Methane emissions from the natural gas transmission and storage system in the United States

Transcription

1 Supporting Information for Methane emissions from the natural gas transmission and storage system in the United States Daniel J. Zimmerle *,a, Laurie L. Williams b, Timothy L. Vaughn a, Casey Quinn a, R. Subramanian c, Gerald P. Duggan a, Bryan Willson a, Jean D. Opsomer d, Anthony J. Marchese a, David M. Martinez a, Allen L. Robinson c a Energy Institute and Department of Mechanical Engineering, Colorado State University, Fort Collins, CO b Department of Physics and Engineering, Fort Lewis College, Durango, CO c Center for Atmospheric Particle Studies (CAPS) and the Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA d Department of Statistics, Colorado State University, Fort Collins, CO * Corresponding author: dan.zimmerle@colostate.edu; Phone This document provides supporting information for the paper Methane emissions from the natural gas transmission and storage system in the United States. Section 2-5 describes the data sources and emission categories utilized in the analysis model. Sections 6-14 provide descriptions of sub-models utilized in the emissions model. Section 15 describes how the study model was compared with the Greenhouse Gas Inventory. Finally, Sections describe results supporting major conclusions in the paper. This material is available free of charge via the Internet at S1

2 Introduction This supplementary information describes the simulation model that was used to create the Study Model Estimate (SME) for this study. Chapters describe the T&S sector, input data, modeling method, sub-models of the SME, and provide additional detail for calculating leak rates, and comparisons to the GHGI and GHGRP. In addition to this document, an auxiliary data set provides data files of input data and results. Some, but not all, of these files are referenced in the descriptions below. Finally, each submodel is documented with a 2-page description describing the inputs and outputs of the sub-model (available from the CSU web site). The study was sponsored by the Environmental Defense Fund (EDF), Interstate Natural Gas Association of America (INGAA), and seven companies who have operations within the transmission and storage (T&S) sector: Columbia Pipeline Group, Dominion, Dow Chemical, Enable Gas Transmission, LLC (formerly CenterPoint Energy Gas Transmission Company, LLC), Kinder Morgan, TransCanada, and The Williams Companies, Inc. Contents 1 Introduction Glossary Description of the T&S Sector Emission Categories and Data used for Modeling Data Sets Data from Study Partners Additional Partner-Provided Emissions Measurements EPA e-ggrt Reported Emissions Additional Data Sources Simulation Model Emission Models Overview Modeling Difference between Partner and Non-Partner Emissions Modeling Unknown Pneumatic Device Counts Modeling Combustion Methane Emissions Estimating Non-Reporting, Non-Partner Station Count Analysis of Compressor Type and Size Estimation of Total Compressor Power Modeling Super-Emitter Emissions GHGI Categories Comparable to the SME Calculation of Total Leakage Rate for the T&S Sector SME Results Comparable to GHGI SME Results Comparable to GHGRP References Figures: Figure S3-a: Definition of the T&S Sector Figure S3-b: Simplified Schematic of a transmission station showing one compressor Figure S6-a: Flow Chart for Simulation of Entire Model Figure S6-b: Example of the SME for a one of the emissions models in Lane S2

3 Figure S10-a: Prime Mover Efficiency Developed from Known Unit Data Figure S11-a: Lane 5 Facility Count Estimate Figure S14-a: Resulting Probability Distribution from Empirical Simulation Figure S14-b: Super-emitter Emissions Model Figure S15-a: Emissions categories not modelled in the SME Figure S17-a: Emissions Distributions for SME and with the Alternative Transmission Count Figure S18-a: Difference between GHGRP and SME Figure S18-b: Compressor Venting Categories Tables: Table S4-a: Emissions Categories for Compressor-Related Emission Sources... 9 Table S4-b Emission Categories for Emissions Sources not Related to Compressors Table S4-c: Correspondence between GHGRP Classifications and GHGI Comparison Categories Table S5-a: Summary of Partner Facility Site Types by Lane Table S6-a: Data sets available for use in simulation model Table S6-b: Facility and Compressor Counts for Simulation Lanes and Data Subsets Table S7-a: Frequency at Which a Facility had No Leaks Detected Table S7-b: Identification of skewed emissions models Table S7-c: Summary of All Emission Models Table S8-a: Comparison of Emissions Data between Partner Facilities and Non-Partner Facilities Reported to the GHGRP Table S8-b: Differential Emissions Model Results Table S8-c: Multiplier Distributions for Lane 5 Emissions Simulations Table S9-a: Comparison of Pneumatic Counts between Partner and Non-Partner Facilities Table S10-a: Measurements Used for Combustion Methane Emissions Models Table S10-b: Comparison of AP-42 Emission Factors and Associated Master Models Table S12-a: Prime Mover Counts by Compressor Type and Facility Reporting Status for Partner Companies Table S12-b: Type of Prime Mover for Each Type of Compressor for Partner Companies Table S12-c: Non-Partner Compressor Type for Facilities Reported to GHGRP Table S12-d: Average Compressor Size from Partner Data Table S13-a: Mean Simulated Compressor Count Subdivided by Prime Mover Type Table S13-b: Mean Simulated Compressor Power Table S13-c: Estimated Total Compressor Capacity for T&S from FERC Form 2 Data Table S15-a: T&S GHGI Indicating Categories Modelled in the SME Table S16-a: Calculation of T&S Leak Rate Table S17-a: SME Results in GHGI Categories Table S17-b: Summary of shifts between GHGI and SME mean estimates by emission category Table S18-a: Comparison of GHGRP and SME Table S18-b: Largest Categories in SME-GHGRP Comparison Table S18-c: Component Leak Categories S3

4 107 2 Glossary CDF CI EPA GHGI GHGRP MC NOD NOP OEL OP Partner Data Set PDF Prime mover PRV SME Study Model Study Partners Study Team T&S Cumulative distribution function Confidence interval Environmental Protection Agency, United States government Greenhouse Gas Inventory EPA estimate of greenhouse gas emissions from the USA. Unless otherwise qualified, GHGI refers only to T&S sector methane emissions in this document. Greenhouse Gas Reporting Program An EPA regulatory program requiring the reporting of greenhouse gasses under Code of Federal Regulations (CFR) Title 40, Part 98 Mandatory Green House Gas Reporting Program. Unless otherwise qualified, GHGRP refers only to T&S sector methane emissions in this document. Monte Carlo the statistical simulation method Not operating, depressurized Not operating, pressurized Open-ended line; used here as a type of component classification. Operating Data provided by the six study partners. Probability distribution function The internal-combustion engine, turbine, or electric motor driving a compressor. Pressure-reducing valve; used here as a type of component classification. Study Model Estimates Distribution of estimates of emissions. The complete statistical model estimating of emissions from the T&S segment. The six sponsor companies who provided data and site access to the study team: Dominion, Enable Gas Transmission, LLC (formerly CenterPoint Energy Gas Transmission Company, LLC), Kinder Morgan, Columbia Pipeline Group, TransCanada, and The Williams Companies, Inc. Data processing, quality control, modeling, and analysis were performed by the study team at Colorado State University (CSU), with assistance from other team members at Carnegie Mellon University (CMU). All contributors are listed as authors. Transmission and storage sector of the natural gas industry, as defined in Chapter 3. The EPA greenhouse gas inventory refers to this sector as the T&S stage. S4

5 Description of the T&S Sector This chapter provides a brief overview of the T&S sector to provide context for following chapters. This study defines the T&S sector as the natural gas system infrastructure between two custody transfer points the receipt meter between the gathering and processing sector and the transmission system, and the delivery meter between the transmission system and the distribution system or end user (see Figure S3-a). The T&S sector contains both interstate and intrastate infrastructure, including compressor stations, pressurized pipeline networks, metering and regulation stations, and supporting equipment. (A) Some gas moves directly from gathering to distribution Transmission System Consumers Distribution or Major Customers Production Midstream Gathering & Processing M M M Storage (B) Storage operated by distribution companies 116 Exploration & Production Gathering & Processing Transmission & Storage Distribution Figure S3-a: Definition of the T&S Sector. Nominal metering points are marked with M and gas flows are indicated with arrows. Liquefied natural gas operations and minor gas flows, including consumption in the sectors for compression or processing, is not shown. Figure S3-a also highlights two exceptions to typical gas flows important to this study. (A) Some gas moves directly from gathering to distribution, does not pass through the T&S sector. Facilities involved in these gas flows were not quantified or modeled, except to the extent that intrastate facilities were considered. (B) The study estimates emissions from all underground storage facilities/fields, even if they were operated by companies which do not operate other T&S infrastructure. Figure S3-b provides a (vastly) simplified schematic of a transmission station showing major gas-handling equipment. Typically the station and each compressor unit (one shown) are isolated from the gas pipeline by a pair of isolation valves (suction and discharge). To allow units to be depressurized (blown down), each unit is equipped with one or more blowdown valves. Some units are also equipped with piping (not shown) that routes some blowdown gas to be used as fuel for compressor engines/turbines. Blowdown valves are connected to vents typically open-ended lines to release gas into the atmosphere. When the compressor is pressurized, isolation valves are open and blowdown valves are closed. When the compressor is depressurized, isolation valves are closed and blowdown valves are S5

6 (typically) open. Fugitive emissions may occur through any of the valves when closed. Therefore, when valves are measured for fugitive emissions depends upon the operating mode of the compressor. Centrifugal compressor seals, wet seal degassing vents, and rod packing vents may also have fugitive emissions, which typically occur when the compressor is pressurized. It is common for multiple fugitive sources to be routed to the same vent. An analogous valve arrangement is applicable to the station piping. Unit Blow Down Condensate Tank Separator Purge Suction Isolation Unit Bypass Seal Or Rod Packing Vent(s) Discharge Isolation Station Blow Down Station Discharge Station Suction Figure S3-b: Simplified Schematic of a transmission station showing one compressor. Major gas connections are shown. Minor gas flows, including gas consumed for fuel are not shown. Finally, most compressors (and possibly the entire station) are equipped with a separator on the suction piping to collect any liquids or foreign material entrained in the natural gas. Liquids from separators are routed to onsite tanks by periodically opening a purge valve in the separator. At some facilities, gas used to purge the separator is vented to atmosphere through vents on the condensate tank. In other facilities, the purge gas may be routed to a flare. In addition to the equipment in Figure S3-b, the GHGRP also defines two categories of component leaks compressor components and non-compressor components. Component leaks include emissions from connectors, valves, pressure-reducing valves, meters, and open-ended lines. Compressor component emissions originate from equipment directly related to compressors, including gas-driven pneumatic starters, skid vents, fuel gas handling and associated equipment. Non-compressor components include all other pressurized gas equipment in the facility. S6

