Comments received on Draft "Inventory of U.S.
Greenhouse Gas Emissions and Sinks: 1990-2014"
Per Federal Register Notice EPA-HQ-OAR-16-000-4157; FRL-9942-62-OAR published on
February 22, 2016 the Environmental Protection Agency (EPA) announced document availability
and request for comments on the draft "Inventory of U.S. Greenhouse Gas Emissions and Sinks:
1990-2014" report. The EPA requested recommendations for improving the overall quality of the
inventory report to be finalized in April 2016 and submitted to the United Nations Framework
Convention on Climate Change (UNFCCC), as well as subsequent inventory reports.
American Gas Association (Pamela Lacey) 2
American Petroleum Institute (Karin Ritter) 9
Clean Air Task Force (David McCabe) 96
National Association of Clean Water Agencies (Cynthia A. Finley) 105
National Council for Air and Stream Improvement, Inc. (Brad Upton) 107
Portland Cement Association (Michael Schon) 110
U.S. Climate Plan (Evan Weber) 113
Waste Management (Kerry Kelly) 117
Bridget Chadwick 121
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American Gas Association
Electronic Filing:
hockstad.leif@epa.gov.
weitz.melissa@epa.gov
March 23, 2016
Ms. Melissa Weitz and
Mr. Leif Hockstad
U.S. Environmental Protection Agency
Climate Change Division
Office of Air and Radiation
1200 Pennsylvania Avenue, NW
Washington, DC 20460
Re: AGA's Comments on EPA's Draft Inventory of U.S. Greenhouse Gas Emissions and Sinks:
1990-2014 Related to Natural Gas Distribution, Transmission and Storage
Dear Ms. Weitz and Mr. Hockstad:
The American Gas Association (AGA) appreciates the opportunity to comment on the U.S.
Environmental Protection Agency's (EPA) Draft Inventory of U.S. Greenhouse Gas Emissions and
Sinks (GHGI) for 1990-2014 (Draft Inventory). AGA's comments focus on revisions to the natural
gas distribution sector and the natural gas transmission and storage sector.1 Because the Draft
Inventory does not include data for years prior to 2013 nor 2014 estimates, AGA's comments are
limited to EPA's revisions to the 2013 data and underlying methodology.
The American Gas Association, founded in 1918, represents more than 200 local energy
companies that deliver clean natural gas throughout the United States. There are more than 72
million residential, commercial and industrial natural gas customers in the U.S., of which 95% -
just under 69 million customers - receive their gas from AGA members. AGA is an advocate for
natural gas utility companies and their customers and provides a broad range of programs and
Draft Inventory 3-75 through 3-77.
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services for member natural gas pipelines, marketers, gatherers, international natural gas
companies and industry associates. Today, natural gas meets more than one-fourth of the United
States' energy needs.
Over the past two decades, AGA member companies have made concerted efforts to
upgrade and modernize our nation's pipeline infrastructure, thereby enhancing pipeline safety
as well as achieving significant reductions in natural gas emissions. AGA members have engaged
in voluntary actions through EPA's Natural Gas STAR program to share technical innovations that
help to reduce emissions from the natural gas distribution system. As a result, since 1990, natural
gas emissions from distribution systems have declined significantly even as miles of the
distribution mains expanded 30% to serve nearly twice as many customers. AGA appreciates
EPA's proposal to revise the GHGI to more accurately estimate methane emissions from the
distribution and transmission and storage sectors and recognize these significant reductions.
Based on these revisions, the Draft Inventory demonstrates that methane emissions from the
natural gas distribution sector in 2013 were 67 percent lower than EPA previously estimated
using older data - equivalent to only 0.1 percent of natural gas as a rate of production rather
than 0.3 percent as previously reported. The new approach also shows that emissions from
natural gas transmission and storage in 2013 were 47 percent lower than previously reported,
equivalent to only 0.2 percent rather than 0.4 percent of annual natural gas produced.
The downward revision for year-end 2013 emissions for the distribution sector is the
result of EPA's incorporating into the GHGI revised emissions factors calculated from data
collected through Lamb et al. Washington State University distribution study.2 The Lamb et al.
study provides the most comprehensive set of direct measurements of emissions from the
natural gas distribution system and confirms the significant reductions in emissions from
distribution systems that have occurred in the last 20 years. As part of the study, the research
team carefully measured numerous sites selected from lists of known leaks provided by the
thirteen participating utilities in geographically diverse regions around the country that met
specific criteria to ensure a comprehensive and representative dataset. The researchers took
direct emissions measurements of 230 randomly selected, representative leaks from
underground pipelines as well as at 229 metering and regulating (M&R) stations where natural
gas is measured and regulated from higher pressure pipelines to lower pressure distribution
pipelines. The researchers found dramatically lower emissions, particularly, at M&R stations.
2 Brian K. Lamb, et al., Direct Measurements Show Decreasing Methane Emissions from
Natural Gas Local Distribution Systems in the United States, Environmental Science & Technology
2015 49 (8), 5161-5169.
2
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EPA previously solicited feedback on its proposed approaches to incorporating new data
on emissions into the GHGI. In response, AGA submitted comments on EPA's Memorandum on
Revisions Under Consideration for Natural Gas Distribution Emissions (Distribution Memo)3 on
January 14, 2016. AGA also submitted comments on EPA's Memorandum on Revisions Under
Consideration for Natural Gas Transmission and Storage Emission (T&S Memo)4 on February 3,
2016. AGA's comments on the Draft Inventory will address the extent to which the Draft
Inventory addresses the issues raised in AGA's January and February comments.
I. AGA Generally Supports Incorporating New Data and Methodology for Estimating
Methane Emissions from Natural Gas Distribution in the Draft Inventory
A. Meter and Regulator Stations
AGA is pleased that EPA has followed through on its proposal in the Distribution Memo
to revise estimated emissions from metering and regulating (M&R) stations by incorporating
updated station counts and emission factors from the Lamb et al. study. As we commented
before, AGA believes that EPA's proposal to use the updated emission factors and the above
grade and below station counts our members report to EPA under 40 C.F.R. Part 98, Subpart W
and scaled for national representation results in a more accurate estimate of the actual number
of M&R stations.
As we noted in our January comments, we agree that it makes sense to estimate M&R
emissions across the time series by using the new updated emission factors for years after 2011
when the Subpart W data became available, to use the 1992-vintage GRI emission factors for
early years beginning in 1990, and to use interpolation for the years in between. We agree this is
the best approach to more accurately reflect net emissions without the need to subtract Gas
STAR program emission reductions.
B. Pipeline Leaks
For estimated pipeline leaks in the Draft Inventory, EPA used the previous activity data
sources for miles of pipeline by material and for leaks per mile, and the Lamb et al. data on
emissions per leak. AGA agrees with this approach, and particularly supports EPA's incorporation
3 EPA Distribution Memo is available on EPA's web site at:
https://www3.epa.eov/climatechanee/gheemissions/usinventorvreport/Proposed Revisions t
o NG Distribution Segment Emissions.pdf
4 EPA Transmission and Storage Memo is available on EPA's web site at:
https://www3.epa.eov/climatechanee/gheemissions/usinventoryreport/DRAFT Proposed Revi
s i o n s to I r3 n s i ss io ri StC3 r3 ^6 S6ei 6 rit E i ss i o ri s 2C310 C31 2C3«pd f
3
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of the Lamb et al. pipeline emission factors. As AGA noted in its prior comments, numerous
regulatory developments and voluntarily operator actions have resulted in significant reductions
in leak rates and incidents, reflected in the overall lower emissions found in the Lamb et al. study.
AGA also agrees with EPA's approach to use interpolation between GRI/EPA emission factors in
early years and Lamb et al. emission factors in recent years.
C. Residential Customer Meters
AGA supports EPA's inclusion in the Draft Inventory of revised emission factors for
residential customer meters by combining data from the 1996 GRI/EPA study with newer data
from a GTI 2009 study and Clearstone 2011 study. As noted in previous comments, the newer
data sources, and in particular the GTI 2009 study, include a robust data set composed of
numerous data points representing a variety of residencies, including single family homes,
duplexes, townhouses, and apartment buildings. Given the homogeneity of the residential
meters found at all the distribution companies sampled through the GTI 2009 study,
incorporating the new residential meter factor into the GHGI is appropriate.
