UnitedStates Environmental Protection Agency 

# Research and Development

METHANE EMISSIONS FROM THE NATURAL GAS INuUSTRY Volume 3: General Methodology


# Preparedfor

EnergyInformation Administration {U.S. DOE)



# Prepared 

# by National Risk Management

________Research Laboratory ResearchTriangle 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 

### scienceknowledge base necessary to manage our eco

### logical resources wisely, understandhow 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 humanhealth and the environment. The focus of the Laboratory's 

## research program is 

## on methods for the 

## prevention andcontrol of pollution 

### to air, land. water. and subsurface resources; protection ofwater quality in

### publicwater systems; remediation ofcontaminated sites and groundwater; and prevention and control of indoor air 

### pollution. The 

### goal of this research effort is 

## to catalyze development andimplementation ofinnovative, cost-effective enVironmental technologies; develop scientific and engineering information neededby EPA to support regulatory and policydecisions; and provide technical support and infOr

### mation transfer to ensure effective implementation of environmentalregulations and strategies. This publication has beenproduced 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. TimothyOppelt. Director National Risk ManagementResearch Laboratory

EPA REVIEW NOTICE This report has been peerand administrativelyreviewed bythe 

### U.S. Environmental Protection Agency, and approved for publication. Mention of trade names or commercial productsdoes notconstitute endorsementorrecommendationforuse. 

### This document is availableto the publicthrough the NationalTechnicallnfonnation Service, Springfield, Virginia 22161.

### METHANE EMISSIONS FROM 

### EPA-600IR-96-0BOc June 

### 1996



## THE NATURAL 

## GAS INDUSTRY, VOLUME3: GENERALMETHODOLOGY
FINALREPORT


## Prepared by: MatthewR. Harrison Hugh

### J. Williamson

Lisa 

### M. Campbell RadianCorporation 8501 N. M<ipac Blvd. P.O.

## Box 201088 

### Austin, TX 78720-1088

DCN: 95-263-081-13
For GRI Project Manager: RobertA. 

## Lott GAS RESEARCH INSTITUTE

Contract No. 5091-251-2171 

## 8600 West

## Bryn Mawr Ave. Chicago, 

### IL 60631 and EPAProjectManager: 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 ofGRI, 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 ofthe information contained 

### in this report, or that the use 

### ofany apparatus, method, orprocess disclosed in 

### this report may not infringe privately 

## owned rights; or b. Assnmes any liability with respect to the use of, orfor 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 ofthe 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 ofexperts listed in 

## Appendix DofVolume 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 ofnatural 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 ofenergy produced than either coal or oil. On the basis ofthe amotmt ofC02 

### emitted, the potential for global warming could 

### be reduced by substituting natural gas for coal or oil. However, since natural gas isprimarily methane, a potent greenhouse gas, losses ofnatural gas during production, processing, transmission, and distribution could reduce the inherent advantage ofits lower C02 

### emissions. To investigate this, Gas Research Institute (GRI) and the U.S. Environmental Protection Agency'sOffice ofResearch and Development (EPNORD) cofunded a major study to quantifY methane emissions from U.S. natural gas operations for the I992 base year. The results ofthis study can be 

### used to construct global methane budgets and to determine the relative impact ofnatural gas on global warming versus coal and oil. This report is Volume 3 ofa multi-volume set ofreports 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 briefsummary ofthe methods used by the 

## GRI/EPA 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 ofthis 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 ofthe emissions estimate. 

### The national emissions for the base year are 314 

## ± 105 Bscf(± 

### 33%), which is equivalent to 1.4 

## ±0.5% ofgross 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 ofannual 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 ofspecific emission factors and activity factors for each source category are presented 

### in 

## separate reports (Volumes 6 through 15). 

### Forthe 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% ofgross 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 bythe 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 ............................... 4 3.2 Production Segment Defmition

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 3.3 Gas Processing Segment Defmition ............................ 9 3.4 Transmission and Storage Segment Defmition .................... 10 3.5 Distribution Segment Defmition ............................. 13 4.0 EMISSION ESTIMATION TECHNIQUES .......................... 15 4.1 Measurement Techniques for Steady Emissions . . . . . . . . . . . . . . . . . . . 15 

### 4.2 Calculation Approach for Unsteady Emissions . . . . . . . . . . . . . . . . . 17 5.0 GENERAL EXTRAPOLATION METHODOLOGY .................... 19 5.1 Emission Factors ....................................... 20 

### 5.2 Activity Factors.

. ....................................... 21 6.0 SAMPLING AND STATISTICAL ACCURACY ...................... 45 6.1 Sampling Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 6.2 Screening for Bias in Activity Factors . . . . . . . . . . . . . . . . . . . . . . . . . 53 

### 6.3 Screening for Bias in Emission Factors ........................ 54 

### 6.4 Accuracy Target ........................................ 57 6.5 Overall 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 ofRandom and Bias Errors ...............•............. 46

vii

### LIST OF TABLES Page 5-l Well-Defined Activity Factors .................................... 23 5-2 Examples ofDeveloped Activity Factors ............................ 24 5-3 Example Data Compilation ofSites 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 GulfCoast 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 ofError 

## 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 (C0 2) 

### per

## unit ofenergy generated than either coal or oiL On the basis ofthe amount ofC02 

### 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 ofnatural gas could reduce 

### or even eliminate the inherent advantage ofits lower carbon dioxide emissions during combustion. For this reason, Gas 

### Research Institute (GRJ) and the U.S. Environmental Protection Agency Office ofResearch and Development (EPA-ORD) developed ajointly funded and managed program to better defme methane emissions from the U.S. natural gas 

### industry. The objective ofthis comprehensive program is to quantify methane emissions from the gas 

### industry, beginning at the wellhead and ending immediately downstream ofthe customer's meter, with an overall accuracy goal of0.5% ofnatural gas production (± 

### I11 Bscf) based on a 90% confidence level.


### This report provides a briefsummary ofthe 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 ofthe emission estimate. These methods are more completely described 

### in other volumes prepared as part ofthis 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 inthe gas industry 

### were estimated c.n the basis ofavailable 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 ofthe program, methods were developed to measure and/or calculate emissions from 

### ail sources ofmethane emissions in 

### the gas industry. These methods were validated through tests 

### designed to quantify the accuracy 

### in the measurement approach (i.e., proofofconcept tests), andthrough 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 ofthe vast number ofsources. Therefore, part ofthe 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 ofthe 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 ofindustry representatives, project sponsors, and other interested parties from both 

### the government and private sectors provided guidance and peer review for all phases ofthe program. In addition, an Industry Review Panel provided more detailed technical review ofthe project.
This report briefly describes the methods used in all phases ofthe GRIIEPA methane emissions study. Section 3 presents the methods for characterizing the industry and identifying sources ofemissions (part 

### ofPhase I ofthe 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 briefsummary ofthe sampling and statistical methods used to determine the accuracy ofeach emissions estimate. The appendices (A, B, C, D) present some ofthe data 

### collected as part ofthe program and the worksheets for determining emissions and extrapolating national annual emissions for each source ofmethane 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 ofthe report characterizes the industry by 

### outlining the segments ofthe industry as well as the types ofequipment found within 

### each segment. (This section is identical to Section 3 ofVolume 5 on activity factors. 1) 

### While this section draws a general picture ofthe industry developed by the GRI/EPA methane emissions project, it 

### is not intended to present a definitive picture ofthe 

### industry regarding all typical operational parameters but only those that are necessary to identify all sources and causes ofmethane 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 ofthe gas to the customer through local distribution pipeline networks.
The generally accepted segments ofthe 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 inthe following subsections. BOlmdaries for the study were defmed to specify what equipment is included orexcluded from the study. These boundaries were set using input from industry experts.
4

### I I 

## PRODUCTION I I I I I I

Surtace Facilities

Liquids

" ,_?. 

### I I 

## PROCESSING I I I I I I I I Gas Plant 

### I I I I I I I I I I I I Liquids 

### I I I I I I I I I I I I I 

## TRANSMISSION/ STORAGE Compressor

Stations I 

### I I I I 

## DISTRIBUTION Main and Service Pipelines 

### Direct 1 I I I 

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

### I I I I I I I


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



### Underground Storage 

### Reservoir Customer Meters 

# 0 Compressor 

### @ Meter t;:::1o Pressure 1*;1 Regulator



### Figure3-1. GasIndustryFlowCbart

### The guideline used for setting the boundaries 

### was to exclude equipment in 

## each segment not required for the marketing ofnarural 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 ofpropane, 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 ofmethane 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 

### ofthe gas industry. The production segment is composed ofgas 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 ofthe 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 **OiiW~il**t==l Wellhead 

## l._J '

OilWell Wellhead (producing

gas}



# ""''"" Metlw!eWen

Gas.Well Wellhead Coropn:ssor 

# r---""'-~_.d_~_"'~'"-~;,,:a·

**~**

SaltWall:!"and OilStocl<Tanb

GasI11dustry - 

## ~ 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 ofthe 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 ofthe liquid piping are considered part ofthe oil industry and are excluded from the GRJ/EPA gas industry study. The gas industry equipment begins only on the gas line downstream ofthe separator, atthe 

## first piece ofgas line equipment, such as the sales meter, compressor, or dehydrator.
In general, an oil oroil and gas field may have centralized surface treatment facilities or each well site may have its 

### own independent surface facilities. In centralized facilities, all ofthe 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 ofthe field configuration, gas wells may or may not have a separator(s), dehydrator, or compressor. The use ofthe equipment depends upon the free liquid production, absorbed moisture content, and well pressure. Forexample, 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 ofthe equipment at 

### these free-flowing oil wells is considered part ofthe gas industry ifit exists to market the gas. Artificial-lift oil wells are most often 

### not part ofthe 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 pumpjacks usually do not produce or market any gas and therefore are not part 

### ofthe 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 ofthe amount injected are considered part ofthe 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) ofthe 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 byabsorption. 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 ofthe product stream. The back end ofthe 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 ofthe gas plant has negligible methane emissions since the liquids handled contain 

### only trace amounts ofmethane. The front end ofthe 

### gas plant often contains dehydration facilities, wet gas compression, and the absorption or compression and cooling process. All 

### gas plants are considered part ofthe 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 GulfCoast to the eastern seaboard ofthe United States. The segment consists oflarge diameter pipelines, compressor stations, and metering facilities. All 

### ofthese facilities and all ofthe equipment they contain are considered part ofthe natural gas industry. Transmission compressor stations usually consist ofpiping manifolds, reciprocating or gas turbine (centrifugal) compressors, and generators. Dehydrators may be included but are not usually present because ofupstream drying. The station may also include metering facilities. Figure 3-4 shows a schematic diagram oftransmission 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 ofpeak 

### demand in the winter. 10

# c

Dehydration Absorptionor Compression &

### Cooling Process 

### to

Backendofthe Plant 

# ,--------------

Liquids 

### 1 I I 

### I I I I I I I I I I I I I I I I 

### I I I I I I I I



### Figure3-3. GasProcessingPlant II 

### C' 2



### r-+C' 4 

### I I I I I I I I 

### I I I I I I 

### I I I 

### I I I I I I I I Natural I Gasolines I

### "



# - 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 ofseveral fonnations: 1) 

### spent gas production fields, 2) 

### aquifers, or 3) salt caverns. Below-ground storage is the predominant means ofgas 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 ofthe residential, commercial, and industrial conslllTiers. The segment includes pipeline (mains and services), meter and regulation stations (city gates), and customer meters. All ofthese facilities are considered to be an integral part ofthe gas industry. Figure 3-5 shows a schematic ofthe distribution segment and associated equipment.

13Meterand Pressure Pressure-Reducing Regulating (M&PR) Station Station Mains (Pipeline)



# ~ @ v 

### M Transmission 

### @ Pipeline v Meter Pressure-Reducing Regulators



### Figure

## 3·5. DistributionSegmentEquipment ervrces 

### rna lp M S (S II 

### p· e) 

## li'l\

**~** 

# ""' _r.'l\



### ~

M 

# r.:.. """

**~**

M 

# """

**~** CustomerMeters (Residential, Commercial,

Industrial, Electric Utility}

## 4.0 EMISSIONESTIMATION TECHNIQUES
After all potential sources ofmethane emissions 

### inthe industry were identified and characterized, the emissions were quantified. The method selected to quantify the 

### emissions from a source depended onthe variability ofemissions 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. Fugitiveemissions are generally considered steady. Unsteady emitters are defined as sources with

### highly 

### variable emissions, suchas a pneumaticdevice onan isolation valve or a 

### maintenance activity that

### requires blowdown. These emissions sources vary from company to company and site to site because ofdifferent maintenance practices and

**operat~g** 

### conditions. "Steady" is a relative term and is defined by the timeperiod ofdata

### needed for the study. For this 

### study, the annual value ofmethane 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 ofthe 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 SteadyEmissions


### The techniques used 

### in the study for measuring·steady emissions is briefly described below. Fugitives MeasurementMethods
Emission factors for estimating fugitive emissions were determined based upon measurements ofemissions 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 ofcomponents were measured and anaverage emission rate percomponentdetermined for each componenttype. Emissions from an equipment source, such as a compressor, ora facility, such as a compressor station, were then calculated by multiplying the number ofcomponents associated with thatequipmentor facility with the average emissionrate per component.2 

### Emissions from individual components were measured using one ofseveral methods:

• Ahigh flow organic vapor analyzer captures the entireleak and measures the methane concentrationand flow rate. The emissions rate is determined from the productofthe concentrationand flow rate. • A total enclosure technique called bagging. Unconuuninated air is blownthrough aplastic bag enclosing the component. The flow rate and outletconcentration is measured by an organic vapor analyzer, and the leak rate is determined from the productofthe concentration and flow rate.
• A screening technique where the methane concentration is measured at the pointofthe leakusing a standard organic vapor analyzer. The concentration is related to anemission rate by a correlation equation that was developed in othersrudies and that related bagged emissions to the concentrationmeasured during the screening test. Tracer GasMethod
The tracergas method ofmeasuring methane emissions consists ofreleasing tracer gas (at a known constant rate) near the emission source and measuring the downwind concentrations ofthe tracer gas and methane. Assuming complete mixing ofthe methane and tracer gas and identical dispersion, the ratio ofthe downwind concentrations is equal to the ratio ofthe release rates. Based upon the downwind concentrations ofmethane and tracer gas and the known release rate ofthe tracer, the emissionrate ofmethanecan then be 

### determined. This method was used primarily to measure emissions from meter and pressure regulating stations.3



### 16

### Leak

### StatisticsMethod
The leak statistics method isused to quantify methane emissions from 

### underground mains and services 

### indistribution systems. Emission rates are measured for a large number ofleaks to accurately determine the average emission rate per leak as a 

### function ofpipe material, age, pressure, and 

### soil characteristics. The leak statistics program was conducted as a cooperative program between EPNGRI and industry. The industry participantsused specially designed equipment to measure leakage rates from underground distributionmains and services. To perform the measurement, a 

### pipe segment containing the leak is isolated, the isolated segment repressurized, and the volumetric flow required to maintainnormal operating pressure in the isolated segment is measured. The leak statistics



# . method combines the measured leakage rate per leakwith the historical leak records ofthe 

### companies and national leak repairdata to determine the numberofleaks permile for different

### pipematerial. The emissions are determined by multiplying the leak rate per leak by the leaks per mile and numberofmiles ofpipe.' 

### DirectFlow Measurement
The direct flow method was used to measure emissions from some pneumatic devices and leaks 

### in some open ended lines. Since the gas 

### consumptionofcertain pneumatic devices is emitted to the atmosphere, a flow measurement ofthe 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 directlyconnecting a gas metertothe line. 

## 4.2 Calculation

### Approach for UnsteadyEmissions
Emissions that are intennitten; orunsteady 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 oftencalculated rather thanmeasured.
17

### Forsome sources, such as maintenance emissions, detailed company calculations are available for multiple years. 6 

### However, most sources ofemissions are not tracked by companies 

### and therefore must be

### calculated. Each unsteady source ofemissions 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 infonnationto quantify annual emissions:

• A detailed technical characterization ofthe source. identifyingthe important parameters affecting emissions. (This information was documented for individual source types 

### in otherTier 3reports on each major emissiontype.

**·~** 

### • Data gathered (from multiple sites) that would be

### needed 

### to calculate emissions

## per event.
• Sufficient data to define the frequency ofevents. An example ofemissions calculated for anunsteady source is the estimate of emissions from a vessel blowdownfor routine maintenance. In this case, the volume, pressure, and temperature ofgas contained 

### in the vessel before blowdown is

**"calcula~"** 

### to quantify 

### the losses from the blowdownevent. Additionally, an average frequency ofthese vessel blowdownevents is necessary to determine the annual losses from this source of methaneemissions.
In some cases, measurement from other studies were used to establish the emissions perevent. Therefore, these emissions data were combined with 

### site data 

### collected in

### this study to quantify the numberofevents per year in 

### order to calculate the annual emissions from these sources. Examples ofsources 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 injectionpumps by measuring the emissions perevent.

18

## 5.0 GENERAL EXTRAPOLATIONMETHODOLOGY 

## By necessity, data were collected on a relatively small percentage ofsources within 

### each source 

### category. These data were extrapolated to obtain nationwide estimates for similarsources throughout the industry. The extrapolation techniques for creating nationwide emissionestimates were developed so that 

### the emissions for each source category could be estimated to 

### meet a specified level ofprecision and negligiblebias. 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 populationof similar sources in 

### the gas industry. The extrapolation approach uses the concept ofemission and activity factors to estimate emissions based on the 

### limited number ofsamples. These factors are defined in 

### such a way that 

### theirproductequals 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 ofrandomly selected sources 

### in a source category and 

### the activity factor is the total 

### number ofsources in

### the entire targetpopulationor source category. However, 

### in applying this simplified approach to developing emission and activity factors it is imponant toensure that there is no bias in

### the data. 

### The extrapolation methodology involvesmore than

### justthe scale-up of emissions data; 

### it also includes the sampling approach which is fundamental 

### to the accuracy ofthe emissions data.
This section describes the two components for the extrapolation equationemissionfactors and activity factors.

19

## 5.1 Emission Factors
The emission factor is generally

### defmed as the annual emissions per source. 

### Inmany cases. the emission factor was calculated by simply summing the emissions data from each source and dividing by the number ofsources sampled. The emissions data would 

### be measurements orestimates for each source. In some cases, the variability ofthe emissions data 

### from source to source is very large. Forsource types ofthis nature, it is often possible to reduce variability byredefining the emissionfactor orby stratification. Reducing the variability is important because itreduces the number ofdata points needed to 

### achieve the accuracy target. RedefmingtheEmission Factor
For a few types ofsources, emissions can be 

### more accurately estimated 

### with fewer data points when the emissionfactor 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 sameas subdividingthe source category into subsets. Since the variability is significantly reduced, fewer total datapoints are required to achieve anacceptable level of accuracy.
Forexample, the internal combustionengines that drive compressors 

### in the 

### gas industry vary in size (i.e., horsepowerrating). Ifdata 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 ofsize differences. However, ifthe emission factor for the engines is defmed by horsepower ofthe engine (i.e., annual emissionsper horsepower), then the variability from engine to engine and therefore the number ofsamples required to reach an acceptable accuracy are both significantly reduced.
The numberofdata points required may also be reduced by stratifying onthe basis ofparameters 

### that affect emissions. An 

### example is quantification ofthe methane 

## 20

### emissions from underground distributionmains and services. Based onlimited data, the variability inemissionmeasurements 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 ofemissions from source to source may be 

### reduced. Data collectionresources 

## can be 

### allocated to the parameters thatcontribute the most to the overall uncertainty ofthe estimate. Therefore, by subdividing a source into categories with differing emission characteristics and allocating data collectionresources to the parameters that influence emissions the most, the overall numberofsamples required to meet the accuracy targetcan 

### be reduced. 

## 5.2 ActivityFactors 

## This sectionon activity factors is an abbreviated version ofthe text presented 

### inVolume 

### 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 

### inthe appendices to

### this report.
In general, the activity factor is the total populationofthe source when the emission factor is defmed as the annual emissions per source. Exceptions to this general definitionofanactivity factor would only include sources thathave anemission factor that can 

### be more accurately represented by a parameter(s) that influences emissions (e.g., the emission factor for internal combustion engines 

### is intenns ofemissions perhorsepowerhour). Forthese 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 populationofa source 

### type, such as gas wells, miles oftransmission and distributionpipelines, and total national production, withinthe natural gas industry, as shown 

### inTable 5-1. However, 

### in manycases, the total population of

### a source type withinthe gas industry is 

### unknown. 

### 21

### Table 5-2 presents some ofthe activity factors that are not tracked nationally, but that were generated by this project.


### For sources that 

### have an unknownpopulation, site visits were conducted to determine the numberofsources ateach 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 ofsites visited, gas produced ormarketed, and equipmentcounts are presented in Section 6.1, Sampling Approach. These site count data are scaled by using populationdata that is known and is related to the source. Forexample, in the GRIIEPA study, no data were available on 

### the nationwide populationofproductionseparators. To calculate this value, the numberof production separators atasite, gathered as part ofsite visits, were divided by the number of 

### wells at each site. Then, the 

### average ratio ofseparators to wells from all 

## site visit 

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

### scaling the site visitdata to represent the entire population, acheck for bias is made. (Refer to Section 6.2, Screening for Bias inActivity Factors.)
Forsources that are not tracked nationally, individualcompanydata or 

### regional surveys (surveys by state agencies ortrade organizations) were sometimes available. Metering/pressure regulating stations, glycol dehydrators, and compressorengines/gas 

### turbines are tracked on acompany wide basis or through regional surveys. For regional or company tracked activity factors, sufficientcompany/regional data had to be 

### gathered to comprise arepresentative sample to extrapolate to anational 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 ofequipment activity factors from individual site data within 

### astratum is usually handled by selecting an "extrapolationparameter" (EP) 

### that 

### is known for the site as well as regionally ornationally. Examples ofextrapolationparameters 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. ofgas wells No. ofoil wells No. ofgas plants No. ofAGR units Miles oftransmission pipeline No. ofstorage facilities No. ofwells Miles ofmains No. ofservices



## 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 OFDEVELOPED ACTIVITY FACTORS Segment 

## ACtivity FactorName Number Total Industry 

### Reciprocating compressordrivers 44,130 

### Turbine compressor drivers 1,543 

### Number ofglycol dehydrators 39,620 

### Production No. ofoil wellsmarketing gas 209,000 No. ofgas wells requiringunloading 114,100 

### Compressordrivers 17,100recips 

### Engineer MMHp-hr 27,460 

### Offshoreplatforms 1,114 Glycol dehydrators 37,820 Glycol dehydratorthroughput (MMscfy) 12,400,000 

### Separators 167,200 

### In-line heaters 51,000 

### Total production vessels 256,000 Chemical injectionpumps 16,970 

### Pressure reliefvalves 529,400 

### Gathering pipelinemiles 340,000 Pneumaticdevices 249.100 

### Processing Compressor drivers and installed HP 4,092

### recips (4.19MMHP) 726turbines (5.19MMHP) Annual 

### compressoroperatinghours (average) 6,626(recips) 6,345(rurbines) 

### Glycol dehydratorthroughput (M:Mscfy) 8,630,000 Acid gasrecovery units 371 (Continued)



### 24

## TABLE S-2. EXAMPLES OFDEVELOPED ACTIVITY FACTORS (Continued) Segment ActiVityFactorName Transmission and Storage Compressordrivers and installed HP

Distribution Annual driver operatinghours (average)



### - Transmission compressordrivers

- 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 

### Outdoorcustomer 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

### numberofwells for production, number ofplants for processing, and number ofcompressor 

### stations for transmission. Populations ofotherequipment, such as the countofseparators at the site, are then divided by that term, allowing the resulting ratio to be easily extrapolated 

### to aregional ornational total.

where: However, the regional ratio of



## AF, = 

### EP 

## --"AF""·'- 

## EP activity factor (population) ofequipment type 

### 1 

### extrapolationparameter.

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

### extrapolation planmustselect one ofthese two methods based upon technical merit. These two methods canbe described as: 1) weighting the site counts by the extrapolation activity factor, or2) using an average countper site (not weighting). 