7 Emission Categories and Data used for Modeling Data from the GHGRP and partners, and the overall simulation model, was structured using emission categories defined by the EPA in Code of Federal Regulations (CFR) Title 40, Part 98 Mandatory Green House Gas Reporting Program (GHGRP), Subparts C (General Stationary Fuel Combustion Sources) and W (Petroleum and Natural Gas Systems). GHGRP emission categories are arranged hierarchically into categorical groups which are sub-divided by component types, and compressors-related emissions are further divided by operating mode. This hierarchy is illustrated in Table S4-a for compressor-related categories and in Table S4-b for other categories. Gray lines are categorical groups ( categories), with reference to the section and paragraph number from the GHGRP regulations. Lines below each gray line are component types within the group ( components ). The column GHGRP Requirements identifies which operating modes are included in the GHGRP reporting rules OP operating mode; pressurized and compressing gas. NOP not-operating pressurized; unit pressurized but not compressing gas NOD not-operating depressurized; unit blown down The column Operating Mode lists the operating modes where measurements of the category / component are active. The field measurement campaign measured all components in these modes. The final two columns ( Origin of ) summarize the origin of measurements utilized for the emission models in each category. Field Meas. indicates the number of points obtained from the field measurement campaign, while Partner Meas. indicates the number of measurements provided by supplemental data from partners, described in Section 5.2. To compare to the GHGI, the modeled categories in tables Table S4-a and Table S4-b were aggregated into categories which can be compared to categories utilized in the GHGI. The correspondence between GHGRP categories utilized for the SME model and those utilized for comparison to the GHGI are identified in Table S4-c. It is important to note that one simulation model was built but two sets of results were extracted one to compare to the GHGRP (reporting facilities only) and one to compare to the GHGI (all facilities). The categories utilized for comparison to the GHGI are similar, but not identical, to those defined by the GHGI. Several key differences: Driven by limitations in available data, all component leak categories are included in station fugitives; the GHGI splits component leaks into compressor- and non-compressor component types. The SME includes exhaust emissions for electrically-driven compressors in both transmission and storage; the GHGI does not. The number of centrifugal compressors in storage was insufficient to produce statistically valid comparisons. Therefore, all storage compression is grouped into one comparison category. It should be noted, however, that storage compressors are overwhelmingly reciprocating compressors. Of the estimated 1515 [+13%/-12%] compressors in storage, the SME estimates 68 [+34%/-28%] centrifugals with wet seals and 47 [+39%/-30%] with dry seals. S7

8 The station venting categories model similar emission sources for both the GHGI and the SME. However, while the GHGI and SME utilize similar definitions for blowdowns, the origins of the data are significantly different. The EPA/GRI emission factors were based upon the following process: The general methodology was to generate the annual emission averages from estimating the frequency of release (times/yr/equipment), the volume per event (function of pressure, volume in the equipment, and gas composition), and the disposition (vents to atmosphere or control volume) of the gas. In contrast the SME is based upon logged blowdown events, as required by the GHGRP, with emissions estimated by engineering calculations. Station venting in the GHGI was based upon annualized emission factors from the 1996 EPA/GRI study[1]. The EPA/GRI study included unit blowdowns, unit starts, and emergency station blowdowns, and found other maintenance and miscellaneous activities to be negligible for T&S stations. The SME is based upon blowdown events logged and reported to the GHGRP. These logs include all blowdowns with volumes 50 ft 3, and include all categories from the EPA/GRI study. The logs also include additional blowdowns including pig launch & receive operations which occurred within the station fence, but would be included in the pipeline venting category of the GHGI. Both sources utilized similar engineering methods to calculate released gas. Episodic, as used herein, are emissions which occur for short, defined, time spans, typically seconds to minutes in length. Examples include blowdowns, dump valve actuation, and purging lines. Intermittent pneumatics, however, are included as a separate emissions category in the SME and GHGRP. There are several episodic emission categories not fully characterized in the SME, and likely not captured in either the GHGRP or GHGI. These include gas-driven engine starters, pig launch events occurring outside facility fence lines, and dump valves on separators or similar vessels. The GHGI does not include a category for super-emitter emissions. Since the modeling of superemitters has a pronounced impact on the model and results, this category was modeled separately, at the station level. S8

9 Table S4-a: Emissions Categories for Compressor-Related Emission Sources Source Category GHGRP Requirements Operating Mode Origin of Emission Data Points Utilized in Study Model Reciprocating Compressor Venting ( (p)) Field Meas. Partner Meas. Rod packing vents OP OP 47 0 NOP excluded NOP 39 0 Blowdown valve 1 OP & NOP OP & NOP Isolation valve NOD NOD Centrifugal Compressor Venting ( (o)) Field Meas. Partner Meas. Wet seal oil degassing vents OP OP Dry seal vents excluded OP Blowdown valve 1 OP OP & NOP Isolation valve NOD NOD Fuel Combustion Sources ( (c)) AP-42 Data 3 Partner Meas. Lean 2-Stroke Subpart C OP 51 3 Lean 4-Stroke Emissions OP Rich 4-Stroke Factor OP 0 46 Turbine OP mode OP 6 10 Notes 1. Blowdown valve venting for reciprocating and centrifugal compressors combined into one model 2. Insufficient data existed to model vent seal emissions in NOP mode. 3. Drawn from data sets utilized to develop AP-42 emission factors S9

10 Table S4-b Emission Categories for Emissions Sources not Related to Compressors Source Category Transmission Storage Tanks ( (k)) Tank vent stack or scrubber dump valve Pneumatic Device Venting ( (a)) Intermittent bleed devices High continuous bleed devices 4 GHGRP Requirements DM at Transmission EF EF Field Measurement Method Origin of Emission Data Points Utilized in Study Model Field Meas. Partner Meas. DM at all facilities Field Meas. Partner Meas. Not modeled 3 Low continuous bleed devices 4 EF Leak Detection and Leaker EFs ( (q)) Field Meas. Gas-service Compressor Components (CC) Connectors EF DM Valves EF DM OELs EF DM 92 0 PRVs/Meters 5 EF DM Gas-service Non-compressor Components (NC) Connectors EF DM Valves EF DM OELs EF DM Partner Meas. PRVs/Meters 5 EF DM Population Count and EFs ( (r)) Natural gas storage wellheads EF DM Not modeled Blowdown Vent Stacks ( (i)) "Unique blowdown volumes" EE DM (Unclassified Pneumatics) Emissions for storage and Lane 3-5 modeled from Lane 1 Study Partner Data Other Field Meas. Partner Meas. Uncategorized/super-emitter 6 not included TFE 20 0 Legend: DM Direct measurement EF Emission factor EE Engineering estimate, transmission only TFE Tracer flux estimate Notes 1. Direct measurements of tank vents were performed at both storage and transmission sites 2. Field measurement campaign did not distiguish between high- and low-bleed pneumatics 3. Insufficient dta was available to develop model for intermittent bleed pneumatic devices 4. High and Low bleed pneumatic devices measurments are combined into one model 5. Compressor & non-compressor gas service PRVs and Meters measurements are combined into one model 4. Insufficient field measurment data was available for storage wellhead modeling 5. Storage facility Blowdown Vent Stack emissions are estimated from transmission data 6. The uncategorized/super-emitter model used 20 separate TFE plumes taken from two field study sites S10

11 Table S4-c: Correspondence between GHGRP Classifications and GHGI Comparison Categories GHGI Comparison Category Transmission Stations Fugitives GHGRP Classification Used in Simulation Model GHGRP GHGRP Category Component Compressor Component All Station Non-Compressor Component All Transmission Tank All Reciprocating Compressor Reciprocating Compressor Venting All All Centrifugal Compressor (wet seals) Centrifugal Compressor Venting, Filtered Centrifugal Compressor (dry seals) by seal type All All Uncategorized / Super-Emitter Uncategorized / Super-Emitter Storage Stations Fugitives GHGRP Mode Station Compressor Component All Transmission Tank All Compressors Recip. & Centrifugal Compressor Venting All All Uncategorized / Super-Emitter Uncategorized / Super-Emitter Compressor Exhaust Engines (Transmission) Combustion Methane Lean 2 Stroke OP Combustion Methane Lean 4 Stroke OP Combustion Methane Rich 4 Stroke OP Turbines (Transmission) Combustion Methane Turbine OP Electric (Transmission) Combustion Methane Electric OP Combustion Methane Lean 2 Stroke OP Engines (Storage) Combustion Methane Lean 4 Stroke OP Combustion Methane Rich 4 Stroke OP Turbines (Storage) Combustion Methane Turbine OP Electric (Storage) Combustion Methane Electric OP Pneumatic Devices Transmission Stations Pneumatics All Storage Stations Pneumatics All Station Venting Transmission Stations Blowdown Volume All Storage Stations Blowdown Volume All S11

12 Data Sets Each of the data sets utilized for the SME are summarized in the sub-sections below. 5.1 Data from Study Partners Six of the study partners provided facility lists and 2011 and 2012 emissions data for their facilities. The remaining partner company provided financial support but no data, as they had only two T&S sector facilities which were of an unusual configuration. Only 2012 data was utilized for the study model. The study partners provided the following data: Facility & Compressor Lists for all of their facilities with T&S operations, current as of September Where differences existed between facility lists and emissions data (typically due to equipment additions or retirements), facility lists were adjusted to match the 2012 operating state in consultation with the partners. Emissions Data for all facilities where it was available, including all facilities reporting to the GHGRP ( reporting ) and facilities where emissions had been measured, typically during GHGRP surveys, but total emissions were below the GHGRP reporting level ( non-reporting ). Mandatory reporting for T&S is based on a threshold level of 25,000 metric tons of carbon dioxide equivalent (mtco2e) or more per year in combined combustion and other facility level emissions. In most cases, combustion CO 2 emissions are significantly higher than the carbon dioxide equivalent emissions of methane, and reporting is mostly likely triggered by combustion CO 2, rather than methane, emissions. Compressor Operating Hours by compressor unit and operational mode. Hours were not available for all compressors. Where available, hours were normalized to 8,784 hours for 2012 prior to simulation. Note: The GHGRP is ambiguous on how to handle leap years. Some partners utilized 8784 hours and some a nominal 8760 hours per year. Prime Mover Descriptions for compressors including make, model, and power ratings, where available. When only partial information was available, best efforts were made to estimate missing data by referring to known compressor units with the same make/model. All data was not available for all facilities/compressors. Partners provided emissions data using a data format similar to EPA s GHGRP reporting tool, the electronic Greenhouse Gas Reporting Tool (e-ggrt), but extended with supplementary data fields not required by the GHGRP. Four of six partners provided data to personnel at INGAA, who then passed it unmodified to the study team. The other two partners provided data directly to the study team. Some T&S sites are co-located with, or contain elements of, operations from other GHGRP sectors, such as distribution, gathering or processing. In these cases, the facility was retained in the study if the majority of the compressors at the facility were listed under the T&S sector in the GHGRP. Data from operations in other sectors were eliminated from the data set and those emissions categories were not simulated in the study model. Two storage facilities and one transmission facility contained no compressors and were retained in the study. Each facility was assigned a primary site type transmission or storage indicating the primary function of the facility. The facilities in Table S5-a had S12