AGA also supports EPA's update of its customer meter activity data for residential meters
to incorporate customer data reported to the U.S. Energy Information Administration (EIA). The
customer data is reported to EIA on its Form EIA-176. EIA does not collect data on meters
specifically. Rather, EIA instructs respondents to report the average number of consumers served
directly from facilities during the year. For residential consumers, this includes master-metered
apartments, mobile homes, multi-family dwellings (individually metered), and single-family
dwellings. Using data reported to the EIA will improve accuracy compared to the previous GHGI
methodology of using 1992 counts driven by gas consumption.
D. Commercial & Industrial Meters
AGA is pleased to see that for commercial and industrial meters, EPA has applied the GTI
2009 commercial customer meter emission factor to the total count of commercial and industrial
meters in the GHGI. As AGA noted in its prior comments, consistent with EPA's approach in the
Draft Inventory, the GTI 2009 industrial meter data should not be incorporated into the GHGI.
The GTI 2009 study only took industrial meter measurements from a limited number of sites (46
meters). Due to limited resources, measurements of industrial meters were intended to
represent the broad range of meters in this sector, but do not provide a statistical sampling
indicative of the industrial meter national inventory, nor does it account for the significant
variance in equipment type and size in industrial meters. For this reason, AGA agrees with EPA
not to include this data into the GHGI.
4
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AGA also supports EPA's update of its customer meter activity data for commercial and
industrial meters to incorporate customer data reported to the EIA. As explained above, the
customer data is reported directly to the EIA. Using this data will improve accuracy compared to
the previous GHGI methodology of using 1992 counts driven by gas consumption.
E. Blowdowns and Mishaps/Dig-Ins
For pipeline blowdowns and mishaps/dig-ins, in the Draft Inventory EPA used PHMSAdata
of distribution main and service miles for the activity data to calculate the estimate of emissions.
Although AGA appreciates EPA's attempt to update the methodology used to calculate emissions
from pipeline blowdowns and mishaps/dig-ins, AGA does not believe that EPA's approach
provides an accurate representation of the emissions from these sources.
As EPA recognizes, the current approach taken in the GHGI for both sources, which relies
on 1992 distribution main and service miles and is scaled by residential gas consumption, results
in a mileage estimate that is influenced by factors that would impact natural gas usage, but are
unrelated to pipeline miles. AGA agrees with EPA that PHMSA data is a more accurate data source
of pipeline miles. Pipeline operators are required to report data directly to the Department of
Transportation on an annual basis, which renders the PHMSA data on pipeline mileage an
accurate representation of installed pipeline mileage and is superior to the current methodology
of estimating pipeline mileage.
However, AGA is concerned with EPA's use of pipeline miles to estimate emissions from
blowdowns and mishaps/dig-ins. These sources of emissions are discrete events and there is no
available data that suggests a correlation between the number of miles in a pipeline system and
the number of mishap events on that system. The number of reported pipeline incidents on gas
distribution systems has been flat or down during the past five years;5 during that time, from
2010 to 2014, the number of miles of installed distribution main in the U.S. has increased by
nearly 60,000 miles or 5%.
AGA encourages EPA to use activity data that reflects the reality that an emission
blowdown or mishap/dig-in is a discrete event that is not correlated to the number of miles in a
pipeline system. AGA recognizes the difficulty in obtaining a comprehensive set of data for these
sources of emissions. However, because data associated with both will be reported through EPA's
5 U.S. DOT Pipeline and Hazardous Materials Safety Administration,
https://hip.phmsa.dot.gov/analyticsSOAP/saw.dll?Portalpages&NQUser=PDM_WEB_USER&NQ
Password=Public_Web_Userl&PortalPath=%2Fshared%2FPDM%20Public%20Website%2F_port
al%2FSC%20lncident%20Trend&Page=AII%20Reported&Action=Navigate&coll=%22PHP%20-
%20Geo%20Location%22.%22State%20Name%22&vall=%22%22
5
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proposed Methane Challenge for companies selecting this best practice, EPA will have more data
for possible use in the future to generate activity data for the GHGI. In addition, for mishaps/dig-
ins, AGA notes that significant incidents are reported to PHMSA, where significant is defined as
an incident above a certain size or impact threshold.6 AGA recommends consideration of incident
data reported to PHMSA and data collected through the Methane Challenge as possible
alternative data sources for development of more representative activity data for mishaps/dig-
ins.
F. New Methodology Obviates Need to Subtract Gas STAR Reductions
In the past, EPA used emission factors based on data collected in 1992 in an EPA-Gas
Research Institute (GRI) Study. The agency recognized that practices and materials changed over
time, as companies modernized their systems and implemented best practices shared through
the Gas STAR program. EPA thus considered the 1992 vintage emission factors to reflect the
potential emissions sources could emit in the absence of modernization, and the agency
attempted to reflect the effect of continuing modernization by subtracting voluntary reductions
reported under the Gas STAR program to calculate net emissions from the sector.
AGA agrees that the new methodology - using new data, including that collected in 2013
from the March 2015 Lamb et al. study and Subpart W reporting - results in a more accurate
representation of current operations practices and emissions levels. We agree this obviates the
need to continue subtracting voluntary emission reductions achieved through the Gas STAR
program to estimate current emission levels for M&R stations, pipeline leaks, and customer
meters, since the new data already reflects current practices and emission levels.
II. AGA Also Generally Supports the Use of New Data and Methodology for Estimating
Methane Emissions from Natural Gas Transmission and Storage
EPA's revisions to the GHGI for the natural gas transmission and storage segment
primarily rely upon Zimmerle et al.7 and an interpolation of existing and new data between the
early and current inventory years. Although AGA believes that these approaches can serve as an
interim step in EPA's GHGI, AGA encourages EPA to recognize the significantly larger data set
6 Incidents on natural gas distribution systems are defined as an event that involves a resale
of gas from a pipeline that results in a death or significant personal injury, property damage of
$50,000 or more, or 3 million cubic feet of lost gas. 49 C.F.R. § 191.3.
7 Zimmerle, D.J.; Williams L.L.; Vaughn, T.L.; Quinn, C.; Subramanian, R.; Duggan, G.P.;
Willson, B.; Opsomer, J.D.; Marchese, A.J.; Martinez D.M.; Robinson, A.L. Methane Emissions
from the Natural Gas Transmission and Storage System in the United States. Environmental
Science and Technology, 49, 9374-9383. 2015
6
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available from measurements conducted at transmission and storage compressor stations
subject to Subpart W of the GHG Reporting Program. For example, the Subpart W data could be
evaluated to assess the relative population of wet seal versus dry seal centrifugal compressors.
AGA also believes that Subpart W data can provide a more accurate representation of activity
data and device type for pneumatic controllers. AGA encourages EPA to commit to additional
updates to the 2017 GHGI report that would integrate Subpart W data.
AGA appreciates the opportunity to comment. If you have any questions, please contact
Pamela Lacey at (202) 824-7340, Christine Wyman at (202) 824-5120, or Richard Meyer at (202)
824-7120.
Respectfully Submitted,
Pamela Lacey
Chief Regulatory Counsel
American Gas Association
400 N. Capitol St., NW
Washington, DC 20001
7
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Karin Ritter
Manager
Regulatory and Scientific Affairs
1220 L Street, NW Washington, DC 20005-4070 USA
Telephone: 202-682-8472
Fax: 202-682-8031
Email: ritterk@api.org
www.api.org
March 23, 2016
Mr. Leif Hockstad and Ms. Melissa Weitz
Climate Change Division, Office of Atmospheric Programs (MC-6207S)
U.S. Environmental Protection Agency - Office of Air and Radiation
1200 Pennsylvania Ave., NW
Washington, DC 20460
hockstad.leif@epa.gov and weitz.melissa@epa.gov
Attention: Docket ID No. EPA-HQ-OAR-16-000-4157
Re: Public Review of EPA's Draft Inventory of U.S. Greenhouse Gas Emissions and
Sinks: 1990-2014
Dear Leif and Melissa,
The American Petroleum Institute (API) appreciates the opportunity to provide comment on the
Public Review Draft Inventory of U.S. Greenhouse Gas (GHG) Emissions and Sinks: 1990-2014
announced in the Federal Register (FR) Vol. 81, No. 34, 8713 on Monday, February 22, 2016.
