore Production in the Western U .. S 

Equipment Type Component Component Average Average Equipment 

Type Emission Factor, Component Emissions, a 

Mscf/component-yr Count scf/equipment-yr 

Gas Wellheads Valve 0.835 11 13,302 (24%) 

Connection O.ll4 36 

OEL 0.215 1 

Separators Valve 0.835 34 44,536 (33%) 

Connection 0.114 106 

OEL 0.215 6 

PRY 1.332 2 

Heaters Valve 0.835 14 21,066 (40%) 

Connection 0.114 65 

OEL 0.215 2 

PRY 1.332 1 

Glycol Dehydrators Valve 0.835 24 33,262 (25%) 

Connection 0.114 90 

OEL 0.215 2 

PRY 1.332 2 

Meters/Piping Valve 0.835 14 19,310 (30%) 

Connection 0.114 51 

OEL 0.215 1 

PRY 1.332 1 

Compressors 

Gathering Valve 0.835 73 97,729 (68%) 

Connection 0.114 179 

OEL 0.215 3 

PRY 1.332 4 

Compressor 2.37 4 

Seal 

Large Compressor 3.01 X 10' (102%) 

Stations b b b 

Station Components 

Co~ressor- b b b 5.55 X 10' (65%) 

!at "' 

• Values in parentheses represent the 90% confidence interval. b Refer to T-1 source sheet for a discussion of :he basis for estimated emissions from large compressor 

stations. 

A-12 
Offshore Gas Production. Emissions from equipment leaks from offshore production sites in the U.S. were 

based on two separate measurement programs: 

• The API/GRI oil and natural gas production operations study. which included 4 offshore 

production sites in the Gulf of Mexico; and 

• The Minerals Management Service study of 7 offshore production sites in the Pacific Outer 

Continental Shelf. 

The component emission factors and component counts were taken directly from the field test reports from these 

studies. The following table presents the component emission factors, component counts, and average facility 

emissions for offshore production in the Gulf of Mexico and Pacific OCS. 

Average Facility Emissions for Offshore Production 

Equipment TYPe Component Type Component Average Average Facility 

Emission Factor, Component Count Emissions,~ 

Mscf/component-yr Mscf/yr 

Gulf of Mex..ico Valve 0.187 2,207 1,064 (27%) 

Platform 

Connection 0.046 8,822 

Open-Ended Line 0.368 326 

Other 2.517 67 

Pacific OCS Valve 0.048 1,833 430 (36%) 

Platform 

Connection 0.021 13,612 

Open-Ended Line 0.092 313 

Other 0.091 307 

• Values in parentheses represent the 90% confidence interval. 

EF DATA SOURCES' 

I. Emission Factors for Eastern Gas Production based upon data from the GRI/Star program (1) 

for the component EF's at 12 gas production sites. 

2. Fraction of methane (78.8 mol%) based on data from Methane Emissions from the Natural Gas 

Industry, Volume 6: Vented and Comhusted Source Summary (3). Conversion of emission 

factors from (pounds THC per day) to (methane Mscf/yr) also required estimation of gas 

average molecular weight. Based on data from Perry's Chemical Engineer Handbook (5th 

Edition) (4), Table 9-15, selected most similar gas composition speciation from C1 through C6.,. 

and performed linear extrapolation from average of 3 lowest data (87 mol% methane) to 78.8 

mol% methane. Resultant weight percent of 69.6 wt% methane used to speciate methane 

emissions. 

3. Component counts in Eastern gas production were based on average counts per equipment 

from the GRI/Star program at 12 gas production sites. Component counts for heaters and 

dehydrator in the Eastern region were based on data collected in the Western region. 

Component counts for onshore production in the Western U.S. were based on the averages 

A-13 
w 

from the GRI/Star program at 4 gas production sites and GRI/Radian data from 13 site visits 

gas production fields. 

4. Offshore data from APIIGRI/Star 20-site program for Gulf of Mexico platforms (4 platforms, 

site numbers 17 through 20), and Minerals Management Service/ABB Pacific OCS fugitive 

study (7 platforms). See respective test repons (GuJf of Mexico Offshore: API!Star 20-site 

study (5); Pacific OCS Offshore: MMS report 92-0043 November 30, 1992) (6). 

5. Large gathering compressors and large gathering compressor station emission factors are taken 

from Transmission segment (see Sheet T-1). 

EF PRECISION: 

Basis: 

Gas Wells - Eastern 

Separators - Eastern 

Heaters - Eastern 

Dehydrators - Eastern 

Meters/piping - Eastern 

Gathering compressors - Eastern 

Gas Wells -Western 

Separators - Western 

Heaters - Western 

Dehydrators - Western 

Meters/piping - Western 

Gathering compressors - Western 

Large Gathering Compressors 

Large Gathering Stations 

Offshore (GuJO 

Offshore (Pacific) 

± 27% 

± 27% 

± 43% 

± 35% 

± 30% 

± 27% 

± 24% 

± 33% 

± 40% 

± 25% 

± 30% 

± 68% 

± 65% 

± 102% 

± 27% 

± 36% 

The 

measurements. 

accuracy is rigorously propagated through the EF calculation from the range of individual 

method. 

Ninety percent confidence intervals were calculated for the sites using the r-statistic 

Computed 90% confidence intervals for site average component counts were combined with 

90% confidence intervals for component emission factors to obtain pooled uncertainty in aggregate 

emission factor. 

ACTIVITY FACTOR: (129157 Gas Wells· Eastern) 

(91670 Separators -Eastern) 

(260 Heaters - Eastern) 

(1047 Dehydrators -Eastern) 

(76262 Meters - Eastern) 

(129 Gathering Compressors -Eastern) 

(142771 Gas Wells - Western 

(74674 Separators -Western 

(50740 Heaters- Western 

(.36777 Dehydrators - Western 

(301180 Meters- Western 

(16915 Gathering Compressors - Western) 

(96 Large Gathering Compressors) 

(12 Large Gathering Stations) 

(1092 Gulf of Mexico platforms) 

(22 Western offshore) 

A-14 

± 5% 

± 23% 

± 196% 

± 20% 

± 100% 

± 33% 

± 5% 

±57% 

± 95% 

± 20% 

± 100% 

±52% 

± 100o/o 

± 100% 

± 10% 

± 10% 
AF DATA SOURCES' 

1. The gas well count is from A.G.A.'s Gas Facts 1992 data (7). 

2. Eastern gas wells and equipment AFs were regionalized using site visit data. Eastern meter 

AF based on 0.43 meter per gas industry well {per Star Environmental). Western U.S. meter 

AF based on industry advisor information of I: 1 meter per gas industry welL 

3. Dehydrator counts are based_ on 37,824 glycol dehydrators in production (see Sheet P-6 for 

details). Adjustment to activity factor for Eastern gas production: subtract I ,047 dehydrators 

(included in Eastern gas production component counts). 

4. Offshore platform counts provided by Offshore Data Services, Inc., Houston, Texas, and 

Minerals Management Service MOAD database for producing platforms. Assumed 50150 split 

between ~ow industry and Mgas" industry. 

5. Large gathering compressors and compressor station counts were estimated from FERC Form 

2 database. Large gathering compressor stations were those with at leas! 16 s!ages of 

compression (5 compressors per station and an average of 3.3 s1ages per compressor). The 

result was extrapolated to the national total by ratioing on gathering miles covered in FERC to 

total gathering mileage. 

6. The other equipment counts were produced from equipment count data taken during the site 

visits by Radian and Star. As explained in the activity factor section of the text of this report, 

extrapolarion to national counts was done on a regional basis to account for regional equipment 

configuration differences. 

AF PRECISION' 

Basis: 

1. 

2. 

REFERENCES' 

The precision for the active wells is assigned by engineering judgement, based upon the fact 

that the number of active wells is tracked nationally and known accurately by A.G.A./DOE, 

etc. 

The accuracy for the other equipme:J.t types is based upon rigorous propagation of error from 

the range in averages from the 9 production sites visited. 

1. Star Environmental. Fugitive Hydrocarbon Emissions: Eastern Gas Wells, Final Report, GRI95/0117, Gas Resean:h Institute, Chicago, IL, July 1995. 

2. Star Environmental. Fugitive Hydrocarbon Emissions from Oil arui Gas Production Operations, {API 

Publication No. 4589). American Petroleum Institute, December 1993. 

3. Shires, T.M. and M.R. Harrison. Methane Emissions from the Natural Gas Industry, Volume 6: 

Vented and Combustion Source Summary, Final Report, GRI-94/0257 .23 and EPA-600/R-96-0SOg. 

Gas Research Institute and U.S. Environmental Protection Agency, June 1996. 

4. Perry, R.H. et al. (ed.). Perry's Chemical Engineers' Handbook. Sixth Edition, McGraw -Hill Book 

Co., New York, NY, 1984. 

5. Star Environmental. Emission Factors for Oil and Gas Production Operations. (API Publication No. 

4615). American Petroleum Institute, January 1995. 

6. R. Countess, e! al. Fugitive Hydrocarbon Emissions from Padfic OCS Facilities. Volume 1, Final 

Report. MMS 92-0043, Minerals Management Service, Washington, DC, 1992. 

7. American Gas Association. Gas Facts, 1992 Data, Arlington, VA, 1993. 

A-15 
ANNUAL EMISSIONS: (17.4 Bscfiyr ± 7.1 Bscf/yr) 

equipment 

The annual emissions were determined by multiplying the average equipment emissions by the population of 

in the segment. 

""'" &niS5ion FIC!Or Activity Fae~or Emi!sion kate Ur>eertainty 

Gas WcllhAC! (&stem U.S.) 2S9S s.Cyr me!b&n< 129157 Sa$ wrll• (East= U.S.) 0.34 Bsdlyrll'lcth&ne 

Sepan10n <Eastem U.S.) 

"" 328 sdlyr methane 91670 ~ (Eur<:m U.S.) 0.03 Bsdi'yrmcthane )6% 

HQ!cn (Eutem U.S.) S 1 17 sd7ynnethcl• 260 heum (E.o.mrn US.) 0.001 Bsef/yrmctht.O.e 21S"/o 

Dehydnton {Eastml U.S.) 1939 se£1yr meth&n< 1047 dehydratcn{Easttrn U.S.) 0.008 Bsdi'yr mctha~~o 4Wo 

Meters/Piping {EUtml U.S.) 3289 s..U)'T mW!a:ne 16262 meier$ (E&s!cm U.S.) 0.2S Bsdlyrm<tlwte 

'""'· Guhering Com~sso" (&slem U.S) 4417 <ciJyT me!hme 129 gatlu:ring ccmprtSson {Easlml US.) 0 0006 &dlyr methane «% 

Gas Wellhuds (West= U.S.) I >302 sd7yr meth..,. 142771 SA! ~n.. (W~ U.S.) 1.9 Bsdi'yr melhme 25"!. 

Seporuon (W.,tem U.S.) 44SJ6 se!7yr mothme 74674 sep.mon (Wesrem U.S.) 3.33 8sdt')'r mcth&ne 69"/o 

Hutern (Western US.) 21066 scf/yr metlw>e 50740 in-Jiae btatm (Western U.S.) I .07 Bsct:'yr methane !10"/o 

Dehydruor$ (We<lml u.S.) 33262 sc:O)T .... m- 36m okhydraton (Wes!Cm U.S.) I .22 Il$o;fi}'T methme 

Me1e:rs (Western U.S.) 

"" 19310 sc:f7yr lllttbme 301JB0111etm (West= U.S.) 5.12 &c:Vyr methllle 109'"!. 

Slllall Galhe:riq Compn$$0rs {Wtstem m29sd/yr~ l691S «>mp<nson; (Wes!Cnl U.S.) !.65 Bscfiyr methllle "% U.S.) 

Lo.rge Galherins Camp~uors (Weslm! S.SS MMscf7)T 111eth..,. 96li%E<' eomprusc:n 

U.S.} 

0.53 Bsdi'yr mtthme ]36% 

I...vv Gathering Ccmpm;scr Swicn• 

(W~!em U.S.} 

l.Ol MMscflyr metha~~e 12 large gathering cQl!lp<eSsor sutiom 0.04 Bscflyr methane 116% 

Offshcre Oil/0.. {Gulf) 1064 Msdl'yrl!lelbl!l< 1092 Gulf cfMexl«> pl.rt!cm"l$ !.16 B>oflyr 'lletbllle 29"/, 

Offshore Oil/Gas ~ific) 430.0 Msdlyr metbn~ 22 plufonn• (P•cific) o.ol Bscflyr 'llethme 38'\'o 

=~ 17.4 Bsc:f/yr ~nethme 41% 

A-16 
P-3 

PRODUCTION SEGMENT SOURCE SHEET 

SOURCES' 

OPERATING MODE' 

EMISSION TYPE' 

ANNUAL EMISSIONS' 

BACKGROUND' 

Gathering Pipelines 

Normal Operations 

Steady, Fugitives (Pipeline Leaks) 

6.6 Bscf ± 108% 

Gathering field pipelines transport the gas from the production well to gas conditioning or processing 

facilities. Leakage from gathering pipelines occurs from corrosion, joint and fitting failures, pipe wall 

fractures, and external damage. 

EMISSION FACTOR: (scflleak-year) 

The emission factors for leakage from gathering pipelines are based on the arithmetic average leakage rates 

value 

for main 

of 

pipelines from the cooperative underground distribution leakage measurement program. A mean 

the estimated leak rate per leak was calculated using the test data for all pipe materials except cast 

iron. For cast iron mains, a segment test approach was used which quantifies the leakage rate for a long 

of 

isolated 

pipe. 

segment 

The 

of pipe; therefore, the mean leakage rate for cast iron is in terms of leakage per unit length 

natural gas leak rate is adjusted for methane by multiplying by the volume percent of methane 

for production (78.8 vol. %), and is adjusted for the soil oxidation of methane. The value of the emission 

factor and standard deviation for each pipe material category is given below: 

Pipe Material Number of Average Units or 90% 

Samples Emission Emission Confidence 

Factor Factor Interval or 

Emission 

Factor 

Protected Steel 17 17,102 scfi1eak-yr 14,548 

Unprotected 20 43,705 scf/leak-yr 40,675 

Steel 

Plastic 6 84,237 scfi'leak-yr 139,729 

Cast Iron 21 201,418 scf7mile-yr 128,290 

EMISSION FACTOR DATA SOURCES' 

I. Leakage rate data on a rate per leak basis for cathodically protected steel mains, unprotected 

steel mains, and plastic mains from the cooperative leak measurement program. 

2. Leakage rate data on a rate per unit length basis for cast iron mains from the cooperative 

leak measurement program for distribution mains. 

3. Assumes that the leak rates from gathering lines are identical to leak rates from distribution 

mains. 

A-17 
ACTIVITY FACTORo 

The estimated number of leaks in field gathering pipelines is based on a leak repair frequency for gathering 

lines owned and operated by transmission companies reported in the 1991 DOT RSPA database (I). This 

database reports an estimated 8,153 repaired leaks and 270 outstanding leaks in 31,918 miles of gathering 

pipeline. The leak frequency is derived by compensating for leaks that are repaired during the year and, 

therefore, not contributing to leakage year round. On average, the repaired leaks are assumed to be leaking 

for half the year, and each leak repair is counted as half an equivalent leak. Outstanding and unreported leaks 

are assumed to be leaking the entire year. 

Most production lines owned and operated by production companies are not regulated by DOT and many are 

not monitored for leaks in the rigorous fashion employed by distribution and transmission companies. 

Therefore, unreported leaks are accounted for based on the effectiveness of the survey method perfonned, 

which is estimated to fmd 35% and 85% of the total leaks for a vegetation and walking survey, respectively, 

based on one contract company specializing in distribution surveys. It is estimated that production company 

owned gathering lines are only surveyed using a vegetation method. However, transmission company owned 

gathering lines are estimated to be surveyed annually using a walking method, based on conversations with 

several transmission companies. 

Based on this analysis of equivalent leaks, the leak frequency is 0.18 leaks per mile for a walking survey and 

0.63 leaks per mile for a vegetation survey. This leak frequency was used to ratio the number of leaks to the 

total estimated population of gathering pipeline. 

Total gathering pipeline mileage is not reported or tracked nationally and must be estimated. The "gathering 

pipeline" designation includes three categories of pipeline: 1) production company owned gathering pipeline 

for gas wells not associated with oil production (i.e., non-associated gas wells); 2) production company owned 

gathering pipeline for oil wells that produce marketed gas (i.e., associated gas wells); and 3) transmission 

company owned gathering pipeline. The third category of utility-owned pipelines are assumed to be in 

addition to the production pipeline miles associated with wells. This is consistent with the site visit data 

since gathering lines owned by transmission companies were intentionally excluded from the site mileage 

totals. (The production companies did not report pipeline miles beyond their custody transfer meters.) 

Total miles of gathering pipeline for non-associated gas wells were estimated using site visit data from the 

thirteen production sites shown in the following table. Seven of the thirteen sites provided estimates of their 

total miles of pipeline. The fifth site's mileage was estimated from a map of its pipelines. 

A-18 
Site Gathering Miles Number of Wells Miles per Total 

Wells 

Site I 46.3 80 

Site 2 8 26 

Site 3 40 130 

Site 4 15.4 12 

Site 5 11 6 

Site 6 5.2 193" 

Site 7 600 1000 

Site 8 441.3 425 

Site 9 0.7 1 

Site 10 27.7 24 

Site 11 2.1 3 

Site 12 7.1 7 

Site 13 154.2 126 

TOTAL 1359.0 2033 0.67 +/- 28% 

•tnc1ucl.es 55 oil welts. 

miles 

The estimate of total gathering miles per non-associated gas well was derived as the weighted average total 

divided by total wells (0.67 ± 28%). The average mile per well ratio was extrapolated by the nationally 

tracked 

miles 

number of non-associated gas wells (276,000). The resulting estimate of national gathering pipeline 

associated with gas wells is 184,000. 

For the gathering pipeline mileage associated with oil wells that market gas, the same ratio of gathering miles 

per well was applied. However, it was assumed that only ha1f of the gathering pipeline mileage was 

attributed to the gas industry; the other half was attributed to the oil industry. Therefore, the average ratio of 

pipeline miles to oil wells marketing gas was estimated to be 0.33. This average ratio was extrapolated by 

the estimated number of oil wells marketing gas in the U.S. (209,000). The resulting estimate of gathering 

pipeline mileage associated with oil wells that market gas is 70,000. 

The third category of gathering pipeline owned by transmission companies is reported by the American Gas 

Association (A.G.A.) (2) to be 86,200 miles. Utility-owned pipelines were assumed to be included in the 

total production owned gathering pipeline miles and are not included in the transmission company owned 

gathering line mileage. 

The resulting total national gathering pipeline mileage from gas wells, oil wells marketing gas, and 

transmission companies was estimated to be 340,200 miles. A rigorous detennination of the 900/o confidence 

interval gave an error less that 4%, which was considered low based on the quality of the data used to 

generate the activity factor. Thus, a 90% confidence interval of± I 0% was assumed based on engineering 

judgement. 

A-19 
Based on the analysis resulting in a leak frequency of0.18 leaks per mile for transmission-owned gathering 

lines employing a walking survey, and 0.63 leaks per mile for production-owned gathering lines employing a 

vegetation survey, the activity factor can be calculated as follows: 

f(86,200 x 0.18)1 + [(340,200- 86,200) x 0.63J ~ 174,779 equivalent leaks/year 

The breakdown of total equivalent leaks by pipe material category is based on the breakdown of pipe mileage 

reported in the 1991 DOT RSPA database (I) for transmission-owned gathering lines. It was estimated that 

production-owned gathering line mileage is equivalent to the transmission-owned pipelines, with the exception 

of cast iron. It was assumed that no additional cast iron gathering lines are in service. (That is, the cast iron 

gathering line mileage reported in the RSPA database accounts for the total in the United States.) 

The total number of estimated gathering line leaks was allocated on a pipeline material category basis in the 

same proportion (adjusted for the fraction of mileage in each material category) as in the distribution sector. 

The precision of the estimated total leaks was calculated based on the estimated 90% confidence interval 

associated with each parameter in the activity factor equation: 

repaired leaks~ outstanding leaks: ± I 00% 

leak duration: ± 25% 

leak survey effectiveness: ± 15% 

A statistical software program [(@ RISK (3)] was used to determine the overall 90% confidence interval of 

the activity factor: ± 76%. 

For cast iron gathering lines, the mileage is based on the 1991 DOT RSPA database for transmission and 

gathering lines. The preCision of the cast iron mileage estimate is assumed to be ± 10%. The following table 

summarizes the estimated average activity factor and the precision: 

Pipe Material Total Miles Average Activity Units of Activity 90% Confidence 

Factor Factor Interval of 

Activity Factor 

Protected Steel 268,082 53,657 equivalent leaks 40,779 

Unprotected Steel 41,400 !14,655 equivalent leaks 87,138 

Plastic 29,862 6,467 equivalent leaks 4,915 

Cast Iron 856 856 miles 86 

ACTIVITY FACTOR DATA SOURCESo 

I. Leak repair frequency from [(DOT RSPA (1)] gathering line data. 

2. Leak survey effectiveness provided by Southern Cross Company (4). 

3. The gathering miles for gas and oil wells marketing gas was estimated using Phase 3 site 

visit data for seven production companies. The number of gas and oil wells for these 

companies was also used to extrapolate out to the nation~! estimate. 

4. The number of producing gas wells in the United States was taken from A.G.A. Gas Facts 

(2) foe 1992. 

5. The number of oil wells producing marketed gas in the United States was estimated by 

Radian (5). See activity factor section and sheet P-2. 

A-20 
6. The field and gathering miles owned by transmission companies was taken from A.GA. Gas 

Facts (2) for 1992. 

ANNUAL EMISSIONS: (6.6 Bscf ± 108%) 

The activity factor was multiplied by the emission factor to derive this total leakage rate. The 90% 

confidence intervals were propagated through this multiplication 

Pipe Material 

Protected Steel 

Unprotected Steel 

Plastic 

Cast Iron 

Total 

•scflmile-yr. 

bmiles. 

REFERENCES 

Average Emission 

Factor 

{scf7leak-yr) 

17,102 

43,705 

84,237 

201,418' 

Average Activity 

Factor 

(equivalent leaks) 

53,657 

114,655 

6,467 

856" 

Annual Emissions 90% Confidence 

Estimate, Interval of 

(Bscf) Leakage Estimate 

(Bsct) 

0.9 1.2 

5.0 7.0 

0.6 1.2 

0.2 0.1 

6.6 7.2 

l. U.S. Department of Transportation, Research and Special Programs Administration. 1991. 

2. American Gas Association, Gas Facts, Arlington, VA, 1992. 

3. Palisade Corporation. @Risk, Risk Analysis and Simulation Add-In for Lotus l-2-3, Version 1.5, 

Manoh 1989. 

4. Southern Cross Corporation. Comments on Dock£! PS-123, Notice 1, Leakage Surveys, 49 CFR Part 

192, Department of Transportation, Research and Special Programs Administration, Materials 

Transportation Bureau, Office of Pipeline Safety Regulations, December 19, 1991. 

5. Stapper, B.E. Methane Emissions from the Natural Gas Industry, Volume 5, Activity Factors, Final 

Report, GRI-94/0257.22 and EPA-600/R-96-0SOe. Gas Research Institute and U.S.Environmental 

Protection Agency, June !996. 

A-21 

-~ 
SOURCES: 

COMPONENTS: 

OPERATING MODE: 

EMISSION TYPE: 

ANNUAL EMISSIONS: 

BACKGROUND: 

P-4 

Pl{ODUCTION SOURCE SHEET 

Various Equipment 

(wells, heaters, separators, dehydrators, compressors) 

Pneumatic Devices 

Normal Operation 

Unsteady, Vented 

31.4 Bscf ± 65% 

Most of the pneumatic devices in the industry are valve actuators and controllers that use nanual gas pressure as 

the force for valve movement. There is a large population of pneumatic devices throughout the gas industry. 

Gas from the valve actuator is vented to the atmosphere during every valve stroke, and gas may be continuously 

bled from the valve controller pilot as well. 

EMISSION FACTOR: 125,925 scf per ava-age device ± 40% 

(This was adjusted for the production methane fraction or natural gas at 78.8 mol%.) 

Pneumatic devices (valve controllers) linked to control valves are the largest source of pneumatic emissions in 

the production segment. There are two types of devices with distinct bleed modes: intermittent and continuous. 

Intermittent bleed devices emit methane to the atmosphere only when the control valve actuates; when the device 

when 

is not moving the bleed rate is zero. Continuous bleed devices emit methane both when the valve actuates and 

the device is not moving. An emission rate for a generic pneumatic device combines the bleed rates of the 

two types of devices, weighted by the population of the device typeS as follows: 

where: 

Fraction ;,..m,u.m 

Fraction conti,..,.,.. 

% Methane 

= 

= 

(F:-action intmnittor:r X EF ;,..,.,iat.o< + Fraction"'""'""""' x EF~) 

x %methane 

0.65 ± 43% 

0.35 ± 43% 

78.8 mol % ± 5% 

Emissions for intermittent and continuous bleed devices were based on measured data provided by a Canadian 

study and U.S. field measurements from a separate contractor's program. The average measured emissions for 

intermittent and continuous bleed devices are 323 ± 34% and 654 ± 31% scfdldevice, respectively. The 

fraction of each type of device was determined from site visits. 