13 both transmission and storage operations; emissions for all categories of both operations were provided by partners and modeled in the SME. Table S5-a: Summary of Partner Facility Site Types by Lane (lanes are defined in next section). Each facility was assigned a primary site type based upon which sector contained the majority of the compression capacity. 266 Lane Lane 1 Lane 2 Lane 3 Lane 4 Primary Site Type Secondary Site Type None Storage Transmission Total Storage Transmission Storage Transmission Storage Transmission Storage Transmission Total Additional Partner-Provided Emissions Measurements Three study partners provided supplemental emissions measurements collected during While all partners complete emissions surveys as required by the GHGRP, these partners engage in more comprehensive measurement programs, including direct measurement of source categories not required for mandatory reporting and measurements at non-reporting facilities. Measurement methods were clarified with partner personnel, and measurements made using instruments and protocols aligned with the field study protocols were utilized to augment field measurements, as indicated in the Partner Meas. column of Table S4-a and Table S4-b. All data utilized for emission models is listed in CDFMaster.xlsx, including the origin of the measurement. The 1,013 additional measurements provided by partners nearly doubled the available field measurements documented in Subramanian, R., et. al.[2] and allowed more robust modeling of several emission categories, as illustrated in tables Table S4-a and Table S4-b. 5.3 EPA e-ggrt Reported Emissions Data for all T&S facilities were downloaded EPA s Envirofacts web interface[3] on April 18, By matching e-ggrt reporting ID, partner facilities were removed from this data, leaving data for nonpartner reporting facilities. The GHGRP data provide basic facility information (significantly less than provided by the study partners), emission data for modes and categories required by GHGRP, leak and pneumatic counts. Compressor type and centrifugal compressor seal type can be deduced from the data, but prime mover type or size cannot be determined. Due to an error in the database at the time of downloading, the component type for component leak categories could not be determined. Specifically, the W_EST_EMISS_FOUND_IN_LEAK_SURV table lacked the field identifying the particular component type for each entry. Therefore, non-partner component leaks were treated as a single aggregate quantity for these facilities. One reported transmission facility, eggrt ID , had no compressors reported. S13

14 Additional Data Sources Additional public data sources were utilized for the following parts of the SME: Combustion methane emissions were based upon data underlying EPA standard Compilation of Air Pollutant Emission Factors (AP-42)[4] and additional exhaust stack measurements provided by the study partners (see Chapter 9). The alternative transmission facility count was developed using FERC Form 2 data.[5] (See Chapter 11) The national count of underground storage compressor stations was estimated from an EIA inventory of underground storage fields.[6] (see Chapter 11) S14

15 Simulation Model To estimate emissions, the SME uses emissions and activity models for each of the categories identified in tables Table S4-a and Table S4-b. Since all data was not available for all facilities and compressors in the data set, facilities were grouped into subsets, termed Lanes, each possessing a consistent set of data. Table S6-a describes the criteria used to assign facilities to lanes. The cells in the table indicate which information was available for the facilities in each lane. Table S6-a: Data sets available for use in simulation model Lane 1 Table Description: Partner facilities with emission and hours 2 Non-partner EPA data Data Type Partner facilities with hours, no emissions Partner facilities without hours or emissions Non-partner, non-reported facilities Compressor Information Prime Compressor Unit Mover Description Description Recip or Centrifugal Centfugal seal type Make/model/size info Recip or Centrifugal Centfugal seal type Hours Emissions in GHGRP Categories Reported to EPA Reporting Facilities Non- Reporting Faclities Complete Complete Complete Some Some No data No data Complete All None Similar to Lane 1 Partial Complete No data None All Mixed Partial No data No data Some Some No data No data No data No data None All Compressor unit description Not all partners were able to provide specific compressor make and model for each unit. However, for all compressors it was at least possible to identify the type of compressor (reciprocating, centrifugal, screw). Screw compressors (1 unit) were treated as centrifugal. Compressor prime mover description Prime mover type and size are required to model combustion methane emissions and total compressor power. Complete indicates that the prime mover type (make/model) was known for all compressors. Partial indicates that some facilities or compressors did not have prime mover descriptions. Compressor hours partners provided hours in each of the EPA-defined operating modes (OP/NOP/NOD). Emissions in GHGRP Categories emissions data were (were not) available compiled as if the facility reported to the GHGRP. Reported to EPA indicates whether emissions data in this lane were reported to the EPA GHGRP in 2012 (based on a reporting threshold of 25,000 mtco 2 e) Facility counts for all lanes are shown in Table S6-b including the SME-estimated count for Lane 5, which is generated by the simulation model. Subdivisions of the model are shown below the primary table for key attributes, such as available compressor, pneumatic and leak count data. S15

16 Table S6-b: Facility and Compressor Counts for Simulation Lanes and Data Subsets Model Lane Reported to GHGRP Facilities Compressors Total Trans Storage Total Recip. Cent. Lane 1 Reported ,694 1, Not Reported Lane 2 Non-partner Reported , Lane 3 Not Reported Lane 4 Reported Not Reported Total Facilities/Units with Data ,436 3,284 1,152 Facility & Compressor Counts Including Simulated Activity Estimated Lane 5 Non-partner, Not Reported ,783 2, SME Estimated U.S. Total 1,758 1, ,219 5,439 1,780 3 GHGI 2,143 1, ,071 8, Ratio (SME / GHG Inventory) 82% 76% 111% 80% 66% 216% Facilities with some level of activity data (compressor description and hours, device counts, etc.) Compressor and seal type known: ,721 2, Compressors with detailed descriptions: ,586 1, Facilities with pneumatic count data: Facilities with leak count data: Facilities which are known to exist, from study partners and non-partner facilities reported to GHGRP Total Reported ,046 2, Total non-reported partner facilities , Estimated non-partner, non-repored facilities ,783 2, % non-reported 72% 67% 88% 58% 58% 57% Known facilities & compressors: 52% 60% 26% 61% 60% 65% 10 Notes: Reported non-partner facilities appear in Lane 2. An estimate of non-reported non-partner facilities appear in Lane 5. Partner 1 facilities are divided between Lane 1, 3 & 4. Facility and compressor counts in Lane 5 is estimated using the model described in Chapter 11. Base station count is shown. 2 Alternative station count and sensitivity analysis is given in the main text. 3 The SME facility count includes all partner facilities, reported non-partner facilities, and the estimated Lane 5 facilities 4 GHGI station count estimates are taken from Table A-129 of the 2012 GHGI. See Chapter Facility and compressors where the compressor type and seal type are known 6 Facility and compressors where available information included operating hours and prime mover type 7 See Chapter 9, Pneumatic Device Model, for additional analysis of pneumatic device types. 8 Due to a data encoding problem, leak counts could not be determined in data downloaded from Envirofacts. 9 Non-partner, non-reported facilities are modeled in Lane 5 10 "Known" facilities and compressors are study partner facilities + non-partner reported facilities. The SME was simulated using Monte Carlo (MC) methods. Flow charts in Figure S6-a highlight the simulation process for Lanes 1-4, with known facility lists, and Lane 5, with a simulated facility list. The simulation method follows the simulation methods described by Ross[7]. An example for one sub-model is shown in Figure S6-b, with an execution description. The next paragraphs walk through the simulation steps for Lanes 1-4, following the flow chart in in Figure S6-a. Execution proceeds as follows: Step 1: In lane 1, all activity data is known and used directly. In lanes 2-5, activity models are executed to fill in unknown activity data. Unknown activity is estimated from known information from similar facilities. For example, compressor hours from reporting facilities in Lane 1 are utilized to model compressor hours in Lane 2 (also reporting facilities). Data from non-reporting Notes S16

17 facilities in Lane 1 are utilized for Lanes 3, 4 and 5 all of which are non-reporting facilities, except for two reporting facilities in Lane 4 for which compressor hour data was unavailable. Since activity models are stochastic, resulting activity data will have a distribution of values i.e. it will be a CDF, as shown in the example in Figure S6-b. Step 2: Emission models are executed by drawing an emissions rate or value from an appropriate distribution, and combining it (typically via multiplication) with the appropriate activity data. Step 3: At the end of each MC iteration, every category and component in the lane has been assigned exactly one emission value during Step 2. In this step, assigned values saved in distributions and are totaled into aggregated categories, such as the GHGI categories shown in Table S4-c. Step 4: Results are summarized. Lanes 1-4 Lanes 5 Generate Facility List using Facility Count Activity Model Execute Activity Models Execute Activity Models Execute Emission Models Execute Emission Models Capture Iteration Results Capture Iteration Results Emission Iteration Complete? No Emission Iteration Complete? No Yes Yes Activity Iteration Complete? No Yes 347 Create Summary Results Create Summary Results Figure S6-a: Flow Chart for Simulation of Entire Model Since the number of facilities in Lane 5 is unknown, an additional activity model is required to simulate the number of facilities. A new facility count is generated every 100 iterations of the model. Thus, for a S17

18 ,000 iteration MC simulation, 500 independent facility lists are generated and simulated in Lane 5. Finally, because the facility list is changing, activity data for every model in Lane 5 varies throughout the simulation. For example: In Lane 3 there are a constant number of facilities but a simulated number of pneumatic devices (Figure S6-b). For the same emissions category in Lane 5, both the number facilities and the number of pneumatic devices vary. The increase in variation caused by a two-stage model widens the confidence interval (CI) for Lane 5 simulation results beyond that in other lanes. At the conclusion of the simulation, results from each of the five simulation lanes are independent of all other lanes. A combinatorial process was utilized to consolidate results from the five lanes into one estimate. Results from each lane are randomly ordered and summed to create an estimate combining all five lanes, creating a distribution for each emissions category in the aggregation with 50,000 values. The same combinatorial process is utilized for total emissions. This method extends the MC method through the consolidation process and produces more representative CI estimates for totaled results. It is important to note that one model was constructed and simulated, but results were aggregated twice, once each to compare with the GHGRP and the GHGI. Confidence intervals were computed empirically from result distributions (e.g. Figure S6-b panel (e)) by identifying the 2.5% and 97.5% fractiles of the distribution to produce an empirical 95% confidence interval. 368 S18

19 Figure S6-b: Example of the SME for a one of the emissions models in Lane 3. The model simulates emissions from continuous-bleed pneumatic devices (CB pneumatics) at transmission stations. Each distribution is displayed as a cumulative distribution function (CDF), where θ denotes the probability axis. Panel (a) is the emissions rate model, consisting of data from field and partner measurements. Panel (b) is the total number of CB pneumatic devices in Lane 3. The count is a distribution because pneumatic device counts are not known for all facilities and had to be simulated for some facilities using an activity model (not shown). Panel (c) is the result of the activity model simulation, showing the distribution of pneumatic devices per facility. Panel (d) is the distribution of simulated CB pneumatic emissions, per facility, for all 73 facilities in Lane 3. Finally, panel (e) displays the simulated emissions for all CB pneumatics in Lane 3. Panels b-e are the result of 50,000 iterations of the models. S19