In lieu of a formal expert review process of the Preliminary Draft of the national GHG Inventory
(GHGI), as was customarily done in past years, EPA released several memos between December
2015 and February 20161 outlining revisions under considerations for estimating GHG emissions
from the Distribution, Transmission & Storage, Gathering & Boosting and Petroleum & Natural
Gas production segments of the Petroleum and Natural Gas Systems sector. API's comments on
those memos are provided herein as an attachment starting on page 6.
API represents over 625 oil and natural gas companies, leaders of a technology-driven industry
that supplies most of America's energy, supports more than 9.8 million jobs and 8 percent of the
U.S. economy, and, since 2000, has invested nearly $2 trillion in U.S. capital projects to advance
all forms of energy, including alternatives.
API has developed an extensive record of engagement with GHG emissions estimation and
reporting and continues to compile and analyze emissions data for petroleum and natural gas
operations. API has provided comments and recommendations to the U.S. EPA on the draft
Natural Gas Systems and Petroleum Systems sections of the national inventory since 2002,
flPI
1 http://www3.epa.gov/climatechange/ghgemissions/usinventorvreport/natural-gas-SYStems.html
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API Public Review Comments on EPA's DRAFT U.S. GHG Inventory: 1990-2014
including at the recent stakeholder workshop in November 2015 addressing GHG data for
Petroleum and Natural Gas Systems.
While the last set of memos on Production and Gathering and Boosting were still under expert
review, EPA released the Public Review Draft of the GHGI, already incorporating the revisions
that were dubbed "under consideration" in EPA's memos, without providing industry the
opportunity to comment on these proposed revisions, or for EPA to incorporate industry's expert
comments, prior to releasing the Draft GHGI for public review. In addition, the released Public
Review Draft does not provide specifics on the revised methodological changes for specific
sources and lacks the normal methodological details usually provided in the applicable Annexes.
Based on information provided in the memo Inventory of U.S. Greenhouse Gas Emissions and
Sinks: Revisions under Consideration for Natural Gas and Petroleum Production Emissions
(February 2016, Table 4), API attempted to recreate the production sector emission data reported
in Table 3-43 of EPA's Public Review Draft Inventory of U.S. Greenhouse Gas Emissions and
Sinks. The following table summarizes API's comparison of 2013 source level emissions
published in the April 2015 GHGI and the 2013 emission estimates from Table 3-43 of the recent
Public Review version of the GHGI.
Table 1. Comparison of 2013 Emission Estimates for Natural Gas Production
(including Gathering and Boosting)
2013 Net ( ll4
Emissions.
M M 1 ( 02e
2013 Net C" 114 Emissions.
M M 1 ( 02e
Pneumatic Controllers
13.5
26.0
Major Equipment Fugitives
8.6
9.7
Chemical Injection Pumps
1.5
3.7
Dehydrator Pumps/Vents
12.2
12.2
Compressor Starts
0.1
0.1
Large Gathering Compressor
Station Fugitives
0.4
43.3
Gathering Pipeline Leaks
4.2
Gas Engines
2.7
2.7
Condensate Tanks
7.8
7.8
Blowdowns
0.2
0.2
Upsets
0.1
0.1
Wellpad Fugitives/Venting
11.5
11.5
Offshore
3.8
3.8
Other Voluntary Reductions
-16.5
-16.0
Regulatory Reductions
-3.0
TOTAL
47.0
105.1
As is shown in the table above, total emissions for Natural Gas Production operations are
estimated to increase from 47 million metric tonnes (MMT) C02e as published in last year's
Docket ID No. EPA-HQ-OAR-16-000-4157
Page 2 of 87
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API Public Review Comments on EPA's DRAFT U.S. GHG Inventory: 1990-2014
2
GHGI, to 105 MMT C02e, which indicates more than a doubling of emissions . It appears that
EPA intends to include approximately 16 MMT C02e in emission reductions from voluntary
activities, although it is unclear to which sources these emission reductions will apply. It is also
unclear if fugitive emissions from wells are included under "Wellpad Fugitive Venting" or under
"Major Equipment Venting". API is concerned that these additional details are not available for
review and comment ahead of the final GHGI that is scheduled to be published in April 2016.
Due to the limited information provided in the draft Public Review version of the GHGI, API's
comments are limited to the following:
• For Petroleum and Natural Gas Systems, EPA provides "computed" emission values for
calendar year 2013, using the proposed, revised methodologies from EPA's sector
specific memos. Emissions for the years 1990-2012 are not back-cast or updated, and
EPA does state in the Public Review draft that the 2013 emissions estimates are
preliminary and subject to revision in the final GHGI. As a result, it looks like a large
step-change in estimated emissions for 2013 resulting from EPA's methodological
changes. The new methodology used by EPA, especially for the Petroleum and Natural
Gas production segments of the industry, does not reflect a "real" increase in emissions
but rather improved availability of some industry activity data as reported to the GHGRP.
The improved industry activity information provided by larger facilities, which are above
the GHGRP reporting threshold, is being used by EPA for scaling up to the nationwide
inventory without recognizing that the smaller (non-reporting) facilities likely have very
different activity characteristics and thus should not be included in the scaled up activity
factors proposed by EPA..
• The estimated Petroleum Systems emissions for 2013 indicate a 151% increase as
compared to what was previously reported for 2013 and is driven by an assumed increase
of 157% in Petroleum Production emissions. This assumed emissions increase from
Petroleum Production is due to EPA's scaling up the count of pneumatic controllers and
process fugitive components as reported through the GHGRP. This does not reflect the
fact that smaller production sites, which are not subject to GHGRP reporting, have much
smaller component counts per wellhead and many of them use little - if any - pneumatic
controllers, particularly in petroleum systems . Most importantly, EPA did not revise the
emission factors used for characterizing overall emissions from pneumatic controllers and
fugitive sources, despite repeated comments from industry that these factors are outdated
and overestimate emissions from properly functioning pneumatic controllers and typical
process components.
• For Natural Gas Systems, EPA estimates that 2013 emissions would increase 23% after
applying EPA's new estimation methodology. The data for individual segments such as
production, processing, transmission & storage and distribution show a respective
emissions change of 136%), 0%, -47% and -64%. Again, the change of 136%) in the
production segment is due to extrapolation of pneumatic controllers and process fugitive
component counts from the GHGRP to a nationwide basis, as well as using the same
2 Note: Table 3-43 of the draft Public Review version shows natural gas production emissions increasing to 106
MMT C02e
Docket ID No. EPA-HQ-OAR-16-000-4157
Page 3 of 87
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API Public Review Comments on EPA's DRAFT U.S. GHG Inventory: 1990-2014
overestimation of component counts for smaller production sites that do not report to the
GHGRP. The change in Natural Gas Production also includes a new and very large
estimate for Gathering and Boosting compressor stations based on limited, short-duration,
downwind measurements. API does not believe the data used to derive emissions for
Gathering and Boosting stations are sufficient for determining national emissions from
these operations due to the large uncertainty associated with the measurement method on
which they are based.
• For some activity data, larger equipment counts would be expected for the types of sites
that are more likely to be reported in the GHGRP. However, applying data from GHGRP
sites to the entire population of U.S. wells is inappropriate. For example, emergency
shut-down devices (ESDs) may be counted as pneumatic controllers in the GHGRP but
have very different emission characteristics (infrequently emitting) than the types of
pneumatic controllers that are assumed in the GHGI.
• EPA's approach appears inconsistent. First, EPA notes that Subpart W GHGRP data
covers 32% of the active wellheads for 2013 and proposes to use this percentage to
"scale" some emission sources to a national level. Simultaneously EPA states that the
GHGRP Subpart W data covers the majority of national oil and natural gas production
sources. Separately, EPA has also determined that Subpart W covers about 85% of the
GHG emissions from the onshore oil and natural gas production sector as indicated in the
"3
Subpart W Technical Support Document . .
• Clearly, if Subpart W covers 85% of the GHG emissions from theoil and natural gas
production sector, then there is no basis for changing the GHGI in a manner that
estimates 90% higher overall GHG emissions (based on the recalculated 2013 inventory).
This discrepancy of GHGRP Subpart W emissions coverage must be fully explored and
explained prior to making the proposed changes to derive GHG emissions for this sector
in the GHGI. Given that the GHGRP Subpart W reported GHG emissions are
substantially less than in the estimated GHGI emissions for 2013, the resultant scaling of
the GHGRP data to national GHG emissions should be less than the 15% of emissions
EPA previously determined are not covered by GHGRP Subpart W.