## (2)

Forexample, to determine the number ofseparators in 

### aregion, the production site count ofseparators and wells at asite could be extrapolated to the regional total by two methods: 1) summing the separators and dividingby the total well count (each site data is weighted by the total well counts), or2) by averaging all ofthe 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 ofwhetherthatmethod would introduce bias. The method selected might vary from segment to segment, but was generally 

### constant across most calculations 

## withina segment. The first method, summing equipment from all sites and dividing by the sum ofthe 

### extrapolation parameter. was used almost exclusively by this project. This is discussed in detail inVolume4 on statistical 

### methodology. 10



## 26

### The following hypothetical example illustrates the two options forextrapolating activity factors. The following table (Table5-3) and 

### calculations give anexample ofthe two methods for determining the number ofseparators 

### in a region 

### inthe natural gas production segment.
TABLE 5-3. EXAMPLE DATA COMPILATION OFSITES IN REGION X Sire Countof Site Countof

### 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, whichequals 0.37 separators/well. This number is heavily weighted by one offive sites that had a low separatorper well count but a high numberofwells (aboutten times as many as any other site). 

### Ifthe secondmethod is used, each site is treated as anequally representative sample and the average ofthe site ratios is used; the result is 0.67 separators/well. The first method was selected for all productionactivity factor extrapolations since there is a reason to believe that

### a randomly selected site that 

### has many wells is representative ofa largerportionofthe population than 

### a randomly selected site with 

### only a few wells. Weighting 

### by well count assumes that 

### a larger numberofwells at a site means that the site is representative ofa largerpopulation than 

### a site with a smaller well count. Volume 

### 5 onactivity factors1

### provides additional details onthis method.
In addition, some equipmentactivity factors sources could 

### be scaled up by 

### several possible EPs. If

### a knownphysical/technical relationship existed betweenthe source 27

### populationand one EP, then that parameter was selected. However, where the relationship between the source populationand the otherparameters is notobvious from atechnical perspective, many approaches having technical merit were used, and eithera) the average of the methods was used, or b) the resulting data from individual companies statistically analyzed to 

### determine the 

### appropriate extrapolation approach. Forexample, it 

### was not clear from atechnical perspective whether to scale-up the number ofmetering/pressure regulating stations bymiles ofmainpipeline or system throughput, which were the only known population statistics. The stationcounts from individual companies were examined both 

### from aper mile

### main and per system throughput basis. A linearregression analysis showed that ifthe data were preferentially extrapolated using apermile mainbasis, the resulting national extrapolation would have lower variability. 

## Inproduction, the number ofseparators appears to be technically related to both well count and throughput. Therefore, separatorcount was extrapolated by bothmethods, and the 

### average ofthe two national estimates was used. Activity FactorsDeveloped for Production Sources 

### Mostproduction activity factors were extrapolated by ratio to known EPs. The extrapolations were done on aregional basis, since regional biases were known to exist aod 

### each ofthe well-knownEPs (i.e., well count andproduction throughput) were also 

### known on aregional basis. Six regions were selected based upon an analysis ofthe productionand well populationcenters in·

### the United States.• as well as based upon known differences inpractices in various regions. The regions are: I)GulfCoast 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 regionsjustify their selection and can be seen in Table 5-4. Specifically, Table 5-4 shows the regional biases that 

### exist inproductionversus well 

### 28

# P.M. Offshore

G.C. Offshore

Figure 5-1. Selected Production Regionsw 0 

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

Stitk:l ID Rqioll

### fbi•re R<Pul Grotapbgs >SDibtUyr
GulrCoast 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 cTable 3-10, 

### Gas Facts 11 1992

### ProdKbr: Gu 

### W""' Ptr«RfGf Coul Totol
63667 lJ.I 4021 

# '·' S9ti46 

# ,,. 80924 293
2266 

# ..

65 0.0 2201 03 129157 46.8
276014 IOO.Oo/e 

## •mProdvdac

## ooWdll"
Pttu.tof 

### 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

..

# - """""" 

# """' ofGrostTotal 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 inpractices between onshore and offshore production operations. The well and productiondemographics also support this split, since the offshore regions account for a small portion ofthe wells (1.5% ofthe gas wells, 1.2 %ofthe oil wells), but produce 26.1 %ofthe U.S. marketed gas production.
As shown in Table 5-4, the majority ofnatural gasproduced in the United States (more than 

### 64% oftotal production) occurs is 

### in the 

### GulfCoast region. Otherregions only account for 36% ofthe production, and 

### the majority ofthat 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% ofthe gross national gas production, has the largest portionofgas wells (46% ofthe national total) as well as a large fraction ofoil wells (24%).
If

### the source beingevaluated is wells orequipment associated with wells (such as separators and 

### chemical injectionpumps), then bias would potentially be introduced if only wells in

### the GulfCoast region were sampled, where most ofthe 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 segmentconsists ofone type offacility: gas processing plants. Major activity factors were limited to the count ofgas plants (and gasplant type), 

### the count of dehydrators, the count ofacid gas recovery units (AGRs), and compressor data. 

### All ofthese 31w N 

### Site Survey Type



### - Site Visit

- Phone Survey



### - Star Site Visit* 

### TABLE 5-5. PRODUCTIONSITESUMMARY

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 orother fugitive emissionscontractors. 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-orrec.orr Gc-orrcc-orr PM-orrPM-orr Off$hore Tolab TotalWells GasWells (l/MMdd) (1/MMc!d) Site 1 2 3 4 

## s 6 Company I 

# ' 2 

# ' 3 4 6SJtf.!l. 

## I GC Sw:veyType 

### 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 EquipmentCounts: Gas Wells 2 0 80 0 0 12 82 12 Oil Wells 3 ISO 0 40 22 0 193 22 +Oil wells that marketgas 3 ISO 0 40 22 0 193 22 Separators 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 I 0 

### +Dehy with VentControl 0 0 0 

### +Dehyw/Kimray Pumps I I 0 +Dchyw/Stripping Gas 0 0 0 Miles ofGalhering Pipeline . . 

### - - . FugitiveComponent'ount y N N N N N Vented(Site Blow& Purge Dala) y y y y y y N01es: I) SurveyTypeV

## =Site Visit (Radian); P = PhoneSurvey; S 

## =Site Visit (Star) 2) • = Gas lift

**compre~sors** not included. 3) Y =Yes, N =No;"-"= No Data: 4) RegionKey: GC = GulfCaast, PM = Pacific Mounlain; CP = Central Plains;A = Atlantic & Great Lakes

### TABLE 5-7. DATA FORGULFCOAST ONSHOREPRODUCTION SITES Region 

### GC GC GC 

### GC GC GC 

# ..Gc GC GC TotalGC Site 7 8 

# • 10 II !2 13 14 15 Equip./ Equip./ Compauy 

### s 6 7 8 

# • 10 II II 11 !JSites Totili Equlp.! Equip.I Mkt. Gas Prod. Ga! SurveyType 

## v v v v v v v v v 7 Companies TotalWe!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 GasProduced {MMcfd) 23.1 25.5 124 

# " 28 250 1.9 7 130 643.4 0.54 F..quipmentCounts: Gas Wells 13 80 18 130 26 300 0 10 31 608 Oil Wells 

## so 0 3 3 0 300 

# "' 127 0 638 +Oil wells that market gas 

## so 0 3 3 0 300 ISS 68 0 579 Separators 38 80 42 71 26 300 0 II 31 S99 0.50 0.99 0.93 0.93 In-line Heaters 2 56 17 23 26 0 0 12 0 136 OJI 0.22 0.21 0.21 Pneumatic Devices 68 170 0 68 109 

# "' 0 11 31 682 0.57 1.12 1.06 106 Chern lnj Pumps 10 

# ' 0 5 0 0 0 0 0 20 002 0.03 0.03 0.03 Compressors• 12 4 2 37 0 0 0 

# " 10 80 0.07 0.13 0.12 0.12 Dehydrators 7 2 2 12 26 2 0 4 26 81 0.07 0.13 0.13 0.13 +Dehy with 3 pH Flash 0 0 2 2 0 0 0 4 0 8 +Deily with VentControl 4 0 2 0 0 0 0 0 0 6 +Dehy w/!Gmray Pumps 7 I I 6 26 2 0 0 26 69 

### +Dehy w/StrippingGas 0 0 0 0 0 0 0 0 0 0 Miles ofGatheringPipeline . 46.3 26.4 40 8 . . . . FugitiveComponentcount 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 =SiteVisit (Star) 2) • "" Gas lift compressorsnot included. 3) Y =Yes, N =No;"-"= No Data; 4) RegionKey: GC = GulfCoast, PM

**~** Pacific Mountain; CP = Central Plains; A .., Atlantic & Great Lakes

### TABLE 5-8. DATA FORCENTRAL 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 SurveyType 

### v 

### v v p p p p 7CompanieS 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 EquipmemCounts; Gas Wells 138 321 1000 400 I 100 

# "

. 1975 Oil Wells 

# " II 0 0 0 0 4 70 +Oil wells thai marketgas 

# " II 0 0 0 0 4 70 Separators 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 withJ pH Flash 0 0 0 0


### - 0 +Dehy with Vent Control 0 0 0



### - - 0 +Dehyw/Kimray Pumps 16 220 0 

# " 0 261 

### +Dehy w/StrippingGas 0 0 0



### - 0 Miles ofGathering Pipeline 5.2


### - 600


### - - 

### - - FugitiveComponentcount y y y



### - - 

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

Notes: I) Survey Type V "" Site Visit (Radian); P "' PhoneSurvey; S "' Site Visit (Star) 2)

**~** "' Gas lift compressorsnot included. 3) Y"' Yes, N "'No; •-· =No Data; 4) Region Key: GC "' GulfCoast, 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 Equip./ Equip./ COmpany 

# ,. " 2l 2l 2l ll 

# " 2l 2l 9Sites Equip./ Rqulp.l Mkt. Gas Prod, Gas Survey 'l)pe 

## v v v v v v v 

## v v 4Companies Total TotalWells 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 EquipmentCounts: 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 4S 0 0 0 0 0 0 0 4S 0.17 0.85 0.41 0.14 In-line

**He~ters** 

# " s 

# ' 2 0 0 0 0 63 0.24 1.00 0.58 0.20 Pneumatic Devices 80 0 0 0 0 0 0 0 0 80 0.011 1.51 0.67 0.25 Chern Inj Pumps 36 0 0 0 0 0 0 0 0 36 0.04 0.68 0.30 0.11 Compressors"' I7 I9 0 0 0 0 I I 38 0.14 0.32 0.35 0.12 Dehydrators 

### s 0 0 0 0 0 I 0 

# • 0.02 0,09 0.05 0.02



### +Dehy with 3 pH Flash 0 0 0 0 +Dehy with VentComrol 0 0 0 0 +Dehyw/Kimray Pumps 

### s 0 I 6 

### +Dehy w/Stripping Gas 0 0 0 0 Miles ofGathering Pipeline 

### - - - 

### - - - 

## - FugitiveComponentcount 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 = PhoneSUrvey; S = Site Visit (Star) 2) • = Gas lift compressorsnot included. 3) Y =Yes, N =No:"-"= No Data; 4) RegionKey: GC = GulfCoast. PM = Pacific Mountain; CP = Central Plains; A = Atlantic & Great Lakes

### TABLE 5-10. DATA FORATLANTIC & 

### GREATLAKES 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 EquipmentCounts: GasWells 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 76 0 10 520 450 1582 1294 Chern Inj Pumps 0 0 0 12 0 8 25 y 0 Compressors"' I 0 Dehydrators 0 

# ' 30 0 0 41 

### +Dehy with 3pH Flash 0 0 0 0 5 +Dehywith VentControl 0 3 2 

### +

Dehyw/K.imray Pumps 0 2 30 8 0 

# '"" +Dehy w!StfippingGas 0 21 0 

# _, MilesofGathering Pipeline FugitiveComponentcount y N N N y y y y Vented(Site Blow& Purge Data) y y Notes: I) SurveyTypeV = Site Visit (Radian); P = PhoneSurvey; S = Site Visit {Star) 

# ,, • = Gas lift compressorsnot included. 3) y = Yes, N = No;"-" = No Data; 

### (Continued) 4) RegionKey: GC "' GulfCoast, PM "' Pacific Mountain;CP = Central Plains; A = Atlantic & Great Lakes

### TABLE 5-l0. (Continued) Region AGL AGL AGL AGL AGL AGL AGL AGL AGL AGL TotaiAGL Site 41 42 43 44 45 46 47 48 49 

## so Equip.! EquJp.l Company 30 31 31 31 31 31 31 31 31 31 19Sites Total Equ1p./ Equip./ Mkt. Ga! -Prod. Gas SurveyType 

## s s s s s s s 

## s s 

## s 10Companies (SUes 32-50) TotalWells

**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 GasThroughput(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(1000BID) EquipmentCounts: Gas Wells 10 23 22 22 II 14 18 21 8 21 8828 Oil Wells 0 0 0 0 0 0 0 0 0 0 581 +Oil wells that marketgas 0 0 0 0 0 0 0 0 0 0 581 Separators 0 10 7 8· 

# ' 3 IS 17 

# ' 7 6766 0.72 0.77 38.97 38.01 In-line Heaters 0 0 0 0 I I 0 0 0 0 2 0.00 0.00 O.o7 

### om Pneumatic Devices
. . . . . . 

## . . . 

## . . 3932 0.43 0.46 23.07 22.50 Chern lnj Pumps 0 0 0 0 0 0 0 0 0 0 45 0.00 0.01 0.26 0.25 Compressors"' 0 0 0 0 0 0 0 0 0 0 I 0.00 0.00 0.04 0.04 Dehydrators
. - . . . . . . . . 74 0.01 0.61 0.43 0.42 +Dchy with 3 pH Plash 

# ' +Dehywith VentControl 

# ' +Dehyw/Kimr:ay Pumps 41 +Dehyw!StrippingGas 21 Mites ofGathering Pipeline . . . . . . . . 

## . . FugitiveComponentcount y y y y y y y y y y Vented (Sire Blow & Purge Data) . . . . . . . Nores: I) Survey Type V = Site Visit (Radian); P = PhoneSurvey; S "" Site Visit (Star) 2) • = Gas lift compressorsno! included. 3) Y =Yes, N =No;·-· =NoData; 4) Region Key: GC = GulfCoast, PM = Pacific Mountain; CP =Central Plains: A = Atlantic & Great Lakes

### activity factors were eitherpublished and well-defined or were developed through other studies such as the report by Wright Killen 

### & CoY

### orVolume 11 on compressor driver exhaust.14 

### The site data 

### used to developedprocessing activity factors are presented in Table 5-11. ActivityFactorsDeveloped forTransmission 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 eithersurface compressor stations, surface metering and 

### regulating stations, buried pipelines, orunderground storage. Most transmission pipelines are one oftwotypes: interstate (cross-country) orintrastate (strictly regional). Therefore, transmission company data 

### can be 

### extrapolated by 

### using pipeline miles, station count, or storage facility count.
The total numberofcompressor stations was extrapolated from data on major transmission companies listed in 

### Gas

## Facrs. 11 

### The total miles oftransmission pipeline and the number ofstorage facilities and storage wells is also published. Counts oftransmission metering stations by type were produced by extrapolating data from Radian's company surveys ofseveral transmission companies. Othertransmission 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. 

## ActivityFactorsDeveloped for DistributionSources
In the

**d~stribution** 

### segment, activity factors were developed for total numberof leaks inunderground 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 oftotal 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 ofcompressor 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 16267" 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



### - 1Pumps 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

- StrippingGas 0



### - Vapor Recovery 0



### - Vent Flash Gas Pneum 3 Wells FugitiveCC 1123 134 Site

### B.D Practices 

### y Co. 

### BID No's Fugcc does not include connections ortubing 

## * = Elec drivencompressors 

## ** = Not includinghydraulic 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**



### ·-~r-·-- 

## >.;11 $1\W 

# ·-·-·-PI :::.:. 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 yCompanies 

### 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 52

- Turb. 

### 0 0 0 2' 0 4 0 0 6

- Recip. Eng 3 

### 2 2 2 0 14 9 9 41 -Total HP 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 13700 Vented Data:

- Site y y y y y y y -Company 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 ofservices).
For metering/pressure regulating stations, the number ofstations was collected 

## from each company and extrapolated by the total miles ofdistribution 

## mains. Other activity factors used 

### in the distribution segment were based on 

### weli-defmed activity 

### data, such 

### as total mileage ofmains/services and 

### throughput.

44

## 6.0 SAMPLING AND STATISTICAL ACCURACY
A key part 

### ofthis project was the estimation ofthe accuracy ofthe 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 ofprecision and bias. Precision can be calculated from a set ofreplicate measurements. Bias cannot be calculated, and must be discovered and eliminated where possible. Figure 6-1 illustrates the role ofrandom and bias errors in 

### the estimation process. In each ofthe four illustrations 

### in this figure, the center ofthe concentric circles represents the correct answer. In the upper left, there is a significant amount ofrandom 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 ofthe 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 ofthe large bias and the poor precision, the accuracy is also poor. In the upper right ofFigure 

### 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

## • • 

## • HighBias+LowPrecision 

### =LowAccuracy

HighBias+HlghPrecision =LowAccuracy 

## • • • • • • 

# 0. •

• •

LowBias +LowPrecision 

# =

LowAccuracy



### LowBias+ High

### Precision 

### =HighAccuracy



## Figure 6-1. Illustration ofRandom and Bias Errors
46

### 6.1 Samplin2 Approach
In general, a sampling program should gather enough replicate samples to 

### meet the precision target. Ifthe 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 ifthe data are biased. Sampling bias occurs if

### the methodology is flawed in a manner that leads to a systematic under-representation ofparts ofthe population and a systematic over

### representation ofother 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 ofa given emission factor 

### was 

### obtained. Ifthe average ofthe entire infinite set ofemission factor estimates equalled the true value, then bias would not exist. If

### the average ofthese 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 ofindependent estimates ofthe emission factor would remove random error altogether, leaving only bias error, ifany. While 

## it is clearly impossible to obtain an infinite set ofestimates ofan emission factor, the example given serves to illustrate the meaning ofbias.
Even ifthere was no bias, the actual estimate ofan emission factor would be expected to differ from the true value. First, the estimate is based on less than the total number ofsources. Random differences bet.veen the set ofsampled sources and the population ofsources introduce a sampling error. Second, physical measurements have uncertainties. As is indicated above, the term "accuracy" refers to the closeness ofan estimate ofa quantity to the true value. Accuracy is a measure ofrandom error plus bias error. The tenn "precision" refers to random error alone.



## 47

### An 

### estimate is precise 

## ifithas a small random error, regardless ofthe bias. Suppose, for example, that sources had been selected only from the GulfCoast, but that a very large number ofsources had been sampled. The averaging ofa large number of emission measurements would lead to an emission factor estimate that had a small random error. Unless GulfCoast sources were representative ofthe source type for the entire nation, however, the estimate could have a large bias because the sample ofsources did not represent the general population. Bias in this example is avoided by sampling in a variety ofregions ofthe country. More subtle potential sources ofsampling 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 ofbeing selected. A random sample is 

### expected to "match" the industry population because no biases are introduced 

### in selecting the sample sites. The number ofdata points required in a random sample depends on the target accuracy ofthe final 

### emissions estimate, the confidence with 

### which this accuracy is to be met, and the underlying variability among the emissions rates ofthe complete set ofsources. Random sampling is not a guarantee ofaccurate results. It is possible, for example, that by pure chance random sampling would produce a disproportionately large number ofsources from the GulfCoast and an under-representation ofsources from the West Coast. While such an outcome is unlikely ifthe sample size is sufficiently large, this particular problem can be avoided altogether by 

### selecting an acceptable number ofsources from each ofa set ofregions. (See the discussion ofstratified random sampling below.) There are two major reasons why truly 

### random sampling was not possible in the GRl/EPA program. First, a complete list ofsources 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% ofthe compressor stations, the list was not complete. Another example is the production segment, where it was not possible to produce a list ofall the individual well owners for random selection. The second point is that the owners ofthe randomly selected sources could not be required to participate inthe study. For this reason, there is no guarantee that a truly random sample ofthe available list could be tested.


### Stratified Random Sampling


### In stratified random sampling, the population ofinterest is divided into subsets, or strata. Then random samples are drawn from each stratum. For example, the sources ofinterest 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 ofsources sampled in.a stratum is in proportion to the total number ofsources in that stratum. For example, ifRegion Ahad 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 ofview, 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 ofsources by

**regio~.** 

### Alternatively, proportionality could be achieved on the basis ofgas production, rather than on the basis ofthe number ofsources. The variable or variables used to achieve proportionality must be closely related to emissions orproportionate random sampling could lead to biased results.


## 49

### Itis 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 ofsources 

### in the stratum (and 

### the throughput ofthe sampled sources is not proportional to total throughput in the stratum). This type ofsample 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 ortotal 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 ifstratified random sampling were 

## used rather than random sampling. Neither type ofstratified 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, atthe outset ofthe 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. Ifstratification had been performed on the basis ofall variables that could possibly have an influence on emissions, the munber ofstrata ( detennined by the number of variables and the number ofcategories for each variable) could have become unreasonably large. For example, for leakage from lUldergrOlmd distribution mains and services, a number ofparameters were identified that potentially influence emissions: pipe material, age, operating pressure, diameter, soil type, and parameters characterizing the leak detection and repair practices ofthe company. The required sample size can become large because ofthe total number ofstrata, 

### especially ifproportional 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 ofsamples were required to produce a proportionate stratified random sample for underground pipelines. Additionally, stratified sampling is ofno use unless there are activity factors that can be used to estimate the emission rate for the population. Complete information for all variables ofpotential interest does not exist. For example, the age ofa dehydrator, in most cases, is not even known by the o'Wller ofthe equipment. It would be pointless to stratify 

### dehydrator emission factors with 

### respect to age ifthe necessary activity factors cannot be obtained. Sampling Approach Selected for This Program 

### Thus, because ofvarious 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 ofthis project. This approach is very similar to disproportionate stratified random sampling, with 

### certain differences. Initially, some data were collected to determine ifa given source was a major contributor to methane emissions. For each source category, an initial estimate ofthe munber ofsources to be sampled was calculated based on an estimate ofthe accuracy target and the estimated standard deviation for the source category. The accuracy targets are based onthe need ultimately to estimate the national emission rate to within 

### 0.5% ofthe national production rate based on a 90% confidence limit. Sites were selected 

### in a random fashion from known lists offacilities, 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 ofall sources 

### in the United States was generally not available. Therefore, the final set ofcompanies 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 ofdata 

### was collected, the data 

### were screened for bias by evaluating the relationship between emission rate and parameters that may affect emissions. The topic ofscreening for bias is discussed further 

### in Sectio115 6.2 and 6.3. Ifa relationship between emissions and a parameter was found, then the population, orthe nwnber ofsources 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 ofstations under each station type 

### in the nation was determined. To stratify the population ofsources by a parameter, data were collected from companies on the distribution ofsources 

### in each stratum and an average over all companies sampled was detennined.
It 

### is important to realize thatjust 

### because a parameter or set ofstrata 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 ofsamples 

### inthe strata. To determine whether this has occurred, information is needed on the ratio ofthe number ofsources in 

### a given stratum to thetotal number ofsources for both the data set and at the national level. Ifthis 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 ofthe emission rate extrapolated to a national basis was evaluated and compared to the accuracy target. (Note: The accuracy target is a function ofthe magnitude ofthe emissions from the source.) Where necessary, additional data 

### were collected in various strata to improve the precision ofthe national estimate ofemissions from the source. The number ofadditional data points needed to meet the newly calculated accuracy target is computed based onthe 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 ofrevealing some bias, there are no tests nor group oftests 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 ofthe 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 ifit existed. All provable biases were corrected.
One example ofthe success ofthis bias review process includes the identification ofregional differences 

### in production practices. These differences were brought up by the advisor's meeting reviewprocess. 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 ofactivity factor screening bias includes extrapolation by two methods that validate each other. Ifboth methods are technically sound and independent, and ifthey deliver the same result for national totals, then this indicates that there is no bias 

### in the data set related to either variable. Ifa data set existed that was the perfect microcosm ofthe gas industry, one could extrapolate equipment counts from the data set to national totals by 

### any variable 

### inthe data set. Any extrapolation from the perfect microcosm would deliver the right answer, even technically unrelated data such as extrapolating separator cotmt by nwnber ofemployees 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, orthat 

### the sample set had some bias related to one or both variables. Nevertheless, ifthe 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 ofthe two extrapolation variables 

### in the data set.
Ifthe two methods produced results which differed widely, that might indicate that one orthe 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 ofthe 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 ofindustry expertise and/or engineering judgement. Ifthese parameters are determined to exhibit statistically different emission characteristics, then the population ofsources is stratified 

### into distinct categories by these design, operational, orregional 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 ofscreening for bias was beneficial. Table 6-1 shows the aVerage measured emission factor 54

### for metering/pressure regulatingstations, in 

### Wlits ofscf/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 ofmetering/pressure regulating stations. Assuming that the sample selection was random orrepresentative, the extrapolated 

### emissions are 

### I04.1 Bscf, based on the average ofall measurements to estimate the emission factor. However, ifthe 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 ofhigh 

### 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 asthe emission factor samples. In some cases, the activity f8.ctor can only 

### be stratified to the necessary level ofdisaggregation by gathering 

### data from industry.
Even ifa process does not produce a bias in the statistical sense described above, it is possible for a given segment ofthe population to 

### be seriously under represented and another segment to be over represented byrandom chance (i.e., by an anomaly 

### inthe random selection ofsources). 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 I00-300 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 ofthese variables. Such a disproportionality need not lead to a bias 

### in the fmal estimate ofemissions, 

### ifthis condition is identified and accounted for



### 56

### properly. Moreover, the screening process has been 

## carried out during the course ofthe study. Thus, additional sampling to correct a disproportionality, ifpresent, 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 ofsources is considered to be a significant benefit ofthe method used 

### in this study.


## 6.4 Accuracy Target


### The target uncertainty 

### in the emission estimate is 0.5% ofthe national methane emissions, on the basis ofa 90% confidence limit for the emissions estimate. Practical considerations allow sampling only a small percentage ofthe large

**num~er** 

### (tens ofthousands) ofsources that exist nationwide. Moreover, there is typically a large amount ofvariability among the sources in 

### a given category. In view ofthese considerations, meeting the accuracy target may seem insunnountable. Despite these facts, the target precision for the industry emission rate was achieved. The purpose ofthis 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 oftotal emissions is the sum ofthe emissions for all the strata. 