Therefore the average annual emission factor for a generic pneumatic device is: 

EF •• 1_ pneu=t>c de'>= = 125,925 ± 40% scf/device 

EF DATA SOURCES: 

l. Methane Emissions from the Natural Gas Industry, Volume 12: Pneumatic Devices (1) 

establishes the important emission-affecting characteristics. 

2. Site visit device counts establish the fraction of continuous bleed versus intermittent bleed 

A-22 
devices for multiple sites. 

3. The Canadian Producers Association (CPA) determined an average emission factor per device 

based on 19 measurements. 

4. An independent contractor provided 18 measurements of pneumatic devices in onshore and 

offshore production services. 

EF PREC!SIONo 

Basis: 

EF accuracy is based on rigorous error propagation from the spread of site device counts and 

measured emission rates. 

ACTIVITY FACTOR~ 249,1Il pneumatic controllers ± 48 % 

The 

number 

average count of devices per equipment type was determined from multiple site visits. The ratios for the 

of devices per gas well and the number of devices per marketed gas production were compiled by 

region. The regional values were summed to give national device counts based on well counts and marketed gas 

production. These values were averaged to give the final national device count of 249,111. 

AF DATA SOURCESo 

1. Methane Emissions from the Natural Gas Industry, Volume 5: Activity Factors (2) establishes 

the methodology for extrapolating the site data to a national count. 

2. Site 

well 

visit device counts, well counts, and production rates establish the number of devices per 

and the number of devices per gas production. 

3. Total regional gas well counts and 1992 marketed gas production rates are from A.G.A. Gas 

Facrs (3). 

4. The oil wells that market gas were calculated by this report and World Oil (4). Total oil wells 

for 1992 are reponed as 602,197 by the Oil & Gas Journal (5). The active oil wells that 

market gas are determined by multiplying the total national active wells by the fraction that 

market gas. The fraction is determined from a Texas Railroad Commission database (6) on oil 

leases and gas disposition from those leases; an analysis that shows the percent of oil leases 

that market the associated gas in Texas is 34.7%. 

AF PRECIS!ONo 

Basis: 

I. 

2. 

The accuracy for the devices per well and devices per gas production rate are calculated from 

the spread of site data collected for each region (a total of 36 sites). 

The accuracy for wells that market gas are based on the spread of data from the Texas 

Railroad Commission database. 

ANNUAL METHANE EMISSIONS: 31.4 Bscf ± 65 % 

The national annual emissions were determined by multiplying an emission factor for an average pneumatiC 

device by the population of devices in the production segment. 

125,925 scf x 249,111 devices = 31 Bscf 

A-23 
REFERENCES 

1. Shires, T.M. and M.R. Harrison. Methane Emissions from the Natural Gas Industry, Volume 12: 

Pneumatic 

U.S. 

Devices. Final Report, GRI-94/0257.29 and EPA-600/R-96-0801, Gas Research Institute and 

Environmental Protection Agency, June 1996. 

2. Stapper, B.E. Methane Emissions from the Natural Gas Industry, Volume 5: Activity Factors. Final 

Report, GRI-94/0257.22 and EPA-600/R-96-080e, Gas Research Institute and U.S. Environmental 

Protection Agency, June 1996. 

3. American Gas Association. Gas Facts: 1993 Data, Arlington, VA, 1994. 

4. Gulf Coast Publishing Company, World Oil, Annual Forecast/Review, Vol. 214, No.2, February 1993. 

5. Oil and Gas Joumal. 1992 Worldwide Gas Processing Survey Dalabase, 1993. 

6. Texas Railroad Commission, P-1, P-2 Tapes, Radian files, Austin, TX, 1989. 

A-24 
SOURCES: 

COMPONENTS: 

OPERATING MODE: 

EMISSION TYPE: 

ANNUAL EMISSIONS: 

BACKGROUND: 

P-5 

PRODUCTION SOURCE SHEET 

Wells, Gathering Facilities 

Chemical Injection Pumps 

Normal Operation 

Unsteady, Vented 

1.5 Bscf ± 203% 

Gas-driven chemical injection pumps use gas pressure acting on a piston to pump a chemical on the opposite 

side of the piston. The gas is then vented directly to the atmosphere. The pumps are used to add chemicals 

such as corrosion inhibitors, scale inhibitors, biocide, demulsifier, clarifier, and hydrate inhibitors to operating 

equipment. Two types of pumps were observed: I) piston pumps, and 2) diaphragm pumps. Some of the 

pumps observed were inactive at the time or had seasonal operation. 

EMISSION FACTOR: 248 scfd/average pump ± 83 % 

(fhis was adjtmed for the production methane content in natural gas at 78.8 mol%.) 

This average emission factor is based upon the following equation: 

where: 

Fpis""' = 

EF pl>IOO = 

F d;.;.tu.gm = 

EFd~ = 

fraction of the pump population that is the piston type = 49.8% ± 38% 

emission factor of an average piston ·pump = 48.9 scfd/pump ± 106% 

fraction of the pump population that is the diaphragm type= 50.2% ± 38% 

emission factor of an average diaphragm pump = 446 scfdlpump ± 77% 

The average device emission factor was determined by an aggregation of device emissions calculated for 

multiple U.S. sites. For piston pumps, the emission factor was determined by the following equation: 

where: 

EFP"""' 

Gas usage = 

Density 

Frequency = 

Operating time = 

% methane = 

Gas usage (acffstrok:e) x Density (scf/acf) x Frequency (strokes/day} x 

Operating time X % methane 

calculated gas usage based on piston diameter and stroke length (in actual ft3

); 

scf/acf at supply gas pressure (average 30 psig) {combined average value of 

volume and density is 0.0037 ± 65% scf/stroke); 

strokes per day of !he average pump (37 ,901 ± 29% strokes/day); 

portion of time that !he pump is operating (0.446 ± 62%); and 

78.8 mol% ± 5% for the production segment. 

Based on site and manufacturer data, the resulting national piston pump emission factor is 48.9 scfdlpump ± 

106%. 

A-25 
For diaphragm chemical injection pumps, tl:e emission factor was determined by the following equation: 

where: 

= Gas usage (scf/gal) x Volume (gal/stroke) x Frequency (strokes/day) x 

Operating time x % methane 

Gas usage = 

Volume = 

Frequency = 

Operating time = 

% methane = 

volume of gas (in standard ft3

) required to pump one gallon of liquid chemical 

(provided by the manufacturer); 

liquid displaced per stroke based on the plunger diameter and stroke length 

(combined average value of gas consumption and volume is 0.0719 ± 10% 

scf/stroke); 

strokes per day of the average pump (19,642 ± 49% strokes/day); 

portion of time that the pump is operating (0.40 ±52%); and 

78.8 mol% ± 5% for the production segment. 

diaphragm 

Using the site, 

pump 

manufacturer, and measured data to calculate the emission factor equation terms, the total 

emission factor was determined to be 446 scfd/pump ± 77%. 

number. 

Stroke volume 

Density 

was 

was 

calculated from pump manufacturers' data and site observations of manufacturer and model 

timed stroke 

calculated based upon observed site supply gas pressure, and frequency was based upon 

was based upon 

intervals observed while on site. Operating time was estimated by site personnel (if seasonal), or 

shown above 

the percent of pumps at the site that were operating during the visit. The emission factors 

(in scfd/pump) have been corrected for the natural gas composition 

78.8 mol % methane. 

in the production segment of 

EF DATA SOURCESo 

!. 

2. 

3. 

4. 

5. 

6. 

EF ACCURACY, 

Basis: 

Chemical 

The report entitled Methane Emissions from the Nanual Gas Industry, Volume I 3: 

Injection Pumps (1) establishes the important emission·affecting 

characteristics. 

Site visit data and reference material established the density from supply gas pressure 

at 30 psig. 

For the piston pumps, the stroke volume was estimated from manufacturers' data of 

pumps found at each site. 

Manufacturers' data for the diaphragm pumps provided scf of gas required to pump 

one gallon of chemical. This information was used with the calculated liquid 

displaced for a range of pumps to give an average gas volume. 

The frequency of actuations per day was determined from 40 timing measurements 

taken 

Measurements 

at 12 sites. The operating time was determined from data at 13 sites. 

of 5 diaphragm chemical injection pumps were provided from an 

emissions estimate program by the Canadian Petroleum Association. 

1. Operating time confidence bounds (at 90% confidence) were calculated by analysis of 

the spread of 7 sites for piston pumps and 10 sites for diaphragm pumps. 

2. Actuation confidence bounds (at 90% confidence} were based on measurements from 7 

sites for the piston pumps and 5 sites for the diaphragm pumps. 

3. It was assumed that the manufacturers' data are completely accurate. Data for the 

piston pumps were based on information from 4 manufacturers. Diaphragm pump 

data were provided by 2 manufacturers. 

4. 90% confidence bounds for each value were carried through error propagation to 

result in the final 90% confidence bound. 

A-26 
ACTIVITY FACTOR: 16,971 pumps in tbe production segment ± 143% 

The number of gas actuated pumps used in the production segment was determined by establishing the ratio of 

the number of pumps to active wells (oil or gas) that market gas. Site data were organized into regions and 

regional values were determined. The regional ratios were then multiplied by the regional count of active wells 

that market gas in that region to produce the total count of chemical injection pumps in the region. Finally, 

regions were added together to determine the national number. The activity factor is then: 

D 

(I) National AF = E (Regional AF) 

i= 1 

where n = total number of regions 

(2) Regional AF = <R/s) x (W) 

AF DATA SOURCESo 

1. 

2. 

3. 

AF ACCURACYo 

Basis: 

1. 

2. 

where RJ = ratio of total pumps to total wells in Region j 

where W = number of wells in the region 

The active oil and gas wells are from A.G.A. Gas Facts (2). The active oil wells that 

market gas are determined by muJtiplying the total national active oil wells times the 

fraction that market gas. The fraction is determined from a Texas Railroad 

Commission lease study that shows the percent of oil leases that market the associated 

gas in Texas (3). 

The pump counts were obtained during the site visits. Inactive, electrically driven. or 

air driven pumps were not counted. 

Regional extrapolation by gas well count was used. 

The accuracy for the active gas wells is assigned by engineering judgement, based 

upon the fact that the number of active wells is tracked nationally and known 

accurately by A.G.A./DOE, etc. 

The accuracy for the national AF is based upon error propagation from the production 

sites visited. 

ANNUAL METHANE EMISSIONS' 1.5 Bsd ± 203 % 

The national annual emissions were determined by multiplying an emission factor for a typical pump by the 

population of chemical injection pumps in the produe'jon segment. 

REFERENCES 

I. Shires, T.M. Methane Emissions from the Jr..'atural Gas Industry, Volume 13: Chemical Injection 

Pumps. Final Report, GRI-94/0257 .30 and EPA-600/R-96..Q80m, Gas Research Institute and U.S. 

Environmental Protection Agency, June 1996. 

2. American Gas Association. Gas Facts: 1993 Dara, Arlington, VA, 1994. 

3. Texas Railroad Commission, P-1, P-2 Tapes, Radian files, Austin, TX, 1989. 

A-27 
SOURCES' 

COMPONENTS' 

OPERATING MODE' 

EMISSION TYPE, 

ANNUAL EMISSIONS' 

BACKGROUND' 

P-6 

PRODUCTION SOURCE SHEET 

Glycol Dehydrators 

NIA 

Normal Operation 

Vented 

3.42 Bscf ± 192% 

water 

Glycol 

from 

dehydrators remove water from a gas stream by contacting the gas with glycol and then driving the 

small amount 

the 

of 

glycol 

methane, 

by heating in the glycol reboiler and into the atmosphere. The glycol also absorbs a 

and some methane can be driven off to the atmosphere through the reboiler vent. 

EMISSION FACTOR: (275.57 scC/MMscf gas processed ± 154.48o/.) 

A 

for 

thermodynamic 

dehydrators. 

computer simulation was used to determine the most impon:ant emission·affecting variables 

existence of 

The variables are: gas throughput, existence of a flash tank, existence of stripping gas, 

effect 

a gas driven pump, and existence of vent controls routed to a burner. Throughput, since its 

of throughput 

is linear, 

are 

is handled by establishing an emission rate per unit of gas throughput. Emission rates per unit 

pumps 

then established for the other important emission affecting characteristics. Gas driven 

Gas 

are ignored here and handled in a separate source analysis (see Methane Emissions from the Natural 

Industry, Volume 15: Gas·Assisted Glycol Pumps) (I). The emission factor is then: 

EF 

0 [ (0.265 X 3.57) + (0.735 X 175.10) + (0.00473 X 670) j X 0.9882 X 2.1 

Fn = Fraction of the population WITH flash tanks 

0.265 ± 8.35% 

Fm "" Fraction of the population WITHOUT flash tanks 

0. 735 ± 2.99% 

Fsc; = Fraction of the population WITH stripping gas 

0.00473 ± 115.78% 

F NYC = Fraction of the population WITHOUT combustion vent 

controls 

0.9882 ± 0.87% 

EFn = Total methane emission rate scf per I MMscf throughput 

with a flash tank 

3.57 + 102%/·58% 

Total methane emission rate scf per I MMscf throughput 

WITHOUT a flash tank 

= 175.10 +101%/·50% 

EFSG = Incremental methane emission rate per 1 MMscf 

throughput per dehydrator that has stripping gas 

670 +40%/·60% 

oc = 

2.1 ±41% 

Overcirculation factor for glycol-number of times the 

industry rule·of·thumb of 3 gallons glycoVIb water 

A-28 
EF DATA SOURCES: 

I. 

2. 

3. 

4. 

5. 

6. 

Methane Emissions from the Natural Gas Industry, Volume 14: Glycol Dehydrators 

(2) establishes emission affecting characteristics of dehydrators. 

GRIJEPA site visit data establishes the Fso and f:-wc for multiple sites (19 PROD 

sites). 

An analysis of a combined database including TMOGA 's 1019 dehydrators and 

GRI/EPA site visits 444 dehydrators established Fro and FND for production dehydrators. 

ASPEN computer simulations were used in combination with measured data to 

determine EFFD> and EFND from the dehydrator vent. 

Sampling data from the GRJ Glycol Sampling and Analytical Program for one 

dehydrator was used to determine EFsG (Glycol Dehydrator Emissions: Sampling 

and Analytical Methods and Estimation Techniques) (3). The upper botmd was 

calculated by assuming that all of the measured noncondensable vent gas was due to 

stripping gas that was 100% methane. The lower bound was calculated as the ruleof-thumb stripping gas rate recommended by a glycol dehydrator manufacturer. 

Overcirculation factor determined using data from the GRI Glycol Sampling and 

Analytical Program data for ten dehydrators. 

EF PRECISION: 275.57 scfi'MJvfscf gas processed± 154.48% 

Basis: 

The accuracy is propagated through the EF calculation from each term's accuracy: 

I. 

2. 

3. 

ASPEN has been demonstrated to match actual dehydrators within ±20% within the 

calculated confidence interVals obtained from site data. 

Individual EF confidence intervals were calculated from the data used in the 

calculation. 

Data from site visits has been assigned confidence intervals based upon the spread 

of the 444 dehydrators from GRIIEPA site data. 

ACTIVITY FACTOR: (12.4 Tscf/year gas throughput in the production segment) 

The amount of gas processed by glycol dehydrators in the production segment was calculated from the 

estimated nwnber of glycol dehydrators in production and the average throughput capacity for production 

dehydrators (Wright Killen and Co., 1994). A capacity utilization factor was estimated based on observations 

at several sites in the GRl Glycol Dehydrator Sampling and Analytical Program. 

AF DATA SOURCES' 

The report: Natural Gas Dehydration: Status and Trends (4) by Wright Killen for the Gas Research Institute, 

provides data and describes the methodology used to develop an estimate of the gas dehydrator count for the 

U.S. The count also estimated the number in several industry segments: production, transmission, and gas 

processing. 

A-29 
Basis: 

l. 

2. 

A GRl study by Wright Killen & Co. found 41700 dehydrators in the U.S. gas 

industry for 1993. Wright Killen & Co. also used a TMOGNGPA database on 

dehydrators to split the population into the following industry segments: 

Production: 25270 

Processing: 7923 

Transmission: 8507 

TOTAL 41700 

The study also found that 95.0 % of the dehydrators were glycol for a total of 

39,615 (versus molecular sieve or other types). 

Site visit data on 24 transmission compressor stations shows: 2/17 = O.I 18 per 

transmission compressor station, and 17/6 = 2.83 per storage compressor station. 

The site visit numbers would lead to an estimate of 1293 total transmission and 

storage dehydrators. Site visit data on II gas plants show 1.41 dehydrators per 

plant, or l ,024 in gas plants. 

Subtracting processing, transmission, and storage glycol dehydrators from the total 

of 39,615 yields 37824 glycol dehydrators in production. 

Average capacity of production dehydrators was reported to be 2 MMscfd by Wright 

Killen & Co. 

especially 

Infonnation on actual dehydrator throughput as compared to design capacity is, in general, difficult to obtain 

Analytical 

for production field units. Data from several sites in the GRI Glycol Dehydrator Sampling and 

may 

Program and other anecdotal information from various site visits indicate that capacity utilization 

be less than 50%, so a value of 45% was chosen for the AF calculations. 

AF PRECISION: 12.4 Tscflyear ± 61.87% 

Basis: 

The 90% confidence limits for total glycol dehydrators were established in the Wright Killen & Co. 

Confidence 

report. The confidence limits for the segments other than production were based on site visit data. 

limits for the capacity utilization was based on engineering judgement. 

ANNlJAL METHANE EMISSIONS: (3.4171 BscUyr ± 191.90%) 

The annual methane emissions were determined by multiplying the dehydrator emission factor by the activity 

factor. 

REFERENCES 

I. 

Gas-Assisted 

Myers, D.B. and M.R. Harrison. Methane .Emissions from the Natural Gas industry, Volume 15: 

Glycol Pumps, Final Report, GRI-94/0257.43 and EPA-600/R-96-080o. Gas Research 

Institute and U.S. Environmental Protection Agency, June 1996. 

2. 

Report, 

Myers, D. 

GRI-94/0257.31 

Methane Emissions from the Natural Gas Industry, Volume 14: Glycol Dehydrators, Final 

and EPA-600/R-96-080n. Gas Research Institute and U.S. Environmental 

Protection Agency, June 1996. 

A-30 
3. Radian Corporation. Glycol Dehydrator Emissions. Sampling and Analytical Methods and 

Estimation Techniques. GRl-94/0324, Gas Research Institute, Chicago, IL, March 1995. 

4. Wright Killen & Company. Natural Gas Dehydration: Status and Trends, Final Report. GRI94/0099, Gas Research Institute, Chicago, IL, October 1993. 

A-31 
SOURCES' 

COMPONENTS' 

OPERATING MODE' 

EMISSION TYPE' 

ANNUAL EMISSIONS' 

BACKGROUND' 

P-7 

PRODUCTION SOURCE SHEET 

Dehydrators 

Gas Driven Kimray Pumps 

Normal Operation 

Unsteady, Vented 

10.96 Bscf ± I !0.0% 

pistons 

Gas driven Kimray glycol circulation pumps use a mixed phase of wet glycol liquid and absorber gas to drive 

directly 

that pump dry (lean) glycol circulation. Unlike chemical injection pumps which vent the driving gas 

to the atmosphere, Kimray pumps pass the driving gas along with the wet glycol to the reboiler. In 

methane 

the reboiler 

may 

the methane is driven off into the vent line. Depending on dehydrator vent gas dispositions, the 

be vented to the atmosphere or controlled and burned. 

EMISSION FACTOR: (992.0 scf CH/MMscf gas processed) 

The average glycol pump gas emission factor was determined by an equation describing the gas generation 

existence 

and disposition of gas from the pump. The disposition of gas generated by the pump depends upon the 

of a flash tank and vent controls. Measured and estimated parameters were input into the equation. 

In general, the emission factor for a gas-assisted pump was determined by the following equation: 

EF pump = PGU X CR X WR X oc X FNT X Fl><'VC 

EF DATA SOURCES' 

I. 

Emissions 

Equation 1, i.e. the effects of operating variables on emissions, was defmed by the report on Methane 

.from the Natural Gas industry, Volume 15, Gas-Assisted Glycol Pumps.(I) 

2. CR =-glycol circulation ratio= 3.0 gal glycol/1b water± 33.3%. 

3. WR =water removed from gas 

= 53 lb/MMscf ± 20% for high pressure 

= 127 lb!MMscf ± 200/o for low pressure 

4. OC =factor to account for overcirculation of glycol= 2.1 ± 72.4%. 

5. FNT =fraction of dehydrators without flash tanks=- 0.735 ± 2.99'1/o. 

6. FNVc = fraction of the dehydrators wii:lout combustion vent controls =- 0.9882 ± 0.87%. 

7. PGU = pump gas usage (assume 83% methane) 

= 3. 73 scf CH/gal glycol ± 30% for high pressure 

A-32 
= 2.31 scf CH/gal glycol ± 30% for low pressure 

CALCULATION METHOD: 

It is estimated that 80% of the production dehydrators would be high pressure (R Garrett memo). The 

overall production emission factor is then calculated as a weighted average of the high and low pressure 

emission factors. 

EF (high pressure)= (3.73 sc£1gal) x {3.0 gaVIb ~0) x (53 lb Hp/MMscf) 

X (2.!) X (0.735) X (0.9882) 

= 904.45 scfJMMscf ± 95.04% 

EF (low pressure)= (2.31 scVgal) x (3.0 gaY!b H,O) x (127 lb H,O!MMsct) 

X (2.1) X (0.735) X (0.9882) 

= 1342.18 scflMMscf ± 95.04% 

EF (Production) = (0.80 ± 12.5%) (904.45 scf!MM:scf ± 95.04%) + 

(0.20 ±50%) (1342.18 scf/MMscf ± 95.04%) 

992.00 scf CH/MM:scf ± 77 .290/o 

EF ACCURACY: (± 77.29%) 

Basis: 

I. Assumption: The manufacturer's data and ranges are relatively accurate (±30%). 

2. Dehydrator characteristics based on site visit observations and TMOGA survey. 

ACTIVITY FACTOR; (11.05 Tscf/year in the production segment with gas·assisted pumps) 

The volume of gas processed through dehydrators using gas·assisted pumps was calculated from the total 

throughput for production dehydrators and the fraction of dehydrators using gas·assisted pumps determined 

from site visits. The activity factor is then: 

AF = (fraction of dehydrators with gas·assisted pumps) x (throughput for production dehydrators) 

(0.8913 ± 2.79%) x (12.4 Tsct/year ± 48.21%) 

11.05 Tsct/year ± 61.96% 

AF DATA SOURCES: 

I. See Methane Emissions from the Natural Gas Industry, Volume 14: Glycol Dehydrators (2) for 

an explanation of production dehydrator throughput. See the Methane Emissions from the 

Natural Gas Industry, Volume 5: Activity Factors (3) for more details. 

2. Fraction of dehydrators using gas·assisted pumps came from data from site visits. 

AF ACCURACY: (± 61.96%) 

Basis: 

Calculated from confidence limits of gas throughput and fraction of dehydrators by standard error 

propagation analysis. 

A-33 
ANNUAL METHANE EMISSIONS: (10.962 Bscf ± 110.03%) 

total 

The annual 

throughput 

methane emissions were determined by multiplying an emission factor (scf CH/MMscf) by the 

for production dehydrators using gas-assisted pumps. 

(992.00 scf/MMscf) x (l 1.05 Tscf) 0< 10.962 Bscf {± 1 !0.03%) 

REFERENCES 

I. 

Assisted 

Myers, D.B. 

Glycol 

and 

Pumps. 

M.R. Harrison. Methane Emissions from the Natural Gas Industry, Volume 15: GasFinal Repon, GRI-94/0257.33 and EPA-600/R-96-0SOo. Gas Research 

Institute and U.S. Environmental Protection Agency, June 1996. 

2. 

Repon, 

Myers, D. 

GRI-94/0257.31 

Methane Emissions from the Natural Gas Industry, Volume 14: Glycol Dehydrators. Final 

Protection Agency, 

and EPA-600/R-96-0SOn. Gas Research Institute and U.S. Environmental 

June 1996. 

3. 

Report, 

Stapper, 

GRI-94/0257.22 

B.E. Methane Emissions from the Natural Gas Industry, Volume 5: Activity Factors. Final 

Protection Agency, 

and EPA-600/R-96-0SOe. Gas Research Institute and U.S. Environmental 

June 1996. 

A-34 
SOURCES: 

OPERATING MODE: 

EMISSION TYPE: 

ANNUAL EMISSIONS: 

BACKGROUND: 

P-8 

PRODUCTION SOURCE SHEET 

Various Production Equipment 

(wells, vessels, compressors, pipelines) 

Maintenance 

Unsteady, Vented 

6.0 Bscf ± 359% 

Maintenance activities can emit gas to the atmosphere through blowdown or through purge. Slowdown is the 

direct, intentional venting to the atmosphere of gas contained inside operating equipment The gas is released 

to provide a safer working environment for maintenance activities around or inside the equipment. After the 

equipment is serviced, the oxygen inside the equipment is often cleared to the atmosphere by purging natural 

gas through the equipment. 

Another type of maintenance venting is associated with low pressure gas wells that sometimes accumulate 

water in the wellbore due to their low flow rate. This water chokes the flow of the well, reducing gas 

production. To clear the water, the well is blown to a tank at atmospheric pressure where the gas is vented. 