• API agrees that updated GHGI activity factors and emissions data are warranted and as
such recommends that EPA form a multi-stakeholder working group comprised of
industry, governmental, and environmental organizations active in GHG emissions
measurements and estimation to evaluate recently published data that may be considered
for updating the national GHGI prior to rushing to implement the proposed revisions that
are based on invalid extrapolation of GHGRP data from large facilities to non-reporting
smaller installations.
• API recognizes that emerging data from recent field studies have raised concerns about
measurements uncertainty, and recognizes the need for a thorough discussion of means of
3 Table 5, Threshold Analysis for Petroleum and Natural Gas industry Segment;
https://www.epa.gov/sites/production/files/2015-05/documents/subpart-w tsd.pdf
Docket ID No. EPA-HQ-OAR-16-000-4157
Page 4 of 87
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API Public Review Comments on EPA's DRAFT U.S. GHG Inventory: 1990-2014
improving the methodology to ensure collection of robust measurement data. API
proposes that a working group - as discussed above - be convened following the
completion of the 2014 GHGI (April 2016) to provide a structured framework for
consultation and review of GHGI updates. An early start (April 2016) and frequent
meetings (every 1-2 months) would provide sufficient time to review and consolidate
information in an informed process for updating the 2015 GHGI (that would be published
in April 2017) and beyond.
API appreciates the opportunity to provide comments during the Public Review phase of the
2014 U.S. national GHG Inventory. API encourages EPA to continue collaborative discussions
with industry and is available to work with EPA to make the best use of the information
available through the GHGRP and recent measurement programs to improve the national
emission inventory.
Sincerely,
Karin Ritter
cc:
Paul Gunning, U.S. EPA, Climate Change Division, Washington DC
Bill Irving, U.S. EPA, Climate Change Division, Washington DC
Mark De Figueiredo, Climate Change Division, Washington DC
Attachment: API comments on EPA's Memos on the updates being considered for the
Transmission and Storage sector, the Production sector and the Gathering and Boosting sector in
the GHG Inventory.
Docket ID No. EPA-HQ-OAR-16-000-4157
Page 5 of 87
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APPENDIX: API comments on EPA's Memos on the updates being considered for
the Transmission and Storage, the Production and the Gathering and
Boosting segments of the Petroleum and Natural Gas Systems Sector
in the GHG Inventory
6 of 87
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API Comments on Updates under Consideration for Natural Gas Transmission and Storage Emissions
Karin Ritter
Manager
Regulatory and Scientific Affairs
1220 L Street, NW Washington, DC 20005-4070 USA
Telephone: 202-682-8472
Fax: 202-682-8031
Email: ritterkffiapi.org
www.api.org
February 5, 2016
Ms. Melissa Weitz
Climate Change Division, Office of Atmospheric Programs
U.S. Environmental Protection Agency - Office of Air and Radiation
1200 Pennsylvania Ave., NW
Washington, DC 20460
weitz.melissa@epa.gov and ghginventory.gov
Re: Updates under Consideration for Natural Gas Transmission and Storage Segment
Emissions in the 1990-2014 GHG Inventory
Dear Melissa,
The American Petroleum Institute (API) appreciates the opportunity to provide comments on
proposed updates to the 1990-2014 U.S. Greenhouse Gas (GHG) inventory for the Natural Gas
Transmission and Storage segment.
API continues to compile and analyze emissions data for petroleum and natural gas operations and
is open to working with EPA on utilizing data provided through EPA's mandatory GHG reporting
program (GHGRP). API has provided comments and recommendations to the U.S. EPA on the
draft Natural Gas Systems and Petroleum Systems sections of the national inventory since 2002,
including at the recent stakeholder workshop in November 2015 regarding GHG data for Petroleum
and Natural Gas Systems.
For this current review, API provides general comments and also addresses several specific
questions raised in EPA's transmission and storage memo. Our review, however, is limited due to
the short response time, overlapping comment periods for other proposed changes to the GHGRP,
and the approaching March deadline for reporting 2015 GHGRP data.
General Comments
EPA's proposed updates for compressor station components rely primarily on two studies published
12
by Colorado State University in 2015 . Substantial new data are available from measurements at
1 Subramanian R.; Williams, L.L.; Vaughn, T.L.; Zimmerle, D.; Roscioli, J.R.; Herndon S.C.; Yacovitch, T.I.;
Floerchinger, C.; Tkacik, D.S.; Mitchell, A.L.; Sullivan, M.R.; Dallmann, T.R; Robinson A.L. Methane Emissions
from Natural Gas Compressor Stations in the Transmission and Storage sector: Measurements and Comparisons with
the EPA Greenhouse Gas Reporting Program Protocol. Enviromnental Science and Technology, 49, 3252-3261. 2015.
IlPI
7 of 87
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API Comments on Updates under Consideration for Natural Gas Transmission and Storage Emissions
transmission and storage compressor stations that report through Subpart W. API agrees that
updated GHGI emissions data are warranted and as such recommends that EPA form a multi-
stakeholder working group comprised of industry, governmental, and environmental organizations
active in GHG emissions measurements and estimates to evaluate recently published data that may
be used for updating the national GHG inventory. API proposes that such a working group be
convened following the completion of the 2014 GHGI to provide a structured framework for
consultation and review of GHGI updates. An early start (April 2016) and frequent meetings (every
1-2 months) would provide sufficient time to review and consolidate information in an informed
process for updating the 2015 GHGI and beyond.
API reiterates that the EPA should carefully analyze and screen GHGRP reported data in order to
improve the validity of data used in the national GHGI. Obvious data errors and/or outliers should
be assessed, corrected or excluded to prevent disproportionately impacting the derivation of
emission factors (EFs) or extrapolation of information for the national GHGI.
Responses to EPA Questions
Transmission and Storage Station Fugitive Emissions
*/ (Question #1 from. memo) As EPA considers options for applying EFs for this
source, the EPA seeks stakeholder feedback on the timing of changes in transmission and
storage stations non-compressor fugitive sources that may result in different emissions in
recent years from those in the GR1/EPA study. The EPA could use GRI/EPA factors for
earlier years in the time series, and Zimmerle factors for more recent years. Alternatively,
the EPA could apply the Zimmerle EF to all years of the GHGI time series. The EPA seeks
stakeholder feedback on these options.
API Comment: GRI/EPA emission factors should be used for initial estimates in the time series
and EPA should use updated emission factors for the current estimate.
*/ (Question #3 from memo) The EPA seeks stakeholder feedback on how to
incorporate information on super emitters into estimates for transmission and storage
stations. For example, the Zimmerle study estimated a fraction of the population that may
be super emitters at a given time, and estimated super emitter emissions from these sources
(incremental to those estimated for the non-super emitter population). The EPA also seeks
stakeholder feedback on which GHGI sources are more likely than others to act as super
emitters and whether and how to apply a super emitter factor or other methodology to those
sources.
API Comment: Recent measurement studies have shown skewed "long tail" distributions for
source level measurements, where a few emission sources may contribute a disproportionately
high fraction of emissions. As the Zimmerle study points out, large data sets are needed to
accurately characterize the "long tail" distributions. Although the Subramanian study
contributes new measurement data for 45 compressor and storage stations, it represents just a
2 Zimmerle, D.J.; Williams L.L.; Vaughn, T.L.; Quinn, C.; Subramanian, R.; Duggan, G.P.; Willson, B.; Opsomer, J.D.;
Marchese, A. J.; Martinez D.M.; Robinson, A.L. Methane Emissions from the Natural Gas Transmission and Storage
System in the United States. Environmental Science and Technology, 49, 9374-9383. 2015.
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subset of all measurements conducted as part of Subpart W reporting, which provides a
substantially larger data set of emissions that are characteristic of the entire distribution.
As the Zimmerle study indicates, the identified "super emitters" fraction of the population is
dynamic and may vary each time a measurement is taken. Therefore the approach being
proposed by EPA in the question - which implies that EPA is considering to separately adjust
the national inventory for super-emitters - is not appropriate for extrapolation of the data to the
national GHGI. This approach would be incorrect and would essentially double count the effect
of super-emitters since they are already accounted for in the Zimmerle emission factors and in
the Subpart W reported data.