## An essential point is that the uncertainties are not additive; the uncertainty ofa sum is related to the sum ofsquares ofthe individual uncertainties. Ifthe errors in a sum vary independently, then they tend to "average out"; as a result, the relative uncertainty in 

### a sum ofterms (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 orvented 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 ofsumming the errors in 

### the different strata. Forthe purposes ofthe 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 ofsumming the emission estimates from a large number ofstrata. Also, it 

### has been assumed that undiscovered bias, ifany, varies "independently" from 

## stratum to 

## stratum. This type 

### oferror would exist ifthe 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 ofstrata would have a more serious effect on the fmal result. Theprocesses described earlier for screening for bias provide a protection against this (or any type 

### of) bias error. Additionally, given the large munber and diversity ofstrata, 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 ofthe calculations. The random error was chosen to be as large as plus or minus 100% ofthe emissions for each stratum, based on a 90% confidence interval. This is equivalent to assuming a coefficient ofvariation of approximately 0.6.



## 58

## TABLE 6-2. PERCENTAGE OF ERROR IN TOTAL EMISSIONS Bias·· Number ofStrata .. 

### (Percent of 20 Strata 40 Strata !00 Strata 

### Emissions) 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 ofthe emissions for a stratum. Inthe calculations, three values have been considered for the bias: 0%, 

### 15%, and 30%. In view ofthe methods used for screening for bias, 30% is considered to be a high 

### estimate.
As previously mentioned, the total number ofstrata 

### is approximately 140. It has been assumed that there are approximately I00 strata 

### with nearly equal emissions that 

### represent the major part ofthe industry emissions. Some ofthe strata (such as distribution 

### pipe type) 

### have been aggregated inthe 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 ofthe random and bias errors are fixed, the relative uncertainty inthe frnal result decreases as the number ofstrata increases. Tills is because the "error averaging effect" is greater ifa larger number of independent estimated quantities are summed. This does not mean that artificially increasing the number ofstrata would improve the accuracy. There would be fewer data points per stratmn, and the uncertainty ofthe emission estimate for each stratum would increase.

59

### Table 6-2 presents the percentage ofuncertainty 

## in the fugitive emissions 

## as a fraction ofthe 

### national production rate. The uncertainty is expressed 

### in terms ofa 90% 

### confidence interval. Since bias errors were considered as well as random errors, the numbers inTable 6-2 represent accuracy, notjust precision.
The accuracy target is met ifthe 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 inthe presence oflarge percentage random errors 

### in the individual strata and 

### an assumed large Wldetectable bias error.
Itmust be remembered that the random and bias errors were expressed as a fraction ofthe 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%) ofthe national gas production per year, which is 22,132 Bscf.
It is stated earlier in this subsection 

### that the uncertainty ofa smn isrelated to the sum ofsquares ofthe individual uncertainties. The uncertainty ofthe industry annual emissions have been calculated asthe square root ofthe sum ofthe squares ofthe uncertainties ofthe emission rates by category. Tbis method is strictly valid ifthe errors in 

### the different terms are uncorrelated. Two terms would have uncorrelated errors if

### there were no common source oferror. The method would still 

### be valid ifthe correlations were negligible.
A method recommended in the 

### Quality Control Handbook" by Juran, Gryna, and Bingham was used for quantifying the uncertainty ofa sum (on the basis ofassumed 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 

### ofwhich have estimated values that are the same within Wlcertainty. Also, no two ofthe terms have the same uncertainty. This method is based on a theorem that is proved byMood, Graybill, and Bees in 

### Introduction to the Theory of Statistics 16 

### (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. Ifinspection 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 ofthe effect ofcorrelated 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 byrigorously calculating errors for average values produced from replicate measmements, and then by propagating error from each individual group ofmeasurements into the national numbers. Tb.is section provides a briefdiscussion ofthe statistical methods used for the overall methane emissions project. Volume 5 on activity factors1 

### summarizes the general statistical propagation techniques used, and Volume 410

### provides the full details ofthe 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 ofthe estimate. The 1992 plan also set an absolute accuracy target 

### 61

### of±0.5% ofgross production for the 90% upper confidence bolllld ofthe annual national emission rate. This is equivalent to an absolute accuracy target ofapproximately ± 111 Bscf. Forthe estimate of307 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) ofthe actual estimate. Any one source category within the sum ofall sources may have a much larger confidence interval than ± 35%, since error bands are not 

### additive directly, but are added as the square-root ofa sum ofsquares. Consequently, 

### it is possible for a sum to have a smaller relative uncertainty 

### than do the individual terms (although the absolute uncertainty ofthe sum is larger than that ofany 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 theprecision. However, accuracy is made ofprecision 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 ofpractical reasons. Another potential source ofbias 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 Emissionsfrom 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 Emissionsfrom 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 Emissionsfrom the Natural Gas Industry, Volume 10: Metering andPressure Regulating Stations in Natural 

### Gas Transmission andDistribution, 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 Emissionsfrom 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 Emissionsfrom the Natural Gas 

### Industry, Volume 7: Blow andPurge 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 Emissionsfrom 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 Emissionsfrom 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. 

### Myers, D.B. Methane Emissionsfrom the Natural Gas Industry, Volume 14: 

### Glycol Dehydrators, Final Report, GRl-94/0257.31 and EPA-600/R-96-080n. 

### Gas Research Institute and U.S. Environmental Protection Agency, June !996. 

### Williamson, H.J., M.B. Hall, and M.R. Harrison. Methane Emissionsfrom the 

### Natural 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. 

### U.S. Department ofEnergy/Energy Infonnation Administration. Natural Gas 

### Annual, 1992. DOEIEIA-0131(92), Washington, DC, Sept. 1992. 

### Wright Killen & 

### Co. Natural GasDehydration: Status and Trends, 

### Final Report. GRJ-94/0099, Gas Research Institute, Chicago, IL, January 1994. 

### Stapper, 

### C.J. Methane Emissionsfrom the Natural Gas Industry, Volume 11: 

### Compressor Driver Exhaust, Final Report, GRJ-94/0257.28 and EPA-600/R

### 96-0SOk. 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 ProductionSourceSheets

A-I

### SOURCE SPECIFIC EMISSIONESTIMATES
This appendix presents the source specific emissionestimates derived from emission factors and activity factors for the sources ofemissions 

## within the narural gas industry. Each significant source ofemissions 

## has a "source sheet" that

### gives a synopsis of the basis ofthe estimate. These estimates are presented in 

### a format which documents the approach for extrapolation ofdata to 

### a national estimate. Theemission factor and activity factor presented represent the fmal 

### estimates from the program. Each source sheet is divided into two sections, eachone describing the basis for the emission factor and activity factor, respectively. The approach used to determine the accuracy ofthe 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 

### CompressorExhaust ............................ A-5 Fugitive Emissions .............................A-10 Gathering Pipeline Leaks .........................A-17 

### Pneumatic Devices .............................A-22 Chemical InjectionPumps .........................A-25 Glycol Dehydrator Vents .........................A-28 Glycol Pumps ................................A-32 Maintenance Venting ............................A-35 Upsets .....................................A-38 Pipeline Dig-ins ...............................A-41 Well Completionand Workovers ....................A-42

A-3

### PRODUCTION SOURCE SHEETS This sectioncontains the specific source sheets for the production segment ofthe natural gas industry. The following table serves as aguide for finding sheets inthis section. The cells in the table give the sheet number (P-1, P-2, 

### etc.) ofthe source sheet. The rows defme the 

### equipment covered. while the columns defme the operating mode and emission type. 

### A category with no sheet numbermeans that 

### the emissions from that 

### area were determined to be negligibly small. The label for each source sheet is shown at the top ofthe 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-4SOURCES' OPERATINGMODE' 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 

### productionfields, processing plants, gas storage fields, and along transmlssion lines. Methane emissions are found incompressor driver exhaust {reciprocating engines and gasrurbines} because ofthe incomplete combustionofthe natural gas burned as fueL 

### EMISSIONFACTOR: (0.240 

### ± 5% scflhpilr, engines and 0.0057 

### ± 30% scf/hp-hr, turbines) An 

### average emissionrate was calculated 

### for each model ofcompressor engine and turbine in

### the GRl 

### TR.ANSDAT Emissions Database (l),which is based on compressor tests conducted by 

### SouthwestResearch Institute (SwRl). 

### The emissionrates were calculated 

### from the reponed methane emissionsper unit

### offuel 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 CHJscffuel) 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 inthe Emissions 

### Database.

where: 1E = 

### total emissions for 

### database, (set)

**~** =o annual operating hours for compressor i, (hr/yr)

K = number ofunique compressor models M = number ofcompressors ofmodel, m



### A-5 (1)

(2)The emissionfactors, for engines and turbines, were then calculated using the followingequation. 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)

Thisequationconsiders that some models could

### be operated at a higherpercentage ofthe time because they 

### are base loaded compressors. The average emissionfactors forthecompressor drivers 

### in the Emissions Database are0.240 scf/hp·hr for reciprocating engines and 0.0057 scflhpilrfor turbines. 

### EF DATA SOURCESo l. "National Estimate ofMethane Emissions from Compressors inthe U.S. Natural Gas Industry" (2). EFACCURACY: 

### ± 5%, engines and 

### ± 30%, turbines Basis: The accuracy for the EFis estimatedbased on propagation oferrorfrom the spread ofsamples in the database. However, engineeringjudgementwas used to assign 

### accuracy for two ofthe individualterms inthe equation, as follows: 

### l. Hydrocarbonanalysis was estimated to be 

### ± 10%, based onthe generally accepted accuracy ofgas chromatographs 

### (flame ionizationdetector). 2. Likewise, fuel flow 

### measurements were estimatedto

### be 

### ± 2.5%. ACTIVITY FACTORS: (horsepower-hour) Horsepower·hour data were available for the prOduction industry segmtnt activity factorcalculation. Two pieces ofinformation are needed to calculate the activity factor, which isexpressed as horsepower·hours (hpilr) for each type ofdriver ineach ofthe remaining industry segments. These are the installedhorsepower and the average operating hours. The following tablepresents these parameters and the resulting activity factors for both engines and turbines 

### in each segment ofthe industry. The sources and methods for calculating all the values presented in the tablebelow are given inthe next section: AF Data Sources. It is estimated that about 94% ofthe emissions 

### in compressor and generatordriver exhaust are from reciprocatingengines used inproduction, processing, and transmission, with about5% attributable to reciprocating engines used in storage. All othercategories arenegligible 

### in comparison. Therefore, 

### it is more important toaccurately determine the activityfactors for reciprocating engines 

### inproduction, processing, and transmission.



### A-6COMPRESSOR DRIVERACTIVI'IYFACTORS FOREACH 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

CompressorD!'ivers 10.2 ± 10.0% 4.55 ± 10.0% 3964 ± 13.8% 2Il8 ± 31.3% 40.380± 17.1% 9635 ± 33.0% GeneratorDrivers !.45 ± 23.3% 0.045 ± 166% 1352 ± 38.0% 474 ± 620% 1962 ± 45.4% 21.2 ± 1215% Storage

CompressorDrivers 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% • Doesn01 include horsepowerassociated with gas lift for oil recovery orwilb electricdrivers. • Averageoftwo estimationmethods. AF DATA SOURCES: l. Theproductionsegmenthorsepower is based onthetotal installedhorsepower-hours for data providedbyonecompany for 516compressor drivers (all reciprocating engines). The horsepower·hours for the company was dividedbytheirproductionbefore scalingto a national estimate. Nationalhorsepower·hou:was calculatedusing the 1992 marketed productionfor the U.S. [Natural GasAnnual 1992, (3)]. 2. Theprocessing segmenthorsepower was determinedby taking the average oftwomethods. Each ofthe methods uses sitedata for the lO gas plants visited. The first method scales toa national estimateby multiplying thetotal U.S. gas plantthroughput as ofJanuary l, 1993 [46,510.7MMcfd, Oil & GasJournal (4)} by the total site visithorsepowerper throughput (47.8hp/MMcfd, engines and 59.2 hp/MMcfd, turbines). The second method scales to a national estimateby multiplying the total number ofgas plants 

### in the U.S. [726, Oil & Gas Journal (4)J by thetotal sitevisit horsepower per number ofgasplants visited (10), which is a scale-upratio ofabout 73. Theannual operatinghours are based on the 10 sites plus data from two companies for an additional 18 gas plants. An average ofthe average operating hours per site was calculated to get !he processing segment operatinghours (203 engines and 9 turbines). 3. The transmission segment compressor stationhorsepower foreach compressor drivertype is based on the GRI TRANSDATdatabase. Installed horsepower was taken from the Industry Database module ofGRI TRANSDAT. The annual operatinghours are based oninformation reported on FERC Form No. 2. FERCdatadoes not distinguish between drivertype. The PERC data were splitbetween engines and turbines based ondata 

### in GRITRA.NSDAT and dataprovidedby one transmission ccmpany (524 engines and 89 turbines). 4. Thestorage segmenthorsepower came from Gas Fads (5)data for 1992 (1,920,441 hp). The splitbetweenengines and rurbines was assumed tobe the same as the engine and turbine splits found 

### in GRITRANSDAT (69.1%, engines and 30.9%, turbines). Theannual operating hours are based on 11 storage stations (50 engines and 6 turbines). An average ofthe average operating hours per station was calculated to get the storage segment operating hours.


### A-75. The generator driverhorsepower (compressor stations) is based onthe total installed horsepower for 7 ofthe transmission sites visited and company data for 34 transmission compressor stations. To scale to a national estimate, the total horsepowerperstation was multipliedby the total number oftransmission compressor stations [1'700, FERC Form No.2 

### (6)J in the 

### U.S. The 

### annual operatinghours are also based ondata 

### from the site visits and company data. An average ofthe average generatoroperatinghours per station was calculated to get generator operatinghours (87engines and 1 turbine). 

### 6. Thegenerator driverhorsepower (storage fields) is based on the total installedhorsepower for 9 storage fields (one company). Toscale to a national estimate, the total horsepower per field was multipliedbythe total number ofstorage fields [475, GasFacts (5)1 

### in the United States. The annual operatinghoursare also based onthe company data. An average ofthe average generatoroperatinghoursper field was calculated to 

### get generatoroperatinghours (3 engines and 1turbine). AF ACCURACY' Basis: Errors were propagated from each ofthe following terms: l. ProductionHp·hr: TheproductionHp·hraccuracy 

### is based upon 

### an engineering analysis and set at ± 200%. 

### 2. Transmission Hp·hr: Thetransmission Hp·hraccuracy is based uponan assigned estimated errorof± 

### IO% for the horsepower 

### data in the 

### GRI TRANSDATdatabase and error propagationfrom the FERCoperatinghours. 

### 3. Other segment Hpilr: The accuracy ofthe site visitdata forhorsepower and operatinghours was alsopropagated using

### the spread ofthe data, but from much smaller data sets. The accuracy ofthehorsepower-hour activity factors for each industry segment are calculated statisticallyusing the individual terms for horsepower and operatinghours. ANNUAL METIIANE EMISSIONS: (24.57

## ±65.1% Bscf, engines+ 0.256

## ±97.8%

### Bscf, turbines) The

### annual emissions were determinedby multiplyingan emissionfactor by the horsepower·houractivity factor for reciprocating engines and turbines and summing these values for each segment. Thefollowingtable shows the resulting emissions foreach industry segment and the overall national estimate. ANNUAL COMPRESSOR EMISSIONS FORTHE NATURALGAS 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, D.L., L.M. Campbell, C.E. Burklin, M. Gundappa, and R.A. Lott, ''National Estimate of Methane 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 ofEnergy/Energy Infonnation Administration. Natural GasAnnual, 

### 1992. DOE/EIA-0131 (92), Washington, DC, September 1992. 4. Oil & GasJournal. 

### 1992 Worldwide Gas Processing Survey Database, 1993. 5. American Gas Association, Gas Facts: 

### 1992 Data, Arlington, VA, 1993. 6. Federal Energy Regulatory Commission (FERC) Form No. 2: Annual Report ofMajor Natural Gas Companies, !992 database.



### A-9SOURCEs, OPERATINGMODE' EMISSION TYPE' ANNUALEMISSIONS' BACKGROUND' 

### P-2 PRODUCTION SOURCE SHEET All ProductionEquipment (See Below) 

### Normal Operation Steady, 

### Fugitive 17.4 Bscf

## ± 41% Equipmentleaks are typically low-level, wrintentionallosses ofprocess fluid (gas orliquid) from the sealed surfaces ofabove-groundprocess equipment. Equipmentcomponentsthat tend to leak includevalves, flanges and otherconnectors, pump seals, compressor seals, pressure reliefvalves, open-ended lines, and sampling connections. These components represent mechanicaljoints, seals, and rotating surfaces, which 

### in time tend to wearand develop leaks. EMISSION FACTOR: (scf/equipment-yr, seebelow) In 

### the componentmethod forestimating emissions from equipment leaks, an average emissionfactor is determined foreach oftlle basic components, such as valves, flanges, seals, and otherconnectors thatcomprise a facility. The average emission factor for each type ofcomponent is determined by measuring the emission rate from a large number Ofrandomly selected componentsfrom similartypes offacilities throughout the country. An average estimate oftheemissions perequipmentor facility are determined as the product ofthe average emission factor per componenttype (i.e., thecomponentemission factor) and the average numberof components associated with the majorequipnentor facility:

where: N, = average countofcomponents oftype x perplant, and EF, = average methane emissionratepercomponent oftype x. Componentemission factors for fugitiveequipment leaks 

### ingasproductionwere estimated separately for onshoreandoffshore productiondue to differences 

### in operational characteristics. Regional differences were found toexistbetween onshoreproduction

### inthe Eastern U.S. (i.e.,Atlantic and Grear Lakes region) and the Western U.S. (i.e., rest ofthe country. excluding the Atlantic and Great Lakes region) and between offshore production inthe GulfofMexico and the Pacific OuterContinental Shelf (OCS). Separate measurement programs were conductedto account for these regional differences. Onshore Production 

### in the Eastern U.S. Region. Gas production in the Eastern U.S. accounts for only 4.2% ofgrossnational gas production, but includes47% ofthetotal gas wells 

### in thecountry. Componentemission factors foronshore production inthe Eastern U.S. were based on a measurement program conductedby GRI/Star Environmental (1) of 192 individualwell sites at 12 eastern gas productionfacilities. Component counts for gas wellheads, separators, meters and the associated above-groundpiping, and gathering compressors were based on informationcollected as panoftheEastern U.S. prOduction measurement program. Sitevisits and phone surveys of7 additional sitesprovided data used for determining the numberofheaters and dehydrators inthe Eastern U.S. region. Component counts for heaters and dehydrators were assumed to be identical to those derived from data collected in theWestern U.S. Thefollowingtable presentsthecomponent emission factors, average componentcounts, and average equipmentemissions for onshore gas production inthe Eastern U.S. region.



### A-10Average EquipmentEmissionsfor Onshore Production 

### in the Eastern U S 

## .. EquipmentType 

### ComponentType 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 inparentheses represent the 90% confidence interval. Onshore Production in the Western U.S. Region. Component emissionfactors for onshoreproduction 

### in the Western U.S. were based on a comprehensive fugitive emissions measurement programconducted by API/GRI (2) at 12 oil and gas production sites. 

### In this program, measurement data were collected from 83 gas wells at4 gas production sites in the Pacific, Mountain, Central, and Gulfregions. The average componentcounts for each pieceofmajor processequipmentassociated with gas production in theWestern U.S. were based on data collected during the APIIGRI study and additional data collected for GRIduring 13 sitevisitsto gas production fields. The followingtable presents the component emlssion factors, average component counts, and average equipmentemissions foronshoregasproduction inthe 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 EmissionFactor, 

### 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 

### Gathering Valve 0.835 73 97,729(68%) 

### Compressors 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

StationComponents

**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:hebasis for estimated emissions from large compressor

stations.


### A-12Offshore GasProduction. Emissionsfrom equipment leaks from offshore production sites inthe U.S. were based on two separate measurement programs:
• The API/GRI oiland natural gasproduction operations study. which included 4 offshore production sites in the GulfofMexico; and
• The Minerals Management Service study of7 offshoreproduction sites in the Pacific Outer Continental Shelf. Thecomponent emission factors and component counts were taken directly from the field test reports from these studies. The following table presentsthe component emission factors, component counts, and average facility emissions for offshoreproduction 

### in the GulfofMexico and Pacific OCS. Average FacilityEmissions for OffshoreProduction EquipmentTYPe Component Type Component Average Average Facility Emission Factor, Component Count

**Emissions,~** Mscf/component-yr Mscf/yr GulfofMex..ico Valve 

### 0.187 2,207 1,064 (27%) Platform Connection 

### 0.046 8,822 Open-EndedLine 

### 0.368 326 Other 

### 2.517 67 Pacific OCS Valve 

### 0.048 1,833 430 (36%) Platform Connection 

### 0.021 13,612 Open-EndedLine 

### 0.092 313 Other 

### 0.091 307 • Values 

### inparentheses represent the 90% confidenceinterval.
EF DATA SOURCES' I. Emission Factors for Eastern Gas Productionbased upon data from the GRI/Starprogram (1) for the component EF's at 12 gasproduction sites. 2. Fractionofmethane (78.8 mol%) based on 

### data fromMethane Emissionsfrom theNatural 

### Gas Industry, Volume 6: Vented and ComhustedSource Summary (3). Conversion ofemission factors from (pounds THCperday) to (methane Mscf/yr) also required estimation ofgas average molecular weight. Based on data from Perry's Chemical EngineerHandbook (5th Edition) (4), Table 9-15, selected most similargas compositionspeciation from C1through C6.,. and performed linearextrapolationfrom average of3 lowest data (87 mol% methane) to 78.8 mol% methane. Resultant weightpercent of69.6wt% methane used to speciate methane emissions. 3. Componentcounts in Eastern gasproduction were based on average counts perequipment from the GRI/Starprogram at 12 gas productionsites. Componentcountsfor heaters and dehydrator inthe Eastern region were based ondata collected intheWestern region. Componentcounts for onshoreproduction inthe Western U.S. were based on the averages 

## A-13from the GRI/Starprogram at 4 gas production sites and GRI/Radian data from 13 site visits 

### wgas production fields. 4. Offshoredata from APIIGRI/Star 20-siteprogram for GulfofMexico platforms (4 platforms, site numbers 17 through 20), and Minerals Management Service/ABB Pacific OCS fugitive study (7 platforms). See respective test repons (GuJfofMexico Offshore: API!Star 20-site study (5); Pacific OCS Offshore: MMSreport 92-0043 November 30, 1992) (6). 