EMISSION FACTORS: Gas Well Unloading 49,570 ± 344% scf/unloading gas well 

Compressor Blowdown 3,774 ± 147% scflcompressor 

Compressor Starts 8,443 ± 157% scf/compressor 

Pipeline Blowdown 309 ± 32% scf/mile 

Vessel Slowdown 78 ± 266% sc(fvessel 

(Emission factors were adjusted for tbe production methane fraction of 

natural gas of 78.8 mol0AI) 

Slowdown volumes and frequencies were averaged from calculations for each GRl/EPA site visit. The 

volume times the frequency results in the annual emissions. The volumes were calculated at each site using 

equations of state, observed vessel dimensions, and pre-blowdown pressures. Frequencies were gathered at 

each site from operator interview. The annual emission factor (scf/Unit) for each category was calculated as 

follows: 

where: 

Volume 

Frequency = 

%Methane = 

EF =Volume x Frequency x% Methane 

Gas released to the atmosphere during an event (set/event/unit); 

Number of events annually; 

78.8 mol % ± 5% for the production segment. 

More details are available in the Methane Emissions from the Natural Gas Industry, Volume 7: Blow and 

Purge Activities (1). 

EF DATA SOURCESo 

I. The blow and purge report establishes emission affecting characteristics of blowdown practices. 

A-35 
2. Volume and frequency data were available from the following number of sites; 

LP Gas Well Unlo~ing (12 sites) 

Compressor Blowdown (17 sites) 

Compressor Starts (12 sites) 

Vessel BD (12 sites) 

Pipeline BD (18 sites) 

3. The count of equipment at each site was gathered during the site visits by observation, record 

search, or interview. 

EF PRECISION: ± 32% to 344% 

Basis: 

The accuracy was calculated from the variance of the site data. A 900/o confidence interval is 

calculated for the sites using the method outlined in the Methane Emissions from the Natural Gas 

Industry, Volume 4: Statistical Methodology (2). 

ACTIVITY FACTORSo 

114,139 ± 45% gas wells requiring unloading 

17,112 ± 52% compressors 

340,000 ± 10% miles of pipeline 

255,996 ± 26% production vessels 

The activity factors for equipment in the production segment were compiled from GRI/EPA site visit averages 

as well as published statistics on the gas industry (see activity factor sections in previous sheets). The 

number of production vessels was assumed to be the sum of separators, heaters, and dehydrators. 

AF DATA SOURCES: 

l. 

GRIIEPA 

The well, compressor, and vessel counts came from the activity factor extrapolation based on 

site visits or surveys (previously discussed in the production fugitives sheet). The 

count of "vessels" is from the addition of dehydrator, separator, and in-line heater counts. 

2. The miles of production gathering pipelines were determined from a site extrapolation of seven 

sites and data from Gas Facts Table 5-3 (3). This extrapolation was previously discussed in the 

production gathering pipeline fugitive leaks sheet, 

P-3. 

3. The number of gas wells requirir..g unloading is based on the ratio of gas wells requiring 

unloading to all active gas wells from 25 GRIIEPA sites (41.4% ± 162%). 

AF PRECISION: Range ± 10% to 52% 

Basis: 

The accuracy for all equipment types is based on error propagation from the spread of available 

production site data. 

ANNUAL METHANE EMISSIONS: 6.0 Bscf ± 359% 

each 

The annual methane emissions were detennined by multiplying an emission factor (rate per average unit) for 

category by the activity factor (population) of the category. 

A-36 
REFERENCES 

1. Shires, T.M. and M.R. Harrison. Methane Emissions from the Natural Gas Industry, Volume 7: Blow 

and Purge Activities, Final Report, GRl-94/0257.24 and EPA-600/R-96-080g, Gas Research Institute 

and U.S. Environmental Protection Agency, J'Jne 1996. 

2. Williamson, H.J., M.B. Hall, and M.R. Harrison. Methane Emissions from the Natural Gas Industry, 

Volume 4: Statistical Methodology, Final Report, GRI-94/0257.21 and EPA-600/R-96-080d, Gas 

Research Institute and U.S. Environmental Protection Agency, June 1996. 

3. American Gas Association. Gas Facts, 1992 Data (Table 5-3), Arlington, VA, 1993. 

A-37 
SOURCES: 

OPERATING MODE: 

EMISSION TYPE: 

ANNUAL EMISSIONS: 

BACKGROUND: 

P-9 

PRODUCTION SOURCE SHEET 

Various Production Equipment (vessels) 

Upsets 

Unsteady, Vented 

0.3 Bscf ± 190% 

equipment. 

Upsets in process 

To 

conditions can cause pressure rises that exceed the maximum design pressure for 

excess gas 

prevent equipment overpressure and damage, pressure relief valves (PRVs) open and vent the 

handle 

to the atmosphere. These PRVs are spring loaded or pilot actuated valves that are designed to 

Shutdown 

the upset conditions. A few offshore production facilities (but no onshore facilities) have Emergency 

Systems (ESDs) that depressure the entire facility to a vent or a flare. 

EMISSION FACTORS: PRV Discharge Blowdowo 34 ± 252% scfi'PRV 

ESD Blowdown 257 ± 200% Mscflplatform 

(Corrected for the production methane composition of 78.8 mol%) 

gas 

Emergency 

released 

blowdown volumes and frequencies were estimated at each site visited. The average volume of 

of PRVs 

at lift pressure was calculated for a typical PRV size and duration, and corrected for the fraction 

corrected 

that 

for 

release gas to the atmosphere. ESD blowdown volumes were based on the platform volume and 

annual emission 

the fraction of platforms with ESDs and the fraction that vent gas to the atmosphere. The 

factor (scfi'unit) for each category was calculated as follows: 

where: 

Volume 

Frequency = 

%Methane = 

EF DATA SOURCESo 

EF =Volume x Frequency x% Methane 

Gas released to the atmosphere during an event (sc:flevent/unit); 

Number of events per year; 

78.8 mol % ± 5% for the production segment 

I. 

Activities 

The GRIIEPA Methane Emissions from the Natural Gas Industry, Volume 7: Blow and Purge 

(I) establishes emission affecting characteristics ofblowdown practices. 

2. 

visit 

Volumes 

based 

(duration, release rate,% to atmosphere) and frequencies were calculated from each site 

on data collection, observation, and interview. Data were available from the 

following number of sites: 

PRV discharge (II sites) 

ESD activation (5 platforms) 

3. The count of equipment at each site was gathered during the site visits by observation, record 

search, or interview. 

EF PRECISION, 

Basis: 

using 

The accuracy was propagated from the spread of the site data. A 90% confidence interval is calculated 

the method presented in the Methane Emissions from the Natural Gas Industry, Volume 4: 

Statistical Methodology (2). 

A-38 
ACTIVITY FACTORS: 529,440 ± 53% Production PRVs 

1,115 ± 10% Platforms 

The activity factors for equipment types in the segment were compiled from GRI!EPA site visit data as well 

as published statistics on the gas industry. 

AF DATA SOURCES: 

1. The count of platforms is from Offshore Data Services and the Minerals Management System 

Outer Continental Activity Database as reported in Methane Emissions from the Natural Gas 

Industry, Volume 5: Activity Factors (3). 

2. The nwnber of production PRVs is based on counts of PRVs per equipment type from site visit 

data: 

Equipment PRV Number 

Type Count of Sites 

Separators 2 ± 68% 20 

Heaters I± 89% II 

Dehydrators 2 ±53% 10 

Compressors 4 ± 84% 13 

Details are provided in the Methane Emissions from the Natural Gas Industry, Volume 8: Equipment Leaks 

report (4). 

AF PRECISION: Range± 10% to 53% 

Basis: 

I. 

2 

Confidence intervals for the platform count were asswned and assigned based upon an excellent 

recorded source of data [see Methane Emissions from the Natural Gas Industry, Volum~ 5. 

Activity Factors (3)]. 

Ninety percent confidence limits for production vessels with PRVs were calculated from the 

confidence intervals of each type of equipment. See Methane Emissions from the Natural Gas 

Industry, Volume 5: Activity Factors (3) for details of equipment count determination. 

ANNUAL METHANE EMISSIONS: 0.30 Bscf ± 190% 

The annual methane emissions were detennined by multiplying an emission factor (rate per avg unit) by the 

activity factor (population) of the category. Each emission factor was adjusted for the average methane 

content in the production segment of 78.8 mol%. 

REFERENCES 

I. Shires, T.M. and M.R. Harrison. Methane Emissions from ihe Natural Gas Industry, Volume 7: Blow 

and Purge Activities, Final Report, GRJ-94/0257.24 and EPA-600/R-96-080g, Gas Research Instirute 

and U.S. Environmental Protection Agency, June 1996. 

2. Williamson, H.J., M.B. Hall, and M.R. Harrison. Methane Emissions from the Natural Gas Industry, 

Volume 4: Statistical Methodology, Final Report, GRJ-94/0257.21 and EPA-600/R·96-080d, Gas 

Research Institute and U.S. Environmental Protection Agency, June 1996. 

A-39 
3. 

Report, 

Stapper, 

GRI-94/0257.22 

B.E. Methane Emissions from the Natural Gas Industry, Volume 5: Activity Factors, Final 

and EPA-600/R-96-0SOe, Gas Research Institute and U.S. Environmental 

Protection Agency, June 1996. 

4. Hummel, 

Volume 

K.E., L.M. Campbell, and M.R. Harrison. Methane Emissions from the Natural Gas Industry, 

8: Equipment Leaks, Final Report, GRI-94/0257.25 and EPA-600/R-96-0SOh, Gas Research 

Institute and U.S. Environmental Protection Agency, June 1996. 

A-40 
SOURCES' 

OPERATING MODE' 

EMISSION TYPE' 

ANNUAL EMISSIONS' 

BACKGROUND, 

P-10 

PRODUCTION SOURCE SHEET 

Pipeline 

Mishaps (Dig-ins) 

Unsteady, Fugitive 

0.2 Bscf ± I ,934% 

Dig-ins are gathering pipeline ruptures caused by unintentional (sometimes third-party) damage. Production 

companies do NOT estimate and record the quantity of gas lost during a dig-in event; therefore, distribution 

data has been used. 

EMISSION FACTOR: 669 ± 1,925% scf/mile 

(Corrected for tbe production methane composition of 78.8 mol%) 

The emission factor was derived from four distribution company estimates of the losses from dig-ins: the 

Pacific Gas and Electric unaccounted-for (UAF) gas study (I) results showed that losses from dig-ins were 

estimated at 91,178 Mscf for 58,024 miles of distribution mains and services; the Southern California Gas 

Company estimate {2) of losses from dig-ins was 170,457 Mscf for 82,337 miles of distribution mains and 

services; a third company estimate of losses from dig· ins was 19,581 Mscf for 24,916 miles of distribution 

mains and services; and a fourth company reponed dig·in losses of 10,453 Mscf for 18,713 miles of 

distribution mains. The ratio of the total dig· in emissions to the total pipeline miles from these companies 

was used to estimate the annual national methane emission factor, resulting in 2.06 Msc£1mile. 

This value was halved (and adjusted for the different methane compositions of the tWo industry segments) 

based upon an engineering assumption that production dig·inS occur much less frequently than distribution 

dig·ins, and so account for approximately one·half of the distribution emission rate per mile. This is 

supported by the fact that most production sites are remotely located, while distribution sites are by definition 

located in population centers where third·party dig·ins are more likely. 

ACflVITY FACTOR: 340,000 ± 10% miles of production gathering pipeline 

The annual number of miles of gathering pipeline in the U.S. gas industry was derived from site data. See P· 

3 and Methane Emissions from the Natural Gas Industry, Volume 5: Activity Factors (3) for more details. 

ANNUAL METHANE EMISSIONS' 0.23 &cf ± 1,934% 

REFERENCES 

I. Pacific Gas & Electric Company and Gas Research Institute. Unaccounted·For Gas Project. Volume 

l, Final Report, San Ramon, CA, June 1990. 

2. Southern California Gas Company and Gas Research Institute. A Study of the 1991 Unaccounted·For 

Gas Volume ar the Southern California Gas Company, Final Report, Los Angeles, CA, April 1993. 

3. Stapper, B.E. Methane Emissions from the Natural Gas Industry, Volume 5: Activity Factors, Final 

Report, GRI-94/0257.22 and EPA-600IR-96--080e, Gas Research Institute and U.S. Envirorunental 

Protection Agency, June 1996. 

A-41-
SOURCES: 

OPERATING MODE: 

EMISSION TYPE: 

ANNUAL EMISSIONS: 

BACKGROUND: 

P-11 

PRODUCTION SOURCE SHEET 

Gas WeJis 

Maintenance 

Venting and Flaring 

0.02 Bscf ± 1,263% 

Two minor sources of maintenance releases are completion flaring and well workover. Completion 

occurs at a new well's open 

flaring 

ended pipe flare immediately 

testing, the gas is flared 

following the drilling process. During completion 

sizing of meters and surface 

to detennine the available pressure and flow rates at the surface. This allows proper 

production rates and needed 

equipment. Most completion flaring occurs at exploratory wells, since the 

can be determined before 

facilities for in·fiii wells (also called development wells) are often available or 

the well is completed. 

Well workovers are another cype of maintenance venting. During a well work.over, the tubing is pulled from 

the well to repair tubing corrosion/erosion or other downhole equipment problems. The well is "killed" by 

opened 

replacing 

to 

the 

the 

gas 

atmosphere. 

in the column with water or mud, thus stopping all production flow. The well can then be 

EMISSION FACTORS: 

Well Workovers 

Completion Flaring 733 ± 200% scflcompletioo well 

2,454 ± 459% scflwell workover 

(Emission factors were adjusted for the production methane fraction of natural gas of 78.8 mol%.) 

The flow rate of gas at completion 

the maximum gas 

is the highest that the well will produce. For emission estimate purposes, 

based on the average 

flow 

annual 

rate was not available. Instead, the completion flaring emission factor was calculated 

natural gas production per well and an assumed flaring efficiency as shown: 

where: 

EFccmpl"""n n.nng =Average Annual Volume x Duration x% Methane x Flaring Efficiency 

Average Annual Volume 

Duration = 

%Methane 

Flaring Efficiency = 

= 16.97 MMscf for natural gas 

Flaring duration is one day/completion well 

78.8 mol% for production 

98% efficient (~/o methane not burned) 

This results in an emission factor of 733 ± 200% scfi'completion well for completion flaring. 

The emission factor for well workovers was determined 

fields are shown 

from two gas production fields. Data from these 

in the following table: 

Total number of wells 

Number of workovers/year 

Methane emissions/workover, scfi'workover 

Average scf methanelworkover 

A-42 

Site I 

21 

I 

670 

Site 2 

400 

8 

4,238 

2,454 ± 459% 
EF DATA SOURCES: 

l. One operator provided data on the typical duration of completion flaring and which types of 

completions were flared. Average is one day/exploratory completion well. 

2. Average gas production per well from Gas Facts(!). 

3. Multiple reports on methane flare combustion efficiency support 98% combustion. 

4. Pipeline Systems Incorporated (PSI) reported gas well workover emissions from two sites (2). 

EF PRECISION: ± 200% to 459% 

1. Engineering judgement was used to establish the upper confidence limit for the completion 

flaring emission factor. 

2. Confidence botu1d for well workover emission factor is based on the average of data from two 

sites. 

ANNUAL ACTIVITY FACTORS: 

844 ± 10% completed gas wells 

9.329 ± 258% well workovers 

AF DATA SOURCES: 

I. Number of exploratory wells completed per year based on data from the Energy Information 

Administration (EIA) Drilling and Production under T1tle I of the Natural Gas Policy Act (3). 

This data excludes Alaska. 

2. PSI data showed I workover/yr per 21 wells at Site 1 and I workover/yr per 50 wells at Site 2. 

3. The Activity Factors Report (4) provides details on the total number of gas producing wells 

{276,0I4 ± 5%). 

AF PRECISION: Range ± IO% to 258% 

I. I 0% upper confidence bound for completion wells is assigned based on good precision from 

national statistics of 1987 data. 

2. Well workover confidence interval is based on the average of data from two sites combined with 

the confidence bound for the total number of gas producing wells. 

ANNUAL METHANE EMISSIONS: Completion Wells: 619 ± 201% Mscf 

Well Workovers: 22.9 ± 1296% MMscf 

The annual methane emissions were determined by multiplying an emission factor (methane emissions per 

event) for each category by the activity factor (events/year) of the category. 

REFERENCES 

I. American Gas Association. Gas Facts: !992 Data (Table 3-3), Arlington, VA, 1993. 

2. Pipeline Systems Incorporated. Annual Methane Emission Estimate of the Natural Gas Systems in the 

United States, Phase 2. For Radian Corporation, September 1990. 

3. Energy Information Administration. Annual Energy Review 1994, Table 4.5 "Oil and Gas Exploratory 

Wells, 1949-1994." EIA, Office of Oil and Gas, U.S. Department of Energy, DOEIEIA-0384(94), 

Washington, DC, July 1995. 

4. Stapper, B.E. Methane Emissions from the Natural Gas industry, Volume 5: Activity Factors, Final 

Report, GRI-94/0257.22 and EPA-600/R-96-080e, Gas Research Institute and U.S. Environmental 

Protection Agency, June 1996. 

A-43 

APPENDIX B 

Gas Processing Source Sheets 

B-1 
GP-1 -

GP-2-

GP-3 -

GP-4-

GP-5-

GP-6-

APPENDIX B 

Gas Processing Source Sheets 

Fugitive Emissions B-4 

Glycol Dehydrator Vents ............................ B-9 

Acid Gas Removal (AGR) Vents ...................... B-11 

Maintenance Venting .............................. B-13 

Glycol Pumps ................................... B-15 

Pnemnatic Devices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B-18 

B-2 
PROCESSING SOURCE SHEETS 

This section contains the specific source sheets for the processing (gas plant) segment of 

the na!Ural gas industry. The following table serves as a guide for fmding sheets in this 

section. The cells in the table give the sheet number (GP-1, GP-2, etc.) of the source sheet. 

The rows defme the equipment covered, while the columns defme the emission type. A 

category with no sheet number means that the emissions from that area were determined to 

be zero or negligibly small. The label for each source sheet is shown at the top of the 

cover page for that sheet. 

. TABLE OF OPERATING MODE. 

CONTENTS EMISSION .TYPE (Fugitive, Vented, or Combusted) 

Start Up Nonnal Operations Maintenance Upsets Mishaps 

EQUIP MENTo v c F v c v c v c v 

Entire Plants GP-1 GP-6 GP-4 GP-4 

Vessels GP-1 GP-6 GP-4 GP-4 

Acid Gas GP-1 GP-3 GP-4 GP-4 

Removal (AGR) GP-6 

Units 

Dehydrators GP-1 GP-2 GP-4 GP-4 

GP-5 

GP-6 

Compressors GP-1 GP-6 P-1 GP-4 GP-4 

Metering GP-1 GP-4 GP-4 

B-3 
SOURCES' 

OPERATING MODE' 

EMISSION TYPE' 

ANNUAL EMISSIONS' 

BACKGROUND, 

GP-1 

PROCESSING SOURCE SHEET 

All Equipment at Gas Processing Plants 

Nonnal Operation 

Steady and Unsteady, Fugitive 

24.45 Bscf ± 68% 

Equipment leaks are typically Jow·level, unintentional 

surfaces of above-ground 

losses of process fluid (gas or liquid) from the sealed 

process equipment. Equipment components 

and other connectors, pump 

that tend to leak include valves, flanges 

seals, compressor seals, pressure relief valves, open-ended 

connections. These 

lines, and sampling 

components represent mechanical 

to wear and develop 

joints, seals, and rotating surfaces, which in time tend 

leaks. 

EMISSION FACTOR' 

a. Plant ""' 2.89 MMscflyr methane per plant 

b. Reciprocating Compressor = 4.09 MMscf/yr methane per recip 

c. Centrifugal Compressor = 7.75 MMscf/yr methane per tnrbine 

The average fugitive emission rate for gas processing plants was determined 

a) plant component counts 

to be composed of two parts: 

(excluding compressor components), and b) compressoNelated 

Fugitives 

components. 

from the compressor-related components have much higher emission factors than components 

rest of the facility. Pan of 

in the 

emissions are due 

this is due.to the high vibration that compressors generate, but most of the larger 

to unique compressor components, as explained below. 

a. The contribution from non-compressor components was determined by multiplying 

count by the component 

the average component 

emission factor. The nwnber of components was subdivided 

connections/flanges, 

into valves, 

small open-ended 

components 

lines, site blowdown (BID) OELs, control valves, and other 

(such as pressure relief valves). (Tubing components were determined 

of these components are 

to be insignificant.) All 

typical fugitive components [as described 

(I)J with the exception 

in the EPA Fugitive Emissions Protocol 

manual isolation valves 

of control valves and site BID OELs. Control valves emit at a higher rate than 

Site BID OELs are 

since their packing is stressed more often as they are activated much more frequently. 

entire site to the atmosphere 

the large 

when 

diameter emergency station blowdown valves that are designed to depressure the 

the valve is opened. 

The component emission factors for gas plant components (i.e., non-compressor 

API/GRI measurement program 

related) were based on an 

as follows: 

conducted at 8 gas plants. The average facility emissions are then calculated 

where: 

N. = average count of components of type x per plant, and 

EF, =average methane emission rate per component of type x. 

b. The contribution from compressor-related components was obtained by multiplying 

fugitive components per compressor 

the average number of 

were based on 

engine by component emission factors. The component emission factors 

the GRl!lndaco measurement program conducted at I 5 compressor stations. Some compressor 

8-4 
components are unique, while others have higher leak rates than identical components elsewhere in the plant 

due to vibration. Compressors have the following types of components: 

l) Comp. BID OEL A blowdown (BID) valve to the atmosphere that can depressure the compressor 

when idle. The BID valve or the large unit block valves (depending on the 

operating status of the compressor) can act as an open-ended line that leaks at an 

extraordinarily high rate through the valve seat. The leak rate is dependent upon 

whether the compressor is pressurized (in operation or idle, pressurized) or 

depressurized (idle, depressurized). 

2) Comp. PRV The pressure relief valve (PRV) is usually installed on a compressor discharge line, 

and leaks at a higher than average rate due to vibration. 

3) Comp. Starter OEL Most compressors have a gas starter motor that turns the compressor shaft to start 

the engine. Some use natural gas as the motive force to spin the starter's turbine 

blades, and vent the discharge gas to the atmosphere. The inlet valve to the starter 

can leak and is therefore an OEL unique to compressors. 

4) Comp. Seal All compressors have a mechanical or fluid seal to minimize the flow of pressurized 

natural gas that leaks from the location where the shaft penetrates the compression 

chamber. These seals are vented to the atmosphere. Reciprocating compressors 

have sliding shaft seals while centrifugal compressors have rotating shaft seals. 

5) Miscellaneous There are many components on each compressor, such as valve covers on 

reciprocating compressor cylinders and fuel valves. 

Each compressor has one BID OEL, one PRV, and one starter OEL. Reciprocating compressors have one 

compressor seal per compression cylinder {which averaged 2.5 per engine), while centrifugal compressors 

have 1.5 seals per gas turbine. For the miscellaneous component category, there are many components per 

compressor engine, but the emission rates were minor and so were added into one lump emission factor per 

compressor for miscellaneous components. 

Ail of the compressor emission factors take several correction factors into account. First, the various phases 

of compressor operations [such as the amount of time that compressors are a) idle and depressured, b) idle 

and pressured up, or c) running]. This is actually a complex adjustment that takes into account valve position 

practices. [See Methane Emissions from the Natural Gas Industry, Volume 8: Equipment Leaks (2) for 

details.] Correction factors were also added for fraction of starter gas turbines using air instead of gas (75% 

for recip, 33% for turbines in gas processing), and fer sites with flares handling PRV or compressor BID 

discharge (approximately 11% of the compressor blowdown OELs were routed to a plant flare). 

EF DATA SOURCES: 

1. Component emission factors based on screening results from APliGRVStar program for the 

component EF's for eight gas processing plants and EPA's current default zero factors, 

correlation equations, and pegged source factors. Confidence limits derived from analysis of 

screening data by Radian in April 1995. 

2. OEL (site BID) emission factor based on results from GRI!Indaco program for compressor 

stations (June 1994). 

3. Plant component counts were based on average of 8 API!Star sites, 6 EPA/Radian sites in 1982, 

and 7 sites visited under this project in 1992. 

4. Compressor emission factors based on results from GRI!Indaco program for 15 compressor 

stations (June 1994). Compressor operating hours(% running) based on data from 3 gas 

processing company databases. 

B-5 
Average Facility Emissions for Gas Processing 

Equipment Type Component TYPe Component Average Component 

Emission Factor, Count 

Msc£'component-yr 

Gas Plant (non- Valve 1.305 1,392 

compressor related 

components) Connection 0.117 4,392 

Open-Ended Line 0.346 134 

Pressure Relief 0.859 29 

Valve 

Site Blowdown 230 2 

Open-Ended Line 

Reciprocating Compressor 2,036b-~ I 

Compressor Blowdown OpenEnded Line 

Pressure Relief 349b.< I 

Valve 

Miscellaneous 189< I 

Starter Open-Ended 1,341 0.25. 

Line 

Compressor Seal 450' 2.5 

Centrifugal Compressor 6,447b.d I 

Compressor Blowdown OpenEnded Line 

Miscellaneous 31' I 

Starter Open-Ended 1,341 0.667' 

Line 

Compressor Seal 228' 1.5 

• Values in parentheses represent 90% confidence interval. 

b Adjusted for 11.1% of compressors which have sources routed to flare. 