20 Emission Models Overview A summary of all activity and emission models is provided in Table S7-c. This chapter discusses emission models for fugitive emissions and pneumatics. Fugitive emissions, as used in the GHGI, include all categories Table S4-a except for exhaust emissions, and all categories in Table S4-b except for pneumatics and blowdowns, which are vented emissions. Chapter 8-11 discusses special considerations for Lane 2 (non-partner reporting facilities), modeling pneumatic device counts, combustion exhaust emissions and facility counts for Lane 5. Chapter 14 describes the model for super-emitter emissions. Master emissions models in provided in CDFMaster.xlsx and indicated in blue in Table S7-c. All models are empirical distributions and the origin of each measurement and whether it was collected at a reporting or non-reporting facility is noted in CDFMaster.xlsx. Measurements utilizing portable acoustic devices were not utilized in the study, due to well-documented concerns with accuracy.[8] All emissions in Lane 1 and several emission categories in Lane 3 are simulated using activity data provided by partners ( Given activity models in Table S7-c). Emissions for Lane 2 were modeled using available activity data and differential emission models, described in Chapter 8. For remaining lanes and categories activity data were not available. One of two approaches was taken. 1) For pneumatic devices and combustion methane ( Count and HP-hrs in Table S7-c) activity was simulated and emissions were modeled as in Lane 1. The emission model for intermittent bleed pneumatics utilized the GHGRP emissions factor (yellow in Table S7-c). 2) For other emissions categories, results from Lane 1 were aggregated and applied by unit ( By Unit in Table S7-c) or by site ( By Site in Table S7-c) in Lane 3-5. The super-emitter model was applied at the site level for all facilities in all lanes. Flares were extremely rare in T&S (only one flare for all reporting facilities). This category was passed through, but is essentially zero. GHGRP-reported emissions for wellhead component emissions were passed through the model unchanged for Lanes 1 & 2, and aggregated emissions from Lane 1 non-reporting storage facilities were utilized to model emissions for Lane 3-5. Blowdowns are estimated using data reported to the GHGRP for transmission. For storage facilities in Lane 1 and 2, an emission model was created from transmission station blowdowns and weighted by compressor count to estimate blowdowns from storage facilities. Other lanes were utilized aggregate emissions models accumulated from Lane 1. Since leak counts were used as the activity driver in the SME, and additional correction was made to component leak count to avoid detection bias which may be present in GHGRP surveys. For the GHGRP leak surveys, component leak emissions are reported by first counting leaks detected at a facility, and then computing emissions by applying the count by an emissions factor. Leaks are detected using an infrared camera or other device. Some partners may also have utilized EPA Method 21[9], a regulation which classifies emission sources as leaks only if the measured concentration exceeds 10,000 ppm v using a specific measurement protocol. Using these detection rules, emissions are zero when no leaks were detected, and are non-zero when leaks are detected. Therefore, zero emissions could be reported even if leaks were detected, provided all detected leaks were below the reporting threshold. S20

21 In contrast, in the field study leaks were detected utilizing an infrared camera, in some cases supplemented by a Remote Methane Leak Detection (RMLD) device, and then all detected leaks were measured using a high-flow sampler. Since each leak is measured and no emission factors were utilized, measured emissions will be zero only if no leaks are detected or if all detected leaks are below the detection limit of the high-flow sampler. Table S7-a summarizes the frequency at which no component leaks were detected on study facilities, compared to partner facilities in Lane 1. Table S7-a: Frequency at Which a Facility had No Leaks Detected Compressor Components Non Compressor Components Connector Meter OEL PRV Valve Connector Meter OEL PRV Valve Field Study 51.1% 97.8% 64.4% 93.3% 51.1% 33.3% 97.8% 48.9% 86.7% 40.0% Partner Data 57.3% 98.7% 81.7% 91.9% 63.4% 49.0% 96.3% 78.5% 84.3% 50.8% Detection Difference 10.8% 0.9% 21.2% -1.5% 19.4% 32.0% -1.6% 37.7% -2.8% 21.3% To avoid this potential bias in the activity data in Lane 1, the following process was utilized, for each facility: 1) If the leak count was non-zero, emissions were simulated utilizing the provided count, and drawing, without replacement, an emission rate for each leak from the model s probability distribution. 2) If the leak count was zero, a random number was drawn to determine if a non-zero count should be assigned, at the proportion listed in the Detection Difference row. If a non-zero count should be assigned, one was drawn from a distribution of counts aggregated from all sites. Emissions were then simulated by drawing an emissions rate from each leak, using the bottom half of the model s probability distribution, since these leaks are (by definition) small enough to not meet reporting criteria. Finally, it is important to distinguish between emissions which are based upon leak counts versus those based upon device counts. For major compressor equipment (isolation valve vents, blowdown valve vents, seals and rod packing) and continuous-bleed pneumatics, the field protocol (or GHGRP protocol) required that every unit was measured in its current operating mode, and all measurements are included in the emissions distribution. For compressor and non-compressor components (connectors, open-ended lines, valves, pressure-reducing valves and meters), leaks were identified using survey techniques and only leaking components were measured. For these categories, measurements in the distribution reflect the distribution of non-zero leaks, not emissions from the entire population of components. Many of the emissions models exhibit significant skew, as illustrated in Figure 2 of the main paper. The 17 emissions models identified in Table S7-b were developed from field measurement data and partner measurement data. Remaining emissions models were developed from other data sources, such as combustion emissions models developed as in Section 7, or utilized emissions factors, such as intermittent pneumatic devices. Data underlying the table is included in CDFMaster.xlsx. S21

22 For the analysis of Figure 2 in the main paper, the models were classified as skewed if 5% of measurements accounted for 30% of measured emissions. Skewed models have 47 to 408 measurements each, and the largest 5% of measurements account for 34-75% of total measurements. Also included in the table is the ratio of the largest measurement to the 97.5% fractile of the distribution. Notes: Emissions Model 4 Table S7-b: Identification of skewed emissions models Operating Mode 1 Total Samples in Model Fraction of Emissions Due to Largest 5% of Measurements Ratio of Maxmium Meas. To 97.5% Fractile NC Open-Ended Line % 6.0 Other Components % 1.3 CC Connector % 22.9 CC Open-Ended Line 92 62% 8.8 Recip. Isolation Valve NOD % 8.7 CC Valve % 4.9 Blowdowns % 4.6 Blowdown Valve Vents % 8.7 NC Connector % 4.3 Continuous-Bleed Pnematics % 2.0 NC Valve % 5.5 Centrifugal Isolation Valve NOD 96 39% 2.1 Recip. Rod Packing Vent OP 47 36% 2.6 Recip. Rod Packing Vent NOP 39 21% 1.0 Centrifugal Dry Seal Vent OP 38 18% 1.0 Tank Vent 33 18% 1.0 Skewed Distribution Centrifugal Wet Seal Vent OP 28 34% 1.2 Other 3 1. Modes defined in Section 4. NOD - not operating, depressurized; NOP - not operating, pressurized; OP - operating 2. Skewed distribution defined as CDFs where the top 5% of measurements account for 30% of emissions 3. This distribution exhibits some elements of a skewed distribution, but has too few values to be classified as skewed 4. NC = Non-compressor component; CC = Compressor Component. Definitions follow the GHGRP definition. Yes 2 No S22

23 Activity Basis Emission Models Lane 1 Lane 2 Lane 3 Lane 4 Lane 5 Lane 1 Lane 2 Lane 3 Lane 4 Lane 5 1 Given By Site By Site By Site By Site Master Diff Agg Agg Agg Emission Source Component Leaks, All GHGRP Categories Master GHGRP EF High & Low Continuous Bleed Given Given Count Count Count Intermittent Bleed Given Given Count Count Count Pneumatics Table S7-c: Summary of All Emission Models Wellhead Components Given Given By Site By Site By Site Pass Pass Agg Agg Agg Flares Given Pass Vent stack or dump valve By site By Site By Site By Site By Site Master Diff Agg Agg Agg Blowdown vent - NOP Blowdown vent - OP Given By Unit Given By Unit By Unit Master Diff Master Agg Agg Transmission Tanks Isolation Valve - NOD Rod Packing - NOP Rod Packing - OP Blowdown vent - NOP Blowdown vent - OP Dry Seal Vent - OP Isolation Valve - NOD Wet Seal Vent - OP Lean 2 Stroke Lean 4 Stroke Rich 4 Stroke Combustion Turbine Reciprocating Compressor Venting Master Diff Master Agg Agg By Unit By Unit Given By Unit Given Centrifugal Compressor Venting Master Given HP-hrs Given HP-hrs HP-hrs Combustion Methane Storage 2 Storage 2 By Site By Site By Site Storage 2 Storage 2 Agg Agg Agg Master By site Station Venting (Blowdowns) Super-Emitter Activity Model Legend: Emission Model Legend Notes: Study-developed emissions model from field & partner measurements Given Activity data was available; no model required. Master Aggregate of GHGRP-SME differences Count Counts simulated, then emissions applied Diff Aggregate model HP-Hrs Utilzation simulated, then emissions applied Agg 1 Lane 5 uses aggregate models that utilize an emission multiplier (see text) 2 Blowdowns are passed through, except for storage sites, By Unit GHGRP EF Uses applicable GHGRP emission factor GHGRP emissions passed through model Emissions are applied at per-unit or per-site basis. By Site No detailed activity model utilized. Pass which are modeled separately Special model for storage sites; see text. Storage Special model for storage sites; see text. Storage S23

24 Modeling Difference between Partner and Non-Partner Emissions For reporting stations, partner reported emissions were compared with the non-partner reported emissions, as shown in Table S8-a, for key GHGRP categories. This comparison illustrates that reported methane emissions for non-partner reporting facilities averaged 1.4 times more than per-facility emissions for partner reporting facilities. On a source category basis, transmission tank emission estimates and centrifugal compressor venting estimates are notably higher for the non-partner facilities, 4.6 times and 7.7 times greater respectively. Table S8-a: Comparison of Emissions Data between Partner Facilities and Non-Partner Facilities Reported to the GHGRP. GHGRP Reported Emissions Partner Reported Non-Partner Reported Facilities Facilities Emissions Per Unit (Mg) Emissions Per Unit (Mg) Ratio of per-unit Emissions GHGRP Emission Category Activity Units Activity Count Activity Count (Mg/Mg) Component Leaks, All GHGRP Categories Station Transmission Tanks Station Reciprocating Compressor Venting Compressor Centrifugal Compressor Venting Compressor Total All GHGRP Emissions Categories Station In order to account for the difference in partner and non-partner emissions, the modeling process was adjusted in two ways: 1) Emissions for Lane 2 facilities (non-partner, reported facilities) were modeled utilizing differential emission models, described below. 2) Simulated emissions for non-partner non-reported facilities (Lane 5) are increased by a multiplier distribution during simulation, to account for systematic difference in emissions between partner and non-partner facilities. The differential models are aggregate models capturing the difference between the SME and the GHGRP emission values. For Lane 1, emissions for each emission category are simulated as in Chapter 6, and are therefore independent of the partner-reported GHGRP emissions. During Lane 1 simulation, the difference between the SME estimate and the GHGRP emissions are aggregated for every activity item (either facility or compressor unit), producing a new emissions model which represents the difference between the emissions reported using the GHGRP protocol and emissions simulated by the SME. As an example, consider isolation valve emissions for the i th compressor, on the k th MC iteration. An emissions value is simulated using the isolation valve model to produce emissions estimate e i,k. The same isolation valve has an emission value reported to the GHGRP of g i, which does not vary across MC iterations. The difference in emissions for the k th MC iteration, which may be positive or negative, is: Δe i,k = e i,k g i (1) S24