### 5. Large gatheringcompressors and large gatheringcompressor stationemission 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 Gatheringcompressors
- Western LargeGathering Compressors LargeGathering Stations Offshore 

### (GuJO Offshore (Pacific) 

### ± 27% 

### ± 27% 

### ± 43% 

### ± 35% 

### ± 30% 

### ± 27% 

### ± 24% 

### ± 33% 

### ± 40% 

### ± 25% 

### ± 30% 

### ± 68% 

### ± 65% 

### ± 102% 

### ± 27% 

### ± 36% Theaccuracy is rigorouslypropagated through the EF calculation from the range ofindividual measurements. Ninety percent confidence intervals were calculated for the sites using the r-statistic method. Computed 90% confidence intervals for site average component counts were combined with 90% confidence intervals for component emission factors to obtain pooleduncertainty inaggregate emissionfactor. ACTIVITY FACTOR: (129157Gas Wells· Eastern) (91670 Separators -Eastern) (260 Heaters

- Eastern) (1047 Dehydrators 

### -Eastern) (76262 Meters

- Eastern) (129Gathering Compressors -Eastern) (142771 Gas Wells

- Western (74674Separators -Western (50740 Heaters- Western (.36777 Dehydrators

- Western (301180Meters- Western (16915Gathering Compressors

- Western) (96 LargeGathering Compressors) (12 Large Gathering Stations) (1092 GulfofMexico 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 equipmentAFs were regionalized using sitevisit

### data. Eastern meter AF based on0.43 meterper gas industry well {per Star Environmental). Western U.S. meter AF based on industry advisor information of I:1meter pergas industry welL 3. Dehydratorcounts are based_on 37,824glycol dehydrators in production (see Sheet P-6 for details). Adjustment to activity factor for Eastern gas production: subtract I,047dehydrators (included 

### in Eastern gas productioncomponentcounts). 

### 4. Offshore platformcounts provided by 

### Offshore Data Services, Inc., Houston, Texas, and Minerals Management Service MOAD database for producingplatforms. 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 of3.3 s1ages per compressor). The result 

### was extrapolated to the national total by ratioing on gathering miles covered in FERC to total gathering mileage. 6. Theotherequipmentcounts were produced from equipment count data taken during the site visitsby Radian and Star. As explained inthe activity factor section ofthe text ofthis report, extrapolarion to national counts was done on a regional basis to account for regional equipment configurationdifferences. AF PRECISION' 

### Basis: 1.


### 2.
REFERENCES' Theprecision for the active wells is assigned by engineeringjudgement, based upon the fact that the number ofactive wells is tracked nationallyand known accurately by A.G.A./DOE, etc. The accuracy for the otherequipme:J.t types is based upon rigorouspropagation oferror 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 Emissionsfrom Oilarui Gas Production Operations, {API Publication No. 4589). American PetroleumInstitute, December 1993. 3. Shires, T.M. and M.R. Harrison. MethaneEmissionsfrom theNatural 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 ProtectionAgency, 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 Factorsfor Oiland Gas Production Operations. (API Publication No. 4615). American Petroleum Institute,January 1995. 6. R. Countess, e! al. FugitiveHydrocarbon Emissionsfrom Padfic OCSFacilities. 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

### ANNUALEMISSIONS: (17.4 Bscfiyr 

### ± 7.1 Bscf/yr) 

### The annual emissions were determined by multiplyingthe average equipmentemissionsby the populationof equipment in

### the segment.



# ""'" &niS5ionFIC!Or Activity

**Fae~or** Emi!sion kate Ur>eertainty Gas WcllhAC! (&stemU.S.) 2S9S s.Cyrme!b&n< 129157Sa$ wrll• (East=U.S.) 0.34 Bsdlyrll'lcth&ne 

# "" Sepan10n<Eastem U.S.) 328 sdlyrmethane 91670

**~** (Eur<:m U.S.) 0.03 Bsdi'yrmcthane )6% HQ!cn (Eutem U.S.) S117 sd7ynnethcl• 260 heum(E.o.mrn US.) 0.001 Bsef/yrmctht.O.e 21S"/o Dehydnton{Eastml U.S.) 1939se£1yrmeth&n< 1047dehydratcn{Easttrn U.S.) 0.008 Bsdi'yr

**mctha~~o** 4Wo Meters/Piping {EUtmlU.S.) 3289 s..U)'TmW!a:ne 16262 meier$ (E&s!cm U.S.) 0.2S Bsdlyrm<tlwte 

# '""'· Guhering

**Com~sso"** (&slemU.S) 4417<ciJyT me!hme 129gatlu:ringccmprtSson {EaslmlUS.) 0 0006&dlyrmethane «% Gas Wellhuds (West= U.S.) I>302 sd7yrmeth..,. 142771 SA!

**~n.. (W~**  U.S.) 1.9 Bsdi'yrmelhme 25"!. Seporuon(W.,tem U.S.) 44SJ6se!7yrmothme 74674 sep.mon(Wesrem U.S.) 3.33 8sdt')'rmcth&ne 69"/o Hutern (Western US.) 21066scf/yrmetlw>e 50740in-Jiaebtatm(Western U.S.) I.07Bsct:'yrmethane !10"/o Dehydruor$(We<lml u.S.) 33262sc:O)T
....

### m- 36mokhydraton(Wes!Cm U.S.) I.22 Il$o;fi}'Tmethme 

# "" Me1e:rs (Western U.S.) 19310sc:f7yrlllttbme 301JB0111etm (West=U.S.) 5.12 &c:Vyrmethllle 109'"!. Slllall Galhe:riqCompn$$0rs{Wtstem **m29sd/yr~** l691S «>mp<nson;(Wes!Cnl U.S.) !.65Bscfiyrmethllle "% U.S.) Lo.rge Galherins

**Camp~uors** (Weslm! S.SS MMscf7)T 111eth..,. 96li%E<' eomprusc:n 0.53 Bsdi'yrmtthme ]36% U.S.} I...vv Gathering Ccmpm;scrSwicn• l.Ol MMscflyr

**metha~~e** 12 large gatheringcQl!lp<eSsorsutiom 0.04 Bscflyrmethane 116% **(W~!em** U.S.} Offshcre Oil/0.. {Gulf) 1064 Msdl'yrl!lelbl!l< 1092 GulfcfMexl«>pl.rt!cm"l$ !.16B>oflyr'lletbllle 29"/, OffshoreOil/Gas

**~ific)** 430.0Msdlyr

**metbn~** 22 plufonn•(P•cific) o.ol Bscflyr'llethme 38'\'o

**=~** 17.4 Bsc:f/yr

**~nethme** 41%



### A-16P-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 orprocessing 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 for main pipelines from the cooperative underground distribution leakage measurement program. A mean value ofthe 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 isolated segment ofpipe; therefore, the mean leakage rate for cast iron is in terms ofleakage per unit length ofpipe. The natural gas leak rate is adjusted for methane by multiplying bythe volume percent ofmethane for production (78.8 vol. %), and is adjusted for the soil oxidation ofmethane. The value ofthe 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 unitlength 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-17ACTIVITY FACTORo The estimated number ofleaks 

### 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 ofgathering 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 halfthe year, and each leak repair is counted as halfan 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 ofthe survey method perfonned, which is estimated to fmd 35% and 85% ofthe total leaks for a vegetation and walking survey, respectively, based on one contract company specializingin 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 walkingmethod, based on conversations with several transmission companies. Based on this analysis ofequivalent leaks, the leak frequency is 0.18 leaks permile for a walking survey and 0.63 leaks permile for a vegetation survey. This leak frequency was used to ratio the number ofleaks tothe total estimated population ofgathering pipeline. Total gathering pipeline mileage is notreported or trackednationally and must be estimated. The "gathering pipeline" designation includes three categories ofpipeline: 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 thatproduce marketed gas (i.e., associated gas wells); and 3) transmission company owned gathering pipeline. The third category ofutility-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 ofgathering pipeline fornon-associated gas wells were estimated using site visit data from the thirteen production sites shown in the following table. Seven ofthe thirteen sites provided estimates oftheir total miles ofpipeline. The

### fifth site's mileage was estimated from a map of

### its pipelines.



### A-18Site Gathering Miles Number ofWells 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. The estimate oftotal gathering miles pernon-associated gas well was derived as the weighted average total miles divided bytotal wells (0.67 ± 28%). The average mile per well ratio was extrapolated by the nationally tracked number ofnon-associated 

### gas wells (276,000). The resulting estimate ofnational gathering pipeline miles associated with gas wells is 184,000. Forthe gathering pipeline mileage associated with oil wells that market gas, the same ratio ofgathering miles perwell was applied. However, it was assumed that onlyha1fofthe gathering pipeline mileage was attributed to the gas industry; the other halfwas attributed to the oil industry. Therefore, the average ratio of pipeline miles to oil wells marketing gas was estimated to be0.33. This average ratio was extrapolated by the estimated numberofoil wells marketing gas in the U.S. (209,000). The resulting estimate ofgathering pipeline mileage associated with oil wells that market gas is 70,000. The third category ofgatheringpipeline owned bytransmission 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 andare 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 tobe 340,200 miles. A rigorous detennination ofthe 900/o confidence interval gave an error less that4%, which was considered low based on the quality ofthe data used to generate the activity factor. Thus, a 90% confidence interval of± I0% was assumed based on engineering judgement.



### A-19Based 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 permile 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 oftotal equivalent leaks by pipe material category is based on the breakdown ofpipe 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 ofcast iron. It was assumed thatno 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 ofestimated gathering line leaks was allocated on a pipeline material category basis 

### in the same proportion (adjusted for the fraction ofmileage in each material category) as in the distribution sector. The precision ofthe 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: 

### ± I00% 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 ofthe cast iron mileage estimate is assumed to be 

### ± 10%. The following table summarizes the estimated average activityfactor 

### and the precision:

Pipe Material Total Miles Average Activity Units ofActivity 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 milesfor gas and oil wells marketing gas was estimated using Phase 3 site visit data for seven production companies. The number ofgas and oil wells for these companies was also used to extrapolate outto the

**nation~!** estimate. 4. The numberofproducing gas wells in the United States was taken from A.G.A. 

### Gas Facts (2) 

### foe 1992. 5. The number ofoil wells producing marketed gas 

### in the United States was estimated by Radian (5). See activity factor section and sheet P-2.


### A-206. 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 toderive 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 ofTransportation, Research and Special Programs Administration. 1991. 2. American Gas Association, 

### Gas Facts, Arlington, VA, 1992. 3. Palisade Corporation. 

### @Risk, RiskAnalysis andSimulation Add-InforLotus l-2-3, Version 1.5, Manoh 1989. 4. Southern Cross Corporation. 

### Comments onDock£! PS-123, Notice 1, Leakage Surveys, 49 CFR Part 192, Department ofTransportation, Research and Special Programs Administration, Materials Transportation Bureau, Office ofPipeline Safety Regulations, December 19, 1991. 5. Stapper, B.E. 

### Methane Emissionsfrom theNatural Gas Industry, Volume 5, ActivityFactors, 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: OPERATINGMODE: EMISSIONTYPE: ANNUALEMISSIONS: BACKGROUND: P-4 

### Pl{ODUCTION SOURCE SHEET 

### Various Equipment (wells, heaters, separators, dehydrators, compressors) 

### Pneumatic Devices Normal Operation Unsteady, Vented 31.4 Bscf

### ± 65% Mostofthepneumaticdevices 

### inthe industryare valve actuators and controllers thatuse nanual gas pressure as the force for valve movement. There is a large populationofpneumatic devices throughout thegas industry. Gas from the valve actuator is vented to the atmosphere during every valve stroke, and gas maybecontinuously 

### bled from the valve 

### controllerpilot as well. EMISSIONFACTOR: 125,925

### scfperava-age

### device 

### ± 40% (This was adjustedfor theproductionmethanefraction

## ornatural gasat 78.8mol%.) Pneumatic devices (valve controllers) linked tocontrol valves are the largest source ofpneumaticemissions in the productionsegment. There aretwotypesofdevices

### with distinctbleed modes: intermittent and continuous. Intermittentbleed devices emit methane to the atmosphere only when the control valve actuates; when the device is notmovingthebleedrate 

### is zero. Continuousbleed devices emit methane both when the valve 

### actuates and when the device is notmoving. An emissionrate for a genericpneumatic device combines thebleed rates ofthe twotypes ofdevices, weighted 

### by the

### populationofthe 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 intermittentand continuousbleed devices were based on measured dataprovidedby a Canadian study and U.S. field measurements from a separate contractor'sprogram. The average measured emissions for intermittent and continuousbleed devices are 323 

## ±34% and 654

## ± 31% scfdldevice, respectively. The fraction ofeach typeofdevice wasdeterminedfrom 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. 

### MethaneEmissionsfrom theNatural GasIndustry, Volume 12: PneumaticDevices (1) establishes theimportantemission-affecting characteristics. 2. Site visit device countsestablish the fraction ofcontinuousbleed versus intermittentbleed 

### A-22devices for multiple sites. 3. The Canadian Producers Association (CPA) determined an average emission factor perdevice based on 19 measurements. 4. An independent contractorprovided 18 measurements ofpneumaticdevices inonshore and offshoreproductionservices. EF PREC!SIONo Basis: EF accuracy is based on rigorous errorpropagation from the spread ofsitedevice counts and measured emissionrates. 

### ACTIVITY

**FACTOR~** 

### 249,1Il pneumaticcontrollers 

### ± 48 % The average count ofdevices perequipmenttype

### was determined from multiplesite visits. The ratios for the number ofdevicesper gas well and the numberofdevices 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 givethe

### final national device countof249,111. AF DATA SOURCESo 1. MethaneEmissionsfrom theNaturalGasIndustry, Volume 5:ActivityFactors (2)establishes the methodology forextrapolatingthe site data to a national count. 2. Site visitdevice counts, well counts, and productionrates establish the number ofdevices per well and the number ofdevices pergas production. 3. Total regional gas well counts and 1992 marketed gas productionrates are from A.G.A. Gas Facrs (3). 4. The oil wellsthat market gas were calculated bythis report and World Oil (4). Total oil wells for 1992 are reponed as 602,197by the Oil & GasJournal (5). Theactive oil wells that market gas are determinedby multiplying the total national active wellsby the fraction that market gas. The fraction is determined from aTexas Railroad Commission database (6) on oil leases and gas disposition from those leases; ananalysis that shows the percent ofoil leases that market the associated gas inTexas is 34.7%. AF PRECIS!ONo Basis: I. 

### 2. The accuracy for thedevicesperwell and devices pergasproductionrate are calculated from the spread ofsitedata collected for each region (a total of36 sites). The accuracy for wells that market gas 

### are based on the spread ofdata 

### from the Texas Railroad Commissiondatabase. 

### ANNUALMETHANEEMISSIONS: 31.4Bscf

### ± 65 % The national annual emissions were determined by multiplying an emission factor for an average pneumatiC deviceby the populationofdevices 

### in the production segment. 125,925 scf x 249,111 devices = 31 Bscf



### A-23REFERENCES 

### 1. Shires, T.M. and M.R. Harrison. Methane Emissionsfrom the Natural Gas Industry, Volume 12: 

### PneumaticDevices. Final Report, GRI-94/0257.29and EPA-600/R-96-0801,Gas Research Instituteand U.S. Environmental Protection Agency, June 1996. 

### 2. Stapper, B.E. MethaneEmissions from theNatural GasIndustry, Volume 5: ActivityFactors. 

### Final Report, GRI-94/0257.22and EPA-600/R-96-080e, Gas Research Instituteand U.S. Environmental ProtectionAgency, June 1996. 3. 

### American Gas Association. 

### GasFacts: 1993 Data, Arlington, VA, 1994. 

### 4. GulfCoast Publishing Company, 

### World Oil, Annual Forecast/Review, Vol. 214, No.2, February 1993. 5. Oiland Gas

### Joumal. 1992Worldwide Gas Processing Survey Dalabase, 1993. 

### 6. Texas Railroad Commission, P-1, P-2 Tapes, Radian 

### files, Austin,TX, 1989.



### A-24SOURCES: COMPONENTS: OPERATINGMODE: EMISSIONTYPE: ANNUALEMISSIONS: BACKGROUND: 

### P-5 PRODUCTIONSOURCESHEET 

### Wells, Gathering Facilities Chemical Injection Pumps Normal 

### Operation Unsteady, Vented 1.5 Bscf

### ± 203%

Gas-driven chemical injectionpumps use gaspressure acting on apistontopump a chemical onthe opposite 

### side ofthe piston. The gas is then vented directly tothe atmosphere. Thepumps are used to add chemicals such as corrosion inhibitors, scale inhibitors, biocide, demulsifier, clarifier, and hydrate inhibitors to operating equipment. Two typesofpumps were observed: I)pistonpumps, and 2) diaphragmpumps. Some ofthe pumps observed were inactive at the time orhad seasonal operation. 

### EMISSIONFACTOR: 248 scfd/averagepump 

### ± 83 % (fhis 

### was adjtmedfortheproductionmethanecontent in

### natural gasat78.8 mol%.) This average emissionfactor is basedupon the following equation:

where: 

### Fpis""' 

### = 

### EFpl>IOO = Fd;.;.tu.gm =

**EFd~** = fraction ofthepump populationthatis the pistontype = 49.8% 

### ± 38% emission factor ofan average piston·pump = 48.9scfd/pump 

### ± 106% fraction ofthe pumppopulationthat is the diaphragm type= 50.2% 

### ± 38% emission factor ofan average diaphragm pump = 446 scfdlpump 

### ± 77% The average device emission factor was determined by an aggregationofdevice emissions calculated for multiple

### U.S. sites. Forpistonpumps, the emission factor was determined by the followingequation:

where: 

### EFP"""'

Gas usage = Density Frequency = Operating time = %methane = Gas usage (acffstrok:e) 

### x Density (scf/acf) 

### x Frequency (strokes/day} 

### x Operatingtime X %methane
calculated gas usage based onpistondiameter and stroke length (inactual ft3); scf/acfat supply gas pressure (average 30psig) {combined average value of volume and density is 0.0037 

### ± 65% scf/stroke); strokesperday of !he average pump (37,901 

### ± 29% strokes/day); portion oftime

### that !hepump isoperating (0.446 

### ± 62%); and 78.8 mol% 

### ± 5% for the production segment. Based on site and manufacturer data, the resulting national pistonpump emission factor is 48.9 scfdlpump 

### ± 106%.



### A-25Fordiaphragm chemical injectionpumps, tl:e emission factor was determinedby the followingequation:
where: = 

### Gas usage (scf/gal) 

### x Volume (gal/stroke) 

### x Frequency (strokes/day) 

### x Operating time 

### x %methane Gasusage = Volume 

### = Frequency 

### = Operating time = %methane = volume ofgas (instandard ft3 ) 

### required topumpone gallonofliquidchemical (providedby the manufacturer); liquiddisplacedper stroke based on the plungerdiameter and stroke length (combinedaverage value ofgas consumption and volume is 0.0719 

### ± 10% scf/stroke); strokes per day oftheaverage pump (19,642 

### ± 49% strokes/day); portionoftime that the pumpis operating 

### (0.40 ±52%); and 

### 78.8 mol% 

### ± 5% for the productionsegment. Usingthe site, manufacturer, andmeasured 

### data to calculatetheemissionfactorequationterms, thetotal diaphragm pumpemission factor was determined to

### be446scfd/pump

## ± 77%. Strokevolumewas calculated from 

### pump manufacturers' data and siteobservations ofmanufacturer and model number. Density was calculated based uponobserved site supplygas pressure, and frequency was basedupon timed stroke intervalsobserved while onsite. Operatingtime was estimated by sitepersonnel (ifseasonal), or wasbased upon the percentofpumpsatthe site that wereoperatingduring the visit. The emission factors shown above (in scfd/pump)have been corrected for thenatural 

### gas compositioninthe productionsegment of 78.8 mol %methane. EFDATA SOURCESo !.


### 2. 3. 4.


### 5. 

### 6.
EF ACCURACY, Basis: The report entitled

### Methane Emissions from theNanual Gas Industry, Volume I3: ChemicalInjection Pumps (1) establishesthe importantemission·affecting characteristics. Site visitdata and reference material established the densityfrom supplygas pressure at 30 psig. Forthe pistonpumps, the stroke volume was estimatedfrom manufacturers' data of pumps found at each site. Manufacturers' data for the diaphragmpumpsprovided scfofgas requiredtopump one gallonofchemical. This informationwas used with the calculated liquid displaced for a range ofpumps togivean average gas volume. The frequency ofactuations

### per day was determined from 

### 40 

### timing measurements taken at 12 sites. Theoperatingtime was determined from data at 13 sites. Measurements of

### 5diaphragm chemical injectionpumps were provided from

### an emissionsestimateprogram bytheCanadian PetroleumAssociation.

1. Operatingtime confidencebounds (at90% confidence) were calculatedbyanalysis of the spread of7 sites for pistonpumps and 10 sites for diaphragmpumps. 2. Actuationconfidencebounds (at 90% confidence} werebased on measurements from 7 sites for the pistonpumps and 5 sites for the diaphragm pumps. 3. It was assumed that the manufacturers' data are completely accurate. Datafor the pistonpumps were based on informationfrom 4 manufacturers. Diaphragmpump data were providedby 2 manufacturers. 4. 90% confidence boundsfor each valuewere carried through errorpropagationto result in the final 90% confidence bound. 

### A-26

### ACTIVITYFACTOR: 16,971 pumps 

### in

### tbeproduction segment 

### ± 143% The number ofgas actuated pumps used inthe productionsegment was determined by establishing the ratio of the number ofpumps 

### to active wells 

### (oil or gas) that market gas. Site data were organized intoregions and regional values were determined. The regional ratios were then multiplied by the regional count ofactive wells that market gas in that region to produce the total count ofchemical injection pumps inthe 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 numberofregions (2) Regional AF = <R/s) 

### x (W)

AF DATA SOURCESo 1.



### 2. 3. AF ACCURACYo Basis: 1.


### 2. where RJ = ratio oftotal pumps to total wells 

### in Regionj where W 

### = numberofwells 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 muJtiplyingthe 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 inTexas (3). The pump counts were obtained during the site visits. Inactive, electrically driven. or airdriven pumps were notcounted. Regional extrapolationby gas well count was used.

The

### accuracy for the active gas wells is assigned by engineeringjudgement, based upon the fact that the numberofactive wells istracked nationally and known accurately by A.G.A./DOE, etc. The accuracy for the national AFisbased upon errorpropagationfrom the production sites visited. ANNUALMETHANEEMISSIONS' 1.5

### Bsd

### ± 203 % The national annual emissions were determined by multiplying an emission factor for a typical pump by the populationofchemical injectionpumps in the produe'jon segment. 

### REFERENCES I. Shires, T.M. 

### Methane Emissionsfrom theJr..'atural Gas

### Industry, Volume 13: 

### ChemicalInjection 

### Pumps. Final Report, GRI-94/0257.30and EPA-600/R-96..Q80m, Gas Research Institute and U.S. Environmental ProtectionAgency, 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-27SOURCES' COMPONENTS' OPERATING MODE' EMISSION TYPE, ANNUAL EMISSIONS' BACKGROUND' P-6 PRODUCTION SOURCE SHEET 

### Glycol Dehydrators NIA 

### Normal Operation Vented 

### 3.42 Bscf

### ± 192% Glycol dehydrators remove water from a gas stream by contacting the gas with glycol and then driving the water from the glycol by heating in the glycol reboiler and into the atmosphere. The glycol also absorbs a 

### small amount ofmethane, and some methane can be driven offto the atmosphere through the reboiler vent. EMISSION FACTOR: (275.57 scC/MMscf gas 

### processed 

### ± 154.48o/.) 

### A thermodynamic computer simulation was used to determine the most impon:ant emission·affecting variables for dehydrators. The variables are: gas throughput, existence ofa 

### flash tank, existence ofstripping gas, existence ofa gas driven pump, and existence ofvent controls routed toa burner. Throughput, since its 

### effect is linear, is handled 

### by establishing an emission rate per

### unit of

### gas throughput. Emission rates per unit ofthroughput are then established for the other important emission affecting characteristics. Gas driven pumps are ignored here and handled in a separate source analysis (see Methane Emissionsfrom theNatural Gas Industry, Volume 15: Gas·Assisted GlycolPumps) (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 ofthe population WITH flash tanks 0.265 

### ± 8.35% Fm "" 

### Fraction ofthe population WITHOUT flash tanks 0.735 

### ± 2.99% 

### Fsc; = 

### Fraction ofthe population WITH stripping gas 0.00473 

### ± 115.78% 

### F

NYC = 

### Fraction ofthe population WITHOUT combustion vent controls 0.9882 ± 0.87% 

### EFn = 

### Total methane emission rate scfper I MMscfthroughput with a flash tank 3.57 +102%/·58% 

### Total methane emission rate scfper I MMscfthroughput WITHOUT 

### aflash tank = 175.10 +101%/·50% 

### EFSG = 

### Incremental methane emission rate per 1MMscf throughput perdehydrator that has stripping gas 670 +40%/·60% 

## oc = 2.1 ±41% 

### Overcirculation factor for glycol-number oftimes the industry rule·of·thumb of3gallons glycoVIb water



### A-28EF DATA SOURCES: I. 

### 2. 

### 3.
4. 5.



### 6. Methane Emissionsfrom theNatural Gas Industry, Volume 14: GlycolDehydrators (2) establishes emission affecting characteristics ofdehydrators. GRIJEPA site visit data establishes the Fso and f:-wc for multiple sites (19 PROD sites). An analysis ofa 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 andAnalyticalMethods andEstimation Techniques) (3). The upper botmd was calculated by assuming that all ofthe 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'MJvfscfgas 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 ofthe 444 dehydrators from GRIIEPA site data. 