<Adjusted for 89.7% of time reciprocating compressors in processing are pressurized. 

d Adjusted for 43.6% of time centrifugal compressors in processing are pressurized. 

• Only 2.?/o of starters for reciprocating compressors in processing use natural gas. 

r Only 66.7% of starters for centrifugal compressors in processing use natural gas. 

B-6 

Average Equipment 

Emissions,• 

MMscf/yr 

2.89 (48%) 

4.09 (74%) 

7.75 (39%) 

. 
EF ACCURACY: a. Plant Emission Factor= ± 48% 

b. Recip. Compressor = ± 74% 

c. Turbine Compressor = ± 39% 

Basis: 

L The accuracy was propagated through the EF calculation from each terms accuracy. 90% 

confidence intervals were calculated for the sites using the t-statistic method. The 90% 

confidence intervals accounted -for variability in component count from the range in site averages 

and estimates were also provided for the component emission factors from the APVStar and 

GRL'Indaco program. 

ACTMTY FACTOR a. Plant Activity Factor= 726 plants 

b. Compressor Activity Factor = 4092 recip engines, 726 turbines 

The number of gas processing plants was detennined from the Oil and Gas Journal (3) (July 1993). 

The number and type of gas processing compressor engines were detennined from eleven gas plant site visits. 

The average ratio of compressors per plant was multiplied by the total number of plants, 726, to obtain these 

estimates. [See Methane Emissions from the Natural Gas Industry, Volume 5: Activity Factors (4) for 

details.] 

AF DATA SOURCES: Oil and Gas Journal (July !993) (3) 

AF ACCURACY: a. Plant Activity Factor: ± 2% 

b. Compressor Activity Factor: Recip engines = ± 48~o; Turbines = ± 77% 

Basis: 

I. An accurate count of gas plants by the Oil and Gas Journal (3) is very likely since counting 

such large, discreet facilities should be straightforward. The ± 2% was assigned by engineering 

judgement. 

2. The compressor count accuracy was detennined by statistical analysis of the "compressor per 

site" averages for 11 gas plant sites. 

3. A check was perfonned to estimate whether gas plant sites visited for compressor counts were 

representative of industry average. Based on Oil and Gas Journal (3), the average plant capacity 

was 88.3 1\tlMscfd and throughput was 51.2 MMscf!d. Site visit data averaged 271 MMscfd and 

throughput was 182 MMscf/d, suggesting that plants visited were larger than average. However, 

further investigation revealed that there is no correlation between plant capacity/throughput and 

number of compressors (The plant visited with the most compressors had 20 engines with 20,000 

HP and a low throughput of 56 MNl:scfd, while the plant with the highest current operating rate 

of 750 MMscfd had only one compressor at 17,500 HP.) 

B-7 
ANNUAL EMISSIONS' (24.45 Bscfi'yr ± 16.7 Bscfi'yr) 

The annual emissions were detennined by multiplying 

population of 

the average equipment/facility emissions by the 

equipment in the segment. 

Category Emission Activity Emission Uncertainty 

'""'' 

Gas 

plants 

processing 2.89 MMscflyr 726 

'""'' 

plants 2.1 

-

Bscli'yr 48% 

methane methane 

Recip Comp 4.09 MMscflyr 4092 tecip 16.7 Bscflyr 95% 

methane methane 

Tutbine Comp 7.15 MMscflyr 726 turbine 5.6 Bscflyr 91% 

methane m-o 

TOTAL 24.4 Bscflyr 68% 

methane 

REFERENCES 

l. 

Environmental 

Hausle, K.J., Protocol for Fugitive Leak Emission Estimates, Final Report, EPA-453/R-93-026, U.S. 

Protection Agency, June 1993. * 

2. Hummel, 

Volume 8: 

K.E., 

Equipment 

L.M. Campbell, and M.R. Harrison. Methane Emissions from the Natwal Gas industry, 

Institute 

Leaks, Final Report, GRI-94/0257.25 and EPA-600/R-96-0SOh, Gas Research 

and U.S. Environmental Protection Agency, June 1996. 

3. Oil and Gas Journal. l992 Worldwide Gas Processing Survey Database, 1993. 

4. 

Report, 

Stapper, 

GRI-94/0257.22 

B.E. Methane Emissions from the Natural Gas Industry, Volume 5: Activity Factors, Final 

Protection 

and EPA-6001R-96-080e, Gas Research Institute and U.S. Environmental 

Agency, June 1996. 

(*)NTIS FB>c-229219. 

B·8 
SOURCES: 

COMPONENTS: 

OPERATING MODE: 

EMISSION TYPE: 

ANNUAL EMISSIONS: 

BACKGROUND: 

GP-2 

PROCESSING SOURCE SHEET 

Glycol Dehydrators 

Reboiler Vent 

Normal Operation 

Unsteady, Vented 

1.05 Bscf ± 208% 

Glycol dehydrators remove water from a gas stream by contacting the gas with glycol and then driving the 

water from the glycol and into the atmosphere. The glycol also absorbs a small amount of methane, and 

some methane can be driven off to the atmosphere through the reboiler vent. 

EMISSION FACTOR: (121.55 sc£!MMscf ± 201.96%) 

A thennodynamic computer simulation was used to determine the most important emission-affecting variables 

for dehydrators. The variables are: (gas throughput, existence of a flash tank, existence of stripping gas, 

existence of a gas-assisted pump, existence of vent controls routed to a burner). 1hroughput, since its effect 

is linear, is handled by establishing an emission rate per gas throughput. Emission rates per throughput are 

then established for the other important emission affecting characteristics. Gas driven pumps are ignored here 

and handled in a separate source analysis. The emission factor is then: 

EF = [ ( FFT x EFFT) + ( Fm x EFm) + ( FsG x EF50 ) J x Fl'>'VC x OC 

EF ~ [ (0.667 X 3.57) + (0.333 X 175.10) + (0.111 X 670) l X 0.900 X 1.0 

F rr = Fraction of the population WITH flash tanks 

0.667 ± 10.13% 

oc 

Fraction of the population WITHOUT flash tanks= 1-Frr 

0.333 ± 20.12% 

Fraction of the population WITH stripping gas 

0.111 ± 186% 

Fraction of the population WITHOUT com busted vent controls 

0.90 ± 10% 

Total CH~ emission rate per 1 MMscf throughput for dehydrator that has a flash 

tank 

3.57 (+102% I -58%) 

Total CH4 emission rate per I MMscf throughput for dehydrator that does NOT 

have a flash tank 

175.10 (+101% /-50%) 

Incremental emission rate per I MI\.1scfd throughput for dehydrator that has stripping 

gas 

670 (+40% I -60%) 

Overcirculation factor for glycol-number of times the industry rule-of-thumb of 3 

gallons glycoL'lb water 

1.0 ± 0% 

B-9 
EF DATA SOURCES' 

I. Methane Emissions from the Natural Gas Industry, Volume 14: Glycol Dehydrators (I) 

establishes emission affecting characteristics of dehydrators. 

2. Site visit data establish the FsG and FNVC for multiple sites (7 PROC sites with dehydrators). 

3. TMOGA/GPA survey of 207 gas plant dehydrators established F3p and F"n and TP for 

dehydrators for the processing segment. 

5. 

4. 

Sampling 

ASPEN computer simulations were used to detennine EF,p, and EFND from the dehydrator vent. 

data from the GRI Glycol Dehydrator Sampling and Analytical Program for one 

dehydrator 

Methods 

was used to determine EFsv (Glycol Dehydrator Emissions: Sampling and Analytical 

of 

and Estimation- Techniques) (2). The upper bound was calculated by assuming that all 

the measured noncondensable vent gas was due to stripping gas that was 100% methane. The 

lower bound was calculated as the rule·of.thumb stripping gas r-ate recommended by a glycol 

dehydrator manufacturer. 

EF ACCURACY 121.55 sc:t7Mlvfscf ± 201.96% 

Basis: 

The accuracy is rigorously propagated through the EF calculation from each tenn's accuracy: 

I. ASPEN has been demonstrated to match actual dehydrators within ± 20% within the calculated 

confidence intervals obtained from site data. 

2. Individual EF confidence intervals were calculated from the other data based upon the spread of 

the II site averages. 

ACTIVITY FACI'OR: (8.63 Tscf/year gas throughput in the gas pocessing segment) 

opposed 

The glycol 

to 

dehydrator 

dzy bed 

throughput is estimated from the fraction of gas processed by refiigerated processes (as 

Journal 

dehydration for cryogenic processes). The estimate was obtained from the Oil & Gas 

dehydrated 

(3) annual Gas Processing Survey. Of a total of 17.44 Tscf, 8.63 Tscfwere detennined to be 

by glycol. 

AF ACCURACY: 8.63 Tscflyear ± 22.45% 

Basis: 

l. Uncertainty based on estimate of confidence limits for Oil and Gas Journal survey. 

AF DATA SOURCES' 

1. Oil & Gas Journal (3) annual Gas Processing Survey. 

ANNUAL METHANE EMISSIONS: (1.0490 Bsc( ± 208.20%) 

The annual methane emissions were detennined by multiplying the dehydrator emission 

factor. 

factor by the activity 

REFERENCES 

I. 

Report, 

Myers, D.B. 

GR1·94/0257.31 

Methane Emissions from the Natural Gas Industry, Volume /4: Glycol Dehydrators, Final 

and EPA.ti001R·96-080n. Gas Research Institute and U.S. Environmental 

Protection Agency, June 1996. 

2. Radian 

Techniques. 

Corporation. Glycol Dehydrator Emissions: Sampling and Analytical Methods and Estimation 

GRI-94/0324, Gas Research Institute, Chicago, IL, March 1995. 

3. Oil & Gas Journal. 1992 Worldwide Gas Processing Survey Database, 1993. 

B-10 
SOURCES' 

OPERATING MODE: 

EMISSION TYPE' 

ANNUAL EMISSIONS' 

BACKGROUND, 

GP-3 

PROCESSING SOURCE SHEET 

Acid Gas Removal (AGR} Units 

Nanna! Operation 

Unsteady, Vented 

0.82 Bscf ± 109% 

AGR units remove acid gas (H2S and C02) from a natural gas stream by contacting the gas with material 

(usually amines) and then driving the absorbed components from the solvent. The amines can also absorb a 

small amount of methane, and some methane can be driven off to the annosphere through the reboiler vent to 

the atmosphere. 

EMISSION FACTOR: (6083 scfd/avg AGR) 

AGRs were assumed to have an absorption of methane similar to water, since the typical AGR solution 

contains over 50% water. The methane emissions were calculated using an ASPEN PLUS process simulation 

based on an actual DEA unit (l). AGRs were assumed to have no three·phase flash tanks nor stripping gas. 

The average AGR throughput {MMscfd) was determined from a 1982 API study, and multiplied times the 

emission rate (CH/MMscfd). The emission factor is then: 

EF = EFNT X FNVC X TP 

EFNT = 

EF DATA SOURCES' 

·Fraction of the AGRs that do vent the waste stream 

0.18± 10% 

Average throughput for AGRs (M:Mscfd) 

35.02 ± 20% 

Total "C~ scfd emission rate per I MMscfd throughput~ for an AGR 

965 ± 100% 

1. ASPEN PLUS process simulations based on an actual DEA unit were used to detennine EFNT 

from the reboiler vent. It was assumed that AGRs have an absorption of methane similar to 

water. 

2. I 982 API Survey, quoted in Investigation of US Natural Gas Reserve Demographics and Gas 

Treatment Processes, shows 287 AGR units, with a cumulative throughput of 10052 M?\.1scfd (2). 

The survey also shows split of AGR vent dispositions: 50% burned, 32% to sulfur recover, and 

18% vented. 

EF ACCURACY: 6083 ± 104.92% 

Basis: 

I. The accuracy is based upon engineering judgement that the methane solubility in AGR solutions 

is similar to the solubility in water. 
ACTIVITY FACTOR: (371 activ.e AGR units in the U.S.) 

The 

factor 

number 

was extracted 

of AGR units in the U.S. have all been assumed to be in the processing segment. The activity 

from the Purvin & Gertz survey. 

AF DATA SOURCES: 

l. Purvin & Gertz, Business Characteristics of the Natural Gas Conditioning Industry (3), 1993. 

AF ACCURACY: 371 ± 20% 

Basis: 

!. The accuracy is based upon engineering 

(± 5%), but 

judgement. The survey should have excellent accuracy 

the upper bound at 90% confidence was revised upward to 20% to be conservative. 

ANNUAL METHANE EMISSIONS: (0.8237 Bscf ± 108.85%) 

by 

The 

the 

annual 

population 

methane 

of AGRs 

emissions were detem:ined by multiplying an emission factor for an average dehydrator 

in the segment. 

REFERENCES 

l. 

Report, 

Myers, D. 

GRI-94/0257.31 

Methane Emissions from the Natural Gas Industry, Volume /4: Glycol Dehydrators, Final 

Protection Agency, 

and EPA--600/R-96-080n. Gas Research Institute and U.S. Environmental 

June !996. 

2. Radian Corporation. 

Processes, Topical 

Irrvestigation of U.S. Natural Gas Reserve Demographics and Gas Treatment 

Report, Gas Research Institute, January 1991. 

3. Tannehill, C.C. and C. Galvin. Business Characteristics of the Natural Gas Conditioning 

Topical Report. GRJ 

Industry, 

Contract 5088-221-1753, Gas Research Institute, May 1993. 

B-12 
SOURCES: 

OPERATING MODE: 

EMISSION TYPE: 

ANNUAL EMISSIONS: 

BACKGROUND: 

GP-4 

pROCESSING SOURCE SHEET 

Ail Equipment (vessels, compressors, pig traps, manifolds) 

Maintenance 

Unsteady, Vented 

3.0 Bscf ± 262% 

Slowdown is the direct, intentional venting to the atmosphere of gas contained inside operating equipment. 

The gas is released to provide a safer working environment for maintenance activities around or inside the 

equipment. 

EMISSION FACTOR: 4,060 ± 262% Msc[lgas plant 

(Corrected for tbe gas processing methane composition of 87 mol%) 

Slowdowns at gas plants consist primarily of the foJlowing types of events: compressor blowdown, 

compressor starts, pipeline pig receiver blowdown, and miscellaneous vessel blowdown. Due to the 

similarities in station blowdown practices between the gas processing and transmission segments, transmission 

station company tracked data were applied to gas plants. Blowdown volwnes per station were ·provided based 

on company tracked data from 9 transmission companies. 

EF DATA SOURCES: 

l. The Methane Emissions from the Natural Gas Industry, Volume 7: Blow and Purge Activities (I) 

establishes emission affecting characteristics of blowdown practices. 

2. Company tracked data were provided from 9 transmission companies representing a total of 328 

stations. 

EF ACCURACY: ± 262% 

Basis: 

The accuracy was calculated from the spread of the company tracked data. A 90% confidence interval 

is calculated for the data using the method presented in Methane Emissions from the Natural Gas 

Industry, Volume 4: Statistical Methodology (2). 

ACTIVITY FACTOR 726 ± 2% gas plants 

AF DATA SOURCES: 

I. The number of gas processing plants for 1992 is repeated in the Oil and Gas Journal (3). 

AF ACCliRACYo 

Basis: 

An accurate count of gas plants by the Oil and Gas Journal is very likely since counting such large, 

discrete facilities should be straightforward. The ± 2% was assigned by engineering judgement. 

B-13 
ANNUAL METHANE EMISSIONS: 2.95 ± 262 Bscf 

(population). 

The annual methane 

Each 

emissions were detennined by multiplying an emission factor by the activity factor 

segment of 87 mol%. 

emission factor was adjusted for the average methane content in the gas processing 

REFERENCES 

l. 

and 

Shires, 

Purge 

T.M. 

ActNities, 

and M.R. 

Final 

Harrison. 

Repon, 

Methane Emissions from the Natural Gas Industry, Volume 7: Blow 

and U.S. Environmental 

GRI-94/0257.24 and EPA-600/R-96-080g, Gas Research Instirute 

Protection Agency, June 1996. 

2. Williamson. 

Volume 4: Statistical 

H.J., M.B. 

Methodology, 

Hall, and M.R. Harrison. Methane Emissions from the Natural Gas Industry, 

Research 

Final Report, GRJ-94/0257.21 and EPA-600/R-96-080d. Gas 

Institute and U.S. Environmental Protection Agency, June 1996. 

3. Bell, L. "Worldwide Gas Processing," Oil and Gas Journal, July 12, 1993, p. 55. 
SOURCES: 

COMPONENTS: 

OPERATING MODE: 

EMISSION TYPE: 

ANNUAL EMISSIONS: 

BACKGROUND: 

GP-5 

PROCESSING SOURCE SHEET 

Glycol Dehydrators 

Gas Assisted Kimray Pumps 

Nanna! Operation 

Unsteady, Vented 

0.170 scf ± 228% 

Most glycol circulation pumps in gas plants are electric. However, some gas driven pumps do exist. Gas· 

assisted Kiinray glycol circulation pumps use a mixed phase of wet glycol liquid and absorber gas to drive 

pistons that pump dry (lean) glycol circulation. Unlike chemical injection pumps which vent the driving gas 

directly to the atmosphere, Klmray pumps pass the driving gas along with the wet glycol to the reboiler. In 

the reboiler the methane is driven off into the vent line. Depending on dehydrator vent gas dispositions, the 

methane may be vented to the atmosphere or controlled and burned. 

EMISSION FACI'OR: (177.75 s<:f CHJMMscf gas processed) 

The average glycol pump gas emission factor was determined by an equation describing the gas generation 

and disposition of gas from the pump. The disposition of gas generated by the pump depends upon the 

existence of a flash tank and vent controls. Measured and estimated parameters were input into the equation. 

In general, the emission factor for a gas-assisted pump was determined by the following equation: 

= PGU X CR X WR X oc X Fl\'T X Fl>.'VC 

'=' (3.73 scflgal) x (3.0 gaVlb H2

0) x (53 lb H20/MMscf) x (LO) x (0.333) x (0.900) 

= 177.75 scf CH/MMscf gas ± 56.85% 

EF DATA SOURCES' 

I. Equation I, i.e. the effects of operating variables on emissions, was defmed in Methane Emissions from 

the Natural Gas Industry, Volume !5: Gas-Assisted Glycol Pumps (1). 

2. CR = glycol circulation ratio = 3.0 gal glycoV!b water± 33.3%. 

3. WR = water removed from wet gas = 53 lb water!MMscf gas ± 20%. For inlet gas stream of 95°F and 

800 psig dried to 7 lb water/lvfio..1scf gas. 

4. OC =factor to account for overcirculation of glycol = 1.0 ± 0%. 

5. FNT = fraction of dehydrators without flash tanks = 0.333 ± 20.12%. 

6. FNvc =fraction of ' the dehydrators without combustion vent controls= 0.900 ± 10%. 

7. PGU =pump gas usage= 3.73 scf CHigal glycol± 30%. Determined by multiplying the volume of 

gas used by high-pressure pump models by a typical fraction of methane in the natural gas {83 mole%). 

B-15 
PGU = 4.49 scflgallon x 83% 

= 3.73 scflgallon ± 30% 

EF ACCURACY: (± 56.85%) 

Basis: 

I. Assumption: The manufacturer's data and ranges are relatively accurate (±30%). 

2. Dehydrator characteristics based on site visit observations and TMOGA survey.8 

ACTIVITY FACTOR: (0.9579 Tsc(lyear in the processing segment witb gas-assisted pumps) 

The volume of gas processed through dehydrators using gas-assisted pumps was calculated from the total 

throughput for gas processing dehydrators and the fraction of dehydrators using gas-assisted pumps 

detennined from site visits. The activity factor is then: 

AF ~ (fraction of dehydrators with gas-assisted pumps) x (throughput for gas processing 

dehydrators) 

= (0.111 ± 186%) x (8.63 Tscf/year ± 22.4%) 

= 0.9579 Tsc£'year ± 191.95% 

AF DATA SOURCES' 

I. See Methane Emissions from the Natural Gas Industry, Volume 14: Glycol Dehydrators (2) for 

an explanation of processing dehydrator throughput (8.63 Tscf/year). See the Methane Emissions 

from the Natural Gas Industry, Volume 5: Activity Factors (3) for more details. 

2. Fraction of dehydrators using gas-assisted pumps came from data from site visits. 

AF ACCURACY: (± 192%) 

Basis: 

Calculated from confidence limits of gas throughput and fraction of dehydrators by standard error 

propagation analysis. 

ANNUAL METHAA"'E EMISSIONS: (0.1703 Bscf ± 228%) 

The annual methane emissions were determined by multiplying an emission factor (scf CH/MMscf) by the 

total throughput for processing dehydrators using gas-assisted pumps. 

(177.75 scf!MMscf) x (0.9579 Tscf) "'0.1703 Bscf (± 228.000/!1) 

REFERENCES 

I. Myers, D.B. and M.R. Harrison. Methane Emissions .from the Natural Gas Industry, Volume 15: GasAssisted Glycol Pumps. Final Report, GRJ-94/0257.33 and EPA-600/R-96-0SOo. Gas Research 

Institute and U.S. Environmental Protection Agency, June !996. 

2. Myers, D.B. Methane Emissions from the Natural Gas Industry, Volume 14: Glycol Dehydrators. 

Final Report, GRJ-94/0257.32 and EPA-600/R-96-0SOn. Gas Research Institute and U.S. 

Environmental Protection Agency, June 1996. 

B-16 
3. 

Report, 

Stapper, 

GRl-94/0257.22 

B.E. Methane Emissions from the Natural Gas Industry, Volume 5: Activity Factors. Final 

and EPA-600/R-96-0&0e. Gas Research Institute and U.S. Environmental 

Protection Agency, June 1996. 
SOURCES' 

COMPONENTS, 

OPERATING MODE' 

EMISSION TYPE' 

ANNUAL EMISSIONS' 

BACKGROUND' 

GP-6 

GAS PROCESSING SOURCE SHEET 

Various Equipment (vessels, compressors, piping) 

Pneumatic Devices 

Nonnal Operation 

Unsteady, Vented 

0.1 Bscf± 133% 

plant, 

The gas 

although 

processing 

some 

segment 

devices 

uses 

may 

compressed air to power the majority of the pneumatic devices within the 

controllers on 

be powered by natural gas. Many plants use gas driven pneumatic 

isolation valves for emergency shut-down or maintenance work. 

segment 

The same 

-

type 

continuous 

of devices 

bleed 

used in the transmission segment are also commonly used in the gas processing 

throttling/regulating valves, displacement operators, and turbine operators. 

EMISSION FACTOR: 165 Msc:f per average plant ± 133% 

(This was adjusted for the gas processing methane fraction of natural gas at 87 moJO/o.) 

The average device gas emission factor was detennined 

emission rates and device 

from a combination of vendor infonnation on device 

counts from several sites. The average emission factor was calculated using the 

following equation: 

n 

EF .:KX avg.pncunt .deviCe 

L (Annual Site Emissions, scf Natural Gas) 

i =I 

x % Methane 

K 

n 

: 

n 

fraction of sites that use natural gas rather than air (0.56 ± 59%) 

nwnber of sites operating with natural gas 

data 

Each 

was 

tenn 

then 

in this 

adjusted 

equation 

based 

was 

on 

determined from site specific information. The summation of the site specific 

sites surveyed. The site 

the number of sites with gas operated devices versus the total number of 

results are shown in the following table. 
Site 

2 

3 

4 

5 

6 

7 

8 

9 

Device Type 

Throttling (Fisher) 

Isolation (Fisher) 

Arr 

Isolation (Turbine) 

Isolation (Rotary Vane) 

Isolation 

(Turbine & Rotary Vane) 

Air 

Arr 

Arr 

Nnmber 

of Devices 

2 

3 

25 

7 

18 

16 

Annual 

Operations/ Displacement/ Displacement/ 

Year Device, scf Site, scr 

Continuous 497,584 995,168 ± 29% 

12 214,675 644,025 ± 29% 

780 19,500 ± 112% 

12 48 1,206 ± 49% 

I 

I 3,376 44,115 ± 68% 

12 

TOTAL 

1,704 Mscf±2l% 

Average (for gas sites) 341 Mscf ± 103% 

EF DATA SOURCES: 

I. Methane Emissions from the Natural Gas industry, Volume 12: Pneumatic Devices (I) 

establishes the important emission-affecting characteristics. 

2. ~ite visit device counts establish the number of continuous bleed devices, turbine operators, and 

displacement operators for each site. 

3. The emission factor for continuous bleed devices was estimated using data provided by one site 

and measurements for transmission pneumatic devices. 

4. Gas usages for the displacement operators were provided by Pantex Valve Actuators and Systems 

and Shafer Valve Operating Systems. The number of devices, supply gas pressure, and operating 

frequency were based on site information. 

5. Gas usages for the turbine operators were provided by Lirnitorque Corp. Operating duration, 

frequency, and supply gas pressure were based on site information. 

EF ACCURACY: 

Basis: 

!. 

2. 

EF accuracy is based on error propagation from the spread of data for the nine sites visited. 

It was assumed that the manufacturers' data are completely accurate. 

ACTIVITY FACTOR: 726 gas processing plants ± 2% 

The activity factor for the gas processing segment was taken from Oil and Gas Journal (2) published 

information from the year 1992. 

B-19 
AF DATA SOURCES: 

l. The number of gas processing plants was taken from the Oil and Gas Journal (2). 

AF PRECISION: 

Basis: 

I. AF accuracy is based on engineering judgement. 

ANNUAL METHANE EMISSIONS: 0.12 Bscf ± 133% 

methane 

The annual emissions were determined by multiplying an average site emission factor (adjusted for the 

composition) by the total number of gas processing sites. 