25 489 The set of all such differences are aggregated into a new CDF, M: M = {Δe i,k } i, k (i for reporting facilities only) (2) During Lane 2 simulations, an emissions difference is drawn from M and added to the GHGRP emissions for each item (facility or compressor unit) to estimate emissions. Therefore the emissions for an isolation valve of the j th compressor in Lane 2 on the l th MC iteration is calculated by drawing an emissions value from M and computing emissions for the isolation valve as: f j,l = g j + draw(m) (3) The reason for applying this method is to reflect the origin of the emissions measurements underlying the emissions models. Emissions measurements were collected only from partner facilities, and the difference between the model results and data reported to the GHGRP reflect two estimates for partner facilities. Had emissions measurements been made at non-partner facilities, we assume that a similar difference would have been seen. This approach therefore drives the difference between SME and GHGRP emissions in Lane 2 to be approximately equal to the difference between SME and GHGRP emissions in Lane 1, on a per-unit basis (blue columns Table S8-b.) (Note: Given infinite iterations, the MC method will drive the Lane 1 and Lane 2 differences to match exactly. For finite iterations, however, there is a slight deviation between the two lanes. Differences shown here are less than 2%.) Since the SME is 2.6 times the GHGRP emissions in Lane 1, the ratio of SME values is smaller than the ratio of GHGRP values, as indicated in the right column of the table. As a net result, the SME estimates that emissions from non-partner reporting facilities are approximately 10% higher than those of partner facilities. Table S8-b: Differential Emissions Model Results Per Unit Differential Activity Emissions After Simulation (Mg) SME Per Unit Emissions For Reporting Facilities (Mg) GHGRP Emission Category Units Lane 1 Lane 2 Lane 1 Lane 2 Ratio Component Leaks, All GHGRP Categories Station Transmission Tanks Station Reciprocating Compressor Venting Compressor Centrifugal Compressor Venting Compressor Total All GHGRP Emissions Categories Station 945 1, To simulate Lane 5 (non-reporting non-partner facilities), emissions models were aggregated from simulation results for non-reporting partner facilities in Lane 1. These emissions were then scaled using a ±25% triangular distribution centered on the ratio observed in Lane 1 for reporting facilities (yellow column in the table). Points for the triangular distributions are shown in Table S8-c. Table S8-c: Multiplier Distributions for Lane 5 Emissions Simulations Triangular Distribution for Multipliers in Lane 5 Simulation GHGRP Emission Category Lower Middle Upper Component Leaks, All GHGRP Categories Transmission Tanks Reciprocating Compressor Venting Centrifugal Compressor Venting S25

26 Modeling Unknown Pneumatic Device Counts Since pneumatic counts were not available for lanes 3-5, these counts were simulated. As can be seen from the average counts provided in Table S9-a, significant differences exist between the partner and non-partner facilities. Reasons for the differential are unknown, but it appears that study partners have designed and/or converted facilities to use other actuation methods more than non-partners. The differences are particularly pronounced at storage facilities, where non-partner facilities utilize 7.3 times more continuous-bleed pneumatics than study-partner facilities. Differences also exist between reporting and non-reporting study partner facilities, particularly for intermittent-bleed devices, where reporting facilities have a population several times larger than non-reporting facilities. Table S9-a: Comparison of Pneumatic Counts between Partner and Non-Partner Facilities where Pneumatic Counts were Available Site Type Data Source Reporting Transmission Storage Low Bleed Population Counts High Intermittent Bleed Bleed Total Count Number of Facilities Per Facility Counts Low High Bleed Bleed Intermittent Bleed All ,629 4, Partner Reporting ,247 3, Non-reporting Non-Partner Reporting ,229 7, All Partner Reporting Non-reporting Non-Partner Reporting 290 1,161 1,234 2, Unfortunately, insufficient data was available to develop probability distributions for all eight possible combinations (e.g. partner/non-partner, storage/transmission, reporting/non-reporting). Site type and partner/non-partner were prioritized, and four separate probability distributions were developed. The following model was applied to simulate pneumatic counts: 1) Lane 1 and 2: Pneumatic counts are available and did not need to be simulated. 2) Lane 3 and 4: Distributions based upon non-reporting facilities in Lane 1. 3) Lane 5: Distributions based upon reported facilities in Lane 2. Since Lane 2 facilities (all reporting) are likely larger than Lane 5 facilities (all non-reporting), this approach may overestimate the pneumatic count in Lane 5. S26

27 Modeling Combustion Methane Emissions Combustion methane emissions is unburned methane in the exhaust of prime movers (engines and turbines) utilized to drive compressors. These emissions are included in GHGI methane emissions for the T&S. For the GHGRP these emissions are calculated using Subpart C of the GHGRP program. Some facilities include engine-driven generators for auxiliary power; emissions from these engines were not included in the model. The emissions model was developed from the data underlying AP-42[4] and partner data from routine stack testing. The AP-42 dataset is available for reciprocating engines[10] and gas turbines[11] on the EPA website. This analysis follows the same prime mover families included in AP-42: combustion turbine, 2-stroke lean-burn (2SLB), 4-stroke lean-burn (4SLB), and 4-stroke rich-burn (4SRB). The AP-42 emissions data were filtered to select data with complete information. Data where prime mover make or model was not provided were excluded from the model. If only partial descriptions were provided (e.g. entries listed as LB (lean-burn), and 4S (4-stroke)), data were utilized if the make and model could be identified by other means or if the exhaust oxygen concentration could be used to place the engine in the correct category. Records that did not include a horsepower rating or a percent of rated horsepower for the test were eliminated. Only test data from that contained direct measurement of methane concentration were used. In particular, all AP-42 data for 4SRB engines were computed by subtracting ethane and volatile organic compounds from total organic compounds, and were eliminated from the emissions model. The final count of measurements is listed in Table S10-a. Table S10-a: Measurements Used for Combustion Methane Emissions Models Number of Measurements Prime Mover Type AP-42 Data From Partners Total Turbine SLB Engine 4SLB SRB Calculation of methane emission rates requires the prime mover s type, efficiency and fuel usage across a range of loads. We discuss each below: Efficiency: Thermal efficiency was modeled using the engine test data and was supplemented with data from manufacturer technical documents. For each class of prime mover, an efficiency map was developed by binning units by size and computing an average efficiency for each size bin. Loading: While operating hours were known, loading was not known. Therefore, the SME assumes prime movers were operating fully loaded, while some operators compute emissions using actual loading while others assume a typical loading, such as 90%. To compare to GHGRP emissions data (reported or partner data), it is important that the GHGRP emissions reflect the same hours and loading as the SME estimate. Therefore, no exhaust methane emissions data from partners or the GHGRP data were utilized. Instead, GHGRP-equivalent exhaust (i.e. un-combusted) methane emissions were computed using the Subpart C formulae and utilizing the same input data that were utilized for the SME. Since this method assumes a loading level, the Subpart C emissions may be larger or smaller than S27

28 emissions data submitted to the GHGRP, but using the same basis for calculation produces directly comparable results between the GHGRP emissions and the SME emissions. Emissions Model: There are four emissions models (probability distributions), one each for the four prime mover categories outlined in above. In keeping with AP-42, emission models are stated in pounds of methane emissions per MMBtu of fuel delivered to the engine. Emissions models are included in CDFMaster.xlsx. The SME uses the emissions models directly, as empirical distributions. However, for comparison purposes, the average and standard deviation of the study models are compared to the AP-42 emissions factors in Table S10-b. The mean of each SME model is comparable to the corresponding AP-42 emission factor, and within 16% of the AP-42 factors. The GHGI utilizes emissions factors similar to AP-42. The GHGRP utilizes one emission factor (Subpart C) of 0.001kg/MMBtu fuel input, for all natural gas combustion sources. The last column of the table compares this emission factor to the mean of the SME emissions model. Differences are substantial, with the SME model averaging more than 550 times larger for lean burn engines. Table S10-b: Comparison of AP-42 Emission Factors and Associated Master Models Ratio of SME Effective Emission Factor Mean to (lb/mmbtu fuel input) Comparison of AP-42 to SME Subpart C Assumed AP-42 Emission Mean of SME Study Standard Difference Emission Prime Mover Type Efficiency* Factor Model Deviation (%) (AP-42 - SME) Factor Turbine 33.6% % 4 2SLB 37.5% % 559 Engine 4SLB 37.3% % 578 4SRB 31.4% % 90 * Used when prime mover type and/or size are unknown Applying the Emissions Model: Where prime mover size and type are known, fuel usage was calculated using the rated power output of the unit and an estimate of thermal efficiency derived from the unit size and type. Thermal efficiencies are summarized in Figure S10-a. An exhaust methane rate is then drawn from the model, as described in Figure S6-b, and multiplied by fuel usage and operating hours to obtain total combustion methane emissions Figure S10-a: Prime Mover Efficiency Developed from Known Unit Data S28

29 For lanes where the prime mover and operating hours are unknown, emissions were simulated utilizing distributions of HP-hours aggregated from Lane 1 and 3. These represent an aggregations of compressor usage expressed as the size of the unit (HP) multiplied by operating hours. Two distributions are assembled, one for reporting and one for non-reporting facilities; it is assumed that units on non-reporting facilities are smaller and/or run fewer hours than reporting facilities for both partner and non-partner facilities. To simulate lanes 2, 4 & 5, usage is drawn from these aggregated usage models for each compressor, an emissions rate is drawn from the emissions models as described above, and a single efficiency is assumed for each prime mover category, as shown in Table S10-b. S29

30 Estimating Non-Reporting, Non-Partner Station Count Unlike most national emissions models, this study had significant data about a majority of the facilities in the T&S sector, the 922 facilities shown in Table S6-b. However, it is still necessary to estimate the number of non-partner, non-reporting facilities, i.e. the facilities simulated in Lane 5. Different methods were utilized for storage and transmission stations. Underground Storage Stations: The U.S. Energy Information Administration (EIA) uses the Natural Gas Annual Respondent Query System (NGQS)[6] to compile data from underground storage operators via the EIA-191 form. The NGQS data provides a list of underground storage fields with the corresponding fieldnames, state and county location, and the operational status (active/inactive). Including only active fields, the April 2014 release of the NGQS data documented 419 underground storage fields. A review of the partner s underground storage facilities for which field names were available indicated that there were 42 storage stations servicing 47 storage fields. Scaling the EIA field number by this ratio results in an estimate of 382 total storage facilities. To account for uncertainty, this total count was simulated using a ±10% uniform distribution. Since there are 99 known facilities (Table S6-b) this is equivalent to simulating the 283 unknown (non-partner, non-reported) facilities with a ±13.5% uniform distribution. This resulted in an estimated underground storage count of 382 ±9% in the SME. Transmission Stations: Transmission facility count was estimated utilizing a bootstrap estimate. The number of reported transmission facilities, R i, and total number of transmission facilities, T i, were computed for each study partner, i. The total number of transmission facilities reported to EPA, N epa, was extracted from the data downloaded from Envirofacts, of which R np = N epa R i are non-partner reporting facilities. Assuming the ratio of reporting to non-reporting sites for partner companies is similar to that of the population at large: 6 i=1 R i 6 i=1 T i N epa N usa 11-1 where N usa is an estimate of the transmission site population in the USA. By extension, the transmission facilities in Lane 5 (non-partner, non-reporting) is given by: N lane5 = [ 6 i=1 T i 6 i=1 R i 6 ] N epa T i R np 11-2 Bootstrap methods were then utilized to compute all possible estimates of Lane 5 transmission site counts by drawing six total and reported site count pairs and utilizing equation Negative estimates were discarded, leaving 46,713 possible combinations. The resulting model for Lane 5 facility count is given "Lane 5 Site Count.csv" in the auxiliary data and summarized in Figure S11-a. i=1 S30