### ACTIVITY FACTOR: (12.4 Tscf/year gas throughput in the 

### production segment) The amount ofgas processed by glycol dehydrators 

### in the production segment was calculated from the estimated nwnber ofglycol 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 ofthe gas dehydrator count for the U.S. The count also estimated the number in several industry segments: production, transmission, and gas processing.



### A-29Basis: 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 splitthe population into the following industry segments:

Production: 25270 Processing: 7923 Transmission: 8507 

### TOTAL 41700 The study also found that 95.0 % ofthe dehydrators were glycol for a total of 39,615 (versus molecular sieve orother 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 of39,615 yields 37824 glycol dehydrators 

### in production. Average capacity ofproduction dehydrators was reported to be 

### 2 MMscfd by Wright Killen & Co. Infonnation on actual dehydrator throughput as compared to design capacity is, 

### in general, difficultto obtain especially for production field units. Data from several sites in the GRI Glycol Dehydrator Sampling and Analytical Program and other anecdotal information from various site visits indicate thatcapacity utilization may be less than 50%, so a value of45%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. report. The confidence limits for the segments otherthan production were based on site visit data. Confidence limits for the capacity utilization was based on engineeringjudgement. 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. Myers, D.B. and M.R. Harrison. Methane.Emissionsfrom the Natural Gas industry, Volume 15: Gas-Assisted 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. Myers, D. Methane Emissionsfrom 

### the Natural GasIndustry, Volume 14: Glycol Dehydrators, Final Report, GRI-94/0257.31 and EPA-600/R-96-080n. Gas Research Institute and U.S. Environmental Protection Agency, June 1996.



### A-303. Radian Corporation. 

### GlycolDehydrator Emissions. Sampling andAnalyticalMethods 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-31SOURCES' 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%

Gas driven Kimray glycol circulation pumps use a mixed phase ofwet glycol liquid and absorber gas todrive pistons that pump dry (lean) glycol circulation. Unlike chemical injection pumps which vent the driving gas directly tothe atmosphere, Kimray pumps pass the driving 

### gas along 

### with the wet glycol to the reboiler. In the reboiler the methane is driven offinto the vent line. Depending on dehydrator vent gas dispositions, the methane may be vented tothe atmosphere or controlled and burned. EMISSION FACTOR: (992.0 scfCH/MMscfgas processed) The average glycol pump gas emission factor was determined by an equation describing the gas generation and disposition ofgas from the pump. The disposition ofgas generated by the pump depends upon the existence ofa 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 bythe following equation: 

### EFpump = PGU X CR X WR X

## oc X FNT X Fl><'VC EF DATA SOURCES' I. Equation 1, i.e. the effects ofoperating variables on emissions, was defmed by the report on Methane Emissions.from theNatural Gas industry, Volume 15, Gas-Assisted GlycolPumps.(I) 2. CR =-glycol circulation ratio= 3.0gal glycol/1b water± 33.3%. 3. WR =waterremoved from gas = 53 lb/MMscf± 20% for high pressure = 127 lb!MMscf

### ±200/o for low pressure 4. OC =factorto account for overcirculation ofglycol= 2.1 ± 72.4%. 5. FNT =fraction ofdehydrators without flash tanks=- 0.735 

### ± 2.99'1/o. 6. FNVc = fraction ofthe dehydrators wii:lout combustion vent controls =- 0.9882 

### ±0.87%. 7. PGU = pump gas usage (assume 83% methane) = 3.73 scfCH/gal glycol ± 30% for high pressure



### A-32

### = 2.31 scfCH/gal glycol ± 

### 30% for low pressure CALCULATION METHOD: It is estimated that 80% ofthe production dehydrators would be high pressure (R Garrett memo). The overall production emission factor is then calculated as a weighted average ofthe 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 scfCH/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 ofgas processed through dehydrators using gas·assisted pumps was calculated from the total throughput for production dehydrators and the fraction ofdehydrators using gas·assisted pumps determined from site visits. The activity factor is then: AF = 

### (fraction ofdehydrators 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 Emissionsfrom the Natural Gas Industry, Volume 14: Glycol Dehydrators (2) for an explanation ofproduction dehydrator throughput. See the Methane Emissionsfrom the 

### Natural Gas Industry, Volume 5: ActivityFactors (3) for more details. 2. Fraction ofdehydrators using gas·assisted pumps came from data from site visits. AF ACCURACY: (± 

### 61.96%) Basis: Calculated from confidence limits ofgas throughput and fraction ofdehydrators by 

### standard error propagation analysis.



### A-33ANNUAL METHANE EMISSIONS: (10.962 Bscf 

### ± 110.03%) The annual methane emissions were determined by multiplying an emission factor (scfCH/MMscf) by the total throughput for production dehydrators using gas-assisted pumps. (992.00 scf/MMscf) x (l1.05 Tscf) 0< 10.962 Bscf{± 1!0.03%) REFERENCES I. Myers, D.B. and M.R. Harrison. 

### Methane Emissionsfrom the Natural Gas Industry, Volume 15: GasAssisted GlycolPumps. Final Repon, GRI-94/0257.33 and EPA-600/R-96-0SOo. Gas Research Institute and U.S. Environmental Protection Agency, June 1996. 2. Myers, D. 

### Methane Emissionsfrom 

### the Natural Gas Industry, Volume 14: GlycolDehydrators. Final Repon, GRI-94/0257.31 and EPA-600/R-96-0SOn. Gas Research Institute and U.S. Environmental Protection Agency, June 1996. 3. Stapper, B.E. 

### Methane Emissionsfrom the

### Natural Gas Industry, Volume 5: ActivityFactors. Final Report, GRI-94/0257.22 and EPA-600/R-96-0SOe. Gas Research Institute and U.S. Environmental Protection Agency, June 1996.



## A-34SOURCES: 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 tothe atmosphere through blowdown or through purge. Slowdown is the direct, intentional venting to the atmosphere ofgas 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 ofmaintenance 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 ofthe well, reducing 

### gas production. To clearthe 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 of78.8 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 ofstate, 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 ofevents annually; 78.8 mol % ± 5% for the production segment. More details are available in the Methane Emissionsfrom theNatural Gas Industry, Volume 7: Blowand Purge Activities (1). EF DATA SOURCESo I. The blow and purge report establishes emission affecting characteristics ofblowdown practices.



### A-352. Volume and frequency data were available from the following number ofsites; 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 ofequipment 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 ofthe site data. A 900/o confidence interval is calculated for the sites using the method outlined in the Methane Emissionsfrom 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 ofproduction vessels was assumed to be the sum ofseparators, heaters, and dehydrators. AF DATA SOURCES: l. The well, compressor, and vessel counts came from the activity factor extrapolation based on GRIIEPA site visits or surveys (previously discussed in the production fugitives sheet). The count of"vessels" is from the addition ofdehydrator, separator, and in-line heater counts. 2. The miles ofproduction gatheringpipelines were determined from a site extrapolation ofseven 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 ofgas wells requirir..g unloading is based on the ratio ofgas 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 ofavailable production site data. ANNUAL METHANE EMISSIONS: 6.0 Bscf

### ± 359% The annual methane emissions were detennined by multiplying an emission factor (rate per average unit) for each category by the activity factor (population) ofthe category.



### A-36REFERENCES 1. Shires, T.M. and M.R. Harrison. Methane Emissionsfrom the Natural Gas Industry, Volume 7: Blow andPurgeActivities, 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 Emissionsfrom the Natural Gas Industry, Volume 4: StatisticalMethodology, 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-37SOURCES: OPERATING MODE: EMISSION TYPE: ANNUAL EMISSIONS: BACKGROUND: P-9 PRODUCTION SOURCE SHEET Various Production Equipment (vessels) 

### Upsets Unsteady, Vented 0.3 Bscf± 190%
Upsets in process conditions can cause pressure rises that exceed the maximum design pressure for equipment. To prevent equipment overpressure and damage, pressure reliefvalves (PRVs) open and vent the excess gas to the atmosphere. These PRVs are spring loaded or pilot actuated valves that are designed to handle the upset conditions. A few offshore production facilities (but no onshore facilities) have Emergency Shutdown Systems (ESDs) thatdepressure 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 of78.8 mol%) Emergency blowdown volumes and frequencies were estimated at each site visited. The average volume of gas released at lift pressure was calculated for a typical PRV size and duration, and corrected for the fraction ofPRVs that release gas tothe atmosphere. ESD blowdown volumes were based on the platform volume and corrected for the fraction ofplatforms 

### with ESDs and the fraction that vent gas tothe atmosphere. The annual emission 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 ofevents peryear; 78.8 mol % ± 5% for the production segment

I. The GRIIEPA Methane Emissionsfrom the Natural Gas Industry, Volume 7: Blow andPurge Activities (I) establishes emission affecting characteristics ofblowdown practices. 2. Volumes (duration, release rate,%toatmosphere) and frequencies were calculated from each site visit based 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 ofequipment at each site was gathered during the site visits 

### by observation, record search, or interview. EF PRECISION, Basis: The accuracy was propagated from the spread ofthe site data. A 90% confidence interval is calculated using the method presented in the Methane Emissionsfrom the Natural Gas Industry, Volume 4: StatisticalMethodology (2).



### A-38ACTIVITY 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 ofplatforms is from Offshore Data Services and the Minerals Management System Outer Continental Activity Database as reported in Methane Emissionsfrom the Natural Gas Industry, Volume 5: Activity Factors (3). 2. The nwnber ofproduction PRVs is based on counts ofPRVs per equipment type from site visit data: Equipment 

### PRV Number Type Count ofSites Separators 2 ± 68% 20 Heaters I± 89% II Dehydrators 2 ±53% 10 Compressors 4 

### ± 84% 13 Details are provided in the Methane Emissionsfrom theNatural 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 ofdata [see Methane Emissionsfrom theNatural Gas Industry,

**Volum~** 5. Activity Factors (3)]. Ninety percent confidence limits for production vessels with PRVs were calculated from the confidence intervals ofeach type ofequipment. See Methane Emissionsfrom the Natural Gas Industry, Volume 5: ActivityFactors (3) for details ofequipment 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) ofthe category. Each emission factor was adjusted for the average methane content in the production segment of78.8 mol%. 

### REFERENCES I. Shires, T.M. and M.R. Harrison. Methane Emissionsfrom ihe Natural Gas Industry, Volume 7: Blow andPurgeActivities, 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 Emissionsfrom the Natural Gas Industry, Volume 4: StatisticalMethodology, Final Report, GRJ-94/0257.21 

### and EPA-600/R·96-080d, Gas Research Institute and U.S. Environmental Protection Agency, June 1996.


### A-393. Stapper, B.E. 

### Methane Emissionsfrom theNatural Gas 

### Industry, Volume 5: ActivityFactors, Final Report, GRI-94/0257.22 and EPA-600/R-96-0SOe, Gas Research Institute and U.S. Environmental Protection Agency, June 1996. 

### 4. Hummel, K.E., L.M. Campbell, and 

### M.R. Harrison. 

### Methane Emissionsfrom theNatural Gas Industry, Volume 8: EquipmentLeaks, Final Report, GRI-94/0257.25 and EPA-600/R-96-0SOh, Gas Research Institute and U.S. Environmental Protection Agency, June 1996.



### A-40SOURCES' 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 ofgas 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 of78.8 mol%) The emission factor was derived from four distribution company estimates ofthe 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 Mscffor 58,024 miles ofdistribution mains and services; the Southern California Gas Company estimate {2) oflosses from dig-ins was 170,457 Mscffor 82,337 miles ofdistribution mains and services; a third company estimate oflosses from dig·

### ins 

### was 19,581 Mscffor 24,916 miles ofdistribution mains and services; and a fourth company reponed dig·in losses of 10,453 Mscffor 18,713 miles of distribution mains. The ratio ofthe total dig·in emissions tothe 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 ofthe tWo industry segments) based upon 

### an engineering assumption thatproduction dig·inS occurmuch less frequently than distribution dig·ins, and so account for approximately one·halfofthe 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 ofproduction gathering pipeline The annual number ofmiles ofgathering pipeline in the U.S. gas industry was derived from site data. See P· 3 and 

### Methane Emissionsfrom theNatural Gas Industry, Volume 5: ActivityFactors (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 ofthe 1991 Unaccounted·For Gas Volume ar the Southern California Gas Company, Final Report, Los Angeles, CA, April 1993. 3. Stapper, B.E. 

### Methane Emissionsfrom theNatural Gas Industry, Volume 5: ActivityFactors, 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 ofmaintenance releases are completion flaring and well workover. Completion flaring 

### occurs at a new well's open ended pipe flare immediately following the drilling process. During completion testing, the gas is flared to detennine the available pressure and flow rates at the surface. This allows proper sizing ofmeters and surface equipment. Most completion flaring occurs at exploratory wells, sincethe production rates and needed facilities for in·fiii wells (also called development wells) are often available or 

### can be determined before the well is completed. Well workovers are another 

### cype ofmaintenance venting. During a well work.over, the tubing is pulled from the well to repair tubing corrosion/erosion or otherdownhole equipment problems. The well is "killed" by replacingthe gas inthe column with waterormud, thus stopping all production flow. The well can then 

### be opened to the atmosphere. 

### EMISSION FACTORS: Completion Flaring 733 

### ± 200% scflcompletioo well Well Workovers 2,454 

### ± 459% scflwell workover (Emission factors were adjusted for the production methane fraction ofnatural gas of78.8 mol%.) 

### The flow rate ofgas at completion 

### is the 

### highest thatthe 

### well will produce. For emission estimate purposes, the maximum gas flow rate was

### not available. Instead, the completion flaring emission factor was calculated based on the average annual natural gasproduction per well and an assumed flaring efficiency as shown: EFccmpl"""n n.nng =Average Annual Volume x Duration x%Methane x Flaring Efficiency where: Average Annual Volume Duration = %Methane Flaring Efficiency = = 16.97 MMscffor 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 of733 ±200% scfi'completion 

### well for completion flaring. The emission factor for well workovers was determined from two gas production fields. Data from these fields are shown in the following table:

Total number ofwells Number ofworkovers/year Methane emissions/workover, scfi'workover Average scfmethanelworkover



### 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 ofcompletion 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. Engineeringjudgement was used toestablish the upper confidence limit for the completion flaring 

### emission factor. 2. Confidence botu1d for well workover emission factor is based on the average ofdata from two 

### sites. ANNUAL ACTIVITY FACTORS: 844 

### ± 10% completed gas wells 9.329 

### ± 258% well workovers AF DATA SOURCES: I. Number ofexploratory wells completed per year based on data from the Energy Information Administration (EIA)Drilling and Production under T1tle I ofthe Natural Gas Policy Act (3). This data excludes Alaska. 2. PSI data showed 

### I workover/yr per21 wells at Site 

### 1and 

### I workover/yr per 

### 50 wells at Site 2. 3. The Activity Factors Report (4) provides details on the total number ofgas producing wells {276,0I4 

### ± 5%). AF PRECISION: Range 

### ± IO% to 258% I. I0% 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 ofdata from two sites combined with the confidence bound for the total number ofgas 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) ofthe category. REFERENCES I. American Gas Association. 

### Gas Facts: !992Data (Table 3-3), Arlington, VA, 1993. 2. Pipeline Systems Incorporated. 

### Annual Methane Emission Estimate of theNatural Gas Systems in the UnitedStates, 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 ofEnergy, DOEIEIA-0384(94), Washington, DC, July 1995. 4. Stapper, B.E. 

### Methane Emissionsfrom theNatural 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.) ofthe 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 ofthe cover page for that sheet.

.



### TABLE OF OPERATING MODE. CONTENTS EMISSION .TYPE (Fugitive, 

### Vented, orCombusted) Start Up 

### Nonnal Operations Maintenance Upsets 

### Mishaps EQUIPMENTo 

## 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-3SOURCES' 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 losses ofprocess fluid (gas or liquid) from the sealed surfaces ofabove-ground process equipment. Equipment components thattend to leak include valves, flanges and other connectors, pump seals, compressor seals, pressure reliefvalves, open-ended lines, and sampling connections. These components represent mechanicaljoints, seals, and rotating surfaces, which in time tend towear and develop 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 pertnrbine The average fugitive emission rate for gas processing plants was determined to be composed oftwo parts: a)plant component counts (excluding compressor components), and b) compressoNelated components. Fugitives from the compressor-related components have much higher emission factors than components in the rest ofthe facility. Pan ofthis is due.to the high vibration that compressors generate, but most ofthe larger emissions are due to unique compressor components, as explained below. a. The contribution from non-compressor components 

### was determined by multiplying the average component count by the component emission factor. The nwnber ofcomponents was subdivided into valves, connections/flanges, small open-ended lines, site blowdown (BID) OELs, control valves, and other components (such as pressure reliefvalves). (Tubing components were determined to be insignificant.) All ofthese components aretypical fugitive components [as described inthe EPA Fugitive Emissions Protocol (I)J with the exception ofcontrol valves and site BID OELs. Control valves emit at a higher rate than manual isolation valves since theirpacking is stressed more often as they are activated much more frequently. Site BID OELs are the large diameteremergency station blowdown valves that are designed to depressure the entire site to the atmosphere when the valve is opened. The component emission factors for gas plantcomponents (i.e., non-compressor related) were based on an API/GRI measurement program conducted at 8 gas plants. The average facility emissions are then calculated as follows:

where: N. = average count ofcomponents oftype xperplant, and EF, =average methane emission rate percomponent oftype x. b. The contribution from compressor-related components was obtained by multiplying the average number of fugitive components per compressor engine by component emission factors. The component emission factors were based on 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 ofcomponents:

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 ofthe 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 reliefvalve (PRV) is usually installed on acompressor discharge line, and leaks ata higher than average rate due to vibration. 3) Comp. Starter OEL Most compressors have agas 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 tothe 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 ofpressurized 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 pergas 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 ofthe compressor emission factors take several correction factors into account. First, the various phases ofcompressor operations [such as the amount oftime 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 ofstartergas turbines using air instead ofgas (75% for recip, 33% for turbines in gas processing), and fer sites with flares handling PRV or compressor BID 

### discharge (approximately 11% ofthe compressor blowdown OELs were routed to aplant 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 of8 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-5Average Facility Emissions for GasProcessing 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% ofcompressors which have sources routed to flare. <Adjusted for 89.7% oftime reciprocating compressors 

### inprocessing are pressurized. d Adjusted for 43.6% oftime centrifugal compressors 

### in processing are pressurized. • Only 2.?/o ofstarters for reciprocating compressors in processing use natural gas. rOnly 66.7% ofstarters 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 ofgas processing plants was detennined from the 

### Oil andGas Journal (3) (July 1993). The number and type ofgas processing compressor engines were detennined from eleven gas plant site visits. The average ratio ofcompressors per plant was multiplied by the total number ofplants, 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 ofgas plants by the 

### OilandGas 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 ofthe "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 ofindustry average. Based on 

### Oiland 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 thatplants visited were larger than average. However, further investigation revealed that there is no correlation between plant capacity/throughput and number ofcompressors (The plant visited with the most compressors had 20 engines with 20,000 HP and a low throughput of56 MNl:scfd, while the plant with the highest current operating rate of750 MMscfd had only one compressor at 17,500 HP.)

B-7ANNUAL EMISSIONS' (24.45 Bscfi'yr 

### ± 16.7 Bscfi'yr) The annual emissions were detennined bymultiplying the average equipment/facility emissions by the population ofequipment in the segment. Category Emission Activity Emission Uncertainty 

# '""'' '""'' 

# - Gas processing 2.89 MMscflyr 726 plants 2.1 Bscli'yr 48% plants methane methane Recip Comp 4.09 MMscflyr 4092 tecip 16.7 Bscflyr 95% methane methane Tutbine Comp 7.15MMscflyr 726 turbine 5.6 Bscflyr 91% methane m-o TOTAL 24.4 Bscflyr 68% methane REFERENCES l. Hausle, K.J., Protocolfor Fugitive LeakEmission Estimates, Final Report, EPA-453/R-93-026, U.S. Environmental Protection Agency, June 1993.

# * 2. Hummel, K.E., L.M. Campbell, and M.R. Harrison. Methane Emissionsfrom the Natwal Gas industry, Volume 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. 3. OilandGas Journal. l992 Worldwide Gas Processing Survey Database, 1993. 4. Stapper, B.E. Methane Emissionsfrom theNatural GasIndustry, Volume 5: ActivityFactors, Final Report, GRI-94/0257.22 and EPA-6001R-96-080e, Gas Research Institute and U.S. Environmental Protection Agency, June 1996. 

### (*)NTIS FB>c-229219.

B·8SOURCES: 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 ofmethane, and some methane can be driven offto 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 ofa flash tank, existence ofstripping 

### gas, existence ofa gas-assisted pump, existence ofvent controls routed toa burner). 1hroughput, since its effect is linear, is handled by establishing an emission rate per gas throughput. Emission rates perthroughput 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 )

## Jx 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 Frr = Fraction ofthe population WITH flash tanks 0.667 ± 10.13%



## oc Fraction ofthe population WITHOUT flash tanks= 1-Frr 0.333 

### ± 20.12% Fraction ofthe population WITH stripping gas 0.111 ± 186% Fraction ofthe population WITHOUT combusted vent controls 0.90 

### ± 10% Total

**CH~** emission rate per 1MMscfthroughput for dehydrator that has a flash tank 3.57 (+102% I -58%) Total CH4 emission rate per I MMscfthroughput for dehydrator that does NOT have a flash tank 175.10 (+101% /-50%) Incremental emission rate per I MI\.1scfd throughput for dehydrator thathas stripping gas 670 (+40% I -60%) Overcirculation factor for glycol-number oftimes the industry rule-of-thumb of3 gallons glycoL'lb water 1.0 

### ±0%



### B-9EF DATA SOURCES' I. Methane Emissionsfrom theNatural Gas Industry, Volume 14: Glycol Dehydrators (I) establishes emission affecting characteristics ofdehydrators. 2. Site visit data establish the FsG and FNVC for multiple sites (7 PROC sites 

### with dehydrators). 3. TMOGA/GPA survey of207 gas plant dehydrators established F 3p and F"n and TP for dehydrators for the processing segment. 4. ASPEN computer simulations were used to detennine EF,p, and EFND from the dehydrator vent. 5. Sampling data from the GRI Glycol Dehydrator Sampling and Analytical Program for one dehydrator was used to determine EFsv (Glycol Dehydrator Emissions: Sampling andAnalytical Methods andEstimation- Techniques) (2). The upper bound was calculated 

### by assuming that all ofthe measured noncondensable ventgas 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 tomatch 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) The glycol dehydrator throughput is estimated from the fraction ofgas processed byrefiigerated processes (as opposed to dzy bed dehydration for cryogenic processes). The estimate was obtained from the Oil & Gas Journal (3) annual Gas Processing Survey. Ofa total of 17.44 Tscf, 8.63 Tscfwere detennined to be dehydrated by glycol. AF ACCURACY: 8.63 Tscflyear ± 22.45% Basis: l. Uncertainty based on estimate ofconfidence limits for Oil andGasJournal survey. AF DATA SOURCES' 1. Oil & GasJournal (3) annual Gas Processing Survey. ANNUAL METHANE EMISSIONS: (1.0490 Bsc(

### ± 208.20%) The annual methane emissions were detennined bymultiplying the dehydrator emission factor bythe activity factor. REFERENCES I. Myers, D.B. Methane Emissionsfrom the Natural Gas Industry, Volume /4: GlycolDehydrators, Final Report, GR1·94/0257.31 and EPA.ti001R·96-080n. Gas Research Institute and U.S. Environmental Protection Agency, June 1996. 2. Radian Corporation. Glycol Dehydrator Emissions: Sampling andAnalyticalMethods andEstimation Techniques. GRI-94/0324, Gas Research Institute, Chicago, IL, March 1995. 3. Oil & Gas Journal. 1992 Worldwide Gas Processing Survey Database, 1993.
B-10SOURCES' 

### 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 C0 2) from anatural 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 ofmethane, and some methane can be driven offto the annosphere through the reboiler vent to the atmosphere. EMISSION FACTOR: (6083 scfd/avg AGR) 

### AGRs were assumed to have an absorption ofmethane similarto 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 ofthe AGRs that do vent the waste stream 0.18± 10% Average throughput for AGRs (M:Mscfd) 35.02 ± 20% Total

**"C~** scfd emission rateper 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 ofmethane similar to water. 2. I982 API Survey, quoted in Investigation ofUS 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 ofAGR vent dispositions: 50% burned, 32% to sulfur recover, and 18% vented. EF ACCURACY: 6083 ± 104.92% Basis: I. The accuracy is based upon engineeringjudgement that the methane solubility in AGR solutions is similar tothe solubility in water.ACTIVITY FACTOR: (371 

### activ.e AGR 

### units in the U.S.) The number ofAGR units in the U.S. have all been assumed to be 

### in the processing segment. The activity factor was extracted from the Purvin & 

### Gertz survey. AF DATA SOURCES: l. Purvin & Gertz, Business Characteristics of theNatural Gas Conditioning Industry (3), 1993. AF ACCURACY: 371 ± 20% Basis: !. The accuracy is based upon engineeringjudgement. The survey should have excellent accuracy (±5%), but the upper bound 

### at 90% confidence was revised upward to 20% to be conservative. ANNUAL METHANE EMISSIONS: (0.8237 Bscf

### ± 108.85%) The annual methane emissions were detem:ined bymultiplying an emission factor for an average dehydrator by the population ofAGRs in the segment. REFERENCES l. Myers, D. Methane Emissionsfrom theNatural Gas Industry, Volume /4: Glycol Dehydrators, Final Report, GRI-94/0257.31 and EPA--600/R-96-080n. Gas Research Institute and U.S. Environmental Protection Agency, June !996. 2. Radian Corporation. Irrvestigation of U.S. Natural Gas Reserve Demographics andGas Treatment Processes, Topical Report, Gas Research Institute, January 1991. 3. Tannehill, C.C. and C. Galvin. Business Characteristics ofthe Natural Gas Conditioning Industry, Topical Report. GRJ Contract 5088-221-1753, Gas Research Institute, May 1993.