165 Mscflsite x 726 sites = 0.12 Bscf 

REFERENCES 

I. 

Pneumatic 

Shites, T.M. 

Devices. 

and M.R. Harrison. Methane Emissions from the Natural Gas Industry, Volume 12: 

U.S. Environmental 

Final Report, GRI-94/0257.29 and EPA-600/R-96-0801, Gas ResearCh Institute and 

Protection Agency, June 1996. 

2. Bell, L. "Worldwide Gas Processing," Oil and Gas Journal, July 12, 1993, p. 55. 

B-20 
APPENDIX C 

Transmission/Storage Source Sheets 

C-1 
APPENDIX C 

Transmission/Storage Source Sheets 

T-1 - Fugitive Emissions (Transmission) C-4 

T-2 - Meter and Regulating Station Emissions .................. C-9 

T-3- Pipeline Leaks ................................... C-13 

T -4 - Pneumatic Devices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C-16 

T-5 - Maintenance Venting .............................. C-19 

T"6 - Glycol Dehydrator Vents . . . . . . . . . . . . . . . . . . . . . . . . . . . C-22 

S-1 - Fugitive Emissions (Storage Facilities) . . . . . . . . . . . . . . . . . . C-24 

S-2 - Glycol Dehydrators (Storage Facilities) . . . . . . . . . . . . . . . . . C-29 

C-2 
TRANSMISSION/STORAGE SOURCE SHEETS 

This section contains the specific source sheets for the transmission and storage segment of 

the natural gas industry. The following table serves as a guide for fmding sheets in this 

section. The cells in the table give the sheet number (T-1, T-2, etc.) of the source sheet. 

The rows defme the equipment covered, while the columns define the emission type. A 

category with no sheet nwnber means that the emissions from that area were determined to 

be zero or negligibly small. The label for each source sheet is shown at the top of the 

cover page for that sheet 

TABLE OF OPERATING MODE, 

CONTENTS EMISSION TYPE (Fugitive, Vente~· or Combusted) 

Start Up Nonna! Operations Maintenance Upsets Mishaps 

EQUIPMENT' v c F v c v c v c v 

Entire Transmission T-I T-4 T-5 T-5 

Compressor Stations 

Trans. Comp. Station T-I T-4, T-5 T-5 

Dehydrators T-6 

Trans. Comp. Station T-I T-4 T-5 T-5 

Vessels 

Trans. Comp. Station T-I T-4 P-I T-5 T-5 

Compressors 

Transmission Pipelines T-3 T-4 T-5 T-5 

Trans. M&R Stations T-2 T-2 T-5 T-5 

Entire Storage Stations S-I T-4 T-5 T-5 

Stor. Sta. Wells S-I T-4 T-5 T-5 

Stor. Sta. Compressors S-I T-4 P-I T-5 T-5 

Stor. Sta. Vessels S-I T-4 T-5 T-5 

Stor. Sta. Dehydrators S-I T-4, T-5 T-5 

S-2 

C-3 
SOURCES' 

OPERATING MODE' 

EMISSION TYPE' 

ANNUAL EMISSIONS' 

BACKGROUND' 

T-1 

TRANSMISSION SOURCE SHEET 

Compressor Stations 

Nonnal Operation 

Steady and Unsteady, fugitive 

50.7 Bscf ± 52% 

Equipment leaks are typically low-level, unintentional 

surfaces of above-ground 

losses of process fluid (gas or liquid) from the sealed 

process equipment. Equipment components 

and other connectors, pump 

that tend to leak include valves, flanges 

seals, compressor seals, pressure relief valves, open-ended 

connections. These 

lines, and sampling 

components represent mechanical 

to wear and develop 

joints, seals, and rotating surfaces, which in time tend 

leaks. 

EMISSION FACTOR: a. Station = 3.2 MMscf/yr methane per plant 

b. Recip. Compressor = 5.55 MMscf/yr methane per recip 

c. Turbine Compressor :: 11.1 MMscflyr methane per turbine 

The average fugitive emission rate for transmission compressor stations was determined 

two parts: a) station components 

to be composed of 

(excluding compressor-related 

components. 

components); and b) compressor-related 

Fugitives from the compressor-related 

components in 

components have much higher emission factors than 

most of the larger 

the 

emissions 

rest of the facility. This is due in part to the high vibration that compressors generate, but 

are due to unique compressor components, as explained below. 

a. The contribution from non-compressor components was determined by multiplying 

count by the component 

the average component 

emission factor. The number of components was subdivided 

connections/flanges, 

into valves, 

small open-ended 

components 

lines, site blowdown (BID) OELs, control valves, and other 

(such as pressure relief valves). (Tubing components were determined 

of these components are 

to be insignificant.) All 

with the exception of 

typical fugitive components (as described in the EPA Fugitive Emissions Protocol) 

isolation valves since 

control valves and site BID OELs. Control valves emit at a higher rate than manual 

BID OELs are the 

their packing is stressed more often as they are activated much more frequently. Site 

large diameter emergency station blowdown valves that are designed to depressure 

entire site to the atmosphere when 

the 

the valve is opened. 

conducted 

The component 

at 6 compressor 

emission factors for station components were based on a GRI!Indaco measurement program 

stations. The average facility emissiQns are then calculated as follows: 

where: 

N, =average count of components of type x per plant, and 

EF, =average methane emission rate per component of type x. 

b. The contribution from compressor-related components was obtained by multiplying 

fugitive components per 

the average number of 

were based on the GRI/Indaco 

compressor 

measurement 

engine by the component emission factors. The component emission factors 

components are unique, while 

program conducted at 15 compressor stations. Some compressor 

others have higher leak rates than identical components elsewhere 

to vibration. Compressors 

in the plant due 

have the following types of components: 

C-4 
l) Comp. BID OEL A blowdown (BID) valve to the atmosphere that can depressure the compressor when 

idle. The BID valve or the large unit block valves (depending on the operating starus 

of the compressor) can act as an open-ended line that leaks at an extraordlnarily high 

rate through the valve seat. The leak rate is dependent upon whether the compressor 

is pressurized (in operation or idle, pressurized) or depressurized (idle, depressurized). 

2) Comp. PRV The pressure relief valve (PRV) is usually installed on a compressor discharge line and 

leaks at a higher than average rate due to vibration. 

3) Comp. Starter OEL Most compressors have a gas starter motor that turns the compressor shaft to stan the 

engine. Some use natural gas as the motive force to spin the staner's turbine blades 

and vent the discharge gas to the atmosphere. The inlet valve to the starter can leak 

and is therefore an OEL unique to compressors. 

4) Comp. Seal All compressors have a mechanical or fluid seal to minimize the flow of pressurized 

natural gas that leaks from the location where the shaft penetrates the compression 

chamber. These seals are vented to the atmosphere. Reciprocating compressors have 

sliding shaft seals while centrifugal compressors have rotating shaft seals. 

5) Miscellaneous There are many components on each compressor, such as valve covers on 

reciprocating compressor cylinders and fuel valves. 

Each compressor has one BID O:EL, one PRV, and one starter OEL. Reciprocating compressors have one 

compressor seal per compression cylinder (which averaged 3.3 per engine), while centrifugal compressors have 

1.5 seals per gas turbine. For the miscellaneous component category, there are many components per 

compressor engine, but the emission rates were minor and so were added into one lump emission factor per 

compressor for miscellaneous components. 

All of the compressor emission factors take several correction factors into account. First, the various phases of 

compressor operations (such as the amount of time that compressors are a) idle and depressured, b) idle and 

pressured up, or c) running). This is actually a complex adjustment that takes into account valve position 

practices. [See Methane Emissions from the Natural Gas Industry, Volume 8: Equipment Leaks (1) for more 

details.} Correction factors were also added for fraction of starter gas turbines using air instead of gas (100% 

for recip, 0% for rurbines in Transmission). 

EF DATA SOURCES: 

I. Component emission factors based on results from GRI/Indaco program for the component EF's for 

6 transmission compressor stations (June 1994). Adjustment of station EF is to account for data 

obtained from one interstate transmission pipeline company that was found to have higher emissions 

than average. 

2. Plant component counts were based on an average of 8 Indaco sites in 1994 and 9 sites visited 

under this project in 1993, plus 7 industry sites. 

3. Compressor emission factors based on results from GRI!Indaco program for 15 compressor stations 

(June 1994). Compressor operating hours(% running) based on data from FERC database, GRI 

TRANSDAT (2) database, and data supplied by one large interstate transmission pipeline company. 

4. Fraction of methane (93.4 mol%) based on data from GRI TRANSDA T database. 

C-5 
Average Facility Emissions for Gas Transmission 

Equipment Type Component Type Component Average Average Equipment 

Emission Factor, Component Emissions: 

Mscf/component~yr Count MMscf/yr 

Compressor Station Valve 0.867 

(non-compressor 

673 3.01 (102%) 

related components) 

{Note: 3.2 MMscf/yr 

Control Valve 8.0 31 used in national 

emission estimate)" 

Connection 0.147 3,068 

OEL 11.2 51 

PRV 6.2 14 

Site BID OEL 264 4 

Reciprocating Compressor BID 3,683 

Compressor OEL I 5.55 {65%) 

PRV 372c I 

Miscellaneous 180' I 

Compressor Staner d d 

OEL 

Compressor Seal 396' 3.3 

Centrifugal Compressor BID 9,352 

Compressor OEL I 11.1 (34%) 

Miscellaneous 18' I 

Compressor Starter 1,440 I 

OEL 

Compressor Seal 165° 1.5 

a Values in parentheses represent 90% confidence interval. 

"Adjusted 

b Adjusted 

for 

for 

the 

data 

fraction 

received from one company that was not considered representative of national average. 

of time the compressor 

centrifugal 

is pressurized (79.1% and 24.2% for reciprocating and 

compressors, respectively). 

d Reciprocating compressor starters were assumed to use compressed air or electricity instead of naroral. gas. 

C-6 
EF ACCURACY: a. Station = 102% 

b. Recip. Compr~or = 65% 

c. Turbine Compressor = 34% 

Basis: 

Rigorous propagation of error from the spread of thousands of individual measurements taken by Indaco. 

ACTIVITY FACTOR: a. Station Activity Factor = 1700 stations 

b. Compressor Activity Factor = 6799 recip engines, 681 turbines 

AF DATA SOURCES' 

I. 1992 FERC Form 2 responses accounted for 70% of national transmission pipeline mileage. Total 

station count extrapolated using national total transmission mileage of 276,900 miles from A.G.A. 

Gas Facts (3). 

2. Compressor engine count based on GRI TRANSDAT ~industry database" with adjustments for total 

industry horsepower. Transmission compressor station counts were split from storage based upon 

storage station site visit data and Gas Facts (3) data on storage stations. Added 0.2% to recip 

count account for electric motor drivers. 

AF ACCURACY, a. Station Activity Factor: ± 10% 

b. Compressor Activity Factor: Recip engines = ± 17 %; Turbines = ± 26% 

Basis: 

1. FERC Form 2 data have a high percentage (70%) of all transmission companies. Therefore a 

national extrapolation should not add much error. This 10% figure was assigned based on 

engineering judgement. 

2. The compressor count accuracy was assigned based upon the propagation from: a) rigorous error 

propagation for the 8 storage station ·compressor/station~ averages; and b) engineering judgement 

assignment of± 10% error to the large GRI TRANSDAT database. 

ANNUAL METHANE EMISSIONS' (50.73 Bscf/yr ± 26.3 Bscflyr) 

The annual emissions were determined by multiplying the average facility/equipment emissions by the population 

of equipment in the segment. 

Category Emission Factor Activity Factor Emission Rate Uncertainty 

Station 3.2 MMscflyr 1700 stations 5.4 Bscffyr 103% 

CH4 CH4 

Rccip Comp 5.55 MMscf/yr 6799 rccip 37. 8 Bscflyr 68% 

CH4 CH4 

Turbin= Comp I 1.1 MMscf/yr 681 rurbine 7.5 Bscflyr 44% 

CH4 CH4 

TOTAL 50.7 Bscflyr ,. CH4 

C-7 
REFERENCES 

l. Hummel, K.E., L.M. Campbell, and M.R. Harrison. Methane Emissions 

Volume 8: Equipment Leaks, 

from the Natural Gas Industry, 

Institute and U.S. Environmental 

Final Repon, GRI-94/0257.25 and EPA-600/R-96..080h, Gas Research 

Protection Agency, June 1996. 

2. 

npb 

Biederman, 

Associates 

N. 

with 

GRl 

Tom 

TRANSDAT Database: Compressor Module. (prepared for Gas Research Institute) 

Joycxe and Associar:es, Chicago, IL, August 1991. · 

3. American Gas Association, Gas Facts. Arlington, VA, 1992. 

C-8 
T-2 

TRMSMJSSION SOURCE SHEET 

SOURCES: 

OPERATING MODE: 

EMISSION TYPE: 

ANNUAL EMISSIONS: 

BACKGROUND: 

Meter and Regulating Stations 

Normal Operation 

Steady, Fugitive, and Vented 

4.5 Bscf ± 835% 

Metering/pressure 

a custody 

regulating (M&PR) stations are located throughout the transmission network to meter gas where 

intermittent 

transfer 

emissions 

occurs. Emissions from M&PR include continuous fugitive losses and also may include 

emissions are 

from pneumatic devices such as pressure regulators, if they exist at the station. Fugitive 

types include various 

relatively low-level emissions of process fluid (gas or liquid) from process equipment. Specific source 

joints, seals, 

finings such as valves, flanges, or compressor seals. These components represent mechanlcal 

and rotating surfaces, which in time tend to wear and develop leaks. 

for 

The 

custody 

transmission segment contains many "metering and regulation stations" (M&R stations) where flow is measured 

companies count 

transfer or system controL The table below shows the types of M&R stations that transmission 

already been counted 

in their system. Most of the meter station types associated with the transmission system have 

distribution). 

in other segment calculations (receipt stations in production and delivery stations in 

industrial 

Only three 

sales 

types remain to be accounted for under the transmission system M&PR stations: l) farm taps, 2) direct 

from the transmission pipeline, and 3) transmission company-to-transmission 

stations. 

company transfer 

Transmission Meter and Regulation Station Types 

GENERAL SPECIF!C TYPE 

STATION 

STATION TECHNICAL ACCOUNTED FOR IN 

SERVICE 

DESCRIPTION OTHER SEGMENT 

SQ{JRCE SHEETS? 

THE 

RECEIPT TO 1 . Gathering meters at produc- Meter Only Yes, P-2 

tion sites 

SYSTEM, 

SYSTEM, 

INTER- 2. Meters at compressor Meter Only Yes, T-1 

stations 

TO 

DELIVERY 

CUS3. City Gate M&R stations Meter and Regulation Yes, D-1 

(Pressure regulation) 

TOMERS' 

4. Industrial sales directly off Meter and Regulation Some in D-1, but those O\IIIled 

of transmission pipelines (Pressure regulation) by transmission companies in 

this sheet (T -2) 

5. Farm sales off gathering Meter and Regulation No, so accounted for in this 

and transmission pipelines (Pressure regulation) sheet (T-2) 

6. 

Companies 

Sales to Other Transmission Most often Meter only, but No, so accounted for in this 

(Inter-connects) can have some flow sheet (T-2) 

regulation 

C-9 
Although direct customer connections (sales) on the transmission pipeline 

owned by distribution 

are rare, where they exist they are often 

transmission companies, 

companies, even if they only own a few feet of line. Many fann taps are still owned by 

Therefore, many direct 

even though there is a trend to let LDCs handle the farm taps or to remove them entirely. 

calculations. Only 

sales from the transmission pipeline are already accounted for in the distribution M&PR 

companies are counted 

the direct sales from the transmission pipeline that are owned completely by the transmission 

under this source sheet. 

of 

Most 

supply. 

large transmission 

These 

companies have interconnects with other transmission companies to allow for flexibility 

shared stations can flow in either direction. 

EMISSION FACTOR: (see below) 

The 

measurement 

average fugitive emission rate for trans::nission M&R stations was determined by analysis of the GRI tracer 

connects to high 

tests 

pressure 

for gas industry M&R stations. Transmission farm raps and industrial meters are both directgates had) in addition 

pipelines, and will have one pressure regulator (and not 3 to 22 regulators, as some city 

pneumatic emissions. 

to 

Therefore 

a meter. The pressure regulator is a self contained device, and so does not have significant 

the tracer data set was soned and adjusted as follows: 

I) include only stations with one regulator, 

2) 

3) delete 

include only stations in vaults (which were known to have no-bleed regulators similar to farm taps), 

4) delete meter 

regulator only stations in the low pressure range (0 to 100 psig inlet pressure), and 

only stations. 

for 

The 

the 

average 

emission 

of the 

factor. 

14 samples in the new transmission direct sales (farm tap & industrial meters) data set is used 

with 

The transmission 

inlet pressures 

company inter-connect meter stations were taken by soning the tracer data set for M&R stations 

above 100 psig. Thiny-seven samples met this criterion. 

Summary of Component Counts and Overall Emission Factors (scf/day) 

METER STATION TYPE SAMPLES EMISSION FACTOR 

(Number of Tracer Measure- (Methane SCFD) 

ments Fitting this Type) 

Trans-Trans Co. 37 3984 ± 80% 

Interconnect points 

Farm Taps and direct industrial 14 

sales 

31.2 ± 80% 

. 

EF DATA SOURCESo 

l. Tracers result based on downwind tracer measurements performed by Aerodyne/WSU 

100 

(l) at over 

gas industry meter/regulation stations. 

2. 

several 

Analysis of tracer results was based upon technical descriptions of meter station types given by 

transmission company measurement expens. 

3. 

meter 

Definition of transmission segment boundaries and other measurement programs shows that several 

types have already been accounted for. See sheet D-1 for sales to distribution M&R 

stations, 

for production 

see sheet T-l and S-1 for compressor station meter fugitive emissions and see sheet P-2 

receipt meters which have already been accounted for at gas production sites. 

C-10 
EF PRECISION: 

Basis: 

The transmission meter/pressure 

propagation 

regulation station (M&PR) upper bounds are based upon rigorous 

of error from the standard de\'iation of the multiple tracer measurements. 

ACTIVITY FACTOR: 

Trans-to--trans company interconnects 

Fann taps and Direct Industrial Sales 

2533 ± 776% 

72630 ± 780% 

activity 

As discussed above, types 1, 2, and 3 of transmission M&R stations are actually already accounted for in other 

has been 

factors. 

counted 

In the production segment meter runs were counted in the well site data. Delivery to distribution 

handle 

in the distribution segment M&R stations (i.e. city gates). There is also a trend to let LDCs 

companies. 

the farm taps, or to remove them entirely; however, many farm taps are still owned by transmission 

depanments 

Transfers to other transmission companies and farm taps were calculated from survey data provided by the metering 

fewer than 10,000 

of three 

miles 

large (over 10,000 miles of pipeline) transmission companies, and from three companies with 

of pipeline, as shown in the following table. 

Transmission M&R Station Populations 

Transfer to 

another Direct Indostrial 

Company Transmission Co. Farm Taps Sales Miles of Pipeline 

I 323 23 Confidential 

2 5 0 Confidential 

3 60 0 Confidential 

4 62 48 Confidential 

5 40 3,800 Confidential 

6 0 10,000 Confidential 

Total 490 13,871 658 55,045 (19.3% of 

U.S. total) 

Activity 

Total U.S. 2,533 ± 776% 71,690 ± 787% 937 ± 100% 284,500 

Factor 

Extrapolated by 

Miles 

companies. 

Only five of the six companies that responded to the survey reponed having interconnects with other transmission 

(transfers). 

The 

The 

activity factor was extrapolated based on pipeline miles and was calculated to be 2533 interconnects 

90% confidence bound was determined to be ± 776%. 

no 

The 

farm 

count of farm taps appears to be extremely regional. Based on interviews, it seems that most companies have 

taps, while others have thousands. The activity factor for farm taps was calculated to be 71,690 ± 787%. 

companies 

The calculated activity factor is believed to be conservatively high. since only .a small percentage of all transmission 

taps. 

have these M&R stations, yet two of the six companies in our data set reponed a large number of farm 

C-11 
The 

sales 

activity 

greater 

factor for direct industrial sales was developed from FERC Form No. 2, page 306 (2). Industrial 

single item. 

than 

In 

50,000 Mcf are listed individually, while sales less than 25,000 Mcf are combined inro a 

number of sales. 

the 

Due 

latter case, the total amount of gas sold was divided by 50,000 to provide an estimate of the 

comple;o.:ity of 

to the uncertainty tha~ fuis approach introduced to the activity factor and to the 

judgement. 

retrieving data from FERC, a confidence bound of ± 100% was assigned based on engineering 

coru.truction 

The activity factor 

of 

for the direct industrial sales was combined with that for farm taps based upon similar 

the two station types. 

AF DATA SOURCES: 

I. 

detennine 

For interconnects and farm taps, six transmission companies responded to the GRIJEPA survey to 

average ratios of meter types per mile of transmission 

were 

line. Averages from the survey 

extrapolated to national interconnect M&R number by multiplying 

miles 

the ratio by the known 

of U.S. transmission line. 

2. Miles of transmission line were from Gas Facts (3). 

3. Direct industrial sales were determined from gas sales reponed to FERC (2). 

AF PRECISION: 

Basis: 

l. 

the 

For 

ratio 

interconnects 

data 

and farm taps, rigorous propagation of error based upon the standard deviation of 

from individual transmission companies. 

2. For direct industrial sales: An engineering estimate based upon interview data. 

ANNUAL METHANE EMISSIONS: (4.5 Bscl" ± 835%) 

population 

The annual 

of 

emissions 

equipment 

were determined by multiplying an emission factor for an each equipment type by the 

in the segment. 

REFERENCES 

I. 

Tracer 

Aerodyne 

Measurements 

Research, Inc., Washington State University and University of New Hampshire. Results of 

94/0257.43, Gas Research 

of Methane Emissions from Natural Gas System Facilities, Final Report, GRIInstitute, Chicago, IL, March !995. 

2. 

Natural 

Federal 

Gas 

Energy 

Companies, 

Regulatory Commission (FERC) Form No.2, page 306: Annual Report of Major 

1992 database. 

3. American Gas Association. Gas Facts: 1992 Data, Arlington, VA, 1993. 

C-12 
SOURCES: 

OPERATING MODE: 

EMISSION TYPE: 

ANNUAL EMISSIONS: 

BACKGROUND: 

T-3 

TRANSMISSION SOURCE SHEET 

Transmission Pipelines 

Normal Operations 

Unsteady, Fugitives (Pipeline Leaks) 

0.16 Bscf +I- 89% 

from 

Transmission pipelines are the inter- and intrastate high pressure underground pipelines that transport natural gas 

the productionlprocessing operations to the end user or distribution network. Leakage from underground 

transmission lines occurs from corrosion pits, joint and fining failures, pipe wall fractures, and external damage. 

EMISSION FACTOR: (scffleak-year) 

Leak survey practices for transmission lines are generally more stringent than for distribution mains. Transmission 

lines are required to be surveyed annually, and more frequently in populated areas. In addition, many transmission 

conversations 

companies perform 

with 

additional routine aerial surveys to monitor the transmission lines for leakage. Based on 

repaired 

several transmission companies, any leaks found in the pi pew all are e:uremely small and are 

companies 

immediately for safety reasons. Based on the rigorous leak survey and repair practices of transmission 

(i.e., leaks are discovered and repaired earlier in transmission lines), the average leak rate from a 

transmission 

though 

leak is believed to be of the same orde: of magnitude as a leak found in a distribution main, even 

there may be a substantial difference in the operating pressure of the pipelines. 

rates 

Therefore, the emission factors for leakage from transmission pipelines are based on the arithmetic average leakage 

value 

for 

of 

main pipelines from the cooperative underground distribution leakage measurement program. A mean 

For cast 

the estimated leak rate per leak was calculated using the test data, for all pipe materials except cast iron. 

of pipe; 

iron mains, a segment rest approach was used which quantifies the leakage rate for a long isolated segment 

gas 

therefore, the mean leakage rate for cast iror: is in terms of leakage per unit length of pipe. The natural 

% 

leak rate i~ adjusted for methane by multiplying by the volume percent of methane for transmission (93 .4 vol. 

each 

), and 

pipe 

is 

material 

adjusted for the soil oxidation of methane. The value of the emission factor and standard deviation for 

category is given below: 

Pipe Material Number of Average Units of 90% 

Samples Emission Emission Confidence 

Factor Factor Interval of 

Emission 

Factor 

Protected Steel 17 20,270 scf/leak-yr 17,243 

Unprotected Steel 19 51,802 scf/leak-yr 48,212 

Plastic 6 99,845 scflleak-yr !65,617 

Cast Iron 21 238,736 scf/mile-yr 152,059 

pipeline 

Preliminary 

pressure. 

data from the underground distribution program indicate that the leakage rate is not a function of the 

difference 

Therefore, the leakage rates for transmission pipelines have not been adjusted based on the 

in average operating pressure of the transmission lines versus distribution lines. 

C-13 
EMISSION FACTOR DATA SOURCES' 

1. 

mains, 

Leakage rate data on a rate per leak basis for cathodically protected steel mains, unprotected steel 

and plastic mains from the cooperative leak measurement program. 

2. Leakage 

measurement 

rate data on a rate per unit length basis for cast iron mains from the cooperative leak 

program for distribution mains. 