31 Figure S11-a: Lane 5 Facility Count Estimate The above distribution estimates Lane 5 transmission count at 558 [+90%/-65%] facilities. Combined with the 823 known transmission facilities from other simulation lanes, the above model produces a simulated estimate of 1,383 [+36%/-26%] facilities for transmission. To validate the site count model, the above model was compared with a facility count estimation employing a method similar to that used for the GHGI. The Federal Energy Regulatory Commission (FERC) requires interstate transmission operators to annually report facilities, compressor counts, operating hours and pipeline mileage (among other data) utilizing FERC Form 2 for major operators (>50,000 deka-therms of gas transport) and Form 2a for smaller interstate operators.[5] The data were cleaned by sorting the appropriate tables into the original line order used by the reporter and eliminating non-transmission stations, inactive stations and separator lines (Cleaned data is available via the CSU web site. The data utilized here were extracted from tables containing operator identity (f2_001_ident_attsttn), compressor station list (f2_508_comp_stations), and pipeline length (f2_514_trans_lines)). After cleaning, 1092 transmission facilities were identified, reported by 68 operating companies and 28 reporting entities. (Note: Data are reported by operating companies, often separate corporate entities which operate a single pipeline system but are owned by one or more major operators. To identify management ownership, the study used the addresses of the reporting point of contact, although some adjustments were made in consultation with the partner companies.) FERC jurisdiction is restricted to facilities on interstate transmission pipelines. To estimate total station count, a scaling method was used to estimate the total number of stations in both interstate and intrastate systems: N t = N f L f + L i L f = 1597 estimated transmission facilities where N f = 1092 is the number interstate transmission facilities identified in the FERC data, L f = 191,660 miles is the length of interstate pipelines from the FERC data, L i = 88,648 miles is an estimate of intrastate pipeline miles from EIA,[12] and N t = 1597 is an estimate of the total number of transmission compressor stations in the USA. No confidence interval can be estimated with the available information. S31

32 The number of facilities from this analysis is approximately 216 stations greater than the mean of the model described above, but still well within the confidence bounds of the bootstrap model discussed earlier. To perform a sensitivity analysis, an estimate of 200 ±100 stations was utilized. The size of these (possible) stations is difficult to estimate, but since Lane 5 facilities are not reported to the GHGRP, a reasonable assumption is that these stations are smaller than most mainline compressor stations. Therefore, for the sensitivity analysis these stations were simulated with site configurations similar to partner, non-reporting, transmission stations and emissions models used for other Lane 5 facilities. S32

33 Analysis of Compressor Type and Size Study partners provided prime mover descriptions make, model and size for many compressor units. Prime mover is used here as the general term of internal combustion engines, combustion turbines, and electric motors, utilized to drive compressor equipment. One steam-driven unit was not included in the analysis. However, all three pieces of information were not available for all compressor units. Data from known make-model combinations were used to estimate power rating and combustion type where that information was incomplete. Results are provided in Prime Mover Map.csv in the auxiliary files. In addition, sizes (but not make/model) were accumulated for electric prime movers. Table S12-a summarizes all available counts, and Table S12-b summarizes the same data as fractions of the total population. Table S12-a: Prime Mover Counts by Compressor Type and Facility Reporting Status for Partner Companies 678 Group All Partner Reported Non-reported All Partner Wet Dry Prime Mover Type Total Prime Mover Missing Data No Prime Mover Definition Compressor Type Electric Turbine Lean 2 Stroke Lean 4 Stroke Rich 4 Stroke Reciprocating , , Centrifugal Combined , , Reciprocating , ,324 0 Centrifugal Combined , , Reciprocating Centrifugal Combined , Reciprocating Cent. Wet Seal Cent. Dry Seal Cent. Unknown Seal Combined Table S12-b: Type of Prime Mover for Each Type of Compressor for Partner Companies 680 Group All Partner Reported Non-reported All Partner Wet Dry Prime Mover Fractions (Units / Total Units) Electric Turbine Lean 2 Stroke Lean 4 Stroke Rich 4 Stroke Fraction Turbine or Compressor Type Electric Reciprocating 2% 0% 68% 19% 10% 2% Centrifugal 6% 89% 0% 4% 0% 96% Combined 3% 22% 51% 16% 8% 25% Reciprocating 1% 0% 78% 15% 6% 1% Centrifugal 2% 93% 0% 5% 0% 95% Combined 1% 20% 61% 13% 5% 21% Reciprocating 4% 0% 54% 26% 17% 4% Centrifugal 11% 86% 0% 4% 0% 96% Combined 6% 24% 39% 19% 12% 30% Reciprocating 2% 0% 68% 19% 10% 2% Cent. Wet Seal 2% 93% 0% 5% 0% 95% Cent. Dry Seal 6% 91% 0% 3% 0% 97% Cent. Unknown Seal 16% 77% 0% 7% 0% 93% Combined 3% 22% 51% 16% 8% 25% S33

34 Table S12-b indicates that the vast majority (96%) of centrifugal compressors are driven by turbines or electric drives, while the vast majority of reciprocating compressors (98%) are driven by reciprocating engines. While some differences exist between reporting and non-reporting facilities, the distribution is largely similar. Table S12-c provides all known compressor type information for non-partner reporting facilities. The fraction of centrifugal compressors with wet seals (41%) is similar for both partner facilities (Table S12-a) and non-partner facilities. Note that the seal types in Table S12-c in the non-partner data are due to data gaps, or reporting errors, in the EPA Envirofacts database. Of the 765 centrifugal compressors included in the partner data set, the type of centrifugal seal was unavailable for 141 compressors, spread across 76 facilities. In these cases, seal type was simulated utilizing an activity model based upon the ratio of wet to dry seals from compressors with known seal type. Table S12-c: Non-Partner Compressor Type for Facilities Reported to GHGRP Compressor Type Reciprocating Centrifugal Wet Centrifugal Dry Centrifugal Unknown All Compressors Count of Reporting Non- Partner Units Table S12-d provides the average unit size of all partner compressors. Table S12-d: Average Compressor Size from Partner Data 697 Group All Partner Reported Non-reported All Partner Wet Dry Total Prime Mover Power (MW/Unit) Compressor Type Electric Turbine Lean 2 Stroke Lean 4 Stroke Rich 4 Stroke Average for Prime Mover (MW/unit) Reciprocating Centrifugal Combined Reciprocating Centrifugal Combined Reciprocating Centrifugal Combined Reciprocating Cent. Wet Seal Cent. Dry Seal Cent. Unknown Seal Combined S34

35 Estimation of Total Compressor Power To estimate total compressor power in the T&S sector, prime mover types were estimated using ratios given in Table S12-b and total compressor counts simulated in the SME, producing the counts in Table S13-a. Total compressor power was then calculated utilizing average size estimates given by Table S12-d, as shown in Table S13-b. A similar process was utilized for the upper and lower CI of the compressor count, producing the estimate of 20.3 GW [16.6 GW to 24.4 GW]. The same process was applied to the compressor counts in the GHGI to produce an estimate of 19.5 GW. Table S13-a: Mean Simulated Compressor Count Subdivided by Prime Mover Type Estimated Total Units Total Simulated Compressor Type Electric Turbine Lean 2 Stroke Lean 4 Stroke Rich 4 Stroke Count Reciprocating ,782 1, ,554 Centrifugal 112 1, ,780 Table S13-b: Mean Simulated Compressor Power Estimated Compressor Power for Mean Simulated Compressor Count (MW) Total Power Compressor Type Electric Turbine Lean 2 Stroke Lean 4 Stroke Rich 4 Stroke (MW) Reciprocating ,733 2, ,702 Centrifugal 1,002 9, ,566 Total 1,478 9,343 6,733 2, ,268 Compressor capacity was also estimated from the FERC Form 2 data as shown in Table S13-c. For stations which report to FERC, compression capacity is provided. Facilities which do not reported to FERC are likely smaller stations. To estimate the compressor capacity at these stations, the FERC reported capacity was scaled by the ratio of compressor capacity for non-reporting to reporting stations for the study partners -- 61% for transmission and 65% for storage. This estimate was developed from facilities in Lanes 1 & 3, including all compressors where prime mover data was available. The resulting additional capacity was added to reported capacity for a total T&S capacity estimate. Table S13-c: Estimated Total Compressor Capacity for T&S from FERC Form 2 Data FERC Form 2 Data Item Facility Type Transmission Storage Capacity from FERC Form 2 (10 6 HP) Capacity from FERC Form 2 (GW) FERC Form 2 Station Count 1, ,217 FERC Form 2 Reported Power / Station (MW) Stations Not Estimated stations not reported to FERC Reported to Ratio of Station Size 2 (-) 61% 65% FERC Additional Capacity (GW) Est. Capacity (GW) Notes: 1. Number of stations was estimated by scaling by pipeline miles. See text. 2. Ratio of non-reported to reported facility compressor power for Lane 1 facilities Total S35

36 Modeling Super-Emitter Emissions During the measurement campaign, an onsite survey was conducted (approximately) contemporaneously with a downwind tracer flux measurement using the protocols and methods described in a companion paper by Subramanian, R., et. al.[2] As described in the companion paper, two of the 45 facilities (sites 14 and 37) were classified as super-emitters due to elevated emissions observed by tracer flux methods which were not be measured using onsite measurements. Since no standardized definition exists for super-emitters, this study utilizes the threshold defined in the companion paper: Facilities with mean tracer flux emissions greater than 200 standard cubic feet per minute (SCFM). Site 14 was undergoing maintenance at the time of measurement. Site 37 was in a normal operating mode. At both facilities, onsite observers indicated that the emissions venting were likely due to anomalous condition, such as emissions through a faulty isolation valve. To model these emissions three pieces of information are required: the frequency at which facilities exhibit super-emitter behavior, the emissions model, and the time over which the emissions occur. We treat each in succession: Frequency: 733 Given that 45 facilities were measured during the field campaign, the probability of occurrence of each 734 large emitter was 1 or 2.2%. To develop an uncertainty distribution for these two observations, a sampling simulation was conducted. This simulation answers the question: What is the probability of 736 finding one super emitter in a random sample of 45 facilities from the available study population of partner facilities? The method utilized here follows the analysis of Wilson[13] for computing the 738 confidence interval of a rare event, but utilizes an empirical approach and a known population size In this approach, we note that the total facility population available to the field study is N pop = 686 from which was drawn a random sample of N test = 45 facilities. There are an unknown number of super-emitters in the population. We therefore assume the number of super-emitters in the facility population, N super, is in the range of 1 to N pop N test + 1. In practice this is done by conducting 50,000 trials for each possible value of N super, randomly selecting a random sample of N test facilities from the population, and counting any sample containing exactly one super-emitter. After 50,000 trials we have a count, x i, i = 1 N pop equal to the number of trials (of 50,000 trials) in which a random sample of N test facilities from N pop facilities produces exactly one super-emitter. These results are shown in (Figure S14-aa). Normalizing both axes produces a probability distribution in Figure S14-ab. S36