B-12SOURCES: 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 ofgas 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 of87 mol%) Slowdowns at gas plants consist primarily ofthe foJlowing types ofevents: 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 Emissionsfrom theNatural GasIndustry, Volume 7: BlowandPurge Activities 

### (I) establishes emission affecting characteristics ofblowdown practices. 2. Company tracked data were provided from 9 transmission companies representing a total of328 stations. EF ACCURACY: 

### ±262% Basis: The accuracy was calculated from the spread ofthe company tracked data. 

### A 90% confidence interval is calculated for the data using the method presented in Methane Emissionsfrom theNatural Gas Industry, Volume 4: Statistical Methodology (2). 

### ACTIVITY FACTOR 726 

### ± 2% gas 

### plants AF DATA SOURCES: I. 

### The number ofgas processing plants for 1992 is repeated in the Oil and Gas Journal 

### (3). AF ACCliRACYo 

### Basis: An 

### accurate count ofgas plants by the Oil and Gas Journal 

### is very likely since counting such large, discrete facilities should be straightforward. The 

### ±2% was assigned by engineeringjudgement.



### B-13

### ANNUAL METHANE EMISSIONS: 2.95 

### ± 262 Bscf The annual methane emissions were detennined by multiplying an emission factor by the activity factor (population). Each emission factor was adjusted for the average methane content 

### in the gas processing segment of87 mol%. 

### REFERENCES l. Shires, T.M. and M.R. Harrison. Methane Emissionsfrom the

### Natural Gas Industry, Volume 7: Blow andPurgeActNities, Final Repon, GRI-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 Emissionsfrom the

### Natural Gas Industry, Volume 4: StatisticalMethodology, Final Report, GRJ-94/0257.21 and EPA-600/R-96-080d. Gas Research Institute and U.S. Environmental Protection Agency, June 1996. 3. Bell, L. 

### "Worldwide Gas Processing," Oiland

### 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 ofwet glycol liquid and absorber gas to drive pistons that pump dry (lean) glycol circulation. Unlike chemical injection pumps which vent the driving gas directly tothe atmosphere, Klmray pumps pass the driving gas along 

### with the wet glycol to the reboiler. In the reboiler the methane is driven offinto 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

### CHJMMscfgas processed) The average glycol pump gas emission factor was determined by an equation describing the gas generation and disposition ofgas from the pump. The disposition ofgas generated by the pump depends upon the existence ofa 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 scfCH/MMscf gas ± 56.85% EF DATA SOURCES' I. Equation I, i.e. the effects ofoperating variables on emissions, was defmed in Methane Emissionsfrom 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 of95°F and 800 psig dried to 7 lb water/lvfio..1scf gas. 4. OC =factor toaccount for overcirculation ofglycol = 1.0 ± 0%. 5. FNT = fraction ofdehydrators without flash tanks = 0.333 ± 20.12%.

### ' 6. FNvc =fraction ofthe dehydrators without combustion vent controls= 0.900 ± 10%. 7. PGU =pump gas usage= 3.73 scfCHigal glycol± 30%. Determined by multiplying the volume of gas used by high-pressure pump models by a typical fraction ofmethane in the natural gas {83 mole%).

B-15PGU = 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 ofgas processed through dehydrators using gas-assisted pumps 

### was calculated from the total throughput for gas processing dehydrators and the fraction ofdehydrators 

### using gas-assisted pumps detennined from site visits. The activity factor is then: AF

**~** (fraction ofdehydrators 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 Emissionsfrom the Natural Gas Industry, Volume 14: GlycolDehydrators (2) for an explanation ofprocessing dehydrator throughput (8.63 Tscf/year). See the 

### Methane Emissions from theNatural Gas Industry, Volume 5: ActivityFactors (3) for more details. 2. Fraction ofdehydrators using gas-assisted pumps came from data from site visits. AF ACCURACY: (± 192%) Basis: Calculated from confidence limits ofgas throughput and fraction ofdehydrators by standard error propagation analysis. ANNUAL METHAA"'E EMISSIONS: (0.1703 Bscf

### ± 228%) The annual methane emissions were determined bymultiplying an emission factor (scfCH/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 theNatural Gas Industry, Volume 15: Gas

### Assisted 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 Emissionsfrom 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-163. Stapper, B.E. 

### Methane Emissionsfrom theNatural Gas Industry, Volume 5: ActivityFactors. Final Report, GRl-94/0257.22 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%


### The gas processing segment uses compressed airto power the majority ofthe pneumatic devices within the plant, although some devices may be powered 

### by natural gas. Many plants use gas driven pneumatic controllers on isolation valves for emergency shut-down or maintenance work. The same type ofdevices used 

### inthetransmission segment are also commonly used 

### in the gas processing segment

- continuous bleed throttling/regulating valves, displacement operators, and turbine operators. EMISSION FACTOR: 165 Msc:fperaverage plant 

## ± 133% (This was adjusted for the gas processing methane fraction ofnatural gas at 87 moJO/o.) 

### The average device gas emission factor was detennined from 

### a combination ofvendor infonnation on device emission rates and 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, scfNatural Gas) i

### =I x 

### % Methane
K n : 

### n
fraction ofsites thatuse natural gas ratherthan air (0.56 ± 

### 59%) nwnber ofsites operating with natural gas Each tenn in 

### this equation was determined from site specific information. The summation ofthe site specific data was then adjusted based on the number ofsites with gas operated devices versus the total number of sites surveyed. The site 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 ofDevices 

### 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 Emissionsfrom the Natural Gas industry, Volume 12: Pneumatic Devices (I) establishes the important emission-affecting characteristics. 2.

**~ite** visit device counts establish the number ofcontinuous 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 ShaferValve Operating Systems. The numberofdevices, 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 ofdata for the nine sites visited. Itwas assumed that the manufacturers' data are completely accurate. ACTIVITY FACTOR: 726 gas processing plants 

## ± 2% The activity factor for the gasprocessing segment was taken from 

### Oil andGas Journal (2) published information from the year 1992.

B-19AF DATA SOURCES: l. The number ofgasprocessing plants was taken from the Oiland Gas Journal (2). AF PRECISION: Basis: I. AF accuracy is based on engineeringjudgement. ANNUAL METHANE EMISSIONS: 0.12 Bscf

### ± 133% The annual emissions were determined by multiplying an average site emission factor (adjusted for the methane composition) bythe total number ofgas processing sites.
165 Mscflsite x 726 sites = 0.12 Bscf REFERENCES I. Shites, T.M. and M.R. Harrison. Methane Emissionsfrom the Natural Gas Industry, Volume 12: Pneumatic Devices. Final Report, GRI-94/0257.29 and EPA-600/R-96-0801, Gas ResearCh Institute and U.S. Environmental Protection Agency, June 1996. 2. Bell, L. "Worldwide Gas Processing," 

### Oiland GasJournal, 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.) ofthe 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 ofthe 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-3SOURCES' 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 losses ofprocess fluid (gas or liquid) from the sealed surfaces ofabove-ground process equipment. Equipment components that tend to leak include valves, flanges and other connectors, pump seals, compressor seals, pressure reliefvalves, open-ended lines, and sampling connections. These components represent mechanicaljoints, seals, and rotating surfaces, which 

### in time tend to wear and develop leaks. EMISSION FACTOR: 

### a. Station = 3.2 MMscf/yr methane perplant 

### b. Recip. Compressor = 

### 5.55 MMscf/yr methane perrecip c. Turbine Compressor :: 11.1 MMscflyr methane perturbine The average fugitive emission rate for transmission compressor stations was determined to be composed of two parts: a) station components (excluding compressor-related components); and b) compressor-related components. Fugitives from the compressor-related components have much higheremission factors than components in the rest ofthe facility. This is due in part tothehigh vibration that compressors generate, but most ofthe larger emissions are due tounique compressor components, as explained below. a. The contribution from non-compressor components was determined by multiplying the average component count bythe component emission factor. The number ofcomponents was subdivided into valves, connections/flanges, small open-ended lines, site blowdown (BID) OELs, control valves, and other components (such as pressure reliefvalves). (Tubing components were determined to be insignificant.) All ofthese components are typical fugitive components (as described in the EPA Fugitive Emissions Protocol) with the exception ofcontrol valves and site BID OELs. Control valves emitata higherrate than manual isolation valves since theirpacking is stressed more often as they are activated much more frequently. Site BID OELs are the large diameter emergency station blowdown valves that are designed todepressure the entire site to the atmosphere when the valve is opened. The component emission factors for station components were based on a GRI!Indaco measurement program conducted at 6 compressor stations. The average facility emissiQns are then calculated as follows:
where: N, =average count ofcomponents oftype x per plant, and EF, =average methane emission rateper component oftype x. b. Thecontributionfrom compressor-related components was obtainedby multiplying the average number of fugitive componentsper compressor engine bythe component emission factors. The component emissionfactors were based on the GRI/Indaco measurement program conducted at 15 compressor stations. Some compressor components are unique, while othershave higherleak rates than identical components elsewhere inthe plantdue to vibration. Compressors have the followingtypes ofcomponents:



### C-4l) Comp. 

### BID OEL A blowdown (BID) valve to the atmosphere that 

### can depressure the compressorwhen idle. The BID valve orthe large unitblockvalves (depending on theoperating starus ofthe compressor) 

### can act as an open-ended line that leaks at anextraordlnarilyhigh rate through the valve seat. The leak rate is dependent upon whether the compressor is pressurized (inoperation oridle, pressurized) ordepressurized (idle,depressurized). 2) Comp. PRV Thepressure reliefvalve (PRV) isusually installed on a compressordischarge line and leaks at ahigher than average rate due to vibration. 3) Comp. StarterOEL Mostcompressors have a gas startermotorthat turns the compressor 

### shaft to stan the engine. Some

### use natural gas as the motive force to spinthe staner's turbineblades and vent the discharge gasto the atmosphere. The inletvalve to the starter 

### can leak and is therefore an OELunique tocompressors. 4) Comp. Seal All compressors have a 

### mechanical orfluid seal to minimize the flow ofpressurized natural gas that leaks from the location where the shaft penetrates the compression chamber. These seals are vented to the atmosphere. Reciprocatingcompressors have sliding shaft seals while centrifugal compressorshave 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, onePRV, and one starter OEL. Reciprocating compressors have one compressor seal per compression cylinder(which averaged 3.3perengine), while centrifugal compressors have 1.5 seals per gas turbine. Forthemiscellaneous component category, there are many componentsper compressorengine, but the emissionrates were minor and so were added into one lump emission factorper compressor for miscellaneous components. All ofthe compressoremission factors take several correction factors into account. First, the various phases of compressoroperations (such as the amount oftime 

### that compressors are a) idle and depressured, b) idle and pressured up, orc) running). This is actually

### acomplex adjustment that takes into account valveposition practices. [See MethaneEmissions from theNatural

### GasIndustry, Volume 8: EquipmentLeaks (1) for more details.} Correction factors were also added for fraction ofstartergas turbinesusing airinstead ofgas (100% for recip, 0% for rurbines inTransmission). EF DATA SOURCES: I. Component emissionfactors based on results from GRI/Indacoprogram forthe component EF's for 6 transmission compressor stations (June 1994). AdjustmentofstationEF is to account for data obtained from one interstate transmissionpipeline company that was found to havehigheremissions than average. 2. Plantcomponentcountswere based onan average of8 Indaco sitesin 1994 and 9 sites visited underthis project in 1993, plus 7 industry sites. 3. Compressor emissionfactors based on results from GRI!Indaco program for 15 compressor stations (June 1994). Compressoroperatinghours(% running) based on data from FERCdatabase, GRI TRANSDAT(2) database, and data supplied by onelarge interstatetransmission pipelinecompany. 4. Fraction ofmethane (93.4 mol%)based on data from GRITRANSDA T database.



### C-5Average FacilityEmissions for Gas Transmission 

### EquipmentType ComponentType Component Average Average Equipment Emission Factor, Component Emissions:
**Mscf/component~yr** Count MMscf/yr CompressorStation Valve 0.867 673 3.01 (102%) (non-compressor {Note: 3.2MMscf/yr related components) Control Valve 8.0 31 used innational emissionestimate)" Connection 0.147 3,068 

### OEL 11.2 51 PRV 6.2 14 Site 

### BID OEL 264 4 Reciprocating Compressor

### BID 3,683 

### I 5.55 {65%) Compressor 

### OEL PRV 

### 372c I Miscellaneous 180' 

### I Compressor Staner d d 

### OEL Compressor Seal 396' 3.3 Centrifugal Compressor BID 9,352 I 11.1 (34%) Compressor 

### OEL Miscellaneous 18' I Compressor Starter 1,440 

### I 

### OEL Compressor Seal 165° 1.5
a Values 

### inparentheses represent 90% confidence interval. b Adjusted for datareceived from one company that was notconsidered representative ofnational average. "Adjustedforthe fraction oftime the compressor is pressurized (79.1% and 24.2% for reciprocating and

centrifugal compressors, respectively). d Reciprocatingcompressor starters were assumed touse compressed airorelectricity instead ofnaroral. gas.



### C-6EF ACCURACY: a. Station

# =102% 

### b. Recip.

**Compr~or** = 65% 

### c. TurbineCompressor 

### = 34% Basis: Rigorouspropagation oferror from the spread ofthousands ofindividual measurements taken by Indaco. ACTIVITYFACTOR: a. StationActivityFactor = 1700stations b. Compressor ActivityFactor = 6799recipengines, 681 turbines AFDATA SOURCES' I. 1992 FERC Form 2 responses accounted for 70% ofnational transmission pipelinemileage. Total station countextrapolated using national total transmission mileage of276,900 miles from A.G.A. Gas

### Facts (3). 2. Compressorengine count based on GRI TRANSDAT

**~industry** database" with adjustments for total industryhorsepower. Transmission compressor station counts were splitfrom storage based upon storage station site visitdata and Gas

### Facts (3) data on storage stations. Added 0.2% to recip count account for electric motor drivers. AF ACCURACY, a. StationActivityFactor: 

### ± 10% b. CompressorActivityFactor: Recipengines 

### = 

### ± 17 %; Turbines = 

### ± 26% Basis: 1. FERC Form2 data have ahighpercentage (70%) ofall transmissioncompanies. Therefore a national extrapolation shouldnot add much error. This 10% figure was assigned based on engineeringjudgement. 2. Thecompressor countaccuracy was assigned based upon the propagationfrom: a) rigorous error propagation for the 8 storage station
**·compressor/station~** averages; and b) engineeringjudgement assignment of± 10% errorto the largeGRI TRANSDATdatabase. ANNUAL METHANEEMISSIONS' (50.73Bscf/yr

### ± 26.3Bscflyr) The annual emissions were determined by multiplyingthe average facility/equipmentemissions by thepopulation ofequipment inthe segment.
Category EmissionFactor Activity Factor EmissionRate Uncertainty Station 3.2MMscflyr 1700stations 5.4Bscffyr 103% CH4 CH4 RccipComp 5.55 MMscf/yr 6799rccip 37.8Bscflyr 68% CH4 CH4 Turbin= Comp I1.1 MMscf/yr 681 rurbine 7.5Bscflyr 44% CH4 CH4 

### TOTAL 50.7Bscflyr 

# ,. CH4



### C-7REFERENCES 

### l. Hummel, K.E., L.M. Campbell, and M.R. Harrison. MethaneEmissions from theNaturalGas Industry, 

### Volume 8: EquipmentLeaks, Final Repon, GRI-94/0257.25and EPA-600/R-96..080h, Gas Research Instituteand U.S. Environmental ProtectionAgency,June 1996. 2. Biederman, N. 

### GRlTRANSDATDatabase: Compressor Module. (prepared for Gas Research Institute) npbAssociates with TomJoycxe and Associar:es, Chicago, IL, August 1991. · 3. 

### American Gas Association, 

### GasFacts. Arlington, VA, 1992.



### C-8T-2 TRMSMJSSION SOURCE SHEET SOURCES: OPERATINGMODE: EMISSION TYPE: ANNUAL EMISSIONS: BACKGROUND: Meterand Regulating Stations Normal Operation Steady, Fugitive, and Vented 4.5 Bscf

### ± 835% Metering/pressureregulating (M&PR) stations are locatedthroughoutthe transmissionnetworktometer gas where a custody transfer occurs. Emissions from M&PR include continuous fugitive losses and also may include intermittent emissions from pneumatic devices such as pressure regulators, ifthey exist at the station. Fugitive 

### emissionsare relativelylow-levelemissionsofprocess fluid (gasorliquid)fromprocessequipment. Specific source types includevariousfiningssuch as valves, flanges, orcompressorseals. These componentsrepresentmechanlcal joints, seals, and rotating surfaces, which in time tend to wear and develop leaks. Thetransmissionsegmentcontainsmany "meteringandregulationstations" (M&Rstations)whereflowismeasured for custody transfer or system controL The table below shows the types of M&R stations that transmission companies count in their system. Most ofthe meter station types associated with the transmission system have already been counted in other segment calculations (receipt stations in production and delivery stations in distribution). Onlythree typesremain tobe accounted forunderthe transmission systemM&PRstations: l) farm taps, 2) direct industrial sales from the transmission pipeline, and 3) transmission company-to-transmission company transfer stations. TransmissionMeterand Regulation StationTypes

GENERAL SPECIF!C TYPE STATIONTECHNICAL ACCOUNTED FOR IN STATION DESCRIPTION OTHER SEGMENT SERVICE SQ{JRCE SHEETS? RECEIPT TO 1
. Gathering meters at produc- MeterOnly Yes, P-2 THE tion sites SYSTEM, INTER- 2. Meters at compressor MeterOnly Yes, T-1 SYSTEM, stations DELIVERY 3. CityGate M&R stations Meter and Regulation Yes, D-1 TO CUS(Pressure regulation) TOMERS' 4. Industrial sales directly off Meterand Regulation Some 

### in D-1, but those O\IIIled oftransmission pipelines (Pressure regulation) by transmissioncompanies in this sheet (T-2) 5. Farm sales offgathering Meter and Regulation No, so accounted for in this and transmission pipelines (Pressure regulation) sheet (T-2) 6. Sales to OtherTransmission Most oftenMeteronly, but No, so accounted for inthis Companies (Inter-connects) canhave some flow sheet (T-2) regulation


### C-9Althoughdirect customerconnections (sales) on the transmission pipeline are rare, where they exist they are often owned by distributioncompanies, even ifthey only own a few feet ofline. Many fann taps are still owned by transmission companies, even though there is atrend to let LDCshandle the farmtapsortoremove them entirely. Therefore, many direct sales from the transmission pipeline are already accounted for in the distributionM&PR calculations. Only thedirect sales from the transmission pipelinethat are owned completely by the transmission companies 

### are countedunderthis source sheet. Most largetransmission companies have interconnects with othertransmission companies to allow forflexibility ofsupply. These shared stations can flow in eitherdirection. 

### EMISSION FACTOR: (see below) The average fugitive emission rate for trans::nission M&R stations was determined by analysis ofthe GRI tracer measurement tests for gas industry M&R stations. Transmission farm raps and industrial meters are both directconnects to high pressure pipelines, and willhaveonepressure regulator (and not 3 to 22regulators, as some city gateshad)inadditiontoameter. Thepressureregulatorisa selfcontaineddevice, andso does not havesignificant pneumatic emissions. Therefore the tracer data set was soned and adjusted as follows: I) include only stations with one regulator, 2) include only stations in vaults (which were known tohaveno-bleed regulators similartofarm taps), 3) delete regulator only stations 

### inthe lowpressure range (0 to 100psig inlet pressure), and 4) delete meter only stations. The average ofthe 14 samples 

### inthe new transmission direct sales (farm tap & industrial meters) data set is used for the emission factor. The transmissioncompany inter-connect meter stationswere takenby soningthetracer data set forM&R stations with inlet pressures above 100psig. Thiny-seven samples met thiscriterion. Summary ofComponent Counts and Overall Emission Factors (scf/day)

METER STATIONTYPE SAMPLES EMISSION FACTOR (Number ofTracer Measure- (Methane SCFD)

ments Fittingthis Type) Trans-Trans Co. 37 3984 

### ± 80% Interconnectpoints FarmTaps and direct industrial 14 31.2 

### ± 80% sales

. EF DATA SOURCESo l. Tracers result basedondownwindtracermeasurementsperformedbyAerodyne/WSU (l) at over 100gas industrymeter/regulation stations. 2. Analysis oftracer results wasbased upon technical descriptions ofmeter station types given by several transmission company measurement expens. 3. Definitionoftransmissionsegmentboundariesandothermeasurementprogramsshowsthatseveral meter types have already been accounted for. See sheet D-1 for sales to distribution M&R stations, see sheet T-l and S-1 forcompressor stationmeterfugitiveemissions and see sheet P-2 forproductionreceipt meters which have already been accounted for at gas productionsites. 