3. 

mains, 

Assumes that the leak rates from transmission pipelines are identical to leak rates from distribution 

based on the more rigorous leak survey and repair practices of transmission companies. 

4. Assumes that the leak rates from underground pipelines are independent of pressure and pipe 

diameter, based on preliminary results from the underground distribution leak measurement 

program. 

ACTIVITY FACTOR: (equivalent leaks) 

The mean activity factor and precision for each pipe material category is given below: 

Pipe Material Total Miles Average Activity Units of Activity 90% Confidence 

Factor Factor IntervaJ of 

Activity Factor 

Protected Steel 287,I55 5,077 equivalent leaks 3,859 

Unprotected Steel 5,233 659 equivalent leaks 501 

Plastic 2,62I 14 equivalent leaks II 

Cast Iron 96 96 miles 10 

database 

The number of total leaks (excluding pipeline incidents) in transmission pipelines is based on the 1991 DOT RSPA 

(1) for transmission pipelines, including both repaired leaks (6,120 leaks) and outstanding leaks (1,369 

of 

leaks). 

unreported 

Because transmission lines are surveyed at least once per year using a walldng survey method, the number 

company speci~izing 

leaks is estimated based on the effectiveness of the walking survey. According to one contract 

This 

in distribution surveys, roughly 85 percent of the. leaks are found using a walking survey. 

estimated survey efficiency was applied to transmission surveys, resulting in roughly I ,320 unreported leaks. 

duration 

The leak duration for outstanding leaks and unreported leaks is estimated to be 8,760 hours per year, and the leak 

represents 

for repaired leaks is half a year (4,380 hours/year), on average. The resulting estimate of equivalent leaks 

equivalent 

the number of leaks with a year round leak duration. (That is, each leak repair is counted as half an 

leak to compensate for the leak duration.) Therefore, the equation used to estimate equivalent leaks is: 

0.5 x (repaired leaks) + {[(repaired leaks +outstanding leaks)/0.85} ~repaired leaks} 

The total number of estimated transmission pipeline leaks, 5, 750, was allocated on a pipeline material category basis 

in the same proponion (adjusted for the fraction of mileage in each material category) as in the distribution sector. 

distribution 

(That is, the ratio of percent leaks to percent miles in the transmission segment is the same as the ratio in the 

confidence 

segment.) The precision of the estimated total leaks was calculated based on the estimated 90% 

interval associated with each parameter in the activity factor equation: 

repaired leaks; outstanding leaks: ± 100% 

leak duration: ± 25% 

leak survey effectiveness: ± 15% 

C-14 
activity 

A statistical 

factor: 

software 

± 

program f(@RISK (2)] was used to determine the overall 90% confidence interval of the 

76%. 

For cast iron transmission 

gathering 

lines, the ntileage is based on the !991 DOT RSPA database for transmission and 

lines. The precision of the estimate is assumed to be ± 10%. 

ACTIVITY FACTOR DATA SOURCES, 

l. 1991 DOT RSPA database (1) for transmission and gathering pipelines. 

2. Total number of leaks is assumed equal to the total number of leak repairs plus the outstanding 

(unrepaired leaks) and unreported leaks. 

3. Leak survey effectiveness estimation provided by Southern Cross Company (3). 

4. The allocation of estimated leaks per pipe material category is based on the leak frequency for 

underground distribution main pipelines, adjusted for the fraction of total mileage per pipe material 

category. 

5. @RISK statistical software program (2) used to estimate the 90% confidence interval. 

Al\'NUAL METHANE El\11SSIONS: (0.16 Bscf ± 89%) 

Pipe Material Average Emission Average Activity Annual Emissions 90% Confidence 

Factor Factor Estimate, Interval of 

(scf/leak-yr) (equivalent leaks) (Bscf) Emissions 

Estimate, 

(BscO 

Protected Steel 20,270 5,077 0.10 0.14 

Unprotected Steel 51,802 659 O.QJ 0.05 

Plastic 99,845 !4 0.00! 0.003 

Cast Iron 238, 736• 96' 0.02 0.02 

Total 0.16 0.14 

•sct/mde y 

' brn,jJes 

estimated 

The total 

number 

leakage was determlned by multiplying an emission factor for each type of pipeline material by the 

of leaks in each respective pipe material category. 

REFERENCES 

1. U.S. Department of Transponation. Research and Special Programs Administration. 1991. 

2. 

1989. 

Palisade Corporation. @Risk, Risk Analysis and Simulation Add-in for Lotus 1-2-3, Version I .5, March 

3. 

Department 

Southern Cross Corporation. Comments on Docket PS-123 Notice 1, Leahlge Surveys, 49 CFR Pan 192, 

Bureau, 

of Transponation, Research and Special Programs Administration, Materials Transponation 

Office of Pipeline Safety Regulations, December 19, 1991. · 

C-15 
T-4 

TRANSMISSION AND STORAGE SOURCE SHEET 

SOURCES' 

OPERA T!NG MODE' 

EMISSION TYPE, 

COMPONENTS' 

ANNUAL EMISSIONS, 

BACKGROUND' 

Various Equipment (vessels, compressors, piping) 

Normal Operation 

Unsteady, Vented 

Pneumatic Devices 

14.1 Bscf ± 60% 

The 

essentially 

transmission 

no pneumatic 

segment is comprised of compressor stations, pipelines, and storage stations. There are 

of the pneumatics are gas-actuated 

devices associated with the pipelines, Within the storage and compressor stations, most 

isolation valves, and there are a few continuous bleed controllers. 

pneumatic 

Meter-only 

controllers 

stations do not have venting pneumatics. Meter and regulation (M&R) stations do have regulating 

in the fugitive 

(the pressure regulator valves), but all of the M&R station pneumatic emissions are counted 

calculation for M&R stations and so are not included in this sheet. 

The continuous bleed controllers 

separatofs and pressure 

in transmission compressor stations are used for liquid level control in filteroperations 

reduction. The higher pressures and large pipe diameters associated with transmission 

similar devices 

require larger actuators and valves than typically found in production, resulting in larger emissions than 

in production. 

Within the storage and mainline compressor stations, most of the pneumatic devices are gas-actuated 

valves. These valves 

isolation 

in the case of an emergency. 

block the flow to or from a pipeline and can isolate the facility for maintenance work or 

intermittent. 

Therefore, the isolation valves are actuated infrequebtly and their emissions are 

EMISSION FACTOR' 162,197 scfi'device ± 44% 

(This was adjusted for the transmission methane fraction of natural gas at 93.4 mol%.) 

sites. 

The average 

Counts 

pneumatic 

of devices 

device emission factor was determined from a compilation of information from several 

categories: continuous 

per site were taker. during Radian site visits. The devices were classified into three 

operators. The 

bleed valves, isolation valves with turbine operators, and isolation valves with displacement 

emission factor was determined based on the following equation: 

EF pneuma~c d..,.icu ( EF =' b!<o:l •• , ... X Fraction ""''" bl-s v&i•os + 

EF tulbmo OP<nl<>" x Fraction 10rt,,. o~'=to" + 

EF di•plooem.,1 Of>OI'I.IO" x Fraction d1.1ploumont operuo" ) x o/G methane 

Listed below are the average fraction of devices for each of the three valve categories: 

Fraction cont bleed valveo 

Fraction ,...,b,n• op"""'" 

Fraction disploument optntoll 

= 0.32 ± 69% 

0.16 ± 94% 

0.52 ± 48% 

Emissions from continuous bleed pneumatics 

contractor. The 

in the transmission segment were measured by an independent 

average emission factor, based on 23 measurements, 

sc£1device). 

is 1,363 scfd/device ± 29% (497,584 

C-16 
gas 

For 

pressure, 

the isolation valves with rurbine operators, the emission factor depends on the gas usage for a given supply 

The annual 

the time required to complete one movement of the valve, and the number of operations per year. 

emission factor is then: 

EF rur~>m• ~pento" "" Gas Usage (scf/min) :x Operating Duration (min/operation) x 2 

(operations/cycle) x Frequency (cycles/year) 

EF rurt>inoopento"' = 67,599 ± 276% scf/device 

The equation for isolation valves with displacement operators is similar: 

EF DATA SOURCES' 

=Gas Usage (scfi'psia) x Supply Pressure (psia) x 2 

(operations/cycle) x Frequency {cycles/year) 

= 5,627 ± 112% scfi'device 

1. 

establishes 

Methane Emissions from the Natural Gas Industry, Volume 12: Pneumatic Devices (1) 

2. Device 

the important emission-affecting characteristics of transmission pneumatic devices. 

operators, 

counts from 16 compressor and storage stations establish the fraction of turbine valve 

establish 

and displacement valve operators. Counts from a total of 54 stations were used to 

the fraction of continuous bleed devices. 

3. The emission factor for the continuous bleed valves was based on 23 field measurements. 

4. Gas usages for the turbine valve operators were provided by Limitorque. Operating duration 

and frequency were estimated based on infonnation from two transmission stations. 

5. Gas usages for the displacement valve operators were provided by Shafer Valve Operating 

Systems. Supply pressure and frequency of operation were estimated based on infonnation from 

four transmission stations. 

EF ACCURACY' 

Basis: 

l. 

measured 

EF accuracy is based on error propagation from the combination of site infonnation and 

data. 

2. It was assumed that the n:tanufacturers' data are completely accurate. 

ACTIVITY FACTORS: 87,206 pneumatic devices ± 38'% 

the 

The 

average 

number 

number 

of gas operated 

of 

pneumatic devices in the transmission and storage segment was calculated based on 

nationally. The 

devices per station and multiplied by the total number of transmission and storage stations 

transmission compression 

average number of devices per site was detennined to be 40 ± 37%. The total count of 

89 LNG storage 

facilities is 2,175, based on 1,700 compressor stations, 386 UG storage stations, and 

stations. 

AF DATA SOURCES' 

I. The 

Commission 

number of transmission compressor stations was compiled from 1992 Fossil Energy 

Fonn No. 2: Annual Report of Major Natural Gas Companies (2). 

2. The number of underground storage facilities is taken directly from A.G.A. Gas Facts: "Number 

of Pools, Wells, Compressor Stations, and Horsepower in Underground Storage Fields." Data 

from base year 1992 were used (3). 

3. The number of liquefied natural gas storage facilities was summed from A.G.A. Gas Facts, 

C-17 
"Liquefied Natural Gas Storage Operations in the U.S. as of December 31, 1987 (4)." The table 

4. 

lists 54 complete plants, 32 satellite plants, and 3 import terminals for a total of 89 facilities. 

The number of devices per site is based on the total number of devices observed during site 

visits. 

AF ACCURACY: 3SO/o 

Basis: 

I. 

2. 

Extremely ti.oght confidence limits are expected due to the well documented and reviewed 

numbers published in A.G.A. Gas Facts and FERC forms. A 10% confidence bound was 

assigned to the number of compressor stations and a 5% confidence bound was assigned to the 

number of storage stations. 

The confidence bound on the number of devices per station was determined based on the spread 

of site data. 

ANNUAL METHANE EMISSIONS: 14.1 Bscf ± 60 % 

composition) 

The annual emissions 

by 

were determined by r.mltiplying an emission factor per device (corrected for the methane 

the population of pneumatic devices in the transmission segment. 

162,197 scfldevice x 87,206 devices= 14.1 Bscf 

REFERENCES 

I. Shires, 

Pneumatic 

T.M. 

Devices. 

and M.R. Harrison. Methane Emissions from the Natural Gas Industry, Volume 12: 

U.S. Environmental 

Final Report, GRI~94/0257.29 and EPA~600/R~96~0801, Gas Research Institute and 

Protection Agency, JWle 1996. 

2. 

No. 

Department 

1902-0028, 

of Energy. 

Department 

FERC Form No. 2: Annual Report of Major Natural Gas Companies. OMB 

December 

of Energy Federal Energy Regulatory Commission, Washington, DC, 

!994. 

3. American Gas Association. Gas Facts:. 1993 Data, Arlington, VA, 1994. 

4. American Gas Association. Gas Facts:. 1991 Data, Arlington, VA, 1992. 

C-18 
SOURCES: 

OPERATING MODE: 

EMISSION TYPE: 

ANNUAL EMISSIONS: 

BACKGROUND: 

T-5 

TRANSMISSION AND STORAGE SOURCE SHEET 

Various Equipment 

Maintenance!Upsets 

Unsteady, Vented 

18.5 Bscf± 177% 

direct, 

Maintenance activities can release gas to the atmosphere through blowdown or through purge. Blowdown is the 

intentional venting to the atmosphere of gas contained inside operating equipment. The gas is released 

equipment 

to provide a safer working environment for maintenance activities around or inside the equipment. After the 

is serviced, the oxygen inside the equipment is often cleared to the atmosphere by purging natural gas 

through the equipment. 

Upsets can also emit gas directly to the atmosphere. Upsets in process conditions can cause pressure rises that 

exceed the maximum design pressure for equipment To prevent equipment overpressure and damage, pressure 

relief valves (PRVs) or remotely actuated valves open and vent the excess gas to the atmosphere. PRVs are 

spring loaded or pilot actuated valves that are designed to handle the upset conditions. Remotely actuated valves 

are usually designed to vent entire compressor stations or areas (such as compressor piping) in the event of a 

station emergency such as a fire or a large gas release. 

EMISSION FACTORS: Station Slowdowns 4,359 ± 262% Mscf/station 

Pipeline Blowdowns 31.6 ± 236% Mscf/mile 

(Corrected for the transmission methane composition of 93.4 mol%) 

Company tracked data were available from either company gas use estimates reported to accounting departments 

from each site (accounted-for), or from special "unaccounted-for" studies that searched for unmetered company 

gas use. Most of the company data could be separated into two event types: station blowdowns (includes 

compressor blowdowns, compressor starts, PRV lifts, ESD activation, and other venting sources) and pipeline 

blowdowns. These data are swnmarized in the following table. 

EF DATA SOURCES: 

I. GRIIEPA Methane Emissions .from the Natural Gas Industry, Volume 7: Blow and Purge 

Activities (l) establishes emission affecting characteristics of blowdown practices. 

2. Company tracked data were available from 8 companies. 

EF ACCURACY: Range ± 236% to 262% 

Basis: 

The accuracy was calculated from the spread of the company data. A 90% confidence interval is 

Gas 

calculated for the 8 companies using the method presented in the Methane Emissions from the Natural 

Industry, Volume 4: Statistical Methodology (2). 

C-19 
Annual. Station AaDual 

EmiSsion~ 

Blowdown Pipeline Total Annual Total Total NurD:ber 

Company Mscf 

Blowdowns, 

Mse{ BlowdoWIJ~ Number of of 

Msef Stations Pipeline Miles 

120,757 189,044 309,801 II 3,857 

2 272,589 I 1 ,358 283,947 15 4,000 

3 33,731 !38,988 172,719 27 5,886 

4 172,776 (19)' (5,450) 

5 325,4!8 Unknown Unknown 47 (4,725) 

6 Unknown 161,628 Unknown (48) 7,896 

7 60,956 750,000 810,956 69 14,666 

8 194,541 315,058 509,599 47 9,9!5 

TOTALS 1,007,992 1,566,076 216 46,220 

ANNUAL AVERAGE, Mscf natural gas/station 

ANNUAL AVERAGE, Mscf 

4,667 ± 262% 

natural gas/milt 33.9 ± 236% 

"Parentheses 

was not available. 

indicate that the value was not included in the total because a station or pipeline emission rate 

ACTIVITY FACTORS• 2,175 ± s•io compression facilities 

284,500 ± 5% transmission pipeline mUes 

count 

The activity 

for transmission 

factors for 

compressor 

the segment were compiled from published statistics on the gas industry. The total 

station count was 475. The number 

stations was 1700; the total underground and liquefied natural gas storage 

shows 284,500 miles of 

of transmission pipeline miles comes from A.G.A. Gas Facts (3) which 

pipeline in the United States for 1992. 

AF DATA SOURCES• 

1. 

Annual 

The number 

Report 

of transmission compressor stations was compiled from FERC Form No. 2: 

of Major Natural Gas Companies (4). 

2. 

4-5, 

The number of underground storage facilities is taken directly from A.G.A. Gas Facts, Table 

"Number of Pools, Wells, Compressor Stations, and Horsepower in Underground 

Storage Fields" (3). 

3. 

Table 

The number 

4-3, 

of liquefied natural gas storage facilities was summed from A.G.A. Gas Facts, 

"Liquefied Natural Gas Storage Operations in the U.S. as of December 31, 1987" 

of 

(3). 

89 

The table lists 54 complete plants, 32 satellite plants, and 3 import terminals for a total 

facilities. 

4. The 

284,500 

number 

miles 

of transmission pipeline miles comes from A.G.A. Gas Facts which shows 

of pipeline in the U.S. for 1992 (3). 

AF ACCURACY: Range± 5% to 8% 

Basis: 

Extremely tight confidence 

numbers 

limits are expected due to the well documented and reviewed DOE 

published in A.G.A. Gas Facts (3). 

C-20 
ANNUAL METHANE EMISSIONS: 18.5 Bscf ± 177% 

category 

The annual methane emissions were determined by multiplying an emission factor (rate per avg unit) for each 

methane 

by the activity factor (population) of the category. Each emission factor was adjusted for the average 

content in the transmission segment of 93.4 mol%. 

REFERENCES 

1. 

and 

Shires, 

Purge 

T.M. and M.R. Harrison. Methane Emissions from the Natural Gas Industry, Volume 7: Blow 

U.S. Environmental 

Activities, Final Report, GRl-94/0257.24 and EPA-600/R.-96-080g, Gas Research Institute and 

Protection Agency, June 1996. 

2. Williamson, H.J., M.B. Hall, and M.R. Harrison. Methane Emissions from the NaJural Gas Industry, 

Research 

Volume 4: Statistical Methodology, Final Report, GRI-94/0257.21 and EPA-600/R-96-080d, Gas 

Institute and U.S. Environmental Protection Agency, June 1996. 

3. American Gas Association. Gas Facts: 1992 Data, Arlington, VA, 1993. 

4. 

No. 

Department of Energy. FERC Form No.2: Annual Report of Mayor Natural Gas Companies. OMB 

December 

1902-0028, Department of Energy, Federal Energy Regulatory Commission, Washington, DC, 

1994. 

C-21 
SOURCES' 

OPERATING MODE' 

EMISSION TYPE' 

COMPONENTS' 

ANNUAL EMISSIONS' 

BACKGROUND' 

T-6 

TRANSMISSION SOURCE SHEET 

Glycol Dehydrators 

Normal Operation 

Unsteady, Vented 

Reboiler Vents 

0.10 Bscf ± 392% 

Glycol 

from 

dehydrators remove water from a gas stream by contacting the gas with glycol and then driving the water 

can be 

the 

driven 

glycol and into the atmosphere. The glycol also absorbs a small amount of methane, and some methane 

off to the atmosphere through the reboiler vent. 

EMISSION FACTOR: (93.72 scfiMMscf gas processed ± 207.99%) 

A thermodynamic computer simulation was used to determine the most important emission·affecting variables 

of 

for dehydrators. The variables are: gas throughput, existence of a flash tank, existence of stripping gas, existence 

handled 

a gas 

by 

driven pump, existence of vent controls routed to a burner. Throughput, since its effect is linear, is 

establishing an emission rate per gas throughput. Emission rates per throughput are then established 

for the other important emission affecting characteristics. The emission factor is then: 

EF ==I ( Frr x EFrr) + ( F~'<'T x EFm) + ( FsG x EFsG) J x FNYC x OC 

EF == [ (0.669 x 3.57) + (0.331 x 175.10) + (0.0741 x 670) J.x 0.852 x 1.0 

FFT == Fraction of the population WITH flash tanks 

0.669 ± 9.70% 

FNT == Fraction of the population WITIIOUT flash tanks 

0.331 ± 19.6% 

F sG == Fraction of the population WITii stripping gas 

0.0741 ± 118.26% 

Fr-Nc"" Fraction of the population WITHOUT com busted vent controls 

0.852 ± 14.0% 

EFFT== Total CH~ emissiOn rate per I MMscf throughput for dehydrator that has a flash tank 

3.57 scf/MMscf (+102% I -5SO!o) 

EFNT== Total CH~ emission rate per 1 MMscf throughput for dehydrator that does NOT have 

a flash tank 

175.1 scf!MMscf (+101% /-50%) 

EF sG"" Incremental emission rate per I M}./[scf throughput for dehydrator that has stripping gas 

670 scf/MMscf (..,.40% I -60%) 

OC == Overcirculation factor for glycol-number of times the industry rule-of-thumb of 3 

gallons glycoVIb water 

1.0 ± 0% 

C-22 
EF DATA SOURCES: 

L Methane Emissions from the Natural Gas Industry, Volume /4: Glycol Dehydrators (1) 

establishes emission affecting characteristics of dehydrators. 

2. Site visit data establishes the F50 and FNVc for multiple sites. Wyoming ADQ data also 

verifies FNVo though it implies a higher F, and thus a higher overall EF. 

3. TMOGA/GPA survey of 1019 dehydrators established Fm and Fr.n and TP for dehydrators. 

4. ASPEN computer simulations were used to determine EFro, and EFND from the dehydrator 

vent. 

5. Sampling data from the GRJ Glycol Dehydrator Sampling and Analytical Program for one 

dehydrator was used to determine EFso (!). The upper bound was calculated by assuming 

methane. 

that all of the measured noncondensable vent gas was due to stripping gas that was I 00% 

The lower bound was calculated as the rule-of-thumb stripping gas rate 

recommended by a glycol dehydrator manufacturer. 

EF ACCURACY: 93.72 scf7M1v[scf ± 207.99% 

Basis: 

The accuracy is propagated through the EF calculation from each term's accuracy: 

I. ASPEN has been demonstrated to match actual dehydrators within ±20% within the 

calculated confidence intervals obtained from site data. 

2. Individual EF confidence intervals were calculated based upon the spread of the site 

averages. 

ACTIVITY FACTOR: (1.086 Tscf/year gas throughput in the transmission segment) 

estimated 

The amount of gas processed by glycol dehydrators in the transmission segment was calculated from the 

number of glycol dehydrators in transmission service and the average throughput capacity for 

transmission 

breakdown of 

dehydrators (Wright Killen & Co., 1994). See Source Sheet P-6 for a detailed discussion of the 

assumed 

glycol dehydrators into industry segments. The capacity utilization factor for transmission was 

to be l. 

AF ACCURACY: I .086 Tscf7year ± 143.85% 

Basis: 

1. Uncertainty based on confidence limits from the site visit data. 

ANNUAL METHANE EMISSIONS: (0.1018 Bscf/yr ± 391.75%) 

The annual methane emissions were detennined by multiplying the dehydrator emission factor by the activity 

factor. 

REFERENCES 

I. 

Report, 

Myers, D. 

GRI-94/0257.31 

Methane Emissions from the Natural Gas Industry, Volume 14: Glycol Dehydrators, Final 

and EPA-600/R-96-080n. Gas Research Institute and U.S. Environmental 

Protection Agency, June 1996. 

2. Wright Killen & Co. Natural Gas Dehydration: Status and Trends, Final Report, Gas Research 

Institute, GRJ-94/0099, January 1994. 

C-23 
S-1 

STORAGE SOURCE SHEET 

SOURCES: 

OPERATING MODE: 

Storage Facilities (Compressor Stations and Wells) 

Normal Operation 

EMISSION TYPE: Steady and Unsteady, Fugitive 

16.76 Bscf.:: 57% ANNUAL EMISSIONS: 

BACKGROUND: 

Equipment leaks are typically low-level, tmintentional losses of process fluid (gas or liquid) from the sealed 

surfaces 

and other 

of above-ground process equipment. Equipment components that tend to leak include valves, flanges 

connectors, pump seals, compressor seals, pressure relief valves, open-ended lines, and sampling 

connections. These components represent mechanical joints, seals, and rotating surfaces, which in time tend 

to wear and develop leaks. 

EMISSION FACTOR: a. Station ""7.85 MMscl7yr methane per station 

b. Wellhead = 41.8 MscfJyr methane per wellhead 

c. Recip. Compressor = i.71 MMscYyr methane per recip 

d. Turbine Compressor :: 11.16 MMscf/yr methane per turbine 

The average fugitive emission rate for storage facilities was determined to be composed of three parts: a) 

storage compressor station components (excluding compressor-related components), b) injection/withdrawal 

wellhead components, and c) compressor-reiated components. Fugitives from the compressor-related 

components have much higher emission factors than components in the rest of the facility. This is due in pan 

to the high vibration that compressors generate, but most of the larger emissions are due to unique compressor 

components as explained below. 

a) The contribution from non-compressor components was detennined by multiplying the average number of 

fugitive components by the component emission factor. The number of components was subdivided into 

valves, connections/flanges, small open-ended lines, and other components (such as pressure relief valves); 

tubing components were determined to be insignificant. All of these components are typical fugitive 

components (as described in the EPA Fugitive Emissions Protocol) with the exception of site blowdown 

(BID) open-ended Jines (OELs). Site BID OELs are the large diameter emergency station b!owdown valves 

that are designed to depressure the entire site to the atmosphere when the valve is opened. Emission factors 

for storage station components were based on the GRI!Indaco program at 6 transmission compressor station 

sites. 

b) The contribution from storage injection/withdrawal wells was determined in the same manner as storage 

updated 

compressor 

API/GRl/Star 

stations (see below). Emission factors for storage injection/withdrawal wells were based on the 

20-site study (4 gas production sites). Physical and operational characteristics of 

injection/withdrawal wells were compared to gas production wells, and were found to be similar but typically 

larger (more components). This was taken into account in the component count data. 