37 Figure S14-a: Resulting Probability Distribution from Empirical Simulation The resulting distribution has a mean of 4.1% and a 95% confidence interval of to The comparable statistic is the Wilson Score Interval using a 95% CI and a 1 in 45 frequency of occurrence, which is determined by calculating p in: z (p p) p(1 p) N z Where p is the actual probability of occurrence in the population, N is the number of samples, p is the observed probability, and z is the confidence parameter. For 95% confidence interval, z = The result is a very comparable, but slightly wider interval of to The distribution in Figure S14-ab was utilized in the SME to simulate the frequency of super-emitter emissions. Emissions model: Qualitative observations during the field study indicated that the emissions on both super-emitter sites were typical of large emissions sources that might be observed in the general population, i.e. this type of anomalous condition could occur on a wide variety of facilities undergoing either maintenance or in normal operating conditions, with or without compressors operating. Therefore, it was decided to form a single emissions distribution from the tracer observations from both facilities, and apply this single emissions model to all simulated super-emitters. To develop the emissions model, emissions observed by the onsite team (for each site) were subtracted from each qualified tracer flux measurement (a.k.a. each plume or FLER from reference [2]). All nine measurements from Site 37 were included in the model, and nine uniformly distributed measurements from Site 14 were also added to the model to equally weight the two facilities. The range of emission values reflects a range of potential emissions which may not be captured by on-site measurements. The distribution has a mean of 496 SCFM, and is shown in Figure S14-b. S37

38 Figure S14-b: Super-emitter Emissions Model. Panel (a) illustrates the empirical data utilized in the model from site 14 (green) and site 37 (red). Also shown is the CDF version of a triangular distribution which approximates the fits the empirical distribution (blue line). The triangular distribution is of the right triangle type, with a minimum and central value at the minimum observation (35.9 SCFM) and a maximum value at the maximum observation (1310 SCFM). The empirical distribution was utilized in the SME, and has a mean of 496 SCFM. Time over which emissions occur: The duration of emissions during maintenance and normal operations is necessarily different. It was decided to model both modes as an independent set of events. For normal operation, it is assumed that emissions persist for 8784 hours/year. While no one facility may emit at this rate for the entire year due to changes in operating or equipment state, SME assumes that the modeled frequency is representative of the state of the entire T&S sector during any given hour of the year. Good data were not available on the length and frequency of maintenance shutdowns. Based upon discussions with the study partners, the duration of maintenance mode emissions were modeled using a triangular distribution of duration, with a peak at 72 hours, lower limit at 8 hours and upper limit at 120 hours. Since emissions and frequency models are identical, maintenance emissions scale with the mean of this duration model (67 hours). Therefore maintenance emissions are: 66.6 ( ) = 0.8% of total super-emitter emissions, indicating that large emissions during maintenance activities are not likely to contribute significantly to national emission estimates. S38

39 GHGI Categories Comparable to the SME The SME emissions were compared against the estimated annual methane emissions reported in 2012 EPA GHGI[14]. The GHGI for the T&S sector is largely based on emission and activity factors from a 1996 study by the Gas Research Institute[1] along with updates in some categories, one of the most significant being a 2012 ICF study of centrifugal compressors.[15] The ICF study updated emission factors for wet seals based upon 48 wet-seal measurements (Exhibit 2), and dry seal measurements based upon data from the Natural Gas STAR program[16]. For T&S, the only activity data that are based on direct industry reporting are the miles of transmission pipeline.[17] Other activity data are extrapolated from a variety of bases. Table S15-a lists the GHGI methane emissions inventory for T&S. To make a direct comparison between the SME and the net estimated annual methane emissions from the 2012 EPA GHGI, the voluntary methane reductions identified in the GHGI are subtracted from each of the categories in as indicated in the Voluntary Reductions column. Voluntary reductions were explicitly documented in the 2012 EPA GHGI only for the categories highlighted in blue in Table S15-a, including reciprocating compressors fugitives, engine exhaust (divided proportionally between storage and transmission), transmission station pneumatic devices and pipeline venting. The remaining voluntary reductions are not itemized and were distributed proportionally among the remaining categories based on the ratio of the potential emissions from that category to the total potential emissions from those categories. This assumption used by Allen et. al. for the natural gas production sector.[18] Of the categories with explicit voluntary reductions, engine exhaust is of particular interest, since this study indicates that the voluntary reductions may be overestimated. Emissions missing from the last column of the table indicate categories not included in this study, and represent 266 Gg of methane emissions. Contributions to this category are shown in Figure S15-a. Uncertainty or accuracy of these emissions is unknown. However, a qualitative look at the top three components of these emissions is informative: Pipeline venting: Since no recent measurement data have been published for the largest category, pipeline venting and leaks, no qualitative observations can be made. M&R stations. City-gate M&R stations were recently measured in a comprehensive study of distribution systems by Lamb, et. al.[19] M&R stations in T&S are most similar to M&R facilities from distribution study with pressures >300 psi. These stations were found to have emissions approximately an order of magnitude lower than measurements from the 1992 EPA/GRI study or the current GHGI estimates. The Lamb study attributes the lower emissions to upgrades completed since the 1992 study. Assuming similar practices in at T&S stations, these emissions may be over-estimated in the GHGI. LNG facilities. Emissions for these facilities may exhibit issues seen in this study for other T&S facilities, such as emission rate differences or uncharacterized super-emitters. Activity data is less uncertain than other T&S facilities, as most LNG operations are sufficiently large that they are reported to the GHGRP. Considering these qualitative factors and assuming that there may be offsetting errors e.g. M&R stations overestimated and LNG stations under-estimated it is reasonable to assume that the 266 S39

40 Gg/yr estimated by the GHGI is within the confidence bounds stated for the GHGI national methane estimate in the GHGI. Data in Table S15-a are duplicated in the appropriate columns of Table S17-a to compare with the SME Figure S15-a: Emissions categories not modelled in the SME S40

41 Table S15-a: T&S GHGI Indicating Categories Modelled in the SME. Table is taken from Table A-129 (2012 Data and CH4 Emissions (Mg) for the Natural Gas Transmission Sector) from reference Error! Bookmark not defined.. To improve readability LNG categories have been consolidated into two lines. Activity Potential CH4 Emissions (Mg) % Total Potential Emissions 2012 Voluntary Reductions (Mg) Net CH4 Emissions (Mg) Emissions for Sources Included in This Study (Mg) Fugitives Pipeline Leaks 3, % ,823 Compressor Stations (Transmission) Station 111, % -16,382 94,655 94,655 Reciprocating Compressor 773, % , ,594 Centrifugal Compressor (wet seals) 232, % -34, , ,475 Centrifugal Compressor (dry seals) 14, % -2,209 12,763 12,763 Compressor Stations (Storage) Station 52, % -7,674 44,339 44,339 Reciprocating Compressor 150, % -22, , ,061 Centrifugal Compressor (wet seals) 22, % -3,297 19,050 19,050 Centrifugal Compressor (dry seals) 6, % ,568 5,568 Wells (Storage) 12, % -1,905 11,007 M&R (Trans. Co. Interconnect) 75, % -11,150 64,423 M& R (Farm Taps + Direct Sales) 17, % -2,589 14,960 Vented and Combusted Dehydrator vents (Transmission) 2, % ,765 Dehydrator vents (Storage) 4, % ,429 Compressor Exhaust Engines (Transmission) 235, % -114, , ,245 Turbines (Transmission) 1, % ,137 1,137 Engines (Storage) 20, % -9,830 10,447 10,447 Turbines (Storage) % Generators (Engines) 11, % -1,699 9,816 Generators (Turbines) % 0 3 Pneumatic Devices Transmission + Storage Pneumatic Devices Transmission 221, % -14, , ,157 Pneumatic Devices Storage 42, % -6,242 36,062 36,062 Routine Maintenance/Upsets Pipeline venting 184, % -100,100 84,679 Station Venting Transmission + Storage Station Venting Transmission 151, % -22, , ,778 Station Venting Storage 28, % -4,261 24,621 24,621 LNG Storage (all categories) 73, ,789 62,335 LNG Import Terminals (all categories) 12, ,826 10,551 Voluntary Reductions (Gg) (390) Total Reductions (Gg) Total Potential Emissions (Gg) 2,461 Total Net Emissions (Gg) 2,071 1,805 S41

42 Calculation of Total Leakage Rate for the T&S Sector This section describes the calculation of an emission rate as a fraction of total T&S sector throughput. Calculations are summarized in Table S16-a. Table S16-a: Calculation of T&S Leak Rate Note Units Quantity 2.5% Fractile Mean 97.5% Fractile 1 T&S Throughput scf 2.38E+13 2 Assumed methane fraction g/g 95.0% 3 Conversion g/scf Sector Methane Throughput Gg 434,422 5 SME Emission Estimate Gg 953 1,237 1,685 6 Other Sector Emissions (from GHGI) Gg SME Estimate for Total T&S 1,218 1,503 1,951 8 SME T&S Emission Rate Gg/Gg 0.28% 0.35% 0.45% 9 SME + Additional Intrastate Gg 1,298 1,633 2, T&S Emission Rate / Add'l Intrastate Gg/Gg 0.30% 0.38% 0.50% Total natural gas throughput for the sector is estimated in 2012 at 23.8 tscf/year, or 434 Tg of methane assuming a methane fraction of 95%, characteristic of pipeline quality natural gas and the volumetric percentage specified in GHGRP calculations. Emission categories not included in the SME are estimated in Table S15-a at 266 Gg/year. Total methane emissions for the mean and CI estimates for sector emissions are shown in Line 7 of the table, and the fraction of sector methane throughput in Line 8. Lines 9 and 10 repeat these calculations for the alternative transmission count estimate. In comparison, using the same method, the emissions rate estimated by the GHGI is 0.48% (2071 Gg/ Gg). T&S Leakage rate estimates for the paper s Introduction section: Total methane emissions from the natural gas system were estimated utilizing the 2012 estimate of total methane emissions from the GHGI[14], 6,186 Gg of methane per year, and including a portion of the 1511 Gg/year of methane emissions from petroleum systems which should be assigned to the natural gas sector to account for methane emissions from the production of associated gas from oil wells. Following the method employed by Alvarez et. al.[20], which defined the percentage of the methane emissions from petroleum operations assigned to the natural gas sector based on the percentage of energy produced at oil wells as natural gas (31% in 2012), the current 2012 EPA GHGI methane emission estimate represents a value of 1.3% of the total gross U.S. natural gas production. The size of T&S sector emissions was estimated using the GHGI estimate, including net reductions, of 2.1 Tg of methane emissions or 33% of the 6.2 Tg of methane emissions for the oil & gas sector. 864 S42