### C-10EF PRECISION: 

### Basis: The transmission meter/pressure regulation station (M&PR) upper bounds are based upon rigorous propagationoferror from the standard de\'iationofthe multiple tracer measurements. ACTIVITY FACTOR: Trans-to--trans company interconnects 

### Fann tapsand Direct Industrial Sales 2533 

### ± 776% 72630 

### ± 780% As discussed above, types 1, 2, and 3 oftransmission M&R stations are actually already accounted for in other activityfactors. In theproductionsegment meterruns were countedin the well sitedata. Deliveryto distribution has 

### been counted in 

### the distribution segment M&R stations (i.e. city 

### gates). There is also a trend to let LDCs handle the farm taps, or to remove them entirely; however, many farm taps are still owned by transmission 

### companies. Transferstoothertransmissioncompaniesandfarm taps werecalculatedfrom survey dataprovidedby themetering depanmentsofthreelarge(over 10,000

### miles ofpipeline)transmissioncompanies, and from three companies

### with fewer than 10,000 miles ofpipeline, as shown in the following table. Transmission M&R Station Populations 

### Transferto

another 

### Direct Indostrial Company Transmission Co. 

### Farm Taps Sales Miles ofPipeline 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) Total U.S. 2,533 

### ± 776% 71,690 

### ± 787% 937 

### ± 100% 284,500 Activity Factor Extrapolated by Miles Only five ofthe sixcompanies that responded to the survey reponedhaving interconnects with othertransmission companies. Theactivityfactorwas extrapolatedbasedonpipelinemilesandwascalculatedtobe2533 interconnects (transfers). The90% confidence bound was determined to be 

### ± 776%. Thecount offarm tapsappears to be extremely regional. Based on interviews, it seems that most companieshave no farm taps, whileothershavethousands. The activity factor for farm taps wascalculatedto be 71,690 

### ± 787%. Thecalculatedactivityfactoris believedtobeconservativelyhigh. sinceonly.asmall percentage ofall transmission companieshavethese M&R stations, yet twoofthe sixcompanies 

### in ourdata set reponed a largenumberoffarm taps. 

### C-11The activity factor for direct industrial sales was developed from FERC Form No. 2, page 306 (2). Industrial sales greater than 50,000Mcfare listed individually, while sales less than 25,000 Mcf

### are combined

### inro a single item. Inthe lattercase, the total amount ofgas soldwas divided by 50,000to provide

### an estimate ofthe numberofsales. Dueto the uncertainty

**tha~** fuis 

### approach introduced to the activity factor and to the comple;o.:ity ofretrievingdata from FERC, aconfidence bound of 

### ± 100% was assigned based on engineering judgement. The activity factor for the direct industrial sales was combined with that for farm taps based upon similar coru.truction ofthetwo stationtypes. AF DATA SOURCES: I. Forinterconnects and farm taps, sixtransmission companies responded to the GRIJEPA survey to detennine average ratios ofmeter typesper mile oftransmission line. Averages from the survey were extrapolated to national interconnect M&R numberby multiplyingthe ratio by the known miles ofU.S. transmissionline. 

### 2. Miles oftransmission line were from 

### Gas

### Facts (3). 3. Direct industrial sales were determined from gas sales reponed to FERC (2). AF PRECISION: Basis: l. Forinterconnects and farm taps, rigorouspropagationoferrorbased upon the standard deviationof theratiodata from individual transmission companies. 

### 2. Fordirect industrial sales: An engineering estimate basedupon interviewdata. ANNUALMETHANE EMISSIONS: (4.5 Bscl" 

### ± 835%) The annual emissions were determined by multiplying

### an emission factor for 

### an each equipment type

### by the populationofequipment inthe segment. REFERENCES I. AerodyneResearch, Inc., Washington State University and University ofNew Hampshire. 

### Results of TracerMeasurements of Methane Emissionsfrom Natural GasSystem Facilities, Final Report, GRI94/0257.43, Gas Research Institute,Chicago, 

### IL, March !995. 

### 2. Federal Energy Regulatory Commission (FERC) Form No.2, page 306: Annual Report ofMajor Natural Gas Companies, 1992 database. 3. American Gas Association. Gas

### Facts: 1992Data, 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) 0.16Bscf +I- 89%
Transmission pipelines are the inter- and intrastatehigh pressure underground pipelinesthat transport natural gas 

### from the productionlprocessing operations to the end user ordistribution 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 fortransmissionlinesare generallymorestringentthanfordistributionmains. Transmission linesarerequiredtobe surveyedannually, and morefrequently inpopulatedareas. In addition, many transmission 

### companies perform additional routine aerial surveys to monitor the transmission lines for leakage. Based on conversations with several transmission companies, any leaks found in the pi pewall are e:uremely small and are repaired immediately for safety reasons. Based on the rigorous leak survey and repair practices oftransmission companies (i.e., leaks are discovered and repaired earlier in transmission lines), the average leak rate from a transmission leak is believed to be ofthe same orde:ofmagnitude as a leak found in a distribution main, even though there may be a substantial difference inthe operatingpressure ofthe pipelines. Therefore, theemissionfactors forleakage from transmissionpipelinesare basedonthe arithmetic average leakage rates for main pipelines from the cooperative underground distribution leakage measurement program. A mean value ofthe estimated leak rateper leak was calculatedusing the test data, for all pipe materials except cast iron. Forcast ironmains, asegmentrestapproach was usedwhichquantifiestheleakage rate for along isolatedsegment ofpipe; therefore, the mean leakage rate for cast iror: is interms ofleakage per unitlength ofpipe. The natural gas leak rate

**i~** adjusted for methane by multiplyingby the volumepercent ofmethane for transmission (93.4 vol. %

), and is adjusted for the soil oxidationofmethane. Thevalue ofthe emission factor and standard deviation for each pipe material category is givenbelow:



### PipeMaterial Numberof Average Unitsof 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 Preliminarydatafrom theunderground distributionprogram indicate that the leakage rate is not a function ofthe pipeline pressure. Therefore, the leakage rates for transmission pipelines have not been adjusted based on the difference in average operatingpressure ofthe transmission lines versus distributionlines.


## C-13

### EMISSION FACTOR DATA SOURCES' 1. Leakage rate data

### onarateperleakbasis forcathodicallyprotected 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

### theleakratesfromtransmissionpipelinesare identicaltoleakrates fromdistribution mains, based on the more rigorous leak survey and repair practices oftransmission companies. 

### 4. Assumes that the leak rates from underground pipelines are independent ofpressure 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 givenbelow:

Pipe

### Material TotalMiles AverageActivity Units ofActivity 90% Confidence Factor Factor IntervaJ of Activity Factor Protected Steel 287,I55 5,077 equivalent leaks 3,859 Unprotected Steel 5,233 659 equivalentleaks 501 Plastic 2,62I 14 equivalent leaks II Cast Iron 96 96 miles 10 Thenumberoftotal leaks (excludingpipelineincidents) 

### intransmissionpipelinesis based onthe 1991 DOTRSPA database (1) for transmission pipelines, including both repaired leaks (6,120 leaks) and outstanding leaks (1,369 leaks). Because transmission linesare surveyed at leastonce peryear usinga walldng survey method, the number ofunreported leaks is estimated based on the effectiveness of the walking survey. According to one contract company
**speci~izing** in distribution surveys, roughly 85 percent ofthe. leaks are found using a walking survey. This estimated surveyefficiency was applied to transmissionsurveys, resulting inroughly I,320unreported leaks. The leak durationfor outstandingleaks and unreported leaks is estimated to be 8,760hours per year, and the leak durationfor repaired leaks is halfayear(4,380hours/year), onaverage. Theresultingestimate ofequivalentleaks represents the number ofleaks with a year round leak duration. (That is, each leak repair is counted as halfan equivalent leak to compensate for the leak duration.) Therefore, the equation used to estimateequivalent leaks is: 0.5 

### x (repaired leaks) 

## + {[(repaired leaks +outstandingleaks)/0.85}

**~repaired** leaks} Thetotalnumberofestimatedtransmissionpipelineleaks,5,750,wasallocatedonapipelinematerialcategorybasis inthe same proponion(adjustedfor the fraction ofmileage ineach material category) as in the distributionsector. (That is, the ratio ofpercent leaks to percent miles in the transmission segment is the same as the ratio in the distribution segment.) The precision of the estimated total leaks was calculated based on the estimated 90% confidence interval associated with eachparameter in the activity factor equation: repaired leaks; outstandingleaks: 

### ± 100% leak duration: 

### ± 25% leak survey effectiveness: 

### ± 15%


### C-14A statistical software program f(@RISK (2)] was used to determine the overall 90% confidence interval of the activity factor: 

### ± 76%. For cast iron transmission lines, the ntileage is based on the !991 DOT RSPA database for transmission and gathering lines. Theprecision ofthe estimate is assumed to be 

### ± 10%. ACTIVITY FACTOR DATA SOURCES, l. 1991 DOTRSPA database (1) for transmission and gathering pipelines. 2. Total number ofleaks is assumed equal to the total number ofleak repairs plus the outstanding (unrepaired leaks) and unreported leaks. 3. Leak survey effectiveness estimationprovidedby Southern Cross Company (3). 4. The allocation ofestimated leaks per pipe material category is based on theleak frequency for undergrounddistribution

### mainpipelines, adjustedforthefractionoftotalmileageperpipematerial 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 The total leakage was determlned by multiplying an emission factor for each type of pipeline material by the estimated number ofleaks ineach respective pipematerial category. REFERENCES 1. U.S. Department ofTransponation. Research and Special Programs Administration. 1991. 2. Palisade Corporation. 

### @Risk, RiskAnalysis and

### SimulationAdd-inforLotus 1-2-3, Version I.5, March 1989. 3. SouthernCross Corporation. Comments on Docket PS-123Notice 1, Leahlge Surveys, 49 CFR Pan 192, Department ofTransponation, Research and Special Programs Administration, Materials Transponation Bureau, Office ofPipeline Safety Regulations, December 19, 1991. ·



### C-15T-4 

### TRANSMISSION AND STORAGE SOURCE SHEET SOURCES' OPERAT!NG MODE' EMISSION TYPE, COMPONENTS' ANNUAL EMISSIONS, BACKGROUND' Various Equipment (vessels, compressors, piping) Normal Operation Unsteady, Vented Pneumatic Devices 14.1 Bscf

### ± 60%


### The transmission segment is comprised of compressor stations, pipelines, and storage stations. There are essentiallynopneumaticdevices associated with thepipelines, Within the storage andcompressor stations, most ofthe pneumatics are gas-actuated isolation valves, and there are a few continuous bleed controllers. 

### Meter-only stations do not have venting pneumatics. Meter and regulation (M&R) stations do have regulating pneumaticcontrollers (thepressureregulatorvalves), butall ofthe M&Rstationpneumaticemissions arecounted in the fugitive calculation for M&R stations and so are not included in this sheet. The continuous bleed controllers in transmission compressor stations are used for liquid level control in filterseparatofs and pressure reduction. The higherpressures and large pipe diameters associated with transmission operations requirelargeractuators

### andvalvesthantypicallyfound inproduction, resulting

### in largeremissions

### than similar devices in production. Within the storage and mainline compressor stations, most ofthe pneumatic devices 

### are gas-actuated isolation valves. These valves block the flow to or from a pipeline and can isolate the facility for maintenance work or in the case of

### an emergency. Therefore, the isolation valves 

### are actuated infrequebtly 

### and their emissions are intermittent. 

### EMISSION FACTOR' 162,197 scfi'device 

### ± 44% (This was adjusted for the transmission methane fraction of natural gas at 93.4 mol%.) The average pneumatic device emission factor was determined from a compilation ofinformation from several sites. Counts ofdevices per site were taker. during Radian site visits. The devices were classified into three categories: continuous bleedvalves, isolationvalveswithturbine operators, andisolation valves withdisplacement operators. The 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 tulbmoOP<nl<>" x Fraction 10

### rt,,.

**o~'=to"** + EF di•plooem.,1Of>OI'I.IO" x Fraction d1.1ploumont operuo" ) x o/G methane Listed below are the average fraction ofdevices for each ofthe 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 in the transmission segment were measured by an independent contractor. The average emission factor, based on 23 measurements, is 1,363 scfd/device 

### ± 29% (497,584 sc£1device).



### C-16Forthe isolation valves with rurbine operators, the emission factor depends on the gas usage for a given supply gas pressure, the time required to complete one movement ofthe valve, and the number ofoperations per year. The annual 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. 

### Methane Emissions from the Natural Gas Industry, Volume 12: Pneumatic Devices (1) establishes the important emission-affecting characteristics oftransmission pneumatic devices. 2. Device counts from 16 compressor and storage stations establish the fraction ofturbine valve operators, and displacement valve operators. Counts from a total of54 stations were used to establish the fraction ofcontinuous 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. Supplypressure and frequency ofoperation were estimatedbased oninfonnation from four transmission stations. EF ACCURACY' Basis: l. EF accuracy is based on error propagation from the combination of site infonnation and measured data. 2. Itwas assumed thatthe n:tanufacturers' data are completely accurate. ACTIVITY FACTORS: 87,206 pneumatic devices 

### ± 38'% The number ofgas operated pneumatic devices in the transmission and storage segment was calculated based on the average number ofdevices per station andmultiplied by the total number oftransmission and storage stations nationally. The average number of devices per site was detennined to be 40 

### ± 37%. The total count of transmission compression facilities is 2,175, based on 1,700 compressor stations, 386 UG storage stations, and 89 LNG storage stations. AF DATA SOURCES' I. The number of transmission compressor stations was compiled from 1992 Fossil Energy Commission Fonn No. 2: Annual Report ofMajor Natural Gas Companies (2). 2. The numberofunderground storagefacilities istakendirectlyfrom A.G.A. 

### Gas Facts: "Number ofPools, Wells, Compressor Stations, and Horsepower in Underground Storage Fields." Data from base year 1992 were used (3). 3. The number ofliquefied natural gas storage facilities was summed from A.G.A. 

### Gas Facts, 

### C-17"Liquefied Natural Gas Storage Operations inthe U.S. asofDecember 31, 1987(4)." Thetable lists 54 complete plants, 32 satellite plants, and 3 import terminals for a total of89 facilities. 4. The number ofdevices per site is based on the total number ofdevices 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 ofcompressor stations and a5%confidence bound was assigned to the number ofstorage stations. Theconfidenceboundonthe numberofdevicesperstation was determinedbased on the spread ofsite data. ANNUAL METHANE EMISSIONS: 14.1 Bscf

### ± 60 % The annual emissions were determined by r.mltiplying an emission factor per device (corrected for the methane composition) by the population ofpneumatic devices in the transmission segment. 162,197 scfldevice x 87,206 devices= 14.1 Bscf REFERENCES I. Shires, T.M. and M.R. Harrison. Methane Emissionsfrom the Natural Gas Industry, Volume 12: Pneumatic Devices. Final Report, **GRI~94/0257.29** and **EPA~600/R~96~0801,** Gas Research Institute and U.S. Environmental Protection Agency, JWle 1996. 2. Department ofEnergy. FERC Form No. 2: Annual Report of Major Natural Gas Companies. OMB No. 1902-0028, Department of Energy Federal Energy Regulatory Commission, Washington, DC, December !994. 3. American Gas Association. Gas Facts:. 1993 Data, Arlington, VA, 1994. 4. American Gas Association. Gas Facts:. 1991 Data, Arlington, VA, 1992.



### C-18SOURCES: OPERATING MODE: EMISSION TYPE: ANNUAL EMISSIONS: BACKGROUND: T-5 TRANSMISSION AND STORAGE SOURCE SHEET Various Equipment Maintenance!Upsets Unsteady, Vented 18.5 Bscf± 177%
Maintenance activities can release gas to the atmosphere through blowdown orthrough purge. Blowdown is the direct, intentional venting to the atmosphere ofgas 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 clearedtothe 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 Toprevent equipment overpressure and damage, pressure reliefvalves (PRVs) or remotely actuated valves open and vent the excess gas to the atmosphere. PRVs are spring loaded or pilot actuated valves thatare designed tohandle the upset conditions. Remotely actuatedvalves are usually designed to vent entire compressor stations or areas (such as compressor piping) in the event ofa station emergency such as a fire ora 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 of93.4 mol%) Company tracked data were available from eithercompany gas use estimatesreported to accounting departments from each site (accounted-for), orfrom 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 ofblowdown 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 calculated for the 8 companies using the method presented in the Methane Emissionsfrom theNatural Gas Industry, Volume 4: Statistical Methodology (2).



### C-19Annual.Station 

### AaDual Blowdown 

### Pipeline 

### Total Annual Total Total NurD:ber

**EmiSsion~** Blowdowns,

**BlowdoWIJ~** 

### Numberof 

### of Company 

### Mscf 

### Mse{ 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, Mscfnatural gas/station 4,667 

### ±262% ANNUAL AVERAGE, Mscfnatural gas/milt 33.9 ± 236% "Parentheses indicate thatthe value was not included in the total because a station orpipeline emission rate 

### was not available. 

### ACTIVITY FACTORS• 2,175 

### ±

## s•io compression facilities 284,500 

## ± 5% transmission pipeline mUes The activity factors for the segment were compiled from published statistics on the gas industry. The total count for transmission compressor stations was 1700; the total underground and liquefied natural gas storage station count was 475. The number oftransmission pipeline miles comes from A.G.A. Gas Facts (3) which shows 284,500 miles ofpipeline 

### in the United States for 1992. AF DATA SOURCES• 1. The number oftransmission compressor stations was compiled from FERC Form No. 

### 2: Annual Report ofMajor Natural Gas Companies (4). 2. The number ofunderground storage facilities is taken directly from A.G.A. Gas Facts, Table 4-5, "Number ofPools, Wells, Compressor Stations, and Horsepower in Underground Storage Fields" (3). 3. The number ofliquefied natural gas storage facilities was summed from A.G.A. Gas Facts, Table 4-3, "Liquefied Natural Gas Storage Operations in the U.S. as ofDecember 31, 1987" (3). The table lists 54 complete plants, 32 satellite plants,and 3 import terminals for 

### atotal of89 facilities. 4. The number oftransmission pipeline miles comes from A.G.A. Gas Facts which shows 284,500 miles ofpipeline 

### in theU.S. for 1992 (3). AF ACCURACY: Range± 5% to 8% Basis: Extremely tight confidence limits areexpected due to the well documented and reviewed DOE numbers published 

### in A.G.A. Gas Facts (3). 

### C-20

### ANNUAL METHANE EMISSIONS: 18.5 Bscf

### ± 177% The annual methane emissions were determined 

### by multiplying an emission factor (rate per avg unit) for each category by 

### the activity factor (population) ofthe category. Each emission factor was adjusted for the average methane content in the transmission segment of93.4 mol%. REFERENCES 

### 1. Shires, T.M. and M.R. Harrison. Methane Emissionsfrom theNatural Gas Industry, Volume 7: Blow andPurgeActivities, 

### Final Report, GRl-94/0257.24 and EPA-600/R.-96-080g, Gas Research Institute and U.S. Environmental Protection Agency, June 1996. 2. Williamson, H.J., M.B. Hall, and M.R. Harrison. Methane Emissionsfrom the NaJural 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, 

### Arlington, VA, 1993. 4. Department ofEnergy. FERC Form No.2: Annual Report ofMayor Natural Gas Companies. OMB No. 1902-0028, Department ofEnergy, Federal Energy Regulatory Commission, Washington, DC, December 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 dehydrators remove waterfrom agas stream bycontactingthe gas with glycol and then driving the water from the glycol and into the atmosphere. The glycol alsoabsorbs a small amount ofmethane, and some methane can be driven offtothe atmosphere through the reboiler vent. 

### EMISSION FACTOR: (93.72 scfiMMscfgas processed 

### ± 207.99%) A thermodynamic computer simulation was used to determine the most important emission·affecting variables for dehydrators. Thevariables are: gasthroughput, existence ofaflash tank, existence ofstripping gas, existence ofa gas driven pump, existence ofvent controls routed to a burner. Throughput, since its effect is linear, is handled by establishing an emission ratepergas throughput. Emission ratesperthroughput 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)

## Jx 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 ofthe population WITH flash tanks 0.669 ± 9.70% FNT == Fraction ofthe population WITIIOUT flash tanks 0.331 

### ± 19.6% FsG == Fraction ofthe population WITii stripping gas 0.0741 

### ± 118.26% Fr-Nc"" Fraction ofthe population WITHOUT combusted vent controls 0.852 

### ± 14.0% EFFT== Total

**CH~** emissiOn rateper I MMscfthroughput for dehydrator that has a flash tank 3.57 scf/MMscf (+102% I-5SO!o) EFNT== Total

**CH~** emission rate per 1MMscfthroughput for dehydrator that does NOT have a flash tank 175.1 scf!MMscf(+101% /-50%) EFsG"" Incremental emission rateper IM}./[scfthroughput for dehydrator thathasstrippinggas 670 scf/MMscf(..,.40% I -60%) OC == Overcirculation factor for glycol-number oftimes the industry rule-of-thumb of 3 gallons glycoVIb water 1.0 

### ± 0%



### C-22EF DATA SOURCES: L Methane Emissionsfrom the Natural Gas Industry, Volume /4: GlycolDehydrators (1) establishes emission affecting characteristics ofdehydrators. 2. Site visit data establishes the F50 and 

### FNVc for multiple sites. Wyoming ADQ data also verifies FNVo though it implies ahigher 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 that all ofthe measured noncondensable vent gas was due to stripping gas that was I00% methane. 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 ofthe site averages. ACTIVITY FACTOR: (1.086 Tscf/year gas throughput in the transmission segment) The amount ofgas processed by glycol dehydrators in the transmission segment was calculated from the estimated number ofglycol dehydrators in transmission service and the average throughput capacity for transmission dehydrators (Wright Killen & Co., 1994). See Source Sheet P-6 for a detailed discussion ofthe breakdown ofglycol dehydrators into industry segments. The capacity utilization factor for transmission was assumed 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. Myers, D. Methane Emissionsfrom theNatural Gas Industry, Volume 14: GlycolDehydrators, Final Report, GRI-94/0257.31 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 ofprocess fluid (gas or liquid) from the sealed surfaces ofabove-ground process equipment. Equipment components that tend to leak include valves, flanges 

### and other connectors, pump seals, compressor seals, pressure reliefvalves, open-ended lines, and sampling connections. These components represent mechanicaljoints, seals, and rotating surfaces, which in time tend to wear and develop leaks. EMISSION FACTOR: 

### a. Station ""7.85MMscl7yr 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 ofthree 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 ofthe facility. This is due in 

### pan to the high vibration that compressors generate, but most ofthe 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 ofcomponents was subdivided into valves, connections/flanges, small open-ended lines, and other components (such as pressure reliefvalves); tubing components were determined to be insignificant. All ofthese components are typical fugitive components (as described in the EPA Fugitive Emissions Protocol) with the exception ofsite 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 compressor stations (see below). Emission factors for storage injection/withdrawal wells were based on the updated API/GRl/Star 20-site study (4 gas 

### production sites). Physical and operational characteristics of injection/withdrawal wells were compared togas production wells, and were found to be similarbut typically larger (more components). This was taken into account in the component count data. The number ofcomponents was 

### subdivided into types, such as valves, connections/flanges, open-ended lines, and other components (such as 

### pressure reliefvalves). The average facility/equipment emissions are calculated as follows: ·
where: N, :: average count ofcomponents oftype x per plant, and EF, :o 

### average methane emission rate per component oftype 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 ofcomponents:

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 ofthe 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 whetherthe compressor is pressurized (in operation or idle, pressurized) or depressurized (idle, depressurized). 2) Camp. PRV The pressure reliefvalve (PRV) is usually installed on a compressor discharge line and leaks at ahigher than average rate due to vibration. 3) Camp. Starter OEL Most compressors have a gas startermotor 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 ofpressurized 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 pergas turbine. Forthe 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 ofthe compressor emission factors take several correction factors into account. First, the various phases ofcompressor operations (such as the amount oftime 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 Emissionsfrom Natural Gas Industry, Volume 8: Equipment Leaks (1) 

### for more details.] Correction factors were also added for fraction ofstarter 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 ofGRIIStar data fer gas production wellheads (Atlantic/Eastern region a.'ld Rest ofU.S.). 5. Fraction ofmethane (93.4 mol%) based on data from GRI TRANSDAT database.


### C-25Average 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%) 

### IWellhead 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 oftime the compressor is pressurized (67.5% and 22.4% for reciprocating and

centrifugal compressors, respectively). <Adjusted for the fraction ofcompressor starters using natural gas (60% and 50% for reciprocating and

centrifugal compressors, respectively).



### C-26EF ACCURACY: a. Station = 

### ± 100% b. Wellhead = 

## ± 76% b. Recip. Compressor = 

### ± 48% c. Turbine Compressor = 

### ± 34% Basis: Rigorously propagation oferror from the spread ofthousands ofindividual 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 The activity factors for the segment were compiled from published statistics in Gas Facts (2). The total count for Undergmund storage stations was 386, and the total LNG storage count was 89. AF DATA SOURCES: l. The number ofunderground storage facilities was taken directly from A.G.A. Gas Facts, (2), Table 4-5: Number ofPools, Wells, Compressor Stations, and Horsepower in Underground Storage Fields. Data from base year 1992 were used. 2. The number ofLiquefied 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 ofDecember 31, !987." The table lists 54 complete plants, 32 satellite plants, and 3 import tenninals for a total of89 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 ofreciprocating compressors in storage was increased by 3I% 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 ofall 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 engineeringjudgement. 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 TRANSDAT 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 ofequipment in the segment.