The number of components was subdivided into types, such as valves, connections/flanges, open-ended lines, 

and other components (such as pressure relief valves). The average facility/equipment emissions are 

calculated as follows: · 

where: 

N, :: average count of components of type x per plant, and 

EF, :o average methane emission rate per component of type x. 

C-24 
c) The contribution from compressoNe!ated components was obtained by multiplying the average number of 

fugitive components per compressor engine by the component emission factors. The component emission 

factors were based on the GRI11ndaco measurement program conducted at !5 compressor stations. Some 

compressor components are unique, while others have higher leak rates than identical components elsewhere 

in the plant due to vibration. Compressors have the following types of components: 

I) Camp. BID OEL A blowdown (BID) valve to the atmosphere that can depressure the compressor 

when idle. The BID valve or the large unit block valves (depending on the 

operating status of the compressor) can act as an open-ended line that leaks at an 

extraordinarily high rate through the valve seat. The leak rate is dependent upon 

whether the compressor is pressurized (in operation or idle, pressurized) or 

depressurized (idle, depressurized). 

2) Camp. PRV The pressure relief valve (PRV) is usually installed on a compressor discharge line 

and leaks at a higher than average rate due to vibration. 

3) Camp. Starter OEL Most compressors have a gas starter motor that turns the compressor shaft to start 

the engine. Some use natural gas as the motive force to spin the starter's turbine 

blades and vent the discharge gas to the atmosphere. The inlet valve to the starter 

can leak and is therefore an OEL unique to compressors. 

4) Camp. Seal All compressors have a mechanical or fluid seal to minimize the flow of pressurized 

narural gas that leaks from the location where the shaft penetrates the compression 

chamber. These seals are vented to the atmosphere. Reciprocating compressors 

have sliding shaft seals wl:ile centrifugal compressors have rotating shaft seals. 

5) Miscellaneous There are many components on each compressor, such as valve covers on 

reciprocating compressor cylinders and fuel valves. 

Each compressor has one BID OEL, one PRV, and one starter OEL. Reciprocating compressors have one 

compressor seal per compression cylirider (which averaged 4.5 per engine), while centrifugal compressors 

have 1.5 seals per gas turbine. For the miscellaneous component category, there are many components per 

compressor engine, but the emission rates were minor and so were added into one lump emission factor per 

compressor for miscellaneous components. 

All of the compressor emission factors take several correction factors into account. First, the various phases 

of compressor operations (such as the amount of time that compressors are a) idle and depressured, b) idle 

and pressured 'up, or c) running). This is actually a complex adjusttnent that takes into account valve position 

practices. [See Methane Emissions from Natural Gas Industry, Volume 8: Equipment Leaks (1) for more 

details.] Correction factors were also added for fraction of starter gas turbines using air instead of _gas (40% 

for recip, 50% for turbines in storage). 

EF DATA SOURCES' 

I. Emission Factors for storage compressor stations are based upon GRJ/Indaco transmission 

compressor station fugitive leak measurement surveys at 6 compressor stations. Compressor 

operating hours (% running) based on data from 5 national gas storage companies. 

2. Component counts for storage compressor stations and injection/withdrawal wellheads are 

based on Radian site visits to 5 storage facilities-. 

3. Component emission factors for compressor-related components based on GRI!lndaco 

transmission compressor station fugitive leak measurement program at 15 compressor 

stations. 

4. Wellhead emission factors based on simple average of GRIIStar data fer gas production 

wellheads (Atlantic/Eastern region a.'ld Rest of U.S.). 

5. Fraction of methane (93.4 mol%) based on data from GRI TRANSDAT database. 

C-25 
Average Facility Emissions for Gas Storage - Equipment Type Component Type Component Average Component Average Equipment 

Emission Factor, Count Emissions,• Msd/component-yr MMscf/yr 

Storage Facility Valve 0.867 I,868 7.85 (100%) 

(non-compressor 

related components) Connection O.I47 5,571 

OEL Il.2 353 

PRV 6.2 66 

Site BID OEL 264 4 

InjectionJWithdrawa Valve 0.9I8 30 0.042 (76%) 

I Wellhead 

Connection 0.125 89 

OEL 0.237 7 

PRV !.464 I 

Reciprocating Compressor BID 5,024b I 7.71 (48%) 

Compressors OEL 

PRV 317b I 

Miscellaneous l53b I 

Compressor Starter 1,440 0.6' 

OEL 

Compressor Seal 300b 4.5 

Centrifugal Compressor BID 10,233b I ll.J6 (34%) 

Compressors OEL 

Miscellaneous J7b I 

Compressor Starter I,440 OS OEL 

Compressor Seal 126b !.5 

• Values in parentheses represent 90% confidence interval. 

h Adjusted for the fraction of time the compressor is pressurized (67.5% and 22.4% for reciprocating and 

centrifugal compressors, respectively). 

< Adjusted for the fraction of compressor starters using natural gas (60% and 50% for reciprocating and 

centrifugal compressors, respectively). 

C-26 
EF ACCURACY: a. Station = ± 100% 

b. Wellhead = ± 76% 

b. Recip. Compressor = ± 48% 

c. Turbine Compressor = ± 34% 

Basis: 

Rigorously propagation of error from the spread of thousands of individual measurements taken by 

Indaco and Star. 

ACTIVlTY FACTOR a. Station Activity Factor= 475 stations 

b. Wellhead Activity Factor= 17999 wellheads 

b. Compressor Activity Factor = 1396 recip compressors, 136 turbines 

for 

The 

Undergmund 

activity factors for the segment were compiled from published statistics in Gas Facts (2). The total count 

storage stations was 386, and the total LNG storage count was 89. 

AF DATA SOURCES: 

l. The number of underground storage facilities was taken directly from A.G.A. Gas Facts, (2), 

Table 4-5: Number of Pools, Wells, Compressor Stations, and Horsepower in Underground 

Storage Fields. Data from base year 1992 were used. 

2. The number of Liquefied Natural Gas Storage Facilities was summed from A.G.A. Gas 

Facts (2), Table 4-3, "Liquefied Natural Gas Storage Operations in the U.S. as of December 

31, !987." The table lists 54 complete plants, 32 satellite plants, and 3 import tenninals for 

a total of 89 facilities. 

3. Compressor engine count based on GRJ TR.t\.NSDAT "industry database" with adjustments 

for total industry horsepower. Storage site visits to 8 storage sites provided number of 

reciprocating engines and turbines per site [see Activity Factor Report (3)]. Also, the number 

of reciprocating compressors in storage was increased by 3 I% to account for electric motor 

drivers. 

AF ACCURACY: a. Station Activity Factor: ± 5% 

Basis: 

I. 

2. 

b. Wellhead Activity Factor: ± 5% 

b. Compressor Activity Factor: Recip engines= ± 58 %; Turbines = ± 119 % 

A.G.A. Gas Facts (2) has a high percentage of all storage facilities represented in Tables 4-5 

and 4-3. Therefore a national extrapolation should not add much error. This 5% figure was 

assigned based on engineering judgement. 

The compressor count accuracy was assigned based upon the propagation from: a. Rigorous 

error propagation for the 8 storage station "compressor/station" averages; and b. Engineering 

judgement assignment of± 10% error to the large GRJ TRANSDA T database. 

ANNUAL METHANE EMISSIONS: (16.76 Bscf/yr ± 9.6 Bscf/yr) 

The annual emissions were detennined by multiplying an emission factor for an average equipment type by 

the population of equipment in the segment. 

C-27 
Category Emission Factor Activity Factor Emission Rate Uncenainty 

Stafion 7.85 MMsd7yr CH4 475 stations 3. 73 Bscfi'yr CH4 100% 

lnj!With Wellheads 4!.8 Mscfi'yr CH4 17999 wellheads 0.752 Bscfi'yr CH4 76% 

Recip Comp 7.71 MMscfi'yr CH4 1396 recip 10.76 Bscfi'yr CH4 80% 

Turbine Comp I !.l6 MMscti'yr CH4 !36 turbine 1.52 Bscflyr CH4 129% 

TOTAL 

16.76 Bscflyr CH4 57% 

REFERENCES 

I. 

Industry, 

Hummel, 

Volume 

K.E., L.M. Campbell, and M.R. Harrison. Methane Emissions from the Natural Gas 

Research Institute 

8: Equipment Leaks, Final Report, GRJ·94/0257.25 and EPA--600IR-96-080h, Gas 

and U.S. Envirorunental Protection Agency, June 1996. 

2. American Gas Association. Gas Facts, Arlington, VA. 1992. 

3. 

Report, 

Stapper, 

GR1·94/0257.22 

B.E. Methane Emissions from the Natural Gas Industry, Volume 5: Activity Factors, Final 

Protection Agency, 

and EPA-600/R·96-080e, Gas Research Institute and U.S. Environmental 

June 1996. 

C-28 
SOURCES' 

OPERATING MODE: 

EMISSION TYPE: 

COMPONENTS: 

ANNUAL EMISSIONS: 

BACKGROUND: 

S-2 

STORAGE SOURCE SHEET 

Glycol Dehydrators 

Normal Operation 

Unsteady, Vented 

ReboiJer Vents 

0.23 Bscf ± 167% 

water 

Glycol dehydrators remove water from a gas stream by contacting the gas with glycol and then driving the 

some methane 

from the glycol and into the atmosphere. The glycol also absorbs a small amount of methane, and 

can be driven off to the atmesphere through the reboiler vent. 

EMISSION FACTOR: (117.18 scf!MMscf -:1: 159.76%) 

A thennodynamic computer simulation was used to determine the most important emission·affecting variables 

existence 

for dehydrators. The variables are: gas throughput, existence of a flash tank, existence of stripping gas, 

linear, 

of a gas-assisted pump, existence of vent controls routed to a burner. Throughput, since its effect is 

established 

is ·handled by-establishing an emission rate per gas throughput Emission rates per throughput are then 

for the other important emission affecting characteristics. The emission factor is then: 

EF = [ ( FFT x EFFT) + ( FNT x EFN,.) + ( ?sG x EFsG) J x FNVc x 0C 

EF =I (0.520 X 3.57) + (0.480 X 175.10) + (0.080 X 670) J X 0.840 X 1.0 

FFT = Fraction of the population WITH flash tanks 

0.520 ± 33.56% 

F ~><"D = Fraction of the population WITHOUT flash tanks 

0.480 ± 36.25% 

F sG = Fraction of the population WITH stripping gas 

0.080 ± I 18.44% 

F ~><"Vc= Fraction of the population WITHOUT com busted vent controls 

0.840 ± 15.24% 

EFFT= Total CH4 emission rate per 1 MMscf throughput for dehydrator that has a flash 

tank 

3.57 (+102% /-58%) 

EF:-T~ Total CH. emission rate per 1 MMscf throughput for dehydrator that does NOT 

have a flash tank 

175.10 ( ... JOI% I -50%) 

EF sG= Incremental emission rate ~r 1 MMscfd throughput for dehydrator that has stripping 

gas 

670 (+40% I -60%) 

OC = Overcirculation factor for glycol--number of times the industry rule-of-thumb of 3 

gallons glycoVIb water 

1.0 ± 0% 

C-29 
EF DATA SOURCESc 

I. Methane Emissions from the Natural Gas Industry, Volume 14.- Glycol Dehydrators (l) 

establishes emission affecting characteristics of dehydrators. 

2. Site visit data establishes the Fsv and FNVc for multiple sites. Wyoming ADQ data also 

verifies Fwo though it implies a higher F, and thus a higher overall EF. 

3. TMOGA/GPA survey of :019 dehydrators established F3p and F~"D and TP for dehydrators. 

4. ASPEN computer simulations were used to detennine EFJP• and EF~-u from tt,e dehydrator 

vent. 

5. Sampling data from the GRl Glycol Dehydrator Sampling and Analytical Program for one 

dehydrator was used to detennine EFsv (I). The upper bound was calculated by assuming 

that 

methane. 

all of the measured noncondensable vent gas was due to stripping gas that was l 00% 

The lower bound was calculated as the rule-of-thumb stripping gas rate 

recommended by a glycol dehydrator manufacturer. 

EF ACCURA.CY: 117.18 ± 159.76% 

Basis: 

The accuracy is propagated through the EF calculation from each tenn's accuracy: 

I. ASPEN has been demonstrated to match actual dehydrators within ±20% within the 

calculated confidence intenrals obtained from site data. 

2. Individual EF confidence intervals were calculated based upon the spread of the site 

averages. 

ACTIVITY FACTOR: (2.00 Tscfi'year gas throughput in the storage segment) 

amount 

The amount 

of gas 

of 

withdrawn 

gas processed by glycol dehydrators in the storage segment was calculated from the estimated 

assumed 

from underground storage. A total of2.4 Tscfwas withdrawn in 1992, and it is 

that most stored gas is dehydrated. 

AF ACCURACY: 2.00 Tscf/year ± 25% 

Basis: 

I. Uncertainty based on estimate of confidence limits. 

ANNUAL METHANE EMISSIONS: (0.2344 Bscf ± 166.56%) 

factor. 

The annual methane emissions were detennined by multiplying the dehydrator emission factor by the activity 

REFERENCES 

I. 

Report, 

Myers, D. 

GRI-94/0257.31 

Methane Emissions from the Natural Gas Industry, Volume 14: Glycol Dehydrators, Final 

and EPA-600/R-96-080n. Gas Research Institute and U.S. Environmental 

Protection Agency, June 1996. 

C-30 
APPENDIX D 

Distribution Source Sheets 

D-1 
APPENDIX D 

Distribution Source Sheets 

Page 

D-1 - Meter and Pressure Regulating Stations . . . . . . . . . . . . . . . . . . D-4 

D-2 - Pipeline Leaks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . D-7 

D-3 - Maintenance/Upsets (PRV) .. .. .. .. .. .. .. .. .. .. .. .. .. D-11 

D-4 -

D-5 -

Pipeline Dig-ins 

Customer Meters 

D-12 

D-14 

D-6 - Pipeline Blowdown . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . D-17 

D-2 
DISTRIBUTION SOURCE SHEETS 

This section contains the specific source sheets for the distribution segment of the natural 

gas industry. The following table serves as a guide for finding sheets in this section. The 

cells in the table give the sheet number (D-l, D-2, etc.) of the source sheet. The rows 

define the equipment covered, while the columns define the emission type. A category 

with no sheet number means that the emissions from that area were detennined to be zero 

or negligibly small. The label for each source sheet is shovm at the top of the cover page 

for that sheet. 

TABLE OF OPERATING MODE, 

CONTENTS EMISSION TYPE (Fugitive, Vented, or Combusted) 

Start Up N onnal Operations Maintenance Upsets Mishaps 

EQUIPMENT' v c F v c v c v c v 

Meter/Pressure D-1 D-1 D-3 D-3 

Regulating Stations 

Main and Service D-2 D-6 D-4 

Pipelines 

Customer Meters D-5 

D-3 
SOURCES, 

OPERATING MODE' 

EMISSION TYPE' 

ANNUAL EMISSIONS: 

BACKGROUND' 

D-1 

DISTRIBUTION SEGMENT SOURCE SHEET 

Meter/Pressure Regulating Stations 

Nonnal Operations 

Steady, Fugitive 

27.3 +1- 23.3 Bscf 

Metering/pressure 

custody 

regulating stations are located throughout the distribution network to meter gas where a 

Emissions 

transfer occurs and/or to reduce and regulate the pressure in the downstream main pipeline. 

continuous 

from 

and 

fugitive losses and normal operations at meter and pressure regulating stations include both 

flanges, 

intermittent emissions from.equipment components, such as pneumatic devices, valves, 

flow meters, and pressure regulators. 

EMISSION FACTOR: (scf/station-hour) 

for 

The 

different 

emission factor and standard deviation are given below for facilities located in vaults and above ground 

inlet pressure ranges: 

Standard Precision 

Average Deviation of 

Inlet 

Station 

EmissioD of Emission Emission 

Type 

Pressure Location in Number of Factor Factor Factor 

(psig) Vault? Samples (scf/sta.-br) (scf/sta.-hr) (scf/sta.-br) 

M&R >300 N 31 179.8 236.! 69.8 

M&R 100-300 N 6 95.6 130.6 107.4 

M&R <100 N 3 4.3 5.8 9.8 

Regulating >300 N 13 161.9 188.8 93.3 

Regulating >300 y 4 13 2.0 2.4 

Regulating 100-300 N 7 40.5 36.4 26.7 

Regulating 100-300 y 10 0.2 0.3 0.2 

Regulating 40-100 N 7 1.0 1.1 0.8 

Regulating 40-100 y 8 0.1 0.1 0.1 

Regulating <40 y 6 0.1 0.2 0.2 

The emission factors were derived from data collected using a tracer gas measurement method. Downwind 

northeastern 

tracer measurements 

companies, 

were performed by Aerodyne/Washington State University at 2 West Coast companies, 3 

performed on metering/regulating 

4 midwestern towns, and 3 southern plains towns. In total, 95 measurements were 

stations in distribution and transmission systems. 

D-4 
The test data were analyzed to evaluate the differences in emissions from stations with different 

vaults 

configurations 

versus 

(i.e., metering/regulating versus regulating only), inlet pressure ranges, and locations (i.e., in 

above.ground). The test data were disaggregated into four distinct inlet pressure categories 

and 

(>300 

pressure 

psig, 100-300 psig, 40·100 psig, and <40 psig), two station types {meter/pressure regulating facilities 

categories. 

regulating facilities), and into stations in vaults versus above-ground, resulting in a total of 10 

These categories were selected for disaggregation of the data based on knowledge of the gas 

industry, and were confirmed to be statistically significant based on the data analyses. 

ACTMTY FACTOR: (number of stations) 

below: 

The mean activity factor and standard deviation for each station type/inlet pressure/location category is given 

Standard 

Average Deviation Precision 

Inlet Activity of Activity of Activity 

Station 

Type 

Pressure Location in Stations per Factor Factor Factor 

(psig) Vault? Mile (stations) (stations) (stations) 

M&R >300 N 0.004 3,460 3,965 2,458 

M&R 100·300 N 0.016 13,335 22,728 14,091 

M&R <!00 N 0.009 7,127 13,550 8,401 

Regulating >300 N 0.005 3,995 4,946 2,702 

Regulating >300 y 0.003 2,346 2,905 1,587 

Regulating 100·300 N 0.015 12,273 13,656 7,461 

Regulating 100-300 y 0.007 5,514 6,136 3,352 

Regulating 40·100 N 0.043 36,328 42,785 23,375 

Regulating 40·100 y 0.039 32,215 37,942 20,729 

Regulating <40 y 0.018 15,377 18,161 9,922 

The number of stations in each inlet pressure/station type category were provided by twelve distribution 

companies. The data were extrapolated based on the total mileage of distribution main pipeline in the 

respective 

average of 

companies. The mean number of stations in each category per mile of main was estimated as the 

of 

the values from eleven of the twelve companies supplying data. Based on conversations with one 

the companies supplying data, the average number of stations per mile for the one company were not 

considered 

overall 

representative of typical industry practices. Therefore, this company was not included in the 

average, but rather was treated separately. The standard deviation represents the variation in the 

estimated 

confidence 

number of stations per mile of main pipeline for each company. The precision represents the 90'% 

interval around the estimated mean activity factor. 

stations 

The extrapolation from stations per mile to total stations in the U.S. was implemented by multiplying the 

per mile for each category by the total U.S. mileage of main pipeline: 836,760 miles. 

regulating 

Data were collected from five companies representing urban, rural, and suburban areas on the number of 

stations in vaults versus above-ground in the U.S. On average, 37% of the regulating stations with 

D-5 
between 

an inlet pressure 

40 and 

greater than 300 psig are located in vaults. For regulating stations with an inlet pressure 

areas were above-ground. 

300 psig, it 

On 

was found that the majority of stations in urban areas were in vaults and in rural 

inlet pressure between 

average, it was estimated that 31% of the stations are located in vaults with an 

psig, 47% of 

I 00 and 300 psi g. For regulating stations with an inlet pressure between 40 and l 00 

{ <40 psig 

the stations are located in vaults. Based on the data collected, the majority of the low pressure 

inlet pressure) stations are located in vaults. 

ANNUAL EMISSIONS ESTIMATE: (27.3 +/- 23.3 Bscf) 

90% Confidence 

Average Average Annual Interval of 

Station 

Inlet Activity Emission Emissions Emissions 

Type 

Pressure Location Factor Factor Estimate Estimate 

(psi g) in Vault? (stations) (scf/sta.-hr) (Bscf) (Bscf) 

M&R >300 N 3,460 179.8 5.5 4.7 

M&R 100-300 N 13,335 95.6 11.2 21.7 

M&R <100 N 7,127 4.3 0.3 1.2 

Regulating >300 N 3,995 16!.9 5.7 5.5 

Regulating >300 y 2,346 1.3 0.03 0.06 

Regulating 100-300 N 12,273 40.5 4.4 4.3 

Regulating 100-300 y 5,514 0.2 0.01 0.01 

Regulating 40-100 N 36,328 1.0 0.3 0.4 

Regulating 40-100 y 32,215 0.1 0.02 0.02 

Regulating <40 y 15,377 0.1 0.02 0.03 

Total 131,970 27.3 23.3 

The emissions estimate for each category of station was derived by multiplying 

(scf/station-hr) by 

the respective emission factor 

assuming continuous 

the activity factor (number of stations), and converted to an annualized estimate by 

confidence 

fugitive leakage (i.e., 8760 hour per year leakage). The precision represents the 90% 

interval around the estimated mean emissions for each category. 

D-6 
D-2 

DISTRIBUTION SEGMENT SOURCE SHEET 

SOURCES: 

OPERATING MODE: 

EMISSION TYPE: 

ANNUAL EMISSIONS: 

BACKGROUND: 

Main and Service Pipeline 

Normal Operations 

Steady, Fugitives (Leakage) 

41.6 Bscf ... ;_ 65% 

Distribution mains are the pipelines that serve as a common source of natural gas supply for more than one 

customer. Services are the branch connection lines from the mains to the customer meters. Leakage from the 

Gas 

underground distribution network occurs from corrosion pits, joint and fitting failures, and pipe wail fractures. 

distribution operators use leak detection procedures to locate and classify leaks. The leak is classified 

and prioritized for repair based on the concentration of gas detected and the proximity of the leak to existing 

structures. 

EMISSION FACTOR: (sc£11eak-year) 

The value of the emission factor and standard deviation for each pipe material category is given below: 

Material Pipe Use Number Average Units of 90% 

Category of Emission Emission Confidence 

Samples Factor" Factor Interval of 

Emission 

Factor 

Cast Iron Main 2! 238,736 scfi'mi-yr 152,059 

Unprotected Main 20 51,802 scfllk-yr 48,212 

Steel 

Protected Steel Main !7 20.270 scfi'lk-yr 17,243 

Plastic Main 6 99,845 scfi'lk-yr 165,617 

Unprotected Service 13 20,204 scfi'lk-yr 21,129 

Steel 

Protected Steel Service 24 9,196 scf/lk-yr 5,58! 

Plastic Service 4 2.386 scfi'lk-yr 3,412 

Cooper Service 5 7,684 scfi'lk-yr 5,559 

Aajustea tort e sou oxtaauon or metnane. 

A cooperative leak measurement program has been C.eveloped to measure a representative sample of 

underground leaks to estimate the average leak ·intensity, which is combined with company leak records to 

estimate leak frequency. Leak measurements were perfonned at five U.S. companies and two Canadian 

distribution companies in accordance with the testing protocol develop~d as part of the program. The test 

data were disaggregated by material type and mains versus services, based on a combination of statistical 

analyses and engineering judgement. A mean value of the estimated leak rate per leak was calculated using 

D-7 
the test data, for all pipe materials except cast iron. In these tests, an individual leak was randomly selected 

measure 

for testing based on criteria outlined in the program plan. For cast iron, long segments of pipe were tested to 

the leak rate per mile rather than the leak rate per leak. Cast iron was tested in long segments since 

it tends to have a very high frequency of leaks (due to the joint spacing of 10 to 16 feet) and the relatively 

high occurrence of undetectable leaks in cast iron. The measured natural gas leak rates were adjusted for the 

average 

methane. 

volume percent of methane in pipeline·quality gas {93.4 vol. %), and the soil oxidation rates of 

ACTIVITY FACTOR, 

The mean activity factor and standard deviation for each pipe material category is given below: 

Material Pipe Use Estimated Average Units of Activity 90% 

Category Total Leak Activity Factor Confidence 

Repairs Factor Interval of 

(Equivalent Activity Factor 

Leaks) 

Cast Iron Main 69,776 55,288 miles 2,764 

Unprotected Main 81,627 174,657 equivalent leaks 101,685 

Steel 

Protected Steel Main 3!,924 68,308 equivalent leaks 42,545 

Plastic Main 23,006 49,226 equivalent leaks 58,0!8 

Unprotected Service 214,271 458,476 equivalent leaks 499,850 

Steel 

Protected Steel Service 182,562 390,628 equivalent leaks 526,354 

Plastic Service 32,202 68,903 equivalent leaks 66,840 

Copper Service 3,608 7,720 equivalent leaks 8,521 

were 

The national database of leak repairs was used to extrapolate data provided by individual companies. Data 

requested from each company participating in the underground leak test program, based on their 

historical leak records. To allocate leak repairs into pipe material categories, data were collected from ten 

local distribution companies representing different regions within North America. 