The Pipeline Research Council International (PRCI) is conducting a research project to compile
and analyze Subpart W data. The dataset includes 2011 through 2013 measurement data
collected from members who have also provided supplemental data on equipment, operations,
and measurement methods. Although a subset of data reported to EPA, it represents well over
half of the reporting facilities. These measurement data should be assessed and can be used to
calculate compressor station emission factors and evaluate the frequency and size of the larger
leaks from key sources - compressor seals, compressor valves and storage tank dump valves.
The report is expected to be available in the second quarter of 2016.
API advises that an alternative approach would be to develop new average emission factors that
integrate data from both the recent measurement study results and Subpart W measurements.
Such average emission factors should incorporate the range of emissions observed in current
operations without artificially superimposing on them a "super emitter" adjustment which is
highly uncertain. The emission factors should be updated periodically based on additional
Subpart W data that become available with each future reporting year and potentially new,
relevant and independent measurement programs.
*/ (Question #4 from. EPA's memo) The EPA seeks stakeholder feedback on how to
incorporate Subpart W data into the GHGI methodology, such that the transmission station
and storage station activity data (AD) and/or EFs would be updated annually to reflect
ongoing trends in the industry. For example, the EPA could consider combining the
Zimmerle et ah data and Subpart W data in some way.
API Comment: A significant amount of information is reported to EPA through Subpart W.
EPA now has four years of fugitive measurement data for specific emission sources and activity
data regarding the distribution of centrifugal versus reciprocating compressors as well as the
fraction of wet seal versus dry seal centrifugal compressors. API encourages EPA to make use
of this information and integrate Subpart W based emission factors as an update to the GHGI.
Activity data and emission factors should be updated periodically based on additional Subpart
W data that become available with each future reporting year and potentially new, relevant, and
independent measurement programs.
EPA's memo on revisions under consideration for transmission and storage emissions indicates
that EPA intends to use the emission factors for compressor fugitive emissions, non-compressor
fugitive emissions, and pneumatic controllers from the Zimmerle study. API supports the use of
this recent measurement data, which accounts for the presence and random nature of super-
emitters. However, API strongly encourages EPA to also make use of the substantial amount of
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measurement data available from Subpart W. The PRCI report is an example of additional
information that should be considered by EPA and a multi-stakeholder workgroup.
*/ (Question #5 from. EPA's memo) In in a California storage field began
leaking methane at an estimated rate of 50 IV clay. The EPA is considering how to
include this emission source in its 2017 GHG1 (with estimates from 1990-2015). For
example, the EPA could review and potentially incorporate estimates of the leak developed
by the California Air Resources Boar
API Comment: The storage field leak in California is a one-off failure event. If EPA believes
the emissions from this event warrant inclusion in the 2015 national GHG emissions for Natural
Gas Systems, then API contends that the emissions should be estimated for this single event
with an annotation in the inventory which references the event and the emission estimation
method. The emissions from this singular event should not be back-cast to prior years, nor
should the emissions be projected to future years.
Reciprocating and Centrifugal Compressors
For Storage, EPA is not considering changes to the method used to count compressors. EPA
plans to report a combined number and will not differentiate between reciprocating and
centrifugal compressors to be consistent with planned updates to the emission factor. EPA's
memo notes that the Zimmerle study found most storage stations employ reciprocating
compressors. However, this is inconsistent with the Subramanian study which observed that the
compressor type can impact emissions and centrifugal compressors have become much more
common at transmission and storage stations. For compressor emission factors applied to
Storage, API recommends utilizing storage station compressor measurement data reported for
Subpart W to develop emission factors separately for reciprocating and centrifugal compressors,
and also report compressor emissions separately by compressor type. This provides greater
transparency and enables trends in compressor counts and emissions to be tracked over time.
Pneumatic Controllers
*/ (Question #11 from EPA's memo) The EPA seeks stakeholder feedback on use of the
Zimmerle et ah estimates of pneumatic controller counts per transmission or storage station
to develop natic ross the time series. For example, the EPA could use GRI/EPA
pneumatic controller counts for earlier years in the time series and Zimmerle et al. counts for
more recent years. Alternatively, the EPA could apply tli rterle et al. pneumatic
controller counts to all years of th I time series. T1 • stakeholder feedback
on these options.
API Comment: Subpart W provides a comprehensive, annual data set for determining the
number of pneumatic controllers by station and the distribution by type of controller. API
recommends using the Subpart W activity data for recent years in the GHGI, the GRI/EPA data
for early years in the time series, and interpolating between the two for intermediate inventory
years rather than using activity data that is based on the Zimmerle or Subramanian study.
•S (Question #13 from EPA's memo) The EPA seeks stakeholder feedback on approaches to
stratify pneumatic controller estimates into specific bleed rate categories (e.g., basing AD on
the number of low-bleed, intermittent bleed, and high bleed devices and applying an EF
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specific to each type). For example, the EPA could use the Subpart W data on the number of
pneumatic controllers of specific controller types per station, and their associated specific
EFs. In addition, the EPA seeks comment on use of GHGRP data to represent national
transmission and storage station pneumatic controller activity and emissions.
API Comment: API recognizes that the stratification of pneumatic controllers into specific bleed
rate categories can be challenging. API has recently engaged in technical assessments of
pneumatic controllers' categories and their leakage vs. engineered venting characteristics3. Over
the past year, through API's standard development process including a stakeholders group, API
has been working to establish a process for categorizing properly functioning pneumatic
controllers and to address fugitive emissions from mal-functioning controllers. API hopes that
this standard, when complete, will go a long way towards addressing the issue raised by EPA
above.
Hi-Flow Sampler Measurements
*/ (Question #14 from EPA's memo) Much of the available measurement data on transmission
and storage segment emissions were developed using Hi-Flow Samplers. A recent study,
Howard 2015, highlights potential malfunctions in certain Hi-Flow instruments under
certain conditions that can lead to underestimates. The EPA is seeking stakeholder feedback
on the impacts of the Hi-Flow sampler issue on the results of studies highlighted here and
whether are there methods for recalculating some of the data points to correct for it.
API Comment: The Subramanian study showed good agreement between the concurrent site
level emission source measurements and down-wind tracer flux measurements. The study
report indicates that the dominant uncertainty in the study onsite estimate is due to
uncharacterized emission sources (undetected or identified as inaccessible) rather than
"parametric uncertainty associated with individual measurements or instruments." Based on
this observation by the researcher/author, it might be concluded that the issues identified by
Howard did not appear to have occurred in the measurements conducted during the
Subramanian study.
The June 2015 article by Howard (Energy Science and Engineering 2015; 3(5):443-455, doi:
10.1002/ese3.81) focusses on measurements conducted in the production sector ("UT Phase 1"
Study) and has drawn attention to a sensor response issue that may be averted to a large extent
with a firmware update, careful calibration, and repeated quality control checks during the
measurement process. Allen responded to Howard's article, providing information that extra
steps were undertaken during to ensure the validity of the measurements from the UT Phase 1
study.4
The Hi-Flow instrument is one of a very few existing devices for cost-effectively quantifying
natural gas emissions from fugitive and venting at the emission source, and it is an approved
measurement device under Subpart W. As with any measurement device, uncertainties in
measured data exist and the experience gained by additional field studies is enabling the
3 [Simpson, 2014] Pneumatic Controllers in Upstream Oil and Gas. Oil & Gas Facilities Volume 3 Number 5, October,
2014
4 Allen, D.T., Sullivan, D.W., and Harrison, M. Response to Comment on "Methane Emissions from Process Equipment
at Natural Gas Production Sites in the United States: Pneumatic Controllers", Environmental Science & Technology,
49, 3983-3984, doi: 10.1021/acs.est.5b00941 (2015).
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research community to alert instrument manufacturers and industry to operation and calibration
problems that ought to be fixed.
API's comments above are based on our long term engagement in reviewing and providing
information for the U.S. GHG Inventory. It includes observations and recommendations for careful
QA/QC of data extracted from the mandatory GHGRP to improve the validity and
representativeness of data used for the U.S. GHG Inventory. We reiterate our recommendation for
EPA to form a multi-stakeholder workgroup to discuss updating the national GHGI to incorporate
information from recent measurement study results and Subpart W data.