43 17 SME Results Comparable to GHGI Table S17-a compares the SME results to the GHGI, using the GHGI categories, and underlies figures 4-6 in the 867 mean emissions paper. Emission factors shown in the table are effective emission factors calculated as. mean activity 868 Table S17-a: SME Results in GHGI Categories 869 Activity Factor Comparison Emissions Comparison SME Emission Factor GHGI Emission Factor GHGI Net Emissions Emission Factor Units SME Mean Emissions (Gg) Activity Units GHGI Activity Estimate (Gg) 4 SME Mean Activity Estimate 1,799 1,375 stations 1, %/-39% Mg/Station Emission Category Transmission Stations Fugitives Station 2 1,799 1, %/-22% stations %/-30% Mg/station Reciprocating Compressor 6 7,235 4, %/-17% units %/-20% Mg/compressor Centrifugal Compressor (wet seals) %/-24% units %/-30% Mg/compressor Centrifugal Compressor (dry seals) %/-15% units %/-24% Mg/compressor Uncategorized / Super-Emitter %/-22% stations %/-63% 200 Mg/station Storage Stations Fugitives stations %/-42% Mg/Station Station %/-9% stations %/-26% Mg/station Compressors 3,6 1, %/-12% units %/-16% Mg/compressor Uncategorized / Super-Emitter %/-9% stations %/-83% 200 Mg/station Compressor Exhaust hp-hr %/-10% g/hp-hr Engines (Transmission) %/-9% 10 9 hp-hr %/-9% g/hp-hr Turbines (Transmission) %/-10% 10 9 hp-hr %/-19% g/hp-hr Electric (Transmission) N/A %/-32% 10 9 hp-hr 0 0 g/hp-hr Engines (Storage) %/-10% 10 9 hp-hr %/-11% g/hp-hr Turbines (Storage) %/-39% 10 9 hp-hr %/-59% g/hp-hr Electric (Storage) N/A %/-44% 10 9 hp-hr 0 0 g/hp-hr devices %/-23% Mg/device Pneumatic Devices Transmission Stations %/-33% 10 3 devices %/-34% Mg/device Storage Stations %/-15% 10 3 devices %/-18% Mg/device Station Venting 2,143 1,758 stations %/-17% Mg/Station Transmission Stations 1,799 1, %/-22% stations %/-14% Mg/station Storage Stations %/-9% stations %/-32% Mg/station 1,805 1, %/-23% Ratio: 69% [53% to 93%] Total for Categories included in Study (Gg) Total including 266 Gg of emissions from categories not included in SME (Gg) 2,071 1, %/-19% Ratio: 73% [59% to 94%] Transmission All Categories 1,799 1, %/-22% stations 1, %/-34% Mg/station Storage All Categories %/-9% stations %/-34% Mg/station Notes Storage blowdowns were modeled based upon transmission blowdown data 1 All component leak categories were included in the station estimate. Transmission and storage models utilized different categories, see supplementary information 2 Due to small numbers of centrifugal compressors, results combined for all compressor types for storage stations. See text for details. 3 Net emissions utilize GHGI estimates including reductions for improvement programs, see supplementary information 4 Pneumatic devices include only those at the storage compressor station and do not include well head devices, which are in Categories not Included in Study 5 Compressor categories include only major compressor components, including seals/rod packing, isolation valves, and blowdown vent value emissions 6 S43

44 Figure S17-a illustrates the SME emissions distributions annotated with confidence intervals, median and mean for both the SME and the sensitivity study on the alternative transmission station count. The only difference between these two estimates is the number of additional transmission stations estimated in Chapter 11. The GHGI estimate is slightly outside the CI for the SME estimate. The CI for the alternative station count estimate is substantially wider than the SME due the increased uncertainty in the number of transmission stations Figure S17-a: Emissions Distributions for SME and with the Alternative Transmission Count. Using data from Table S17-a, Table S17-b summarizes the shifts between the SME mean value and the GHGI mean value for principal GHGI emission categories. The first three data columns display the ratio of activity data, effective emission factor, and total emissions, respectively. Ratios are also provided for engine and turbine exhaust, which are specific interest due to the dominance of engine methane exhaust emissions. The second group of three columns provides the fraction of the total modeled categories (excluding categories in the GHGI which were not modeled in the SME) in each emission category. In most categories, shifts in both mean activity and effective emission factor are responsible for the shift in the mean value. Table S17-b: Summary of shifts between GHGI and SME mean estimates by emission category Fraction of Total for Modeled Categories Ratios (Mean SME / Mean GHGI) Activity (-) Emission Factor (Mg/Mg) Total Emissions (Mg/Mg) GHGI SME Shift GHGI to SME (% pts) Emission Category Transmission Stations Fugitives % 58% -2.1 Storage Stations Fugitives % 17% 6.0 Compressor Exhaust % 9% 2.1 Pneumatic Devices % 8% -5.2 Station Venting % 8% -0.8 Total SME - All Modeled Categories % 100% Additional Data for Exhaust Emissions Engines % 9.3% Turbines % 0.1% Emission Factor Units Mg/Station Mg/Station g/hp-hr Mg/device Mg/Station g/hp-hr g/hp-hr S44

45 Methane emissions from the natural gas transmission and storage system in the United States 18 SME Results Comparable to GHGRP To compare SME to the GHGRP, results from reported facilities in Lane 1 and all facilities in Lane 2 (all reported) were combined into the estimate shown in Table S18-a. Columns in the table include the emissions from the GHGRP and SME and the SME confidence interval. Category ratio is the ratio of the 892 SME estimate to the GHGRP estimate, i.e. ratio =. The difference between the two estimates GHGRP 893 and impact on the total difference is also shown. Note that, unlike comparisons to the GHGI, all facilities 894 in this comparison are known, and there is no uncertainty in the facility count. SME The column primary origin of difference in emissions is a qualitative assessment of the principal cause of differences between the SME and the GHGRP reported emissions, and is summarized in Figure S18-a. This analysis indicated that three principal factors drove differences between the two estimates: 1. GHGRP Omission The GHGRP program does not require reporting of certain emission sources in certain operating modes (see Table S4-a). These sources were included in the SME, and in some cases represent a significant fraction of the SME-estimated emissions (e.g. rod packing emissions in NOP mode). Including super-emitter emissions, which accounted for one third of the difference between SME and GHGR, GHGRP omissions accounted for 54% of the difference. 2. Emission Factor Evidence from this study indicates that certain emission factors particularly combustion methane emissions from lean-burn engines and fugitives from open-ended lines (see Table S18-c) are not representative of actual emissions. These differences in estimated emission rates account for 40% of the difference between the SME and GHGRP. 3. Measurement Method In some categories where emissions estimates depend upon direct measurements, differences exist in measurement methods allowed in the GHGRP protocols and those allowed in study protocol.[2] In particular, the study protocols excluded measurements from portable acoustic instruments, which are often used to measure isolation and blowdown valve emissions. Measurement methods account for the remaining 6% of the difference between SME and GHGRP. As described in Chapter 10, exhaust methane emissions were calculated for the GHGRP totals using the Subpart C method, rather than utilizing the values reported to the GHGRP. This assures that the operating hours, estimated size, loading and efficiency are comparable between the SME and GHGRP values used here. Comparing the SME and GHGRP, the SME estimates emissions that are 495 Gg [+26%/- 17%] compared with 191 Gg reported to the GHGRP. Three categories drive three quarters of the difference between the estimates, as shown in Table S18-b, and over 50% of the difference is due to two categories combustion methane and super-emitter emissions. 920 S45

46 Table S18-a: Comparison of GHGRP and SME Notes Difference (SME - MRR) (Mg) Fraction of Total Difference Primary Origin of Difference in Emissions GHGRP (Mg) SME (Mg) SME Confidence Interval Category Ratio Notes 17,780 43,961 [+81%/-31%] , % Emission Factor High & Low Continuous Bleed 7,387 13,152 [+7%/-7%] 1.8 5, % Emission Factor Intermittent Bleed 4,312 4,312 [+0%/0%] % Not modeled 1 Wellhead Components [+0%/0%] % Not modeled 1 Emission Source Component Leaks, All GHGRP Categories Pneumatics Transmission Tanks Reciprocating Compressor Venting Centrifugal Compressor Venting Combustion Methane Flares 0 0 [+0%/0%] % Not modeled 3 Vent stack or dump valve 4,062 5,832 [+18%/-18%] 1.4 1, % Meas. Method Blowdown vent - NOP 11,730 18,281 [+12%/-10%] 1.6 6, % Meas. Method Blowdown vent - OP 9,480 17,077 [+15%/-13%] 1.8 7, % Meas. Method Isolation Valve - NOD 16,105 28,284 [+22%/-19%] , % Meas. Method Rod Packing - NOP 0 44,407 [+7%/-7%] - 44, % GHGRP Omission Rod Packing - OP 42,994 35,701 [+9%/-9%] 0.8-7, % Other Blowdown vent - NOP 0 1,385 [+74%/-45%] - 1, % Meas. Method Blowdown vent - OP 3,393 6,131 [+25%/-19%] 1.8 2, % Meas. Method Dry Seal Vent - OP 0 4,814 [+13%/-12%] - 4, % GHGRP Omission Isolation Valve - NOD 16,055 20,602 [+7%/-7%] 1.3 4, % Meas. Method Wet Seal Vent - OP 4,580 11,651 [+20%/-18%] 2.5 7, % Other Lean 2 Stroke ,137 [+4%/-4%] , % Emission Factor Lean 4 Stroke 29 16,499 [+13%/-12%] , % Emission Factor Rich 4 Stroke [+19%/-17%] % Emission Factor Combustion Turbine [+23%/-20%] % Emission Factor Station Venting (Blowdowns) 51,250 55,744 [+9%/-5%] 1.1 4, % GHGRP Omission 2 Super-Emitter 0 100,074 [+128%/-80%] - 100, % GHGRP Omission Total for Available Emissions Data 190, ,539 [+26%/-17%] , % 1 Intermittent bleed pneumatics and wellhead components were modeled using GHGRP emission factors. SME estimate for blowdowns reflects a pass through of transmission blowdowns and a per-facility estimate of storage blowdowns. The 2 storage blowdowns are an omission from the GHGRP requirements. 3 Tank flare emissions (both GHGRP and SME) are smaller than the precision of the model and display as zero Figure S18-a: Difference between GHGRP and SME S46