Data on the total number of annual leak repairs, leak indications, and outstanding leaks within the distribution 

system were provided by six companies. An estimate of the number of annual equivalent leaks for each of 

the six companies was developed based on the following methodology: 

Total Equivalent Leaks =Outstanding Leaks+ New Leaks- Leak Repairs 

The total number of annual equivalent leaks represents the equivalent leaks which are leaking all year. (That 

is, for leaks with a leak duration of half year, these leaks are counted as half an equivalent annual leak.) 

The total number of leaks in the system are quantified by incorporating the leak duration into the estimated 

The 

equivalent leaks. For example, if a leak is only leaking half the year, it is counted as 0.5 equivalent leaks. 

assumptions made in deriving the estimated number of equivalent leaks for each company include: 

D-8 
Approximately 85 percent of leaks are found during a leak survey when an organic vapor 

analyzer (OVA) instrument is used along with bar holing. 

Leaks that are repaired during the year are leaking half of the year, on average. 

Outstanding leaks are leaking at the beginning of the year. 

The number of new leaks in the system is estimated based on the annual leak indications and 

the frequency of the leak survey. 

The number of new leaks in a system that is surveyed every n years is calculated based on the following: 

For the frrst year in the cycle -- lin leaks are leaking half the year; (n-1 )In leaks are not yet 

leaking. 

For the second year in the cycle -- !In leaks are leaking the entire year; 1/n leaks are leaking 

half the year; and (n-2)/n leaks are not yet leaking. 

For the third year in the cycle -- 2/n leaks are leaking the entire year; 1/n leaks are leaking 

half the year; and (n-3)/n leaks are not yet leaking. 

For the founh year in the cycle - 3/n leaks are leaking the entire year; lin leaks are leaking 

half the year; and (n-4)/n leaks are not yet leaking. 

was 

Based on the data provided by each of the six companies, a ratio of the annual equivalent leaks to leak repairs 

material 

calculated. The average ratio (2.14) was multiplied by the estimated number of leak repairs in each pipe 

precision 

category to extrapolate the national database of leak repairs to represent anhual equivalent leaks. The 

of the estimate is based on the variability in the leak repair disaggregation provided by ten 

companies. 

companies and the variability in the calculated ratio of annual equivalent leaks to leak repairs provided by six 

The activity factor for cast iron mains is the total estimated mileage of cast iron mains in the U.S., as reported 

by the U.S.DOT RSPA (I). The standard deviation was assumed to be 5% of the estimated mileage, based 

on engineering judgement. 

D-9 
EMISSIONS ESTIMATE: (41.6 +/- 65 %) 

The emissions estimate for each category of pipe material/use was dervied multiplying the respective emission 

factor (scf/leak-yr or scf/miie-yr) by the aC"::ivity factor (total number of leaks or miles). 

Material 

Category 

Cast Iron 

Unprotected Steel 

Protected Steel 

Plastic 

Unprotected Steel 

Protected Steel 

Plastic 

Copper 

Total 

•scf/mile-yr 

bmiles 

REFERENCES 

Pipe Average 

Use Emission 

Factor 

(scUik-yr) 

Main 238,736' 

Main 51,802 

Main 20,270 

Main 99,845 

Service 20,204 

Service 9,!96 

Service 2,386 

Service 7,684 

Average Annual 90% Confidence 

Activity Emissions Interval of 

Factor Estimate Emission Estimate 

(equivalent (Bsc~ (Bsc~ 

leaks) 

55,288b 13.2 8.4 

174,657 9.! 11.1 

68,308 !.4 !.6 

49,226 4.9 !3.9 

458,476 9.3 17.5 

390,628 3.6 6.! 

68,903 0.2 0.4 

7,720 0.! 0.! 

41.6 27.1 

I. U.S. Department of Transportation. Research and Special Programs Administration. 1991. 

D-10 
SOURCES: 

OPERATING MODE: 

EMISSION TYPE: 

ANNUAL EMISSIONS: 

BACKGROUND: 

D-3 

DISTRIBUTION SEGMENT SOURCE SHEET 

Pressure Relief Valves 

Maintenance/Upsets 

Unsteady, Vented 

0.04 Bscf ± 3,919% 

Pressure relief valves (PRVs) are often used in the distribution network to prevent the over·pressure of 

distribution main pipelines. Typically, PRVs are used in conjunction with pressure regulators as a secondary 

protection mechanism in the event of regulator failure. Gas is released during any emergency actuation of the 

PRVs. 

EMISSION FACTOR: 0.050 ± 3,914% Mscf/mile 

(Adjusted for the distribution methane fraction of natural gas of 93.4 mol%) 

The estimated emission factor was based on two separate distribution company studies which quantified losses 

from PRVs as part of unaccounted-for (UAF) gas studies. The studies calculated PRV releases per mile of 

pipeline mains. The GRIIEPA emission factor was estimated as the ratio of emissions per mile of main from 

the two companies, and corrected for the methane composition in distribution. 

EF PRECISION: ± 3,914% 

Basis: 

The precision was calculated using the method outlined in the Statistics Report (I). 

ACTIVITY FACTOR: 836,760 ± 5% miles of main 

The activity (actor is based on the total miles of distribution main pipeline in the U.S. 

AF PRECISION: ± 5% 

Basis: 

The accuracy was assigned based on engineering judgement. 

ANNUAL METHANE EMISSIONS: 0.042 ± 3,919% Bscf 

The annual methane emissions were determined by multiplying an emission factor (annual methane emissions 

per mile of main) by the activity factor {miles of distribution main pipeline nationally). 

REFERENCES 

1. Williamson, HJ., M.B. Hall, and M.R. Harrison. Methane Emissions from the Natural Gas Industry, 

Volume 4: Statistical Methodology, Final Report, GRI-94/0257.21 and EPA-600/R-96-080d, Gas 

Research Institute and U.S. Environmental Protection Agency, June 1996. 

D-11 
D-4 

DISTRIBUTION SEGMENT SOURCE SHEET 

SOURCES: 

OPERATING MODE: 

EMISSION TYPE: 

ANNUAL EMISSIONS: 

BACKGROUND: 

Pipeline 

Mishaps (Dig-ins) 

Unsteady, Fugitive 

2.1 Bscf ± 1,925% 

Dig-ins are distribution main or service pipeline ruptures caused by unintentional 

distribution companies 

third-party damage. Some 

records of estimated 

estimate and record the quantity of gas lost during a dig-in event; therefore, they keep 

ins was detennined. 

annual losses due to dig-ins. From these annual records, a national emission rate for digANNUAL EMISSION FACTOR: 1.59 ± 1,922% Msc£1mile 

(Adjusted for the distribution methane fraction of natural gas of 93.4 mol%) 

The 

Pacific 

emission 

Gas 

factor was derived from four distribution company estimates of the losses from dig-ins: the 

and Electric unaccounted-for 

estimated at 

(UAF) gas study {I) results showed that losses from dig-ins were 

Company estimate 

91,178 Mscf for 58,024 miles of distribution mains and services; the Southern California Gas 

services; 

(2) of losses from dig-ins was 170,457 Mscf for 82,337 miles of distribution mains and 

mains and 

a third company estimate of losses from dig-ins was 19,581 Mscf for 24,916 miles of distribution 

distribution 

services; 

mains. 

and a fourth company reported dig-in losses of 10,453 Mscf for 18,713 miles of 

used to estimate 

The ratio of the total dig-in emissions to the total pipeline miles from these companies was 

the national methane emission factor, resulting in 2.06 Mscfi'mile. 

EF PRECISIONo 

Basis: 

± 1,922% 

Methane 

The precision 

Emissions 

was calculated from the spread of the company data using the method presented in the 

from the Natural Gas Industry, Volume 4: Statistical Methodology (3). 

ACTIVITY FACTORo 1,297,569 ± 5% miles of mains and services 

Transportation, 

The total number 

Research 

of miles of main pipeline in the U.S. gas industry was based on U.S. Department of 

and Special Projects Administration 

reported 

(4). The total miles of service pipeline was 

in A.G.A.'s Gas Facts, 1990 (5). 

AF PRECISION: ± 5% 

Basis: 

data. 

A 5% confidence bound was assigned on the basis of good precision from national statistics of ~ 990 

ANNUAL METHANE EMISSIONS; 2.06 ± 1,925% Bscf 

per 

The 

mile 

annual methane emissions were determined by multiplying an emission factor (annual methane emissions 

of pipeline) by the activity factor (number of miles). 

D-12 
REFERENCES 

I. Pacific Gas & Electric Company and Gas Research Institute. Unaccounted-For Gas Project. Volume 

l, Final Report, San Ramon, CA, June 7, !990. 

2. Southern California Gas Company and Gas Research Institute. A Study of the 1991 Unaccounted-For 

Gas Volume at the Southern California Gas Company, Final Report, Los Angeles, CA, April 1993. 

3. Williamson, H.J., M.B. Hall, and M.R. Harrison. Methane Emissions from the Natural Gas Industry, 

Volume 4. Statistical Methodology, Final Report, GRI-94/0257.21 and EPA-600/R-96-080d, Gas 

Research Institute and U.S. Environmental Protection Agency, June 1996. 

4. U.S. Department of Transportation, Research and Special Projects Administration, Washington, DC, 

1991. 

5. American Gas Association. Gas Facts, 1992 Data, Arlington, VA, 1993. 

D-!3 
SOURCES' 

OPERATING MODE' 

EMISSION TYPE: 

ANNUAL EMISSIONS' 

BACKGROUND' 

D-5 

DISTRIBUTION SEGMENT SOURCE SHEET 

Customer Meters 

Normal Operations 

Steady, Fugitive 

5.8 ± l.l bscfy 

Losses from customer meters are caused by fugitive leakage from the connections and other fittings 

surrounding the meter set. 

EMISSION FACTOR: (outdoor residential meters: 138.5 ± 23.1 scffmeter-yr 

commerciaVindustrial meters: 47.9 ± 16.7 scfi'meter-yr) 

The estimate of leakage from customer meters is based on screening and bagging studies conducted at ten 

the 

sites 

west 

throughout 

coast 

the United States. The initial study was conducted by Indaco to measure customer meters in 

[Indaco Air Quality Services, Inc., Methane Emissions from Natural Gas Customer Meters: 

Screening and Enclosure Studies, draft repon, August 15, 1992 (!)]. Data were also collected at nine 

site, 

additionai sites across the United States, including three east coast sites, a mid·western site, a rocky mountain 

each 

and 

of 

five western U.S. sites. A summary of the average emissions from residential customer meters from 

the ten sites is shown in the foilowir.g table: 

Site Number of Meters Number of Meters Average Leak Rate • Standard 

Screened Leaking (lb methane/day) Deviation• 

(lb methane/day) 

Site I •• West Coast 134 37 0.0098 0.0239 

Site 2 - East Coast 40 29 0.0002 0.0004 

Site 3 •• East Coast 158 37 0.0789 0.!753 

Site 4 •• Mid· West 156 8 0.0057 0.0061 

Site 5 •· Rocky 188 28 0.0035 

Mountain 

0.0082 

Site 6 ·• West Coast 194 5 0.0002 0.0001 

Site 7 ·· South East 201 56 0.0146 0.0328 

Site 8 -- North West IOI 31 0.0101 0.0199 

Site 9 -· South West 150 50 0.0222 0.0404 

Site l 0 - North West 150 40 0.0125 0.0230 

•A verage value for all meters (i.e., leaking and non-leaking) screened at the site. 

D-14 
The average emission factor 

the ten sites. The 

for residential customer meters was derived by averaging the emission rates for 

leaking meters were 

emission factor was converted to units of scfi'meter-yr by assuming that the losses from the 

continuous throughout the year. 

for 

The precision represents the 90 % confidence interval and was calculated by averaging the standard deviations 

the ten sites. 

The emission factor for commerciaVindustrial 

total of four 

customer meters was derived from screening data collectea at a 

table: 

sites. A summary of the average emissions from each of the four sites is shown in the following 

Site Number of Meters Number of Leaking Average Leak Rare• Standard Deviationa 

Screened Meters (lb methane/day) (lb methane/day) 

Site 3 ·- East Coast 45 12 0.0112 0.0251 

Site 4 --Mid-West 61 0 -- --

Site 5 ·- Rocky 21 

Mountain 

6 0.0088 0.0076 

Site 6 -· West Coast 22 I 0.0018 --

•Average value for all meters (i.e., leaking and non-leaking) screened at the site. 

The average emission factor for commerciaVindustrial 

rates for 

customer meters was derived by averaging the emission 

losses 

the four sites. The emission factor was converted to units of scf/meter-yr by assuming that the 

from the leaking meters was continuous throughout the year. 

ACTIVITY FACTOR: (outdoor residential meters: 40,049,306 ± 4,200,135 

commercial/industrial meters: 4,608,000 ± 230,400) 

The total number of customer meters in the U.S. gas industry, 56,132,300, and the number of residential 

residential 

customer meters, 

customer 

51,524,600, 

meters 

were based on Gas Facts, American Gas Association, 1992 {2). The number of 

total customers presented 

located indoor-s versus outdoors was estimated based on a regional breakdown of 

within different 

in Gas Facts (2) combined with data obtained from 22 individual gas companies 

regions of the country. (Note: The number of customers in each region was used to estimate 

available.) 

the number of indoor meters because data on number of customer- meters segregated by region were not 

Following is the average percentage of customer meters located indoors in each region: 

D-15 
Total 

Residential Average Percent 

Region Customers Indoor Meters 

New England 1,886,500 52 

Middle Atlantic 8,403,400 61 

East North 11,633,500 17 

Central 

West North 4,684,100 40 

Central 

South Atlantic 4,987,700 21 

East South 2,465,200 0 

Central 

West South 5,666,600 0 

Central 

Mountain 3,318,700 0 

Pacific 9,724,500 5 

TOTAL 52,770,200 

"Estimated based on engineering judgement. 

bEstimated for each state separately in region. 

Estimated 

Sample Indoor 

Size Meters Precision 

1 980,980 471,625" 

7 5,126,074 1,905,371 

7 1,977,695 1,461,663 

I 1,873,640 1,873,640' 

4 l,030,680b I ,030,680' 

-- 0 123,260' 

-- 0 283,330" 

- 0 331,870' 

2 486,225 486,225' 

22 1!,475,294 3,317,254 

<Estimated based on industry comments suggesting that customer meters in southern regions are essentially all 

located outdoors. 

The estimated number of indoor meters, 1!,475,294, was subtracted from the total number of reported meters, 

precision 

5!,524,600, 

was 

to derive an estimated 40,049,306 outdoor residential customer meters in the United States. The 

estimated from the data provided by the companies, engineering judgement for some regions, 

and an estimated 5% error in the nationally reported number of residential customer meters. 

The leakage rates from customer meters located indoors was as~umed to be negligible based on the increased 

probability that leaks on indoor meter sets are detected and repaired promptly. This assumption of negligible 

leakage from indoor meters is consistent with the fmdings from pressure regulating stations located in vaults. 

The precision of the total estimated commercial/industrial customer meters is assumed to be ± 5% of the 

estimated 4,608,000 meters. 

ANNUAL METHANE EMISSIONS: (5.8 ± 1.1 Bscflyr) 

REFERENCES 

1. Indaco Air Quality Services, Inc. Methane Emissions from Natural Gas Customer Meters: Screening 

and Enclosure Studies, Draft Report, August 15, 1992. 

2. American Gas Association. Gas Facts. Arlington, VA. 1992. 

D-16 
SOURCES: 

OPERATING MODE: 

EMISSION TYPE: 

ANNUAL EMISSIONS: 

BACKGROUND: 

D-6 

DISTRIBUTION SEGMENT SOURCE SHEET 

Pipeline 

Maintenance 

Unsteady, Vented 

0.13 Bscf ± 2,524% 

Gas is blown to the atmosphere as a result of pipeline abandonment, installation, and repair. 

ANNUAL EMISSION FACTOR: 0.102 ± 2,521% Mscfi'mile 

(Adjusted for the distribution methane fraction of natural gas of 93.4 mol%) 

The emission factors for pipeline b!owdown are based on estimates from four companies: 

Electric Unaccounted·for Gas 

the Pacific Gas & 

{2); and two additional company 

(UAF) Project, !987 (l); the Southern California Gas Company (SoCal) project 

percent methane. The 

estimates. The estimated total gas losses were adjusted for 93.4 volume 

companies was 

annual methane emissions per mile of mains and services for each of the four 

following table 

calculated 

summarizes 

based on the ratio of emissions to miles of distribution mains and services. The 

of the estimate 

the individual company estimates and the national emission factor. The precision 

is based on the 90 percent confidence level for the four companies providing data. 

A11nuaf Annual 

Blowdown Bfowdown Methane 

Company 

Methane Pipeline Emission Factor, 

Emissions, Mcsf Miles scUmile 

8,972 58,024 0.155 

2 5,688 82,337 0.069 

3 2,360 24,916 0.095 

4 1,695 18,713 0.091 

TOTALS 18,715 183,990 

ANNUAL BLOWDOWN EF, Mscf methane/mile 0.102 ± 2,521% 

ACTIVITY FACTOR: (1,297,569 ± 5% miles mains and services) 

Transportation, 

The total number 

Research 

of miles main pipeline in the U.S. gas industry was based on U.S. Department of 

and Special Projects Administration 

Gas Facts (4). The precision, 

(3). The total miles of service was reported in 

or 90 percent confidence 

engineering judgement. 

level, was estimated to be ± 5%, based on 

ANNUAL METHANE EMISSIONS: 0.13 ± 2,524% Bscf 

per 

The 

mile 

annual 

of pipeline) 

methane emission~ were detennined by multiplying an emission factor (annual methane emissions 

by the activity factor (number of miles). 

D-17 
REFERENCES 

I. 

Volume 

Pacific Gas & Electric Company and Gas Research Institute. Unaccounted-For Gas Project. 

1, Final Report, San Ramon, CA, June 7, 1990. 

2. 

Gas 

Southern California Gas Company and Gas Research Institute. A Study of the 1991 Unaccounted-For 

Volume at the Southern California Gas Company, Final Report, Los Angeles, CA, April 1993. 

3. U.S. 

1991. 

Department of Transportation, Research and Special Projects Administration, Washington, DC, 

4. American Gas Association. Gas Facts, 1992 Data, Arlington, VA, 1993. 

D-18 
APPENDIX E 

Conversion Table 

E-1 
Unit Conversion Table 

English to Metric Conversions 

1 scf methane ~ I9.23 g methane 

1 Bscf methane ~ O.OI923 Tg methane 

1 Bscf methane ~ '9,230 metric tonnes methane 

I Bscf ~ 28.32 million standard cubic meters 

I short ton (ton) ~ 907.2 kg 

I Ib ~ 0.4536 kg 

1ft' ~ 0.02832 m' 

I ft' ~ 28.32 liters 

I gallon ~ 3.785 liters 

I barrel (bbl) ~ 158.97 liters 

I inch ~ 2.540 em 

I ft ~ 0.3048 m 

1 mile ~ 1.609 km 

I hp ~ 0.7457 kW 

I hp-hr ~ 0.7457 kW-hr 

I Btu ~ 1055 joules 

I MMBtu = 293 kW-hr 

I lb!MMBtu ~ 430 !ifGJ 

T ("F) ~ 1.8 T ("C)+ 32 

I psi ~ 51.71 mm Hg 

Global Warming Conversions 

Calculating carbon equivalents of any gas: 

MMTCE = (MMT of gas) x (MW, carbon) x (GWP) MW, gas 

E-2 
Calculating C02 equivalents for methane: 

MMT of C02 equiv. = (MMT CH,) X X (GWP) (

MW, co,) 

MW, CH4 

where MW (molecular weight) of C02 ~ 44, MW carbon~ 12, and MW CH4 ~ 16. 

Notes 

scf 

Bscf 

Tscf 

MMscf 

Mscf 

Tg 

Giga (G) 

Metric tonnes 

psta 

scfd,sczy 

mol% 

vol% 

Standard cubic feet. This is the cubic feet that the gas would 

occupy if it were at the standard conditions of 14.73 psi, absolute, 

and 60°F. For a fixed gas composition, a scf defines a mass. 

Billion standard cubic feet (109 scf). 

Trillion standard cubic feet (1012 set). 

Million standard cubic feet. 

Thousand standard cubic feet. 

T eragrarn (I 0" g) . 

Same as billion (1 09

). 

1000 kg. 

Gauge pressure. 

Absolute pressure (note psia = psig + atmospheric pressure). 

Standard cubic feet per day, standard cubic feet per year. 

Percent of molecules in a stream that are of one type. 

Percent of the volume of a stream that is of one species. For an 

ideal gas, vol% is equal to mol%. 

E-3 
wt% 

Prod 

Proc 

Trans 

Dist 

GWP 

MMT 

MMTCE 

= Percent of the mass (weight) of a stream that is of one sp~cies. 

= Production 

= Gas Processing 

Transmission 

Distribution 

= Global Warming Potential of a particular greenhouse gas for a given 

time period. 

= Million metric tonnes of a gas. 

= Million metric tonnes, carbon equivalent. 

MMT of C02 eq. ~ Million metric tonnes, carbon dioxide equivalent. 

E-4 
TECHNICAl REPORT DATA (PI~ read IIUhv.ctiOIU on tht: «VUU h<[ou rompleting) 

1. REPORT NO. 

EPA-600/R-96-080c 3. RECIPIENT'S ACCESSION NO. 

4. TITLE ANO SUBTITLE 

Methane Emissions 5. REPORT DATE 

from the Natural Gas Industry, 

Volumes l-15 (Volume 3~ General Methodology) June 1996 . PERFORMING ORGANIZATION CODE 

7.AUTHOAIS) L. Campbell, M. Campbell. M. Cowgill, D. Ep- person, M. HalL M. Harrison, K. HummeL D.l\1yers, T. Shires, B. Stapper, C. Stapper, J. Wessels, and * 

B. PERFORMING ORGANIZATION REPORT NO. 

DCN 96-263-081-17 

9. PERFORMING OAOANIZATION NAME AND ADDRESS 

Radian International LLC 

P. 0. Box 201088 

Austin, Texas 78720-1088 

12. SPONSORING AGENCY NAME AND ADDRESS 

EPA, Office of Research and Development 

10. PROGRAM Et.EMENT NO. 

11. CONTRACT/GRANT NO. 

5091-251-2171 (GRI) 

68-DI-0031 (EPA) 

13. TYPE OF R~PORT ~NO PERIOD COVERED 

Final; 3 91-4;96 

- Air Pollution Prevention and Control Division 

Research Triangle Park, NC 27711 

1•. SPONSORING AGENCY CODE 

EPA/600/13 

1s...suPPt.EMENTARY Nons EPA project officer is D. A. Kirchgessner. MD-63, 919/541-4021. 

~V>awr 

l~ ... osponsor Ave. 

GRI project officer is R. A. Lett, Gas Research Institute. 8600 West Bryn , Chicago, IL 60631. (*)H. Williamson (Block 7), 

~ 1&. ABSTRACT The 15-volume report summarizes the results of a comprehensive program 

~ o quantify methane (CH4) emissions from the U.S. natural gas industry for the base 

brear. The objective was to determine CH4 emissions from the wellhead and ending 

~ownstream at the customer's meter. The accuracy goal was to determine these -

lemissions within +/-0. 5% of natural gas production for a 90% confidence interval. Fm 

(the 1992 base year. total CH4 emissions for the U.S. natural gas industry was 314 

+I- 105 Bscf (6. 04 +{- 2.01 'Tg). This is equivalent to!. 4 +I- 0. 5% of gross natural 

gas production, and reflects neither emissions reductions (per the voluntary AmeriGas Association/EPA Star Program) nor incremental increases (due to increased 

gas usage) since 1992. Results from this program were used to compare greenhouse 

as emissions from the fuel cycle for natural gas. oil, and coal using the global warming potentials (GWPs) recently published by the Intergovernmental Panel on Climate 

Change (IPCC). The analysis showed that natural gas contributes less to potential 

global warming than coal or oil. which supports the fuel switching strategy suggested 

by the IPCC and others. In addition, study results are being used by the natural gas 

industry to reduce operating costs while reducing emissions. 

7. 

DESCRIPTORS 

Pollution 

Emission 

Greenhouse Effect 

Natural Gas 

Gas Pipelines 

Methane 

18. OISTA!BUT!ON STATEMENT 

ReleaBe to Public 

~··~''' 

KEY WORDS AND DOCUMENT ANALYSIS 

b.IOENTIFIEFIS/OPEN ENDED TERMS c. COSATl Field/Group 

lPollution Prevention 

Stationary Sources 

Global Warming 

19. SECURITY CLASS (This Report} 

Unclassified 

20. SECURITY CLASS {rhi:rpagt!) 

Unclassified 

:5 

13B 

14G 

04A 

210 

15E 

07C 

21. NO. OF PAGES 

!88 

22. PRICE 
i 

U.S. ENVIRONMENTAL PROTECTION AGENCY 

Office of Research and Development 

National Risk Management Research Laboratory 

Technology Transfer and Support Division 

Cincinnati, Ohio 45268 

OFFICIAL BUSINESS 

PENALTY FOR PRIVATE USE. :S300 

AN EQUAL OPPORTUNITY EMPLOYER 

II your llddress is incorrect. pleBn change on the above label 

ltUif off; 8/Jd return to thtt above llddtess. 

II you do not des itt! to continut! rectdving th11se lt!Chnica/ 

teports, CHEC~ HER£0; tear off label, and return ;r to the 

above iJddress. 

Publication No. EPA-600/R-96-0SOc 

. ... , ....... ~ ··~·····-·--