API appreciates the opportunity to provide comments on the proposed revisions to the U.S. national
GHG Inventory and EPA's willingness to work with industry to improve the data used for the
national inventory. API encourages EPA to continue these collaborative discussions and is
available to work with EPA to make best use of the information available under the GHGRP to
improve the national emission inventory. We look forward to continuing our collaborative work in
the GHGI development process.
Sincerely,
Karin Ritter
cc: Alexis McKittrick, Climate Change Division
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Karin Ritter
Manager
Regulatory and Scientific Affairs
1220 L Street, NW
Washington, DC 20005-4070
USA
Telephone
202-682-8340
202-682-8270
March 2, 2016
Fax
Email
ritterk@api.org
www.api.org
Ms. Melissa Weitz
Climate Change Division, Office of Atmospheric Programs
U.S. Environmental Protection Agency - Office of Air and Radiation
1200 Pennsylvania Ave., NW
Washington, DC 20460
weitz.melissa@epa.gov and ghginventory.gov
Re: Updates under Consideration for Natural Gas and Petroleum Production Sector Emissions
and Gathering and Boosting Emission in the 1990-2014 GHG Inventory
Dear Melissa,
The American Petroleum Institute (API) appreciates the opportunity to provide comments on
proposed updates to the 1990-2014 U.S. Greenhouse Gas Inventory (GHGI) for the Natural Gas and
Petroleum Production Sectors, and for Gathering and Boosting emissions.
API continues to compile and analyze emissions data for petroleum and natural gas operations and
appreciates the opportunity to work with EPA on utilizing data provided through EPA's mandatory
greenhouse gas reporting program (GHGRP). API has provided comments and recommendations to
the U.S. EPA on the draft Natural Gas Systems and Petroleum Systems sections of the national
inventory since 2002, including at the recent stakeholder workshop in November 2015 regarding
greenhouse gas (GHG) data for Petroleum and Natural Gas Systems.
For this current review, API provides general comments and also addresses several specific
questions raised in the two EPA memos:
• Inventory of U.S. Greenhouse Gas Emissions and Sinks: Revisions under Consideration for
Natural Gas and Petroleum Production Emissions, February 2016; and
• Inventory of U.S. Greenhouse Gas Emissions and Sinks: Revisions under Consideration for
Gathering and Boosting Emissions, February 2016.
Our review, however, is as comprehensive as is possible within the short response time, overlapping
comment periods for other proposed changes to the GHGRP and the approaching March deadline
for reporting 2015 GHGRP data. On top of our response to these memos, API intends to also
comment on the "public review" version of the 1990-2014 preliminary Draft Inventory of U.S.
Greenhouse Gas Emissions and Sinks that was released on February 22, 2016.
General Comments
• EPA's current methodological updates for natural gas and petroleum production
operations rely primarily on Subpart W reported activity data with a focus on fugitive
emission sources and pneumatic devices. Of note is that the production memo does not
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address new measurement studies or updates that were previously outlined in two memos
EPA issued in April 2015.l'2
• EPA's logic, presented in these memos appears inconsistent. First, EPA notes that Subpart
W GHGRP data covers 32% of the active wellheads for 2013 and proposes to use this
percentage to "scale" some emission sources to a national level. Simultaneously EPA states
that the GHGRP Subpart W data covers the majority of national oil and natural gas
production sources. Separately, EPA has also determined that Subpart W covers about 85%
of the GHG emissions from the onshore oil and natural gas production sector - see the
Subpart W Technical Support Document (Table 5, Threshold Analysis for Petroleum and
Natural Gas industry Segment; https://www.epa.gov/sites/production/files/2015-
05/documents/subpart-w tsd.pdf). Clearly, if Subpart W covers 85% of the GHG emissions
from this sector, then there is no basis for changing the GHGI in a manner that estimates
90% higher overall GHG emissions (based on the recalculated 2013 inventory). This
discrepancy in GHGRP Subpart W emissions coverage must be fully explored and explained
prior to making the proposed changes to derive GHG emissions in the GHGI for this sector.
Given that the GHGRP Subpart W reported GHG emissions are substantially less than in the
GHGI for 2013, the scaling to national GHG emissions for the GHGI should also be less
than the 15% of emissions EPA previously determined are not covered by GHGRP Subpart
W.
• EPA's methodological updates for Gathering and Boosting relies solely on data from the
Mitchell et al.3 and Marchese et al.4 studies. However, the study focused on downwind, site-
level ambient concentration measurements that are not appropriate nor designed to
characterize activity data or emission factors for the Gathering and Boosting sector sources.
• API suggests that EPA review the work of Eben Thoma et al. with the EPA's Office of
Research and Development (ORD) pertaining to off-site ambient concentration type studies,
and the criteria necessary to obtain useful information from such a study as well as the
limitations to the accuracy and usefulness of the information developed.5 The conclusions
are similar to the conclusions from an Australian government commissioned study
conducted by CSIRO.6 (For EPA's convenience, copies of both papers are provided in the
appendix to these comments, beginning on page 20)
1 "Inventory of U.S. Greenhouse Gas Emissions and Sinks: Potential Revisions to Liquids Unloading Emissions
Estimate" April 2015.
2 "Inventory of U.S. Greenhouse Gas Emissions and Sinks: Potential Revisions to Pneumatic Controller Emissions
Estimate (Production Segment)" April 2015.
3 Mitchell, A. L.; Tkacik, D. S.; Roscioli, J. R.; Herndon, S. C.; Yacovitch, T. I.; Martinez, D. M.; Vaughn, T. L.;
Williams, L.L.; Sullivan, M.R.; Floerchinger, C.; Omara, M.; Subramanian, R.; Zimmerle, D.; Marchese, A.J.;
Robinson, A.L. Measurements of Methane Emissions from Natural Gas Gathering Facilities and Processing Plants:
Measurement Results. Environmental Science & Technology, 49, 3219-3227. 2015.
4 Marchese, A. J.; Vaughn, T. L.; Zimmerle, D.J.; Martinez, D.M.; Williams, L. L.; Robinson, A. L.; Mitchell, A. L.;
Subramanian, R.; Tkacik, D. S.; Roscioli, J. R.; Herndon, S. C. Methane Emissions from United States Natural Gas
Gathering and Processing. Environmental Science & Technology, 49, 10718-10727. 2015.
5 Halley L. Brantley,f,# Eben D. Thoma,*,f William C. Squicr.'i" Birnur B. Guven,{ and David Lyon§; Assessment of
Methane Emissions from Oil and Gas Production Pads using Mobile Measurements
6 Day, S., Dell'Amico, Fry, R., Javanmard Tousi, H., (2014). Field Measurements of Fugitive Emissions from
Equipment and Well Casings in Australian Coal Seam Gas Production Facilities. CSIRO, Australia
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• API is concerned about EPA's intent to utilize the Mitchell et al. and Marchese et al. studies
to develop a station-level emission factor which would significantly limit any evaluation of
source-level emission trends over time. The small population size of the underlying
Mitchell et al. study, the lack of emission source detail, and the numerous compounding
assumptions made in the Marchese et al. study to "scale" the modeled results, may not
provide sufficient certainty to use the study results for GHGI revisions to the Gathering and
Boosting sector.
• Conversely, significant activity data will be available through the GHGRP in coming years.
API urges EPA to delay significant revisions to the GHGI related to Gathering and Boosting
until the GHGRP data are available. At that time, API recommends that EPA provide a
separate accounting of activity data and emissions for Gathering and Boosting sources as a
separate sector or as a subset of the Production sector.
• As stated previously in our comments on EPA's Transmission/Storage memo, API agrees
that updated GHGI emissions data are warranted and as such recommends that EPA form a
multi-stakeholder working group comprised of industry, governmental, and environmental
organizations active in GHG emissions measurements and estimation to evaluate recently
published data that may be used for updating the national GHG inventory. API proposes
that such a working group be convened following the completion of the 2014 GHGI (April)
to provide a structured framework for consultation and review of GHGI updates. An early
start (April 2016) and frequent meetings (every 1-2 months) would provide sufficient time to
review and consolidate information in an informed process for updating the 2015 GHGI and
beyond.
• Additionally, API reiterates that the EPA should carefully analyze and screen GHGRP
reported data in order to improve the validity of data used in the national GHGI. Obvious
data errors and/or outliers should be assessed, corrected or excluded to prevent
disproportionately impacting the derivation of emission factors (EFs) or extrapolation of
information for the national GHGI.