### C-27Category Emission Factor Activity Factor Emission Rate Uncenainty Stafion 7.85 MMsd7yr CH4 475 stations 3.73 Bscfi'yrCH4 100% lnj!With Wellheads 4!.8 Mscfi'yr CH4 17999 wellheads 0.752 Bscfi'yr CH4 76% Recip Comp 7.71 MMscfi'yr CH4 1396recip 10.76 Bscfi'yr CH4 80% Turbine Comp I!.l6MMscti'yr CH4 !36turbine 1.52 BscflyrCH4 129% TOTAL 16.76 BscflyrCH4 57% 

### REFERENCES I. 

### Hummel, K.E., L.M. Campbell, and M.R. Harrison. Methane Emissionsfrom theNatural Gas Industry, Volume 8: Equipment Leaks, 

### Final Report, GRJ·94/0257.25 and EPA--600IR-96-080h, Gas Research Institute and U.S. Envirorunental Protection Agency, June 1996. 2. American Gas Association. Gas Facts, 

### Arlington, VA. 1992. 3. Stapper, B.E. Methane Emissionsfrom theNatural Gas Industry, Volume 5: ActivityFactors, 

### Final Report, GR1·94/0257.22 and EPA-600/R·96-080e, Gas Research Institute and U.S. Environmental Protection Agency, June 1996.



### C-28SOURCES' 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%
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 ofmethane, and some methane can be driven offto 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 for dehydrators. The variables are: gas throughput, existence ofa flash tank, existence ofstripping gas, existence ofa gas-assisted pump, existence ofvent controls routed to a burner. Throughput, since its effect is linear, is ·handled by-establishing an emission rate pergas throughput Emission rates per throughput are then established for the other important emission affecting characteristics. The emission factor is then: 

### EF = [( 

### FFT x 

### EFFT) + ( 

### FNT x 

### EFN,.) + ( 

### ?sG x 

### EFsG)

## Jx FNVc x 0C 

### EF 

## =I (0.520 X 3.57) + (0.480 

### X175.10) + (0.080 X 670)

## JX 0.840 X 1.0 

### FFT = Fraction ofthe population WITH flash tanks 0.520 ± 33.56% F

**~><"D** = Fraction ofthe population WITHOUT flash tanks 0.480 ± 36.25% FsG = Fraction ofthe population WITH stripping gas 0.080 

### ± I18.44% F

**~><"Vc=** Fraction ofthe population WITHOUT combusted vent controls 0.840 ± 15.24% 

### EFFT= Total CH4 emission rate 

### per 1 MMscfthroughput for dehydrator that has a flash tank 3.57 (+102% /-58%)

**EF:-T~** Total 

### CH. emission rate per 1 MMscfthroughput for dehydrator that does NOT have a flash 

### tank 175.10 (
...JOI% I -50%) 

### EFsG= Incremental emission rate

**~r** 1 MMscfd throughput for dehydrator that has stripping gas 670 (+40% I -60%) OC = Overcirculation factor for glycol--number oftimes the industry rule-of-thumb of3 gallons glycoVIb water 1.0 ± 0%



### C-29EF DATA SOURCESc I. Methane Emissionsfrom the Natural Gas Industry, Volume 14.- GlycolDehydrators (l) establishes emission affecting characteristics ofdehydrators. 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 todetennine 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 all ofthe measured noncondensable vent gas was due tostripping gas that was l00% methane. 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 ofthe site averages. ACTIVITY FACTOR: (2.00 Tscfi'year gas throughput in the storage segment) The amount ofgas processed by glycol dehydrators in the storage segment was calculated from the estimated amount ofgas withdrawn from underground storage. A total of2.4 Tscfwas withdrawn in 1992, and it is assumed that most stored gas is dehydrated. AF ACCURACY: 2.00 Tscf/year 

### ±25% Basis: I. Uncertainty based on estimate ofconfidence limits. ANNUAL METHANE EMISSIONS: (0.2344 Bscf

### ± 166.56%) The annual methane emissions were detennined by multiplying the dehydrator emission factor by the activity factor. REFERENCES I. Myers, D. Methane Emissionsfrom theNatural Gas Industry, Volume 14: Glycol Dehydrators, Final Report, GRI-94/0257.31 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 ofthe 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.) ofthe 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 ofthe cover page for that sheet.

TABLE OF OPERATING MODE, CONTENTS EMISSION 

## TYPE (Fugitive, Vented, orCombusted) Start Up 

### Nonnal 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 regulating stations are located throughout the distribution network to meter gas where a 

### custody transfer occurs and/or to reduce and regulate the pressure in the downstream main pipeline. Emissions from fugitive losses and normal operations at meter and pressure regulating stations include both continuous and intermittent emissions from.equipment components, such as pneumatic devices, valves, flanges, flow meters, and pressure regulators. 

### EMISSION FACTOR: (scf/station-hour) The emission factor and standard deviation are given below for facilities located in vaults and above ground for different inlet pressure ranges:
Standard 

### Precision Average Deviation 

### of Inlet 

### EmissioD ofEmission Emission Station Pressure Location in Number of Factor Factor Factor

Type (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 tracer measurements were performed by Aerodyne/Washington State University at 2 West Coast companies, 3 northeastern companies, 4 midwestern towns, and 3 southern plains towns. In total, 95 measurements were performed on metering/regulating stations in distribution and transmission systems.



### D-4The test data were analyzed to evaluate the differences in emissions from stations with different configurations (i.e., metering/regulating versus regulating only), inlet pressure ranges, and locations (i.e., in vaults versus above.ground). The test data were disaggregated into four distinct inlet pressure categories (>300 psig, 100-300 psig, 40·100 psig, and <40 psig), two station types {meter/pressure regulating facilities and pressure regulating facilities), and into stations in vaults versus above-ground, resulting in a total of 10 categories. These categories were selected for disaggregation ofthe data based on knowledge ofthe gas industry, and were confirmed to be statistically significant based on the data analyses. 

### ACTMTY FACTOR: (number ofstations) The mean activity factor and standard deviation for each station type/inlet pressure/location category is given below:
Standard Average Deviation Precision Inlet Activity ofActivity ofActivity Station Pressure Location in Stations per Factor Factor Factor

Type (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 ofstations in each inlet pressure/station type category were provided by twelve distribution companies. The data were extrapolated based on the total mileage ofdistribution main pipeline in the respective companies. The mean number ofstations in each category per mile ofmain was estimated as the average ofthe values from eleven ofthe twelve companies supplying data. Based on conversations with one ofthe companies supplying data, the average number ofstations per mile for the one company were not considered representative oftypical industry practices. Therefore, this company was not included in the overall average, but rather was treated separately. The standard deviation represents the variation in the estimated number ofstations permile ofmain pipeline for each company. The precision represents the 90'% confidence interval around the estimated mean activity factor. The extrapolation from stations per mile to total stations in the U.S. was implemented by multiplying the stations permile for each category by the total U.S. mileage ofmain pipeline: 836,760 miles. Data were collected from five companies representing urban, rural, and suburban areas on the number of regulating stations in vaults versus above-ground in the U.S. On average, 37% ofthe regulating stations with 

### D-5an inlet pressure greater than 300 psig are located in vaults. For regulating stations with an inlet pressure between 40 and 300 psig, 

### it was found that the majority ofstations in urban areas were in vaults and in rural areas were above-ground. On average, 

### it was estimated that 31% ofthe stations are located in vaults with an inlet pressure between I00 and 300 psig. For regulating stations with an inletpressure between 40 and l00 psig, 47% ofthe stations are located in vaults. Based on the data collected, the majority ofthe low pressure { <40 psig inlet pressure) stations are located in vaults. ANNUAL EMISSIONS ESTIMATE: (27.3 +/- 23.3 Bscf)
90% Confidence Average Average Annual Interval of Inlet Activity Emission Emissions Emissions Station Pressure Location Factor Factor Estimate Estimate

Type (psig) 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 ofstation was derived by multiplying the respective emission factor (scf/station-hr) by the activity factor (number ofstations), and converted to an annualized estimate by assuming continuous fugitive leakage (i.e., 8760 hour peryear leakage). The precision represents the 90% confidence interval around the estimated mean emissions for each category.



### D-6D-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 acommon source ofnatural gas supply for more than one customer. Services are the branch connection lines from the mains to the customer meters. Leakage from the underground distribution network occurs from corrosion pits,joint and fitting failures, and pipe wail fractures. Gas distribution operators use leak detection procedures to locate and classify leaks. The leak is classified and prioritized for repair based on the concentration ofgas detected and the proximity ofthe leak to existing structures. EMISSION FACTOR: (sc£11eak-year) The value ofthe 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 hasbeen 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 ofthe program. The test data were disaggregated by material type and mains versus services, based on a combination ofstatistical analyses and engineeringjudgement. A mean value ofthe estimated leak rate per leak was calculated using 

### D-7the test data, for all pipe materials except cast iron. In these tests, an individual leak was randomly selected for testing based on criteria outlined in the program plan. For cast iron, long segments ofpipe were tested to measure the leak rate per mile ratherthan the leak rate per leak. Cast iron was tested in long segments since it tends to have a very high frequency ofleaks (due to thejoint spacing of 10 to 16 feet) and the relatively high occurrence ofundetectable leaks in cast iron. The measured natural gas leak rates were adjusted for the average volume percent ofmethane in pipeline·quality gas {93.4 vol. %), and the soil oxidation rates of methane. ACTIVITY FACTOR, The mean activity factor and standard deviation for each pipe material category is given below:

Material Pipe Use Estimated Average Units ofActivity 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 The national database ofleak repairs was used to extrapolate data provided by individual companies. Data were requested from each company participating in the underground leaktest 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 ofannual leak repairs, leak indications, and outstanding leaks within the distribution system were provided by six companies. An estimate ofthe number ofannual 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 ofannual equivalent leaks represents the equivalent leaks which are leaking all year. (That is, for leaks with a leak duration ofhalfyear, these leaks are counted as halfan equivalent annual leak.) The total number ofleaks in the system are quantified by incorporating the leak duration into the estimated equivalent leaks. For example, ifa leak is only leaking halfthe year, it is counted as 0.5 equivalent leaks. The assumptions made in deriving the estimated number ofequivalent leaks for each company include: 

### D-8

### Approximately 

### 85 percent ofleaks 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 halfofthe year, on average. Outstanding leaks are leaking at the beginning ofthe year. The number ofnew leaks in the system is estimated based on the annual leak indications and the frequency ofthe leak survey. The number ofnew 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 halfthe 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 halfthe 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 halfthe 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 halfthe year; and (n-4)/n leaks are not yet leaking. Based on the data provided by each ofthe six companies, a ratio ofthe annual equivalent leaks to leak repairs was calculated. The average ratio (2.14) was multiplied by the estimated number ofleak repairs in each pipe material category to extrapolate the national database ofleak repairs to represent anhual equivalent leaks. The precision ofthe estimate is based on the variability in the leak repair disaggregation provided by ten companies and the variability in the calculated ratio ofannual equivalent leaks to leak repairs provided by six companies. The activity factor for cast iron mains is the total estimated mileage ofcast iron mains in the U.S., as reported by the U.S.DOT RSPA (I). 

### The standard deviation was assumed to be 5% 

### ofthe estimated mileage, based on engineeringjudgement.



### D-9EMISSIONS ESTIMATE: (41.6 +/- 65 %) The emissions estimate for each category ofpipe material/use was dervied multiplying the respective emission factor (scf/leak-yr or scf/miie-yr) by the aC"::ivity factor (total number ofleaks 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 ofTransportation. Research and Special Programs Administration. 1991.



### D-10SOURCES: OPERATING MODE: EMISSION TYPE: ANNUAL EMISSIONS: BACKGROUND: D-3 DISTRIBUTION SEGMENT SOURCE SHEET
Pressure ReliefValves Maintenance/Upsets Unsteady, Vented 0.04 Bscf± 3,919%

Pressure reliefvalves (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 ofregulator failure. Gas is released during any emergencyactuation ofthe PRVs. EMISSION FACTOR: 0.050 

### ± 3,914% Mscf/mile (Adjusted for the distribution methane fraction ofnatural gas of93.4 mol%) The estimated emission factorwas based on two separate distribution company studies which quantified losses from PRVs as partofunaccounted-for (UAF) gas studies. The studies calculated PRV releases per mile of pipeline mains. The GRIIEPA emission factor wasestimated as the ratio ofemissions permile ofmain from the two companies, and corrected for the methanecomposition in distribution. EF PRECISION: 

### ± 3,914% Basis: The precision was calculatedusing the method outlined in the Statistics Report (I). ACTIVITY FACTOR: 836,760 

### ± 5% miles ofmain The activity (actor is based on the total miles ofdistribution mainpipeline in the U.S. AF PRECISION: ± 5% Basis: The accuracy was assigned based on engineeringjudgement. ANNUAL METHANE EMISSIONS: 0.042 

### ± 3,919% Bscf The annual methane emissions were determined by multiplying an emission factor (annual methane emissions permile ofmain) by the activityfactor {miles ofdistribution main pipeline nationally). REFERENCES 1. Williamson, HJ., M.B. Hall, and M.R. Harrison. Methane Emissionsfrom theNatural Gas Industry, Volume 4: StatisticalMethodology, Final Report, GRI-94/0257.21 and EPA-600/R-96-080d, Gas Research Institute and U.S. Environmental Protection Agency, June 1996.



### D-11D-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 orservice pipeline ruptures caused by unintentional third-party damage. Some distribution companies estimate and record the quantity ofgas lost during a dig-in event; therefore, they keep records ofestimated annual losses due to dig-ins. From these annual records, a national emission rate for digins was detennined. 

### ANNUAL EMISSION FACTOR: 1.59 

### ± 1,922% Msc£1mile (Adjusted for the distribution methane fraction ofnatural gas of93.4 mol%) The emission factor was derived from four distribution company estimates ofthe losses from dig-ins: the Pacific Gas and Electricunaccounted-for (UAF) gas study {I)results showed that losses from dig-ins were estimated at 91,178 Mscffor 58,024 miles ofdistribution mains and services; the Southern California Gas Company estimate (2) oflosses from dig-ins was 170,457 Mscffor 82,337 miles ofdistribution mains and services; a third company estimate oflosses from dig-ins was 19,581 Mscffor 24,916 miles ofdistribution mains and services; and a fourth company reported dig-in losses of 10,453 Mscffor 18,713 miles of distribution mains. The ratio ofthe total dig-in emissions tothetotal pipeline miles from these companies was used to estimate the national methane emission factor, resulting 

### in 2.06 Mscfi'mile. 

### EF PRECISIONo Basis: 

### ± 1,922% Theprecision was calculated from the spread ofthe company data using themethod presented in the Methane Emissionsfrom theNatural Gas Industry, Volume 4: StatisticalMethodology (3). 

### ACTIVITY FACTORo 1,297,569 

### ± 5% miles ofmains and services The total number ofmiles ofmain pipeline in the U.S. gas industry was based on U.S. Department of Transportation, Research and Special ProjectsAdministration (4). The total miles ofservice pipeline was reported in A.G.A.'s Gas Facts, 1990 (5). AF PRECISION: 

### ±5% Basis: A 5% confidence bound was assigned on the basis ofgood precision from national statistics of

**~**990 data. ANNUAL METHANE EMISSIONS; 2.06 

### ± 1,925% Bscf The annual methane emissions were determined by multiplying an emission factor (annual methane emissions permile ofpipeline) by the activity factor (number ofmiles).



### D-12REFERENCES 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 ofthe 1991 Unaccounted-For Gas Volume atthe Southern California Gas Company, Final Report, Los Angeles, CA, April 1993. 

### 3. Williamson, H.J., M.B. Hall, and M.R. Harrison. Methane Emissionsfrom the Natural Gas Industry, Volume 4. Statistical Methodology, Final Report, GRI-94/0257.21 andEPA-600/R-96-080d, Gas Research Institute and U.S. Environmental Protection Agency, June 1996. 4. U.S. Department ofTransportation, Research and Special Projects Administration, Washington, DC, 1991. 

### 5. American Gas Association. Gas Facts, 1992 Data, 

### Arlington, VA, 1993.



### D-!3SOURCES' 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 ofleakage from customer meters is based on screening and bagging studies conducted at ten sites throughout the United States. The initial study was conducted by Indaco to measure customer meters in the west coast [Indaco Air Quality Services, Inc., Methane Emissionsfrom Natural Gas Customer Meters: Screening andEnclosure Studies, draft repon,August 15, 1992 (!)]. Data were also collected at nine additionai sites across the United States, including three east coast sites, a mid·western site, a rocky mountain site, and five western U.S. sites. A summary ofthe average emissions from residential customer meters from each ofthe ten sites is shown in the foilowir.g table:

Site Number ofMeters Number ofMeters 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 0.0082 Mountain 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 l0

- North West 150 40 0.0125 0.0230 •Average value for all meters (i.e., leaking and non-leaking) screened at the site.



### D-14The average emission factor for residential customer meters was derived by averaging the emission rates for the ten sites. The emission factor was converted to units ofscfi'meter-yr by assuming that the losses from the leaking meters were continuous throughout the year. The precision represents the 90 % confidence interval and was calculated by averaging the standard deviations for the ten sites. The emission factor for commerciaVindustrial customer meters was derived from screening data collectea at a total offour sites. A summary ofthe average emissions from each ofthe four sites is shown in the following table:

Site Number ofMeters Number ofLeaking 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 6 0.0088 0.0076 Mountain 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 customer meters was derived by averaging the emission rates for the four sites. The emission factor was converted to units ofscf/meter-yr by assuming that the losses 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 ofcustomer meters in the U.S. gas industry, 56,132,300, and the number ofresidential customer meters, 51,524,600, were based on Gas Facts, American Gas Association, 1992 {2). The number of residential customer meters located indoor-s versus outdoors was estimated based on a regional breakdown of total customers presented in Gas Facts (2) combined with data obtained from 22 individual gas companies within different regions ofthe country. (Note: Thenumber ofcustomers in each region was used to estimate the number ofindoor meters because data on number ofcustomer- meters segregated by region were not available.) Following is the average percentage ofcustomer meters located indoors in each region:



### D-15Total 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 WestNorth 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 engineeringjudgement. bEstimated for each state separately inregion. 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 thatcustomer meters 

### in southern regions are essentially all located outdoors. The estimated number ofindoor meters, 1!,475,294, was subtracted from the total number ofreported meters, 5!,524,600, to derive an estimated 40,049,306 outdoor residential customer meters in the United States. The precision was estimated from the data provided by the companies, engineeringjudgement for some regions, and an estimated 5% error 

### in the nationally reported number ofresidential 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 ofnegligible leakage from indoor meters is consistent with the fmdings from pressure regulating stations located in vaults. The precision ofthe total estimated commercial/industrial customer meters is assumed to be ± 5% ofthe estimated 4,608,000 meters. ANNUAL METHANE EMISSIONS: (5.8 

### ± 1.1 Bscflyr) REFERENCES 1. Indaco Air Quality Services, Inc. Methane Emissionsfrom Natural Gas Customer Meters: Screening andEnclosure 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 ofpipeline abandonment, installation, and repair. 

### ANNUAL EMISSION FACTOR: 0.102 

### ± 2,521% Mscfi'mile (Adjusted for the distribution methane fraction ofnatural gas of93.4 mol%) The emission factors for pipeline b!owdown are based on estimates from four companies: the Pacific Gas & Electric Unaccounted·for Gas (UAF) Project, !987 (l); the Southern California Gas Company (SoCal) project {2); and two additional company estimates. The estimated total gas losses were adjusted for 93.4 volume percent methane. The annual methane emissions per mile ofmains and services for each ofthe four companies was calculated based on the ratio ofemissions to miles ofdistribution mains and services. The following table summarizes the individual company estimates and the national emission factor. The precision ofthe estimate is based on the 90 percent confidence level for the four companies providing data. A11nuaf Annual Blowdown Bfowdown Methane Methane Pipeline Emission Factor, Company 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, Mscfmethane/mile 0.102 ± 2,521% ACTIVITY FACTOR: (1,297,569 

### ± 5% miles mains and services) The total number ofmiles main pipeline in 

### the U.S. gas industry was based on 

### U.S. Department of Transportation, Research and Special Projects Administration (3). The total miles ofservice was reported in Gas Facts (4). The precision, or 90 percent confidence level, was estimated to be ± 5%, based on engineeringjudgement. 

### ANNUAL METHANE EMISSIONS: 0.13 

### ± 2,524% Bscf The annual methane

**emission~** were detennined by multiplying an emission factor (annual methane emissions per mile ofpipeline) by the activity factor (number ofmiles).



### D-17REFERENCES I. Pacific Gas & Electric Company and Gas Research Institute. Unaccounted-For Gas Project. Volume 1, Final Report, San Ramon, CA, June 7, 1990. 2. Southern California Gas Company and Gas Research Institute. A Study of the 1991 Unaccounted-For Gas Volume atthe Southern California Gas Company, Final Report, Los Angeles, CA, April 1993. 3. U.S. Department ofTransportation, Research and Special Projects Administration, Washington, DC, 1991. 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 1scfmethane

**~** 

### I9.23 g methane 1Bscfmethane

**~** 

### O.OI923 Tg methane 1Bscfmethane

**~** 

### '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 1mile

**~** 

### 1.609 

## km I hp

**~** 

### 0.7457 kW I hp-hr

**~** 

### 0.7457 kW-hr I Btu

**~** 

### 1055joules 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 ofany 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, CH 4


### where MW (molecular weight) of

### C02

**~** 

### 44, MW

**carbon~** 

### 12, and MW CH 4

**~** 

### 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 ifit were atthe standard conditions of 14.73 psi, absolute, and 

### 60°F. For a fixed gas composition, a scfdefines a mass. Billion standard cubic feet 

### (109 

### scf). Trillion standard cubic feet (1012 

### set). Million standard cubic feet. Thousand standard cubic feet. Teragrarn (I

### 0" g)

. 

### Same as billion 

### (109 ). 

### 1000 kg. Gauge pressure. Absolute pressure (note psia = 

### psig 

## + atmospheric pressure). Standard cubic feet per day, standard cubic feet per year. Percent ofmolecules in a stream that are ofone type. Percent ofthe volume of

### a stream that is ofone species. For 

### an ideal gas, vol% is equal to mol%.


## E-3

### wt% Prod 

### Proc Trans Dist 

### GWP 

### MMT MMTCE = 

### Percent ofthe mass (weight) ofa stream that is ofone

**sp~cies.** = 

### Production = 

### Gas Processing Transmission Distribution
= 

### Global Warming Potential ofa particular greenhouse gas for a given time period.

= 

### Million metric tonnes ofa gas.
= 

### Million metric tonnes, carbon equivalent. 

### MMT 

## of C0 2

## eq.

**~** 

### Million metric tonnes, carbon dioxide equivalent.



### E-4TECHNICAl REPORTDATA

**(PI~**readIIUhv.ctiOIUon tht: «VUUh<[ourompleting) 1. REPORT NO. 3. RECIPIENT'S ACCESSION NO. 

### EPA-600/R-96-080c 4. TITLE ANO SUBTITLE 5. REPORT DATE 

### Methane Emissions from the Natural GasIndustry,

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.

### HummeLD.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 ANDADDRESS 

## EPA, Office of Researchand 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.

**l~**



### ... osponsor GRI project officer is R.A.

### Lett, Gas Research Institute. 

### 8600 West Bryn

**~V>awr** 

### Ave., 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% ofgross 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 beingused 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

StationarySources Global Warming

19.SECURITY CLASS (ThisReport} 

## 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 PROTECTIONAGENCY Office of Research and Development NationalRisk ManagementResearch Laboratory 

### TechnologyTransferandSupportDivision 

### Cincinnati, Ohio45268 OFFICIAL BUSINESS PENALTY FOR PRIVATE USE. :S300 

### AN EQUAL OPPORTUNITY EMPLOYER



### IIyour

### llddress is incorrect. pleBn

### change on the above label ltUifoff; 8/Jdreturn to thtt above llddtess. II

### you do

### not desitt! to continut! rectdving th11se lt!Chnica/ teports,**CHEC~** HER£0; tear offlabel, andreturn 

### ;r to the above iJddress. 

# Publication No. EPA-600/R-96-0SOc

.

## ... ,

## .......**~ ··~·····-·--**