Responses to EPA Questions for Revisions under Consideration for the Production
Sector
General Use of Subpart W Data
*/ (Question #1 from. EPA's Production memo) The EPA seeks feedback on how to take into
account the reporting threshold when using Subpart W data, and the appropriateness of
using Subpart W-based AFs for the national population of major equipment and pneumatic
controllers.
a. Are other data sources available that would help the EPA determine characteristics
of the non-reporting population9
b. Are other approaches available for scaling up this data for use in the GHGI9
API Comment: Although Subpart W does not capture all U.S. production operations, it is the
most significant source of activity data available. We would expect that production operations
not reporting through Subpart W are likely much smaller facilities, such as those associated with
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stripper wells. It is reasonable to expect a difference in major equipment and pneumatic
controller counts in these smaller facilities compared to facilities that meet the Subpart W
reporting threshold. However, sufficient information for major equipment and pneumatic
controller counts, for emission estimates, is lacking for the facilities that fall below the reporting
threshold. Therefore, although API supports EPA's use of information available through the
GHGRP to update equipment counts in the national inventory, a note of caution is advised when
using the GHGRP pneumatic device count to characterize stripper wells or other smaller
production well types, which tend to typically have fewer, if any, pneumatic controllers for their
operations. As a result, the use of activity factors (AFs) based solely on average reporting data
in the GHGRP will likely over-estimate equipment counts from non-GHGRP wells.
In addition, estimates of the coverage of the GHGRP would be expected to be different in each
production basin depending on the characteristics of ownership (many small operators vs. larger
companies), historical development trends, and type of production in the region. For example, a
recent analysis of available data in the Barnett Shale7 in 2013 found that the oil and gas well
count in the GHGRP (15,900 wells) only represented 46% of the well count (34,800) derived
from GHGI methods. In that same study, the author estimated 29,900 oil and gas wells from
other available data. This discrepancy highlights the need for more transparency in GHGI well
count methods, as API has previously commented (see Question #7).
The correlation between GHGRP and GHGI well counts would be expected to be worse in other
o
production regions since much of the Barnett Shale development has occurred over the last 8
years for shale oil and gas production, which typically includes more on-site production
equipment and may be more likely to be reported under the GHGRP. In addition, some
operators have begun to move towards multi-well pads and shared production equipment for
multiple wells. Properly-scaling GHGRP and other activity factors to a national level is a
difficult technical challenge that will require substantial data analysis and a multi-stakeholder
group for proper implementation. Such a group should be convened in order to ensure that
future changes to the GHGI represent a true and robust national emissions estimate.
Furthermore, under the GHGRP, companies report devices that do not emit as typical pneumatic
controllers so the population of controllers in the GHGRP data is very different than the
population measured in the GRI/EPA study (conducted in 1992-1993 and published in 1996)
and it is erroneous to take the count of all such devices and scale them up to the national
inventory by using the wellhead count and the emission factors from the GRI/EPA study. For
example, emergency shutdown devices (ESD) are largely designed to emit only during a process
upset in order to shut-in production. Given the infrequency of this type of event, it would be
improper to characterize these controllers in the same way as the continuous vent pneumatics
that are assumed as part of current GHGI inventory factors.
7 Lyon, D.R., Zavala-Araiza, D., Alvarez, R A., Harriss, R., Palacios, V., Lan, X., Talbot, R., Lavoie, T., Shepson, T.,
Yacovitch, T. I., Herndon, S. C., Marchese, A.J., Zimmerle, D., Robinson, A. L. and Hamburg, S. P. Constructing a
spatially resolved methane emissions inventory for the Barnett Shale Region, Environmental Science and Technology,
49, 8147-8157, 2015
8 http://www.rrc.state.tx.us/oil-gas/maior-oil-gas-formations/barnett-shale-information/
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*/ (Question #2 from. EPA's Production memo) The EPA seeks feedback on other data sources
(e.g., Allen et al. 2013 and 2014, the Prasino Group 2013) that could be considered for the
development of emission factors for equipment leaks and/or pneumatic controllers.
a. Allen et al. 2014 study did not differentiate between controller types. Is it possible to
disaggregate the Allen emissions data in a way that would allow the EPA to calculate
emissions for various control types9
API Comments on Pneumatic Controllers: API commented previously9 that the emission
factors used for quantifying pneumatic controller emissions, especially the intermittent-bleed
controller factor, largely overestimates these emissions. Therefore, if EPA intends to update the
count of pneumatic controllers in the national inventory then EPA must also in parallel (or at the
same time) update the emission factors.
EPA's current memo outlining methodological changes under consideration for estimating
methane (CH4) emissions from production operations does not refer to, nor draw on information
EPA presented in its April 2015 memo on potential revisions to pneumatic controller emission
estimates . In the April 2015 memo, EPA summarized the following studies:
• Allen, D.T., Pacsi, A., Sullivan, D., Zavala-Araiza, D., Harrison, M., Keen, K., Fraser,
M., Hill, A.D., Sawyer, R.F., and Seinfeld, J.H. , Methane Emissions from Process
Equipment at Natural Gas Production Sites in the United States: Pneumatic Controllers,
Environmental Science & Technology. 10.1021/es5040156.
• Oklahoma Independent Petroleum Association (OIPA), Pneumatic Controller Emissions
from a Sample of 172 Production Facilities, November 2014.
• The Prasino Group, Final Report- For Determining Bleed Rates for Pneumatic Devices
in British Columbia, December 18, 2013.
• The Independent Petroleum Association of Mountain States (IPAMS) and Western
Regional Air Partnership (WRAP), 2006.
• Central States Air Resources Agencies (CenSARA), 2011.
In the April 2015 memo, EPA noted that the Allen et al. 2014 study (a.k.a UT/EDF Phase 2
Study) did not differentiate between controller types. However, supplemental information for
the Allen et al. 2014 study does provide classification of pneumatic controllers by Subpart W
types, for a subset of controllers and also determined classification based on gas flow time-
series measured during the study for all measured controllers (refer to Table S4-2 from the Allen
et al. 2014 study10). EPA could examine this information for updating emission factors for
intermittent-bleed controllers. However, it may be more difficult to analyze the data for high-
bleed versus low-bleed controllers since malfunctioning low-bleed controllers could exhibit
characteristics of high-bleed controllers. It is our understanding that the Allen et al. 2014 study
also collected meta-data for each controller that includes the manufacturer and model number of
each controller and that this information is available upon agreeing to confidentiality provisions.
9 Shires, T.; "Onshore Oil and Gas Production - Pneumatic Controllers", Presented at the Stakeholder Workshop on
EPA GHG Data on Petroleum and Natural Gas Systems, November 19, 2015.
10 Allen, D.T., Pacsi, A., Sullivan, D., Zavala-Araiza, D., Harrison, M., Keen, K., Fraser, M., Hill, A.D., Sawyer, R.F.,
and Seinfeld, J.H., Methane Emissions from Process Equipment at Natural Gas Production Sites in the United States:
Pneumatic Controllers Supporting Information, Environmental Science & Technology. 10.1021, Pneumatics
es5040156_si_001.pdf
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The manufacturer and model number would enable classification of each controller into the
appropriate EPA "bucket" on the basis of the controller design rather than the measured
emission profile.
Generally, the Allen et al. 2014 data showed lower emission rates per controller than the current
emission factors in the GHGI. For example, the current GHGI emission factor for gas wells is
15.4 scf/hr/controller. On average, the estimate from the Allen et al. 2014 study was 5.5
scf/hr/controller, even accounting for emissions from malfunctioning controllers or related
systems (i.e. a pinhole leak in the control valve) that were included in the emission factor for
pneumatic controllers. There are reasons to believe that the current GHGI emission factor over-
estimates the emissions from current controllers in operations. For example, many operators
have changed out or retrofitted continuous high-bleed controllers as part of voluntary and
regulatory programs.
The Oklahoma Independent Petroleum Association (OIPA) conducted an analysis of the Allen
et al. 2014 pneumatic data to complement the data from the OIPA study, by including emissions
from leaking or malfunctioning intermittent-bleed controllers. In the Allen et al. 2014 study, 10
of 320 intermittent-bleed controllers (3%) were "high emitters;" (i.e., were either leaking or
malfunctioning and had an average "malfunctioning" emissions factor of 50 scf/hr). The OIPA
study calculated an emission factor for vented emissions from intermittent-bleed pneumatic
controllers of 0.4 scf/hr based on physical observations of actuation frequency and calculated
volume of gas released per actuation. The distinction is that "vented" emissions from pneumatic
controllers represent the gas released due to normal operation of the controller, while
"malfunction" emissions from pneumatic controllers represent leaking or malfunctioning
controllers. Applying the OIPA "vented" emissions factor of 0.4 scf/hr to 310 of the properly
functioning intermittent-bleed controllers in the Allen et al. 2014 study, while applying the
"malfunction" emissions factor of 50 scf/hr to the 10 leaking or malfunctioning intermittent-
bleed controllers gives a weighted average emissions factor of 2.0 scf/hr for all intermittent-
bleed controllers ([(310 x 0.40 scf/hr) + (10 x 50 scf/hr)]/320controiiers = 2.0 scf/hr). The OIPA
study also provides information on the count of pneumatic controllers for new well sites and old
well sites (including stripper wells and smaller conventional well pads). As shown in the OIPA
study, a robust emission estimate must include understanding the characteristics of both of these
types of wells.
Regarding the Prasino study, API cautions EPA in using data from that study as the focus was
only on pneumatic controllers with manufacturer bleed rates > 6 scfh and thus the Prasino study
is intentionally biased toward high emitting pneumatic controllers.
Overall, while all these recent studies present the most current data available, they likely should
not be EPA's primary source of data due the variability from study to study. Addressing the use
of new measurement data to update the GHGI would benefit from further evaluation of all
available data by a multi-stakeholder working group. Such an approach would provide for a
structured update of the applicable emission factors to complement the revised counts being
obtained from Subpart W. If the EPA decides to update the inventory without such a
stakeholder engagement, API recommends the use of the Allen et al. 2014 study emission
factors for pneumatic controllers, as the best available current data set, which can also provide
improved understanding of these emissions. As an area with expected future studies, EPA
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should consider that understanding of emission rates from this source is likely to evolve in the
near term as new data sets and measurement techniques are considered. API is interested in
maintaining an on-going dialogue of emission sources in this sector.
*/ (Question #3 from. EPA's Production memo) The EPA seeks feedback on how to take into
account reported emissions data under Subpart W for major equipment fugitives in the
GHG1. For reporters using equipment leak methodology 1 (98% of reporters in RY2014),
emissions data are reported at the facility level based on use of component-level EFs
specified in the rule, not at the equipment level. The EPA seeks feedback on how to use such
data in developing equipment-specific fugitive EFs that could be applied in the natural gas
and petroleum systems sectors of the GHGI. The Subpart W specified EF for reporting
vented emissions from CIPs uses the same basis (GRI/I " > the current G' he EPA
is considering adjusting the GHGI emission factor for GIF using Subpart W reported data,
which takes into account operating hours.
API Comment: Existing GHGRP data on fugitive emissions reported for the production sector
is of limited value for the GHGI since it relies on a set of average emission factors per
component counts as prescribed by EPA and does not contain measurement information that
may be useful to update the emission factors. Equipment counts reported through Subpart W
could be useful for updating activity data for the GHGI, but such extrapolations would be
technically challenging as discussed in Question #1. As a result, API strongly encourages a
detailed stakeholder process related to determining the best method for this extrapolation given
the different populations of wells expected to be covered and not covered under the GHGRP.
However, EPA should refrain from using the default component level emission factors specified
for Subpart W to develop equipment-based fugitive emission factors for the GHGI.
Subpart W provides counts of chemical injection pumps (CIPs) and operating hours that can be
used to scale up GHGRP data to a national emission estimate. However, Subpart W does not
provide information to support updating the emission factor for CIPs. The Allen et al. 2013
study (a.k.a. UT/EDF Phase 1 study) provides measurement data for 62 CIPs with an average
emission rate of 0.192 scf CHVmin/device. EPA should consider evaluating this information for
updating both the default emission factor available in Subpart W and the emission factor
currently used in the GHGI.
Calculations Using Subpart W Data
*/ (Question #4 from EPA's Production memo) The EPA seeks feedback on the methodology
for allocating Subpart W data between the natural gas and petroleum production sectors. Are
other approaches available for allocating Subpart W equipment and pneumatic controller
counts between production types9 For example, one limitation in the current methodology is
that for facilities covering both oil and gas sub-basins and having separators, the count of
separators-per-gas well is equivalent to separators-per-oil well.
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API Comment: Following IPCC guidance, EPA separately reports production operations for
Natural Gas Systems and Petroleum Systems in production operations11, while oil and gas
production activities are combined in the GHGRP. EPA's current approach of separating
GHGRP data based on the ratio of oil production basins to high permeability gas, shale gas, coal
seam, or other tight reservoir rock, although somewhat arbitrary is reasonable.
To aid in comparing the GHGI to GHGRP data, API suggests that EPA resolve differences in
emission source types between the two reporting programs and between natural gas and
petroleum production activities. For example:
• Production operators report emissions from associated gas venting and flaring in the
GHGRP, but this source is not included in the GHGI;
• Well drilling emissions are a vented source in the GHGI under Natural Gas Systems, but
combustion and fugitive emissions from well drilling are tracked under Petroleum
Systems;
• "Wellheads" are an equipment category for reporting fugitive emissions in the GHGRP,
but the GHGI reports emissions for associated gas wells, non-associated gas wells (less
wells with hydraulic fracturing), gas wells with hydraulic fracturing, oil wellheads
(heavy crude) and oil wellheads (light crude).
These are just a few examples where inconsistencies in terminology complicate comparing
emissions between the GHGRP and Natural Gas Systems and Petroleum Systems in the GHGI.
•S (Question #5 from. EPA's Production memo) The EPA seeks feedback on whether and how
to use Subpart W data to reflect geographic variation of activity factors and/or emission
factors. In the current GHGI, emissions from natural gas systems are calculated separately
for six NEM5 regions, and emissions from petroleum systems do not have geographic
variation. The update under consideration is applied at the national level. The EPA plans to
explore options to reflect geographic variation in future GHGIs.
API Comment: In the Natural Gas Systems production sector, EPA reports emission factors
and activity factors by National Energy Modeling System (NEMS) regions. Except for fugitive
emission factors, emission factors vary from year to year due only to slight changes in the
methane composition between each NEMS oil and gas supply region. The methane
compositions are derived from a 2001 GTI study12 and adjusted year to year using gross
production for NEMS oil and gas supply modelled regions from the EIA.
Distinctions made between eastern and western fugitive emission factors, derived from the 1996
GRI/EPA study were based on operational differences and the extent of production of sour
crude, and are no longer relevant to operations today.
API recommends that EPA drop the breakout of natural gas production data by NEMS region.
This breakout gives a false sense of data accuracy, as most of the emission factor variability is
based on methane concentration and not on different operating practices. In addition, regional
11 2006 IPCC Guidelines for National Greenhouse Gas Inventories, Volume 1, Section 8.0 Reporting Guidance and
Tables, Table 8.2
12 GTI (2001) Gas Resource Database: Unconventional Natural Gas and Gas Composition Databases. Second Edition.
GRI-01/0136.
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data is not needed for the GHGI, as evidenced by the other natural gas and petroleum sectors
that are only reported at the national level.
*/ (Question #6 from. EPA's Production memo) The EPA seeks stakeholder feedback on year-
to-year trends in reported Subpart W data, and whether it is more appropriate to recalculate
activity factors and/or emission factors separately for each FLY, or to use another approach
(e.g., combine data from multiple early RYs such as the current methodology for
hydraulically fractured gas well completions which uses combined RY2011 through
RY2013 data to calculate the emission factor).
API Comment: For Subpart W, the 2011 and 2012 GHGRP data include estimates due to the
use of BAMM, and for pneumatic controllers due to the option to estimate counts initially. In
addition, data tend to improve over time as reporters become more familiar with the
requirements and establish more robust reporting processes. API does recognize the value in
using Subpart W data to reflect year to year trends. However, API suggests that early-year
reporting data may not be as accurate as data reported in the third year and beyond. For
production operations, API recommends that EPA use an average of 2013 and 2014 GHGRP
data to update activity factors. As data become available for the Gathering and Boosting sector,
EPA should recognize that reporting year 2016 will include the use of BAMM and even
reporting year 2017 may reflect the learning curve in establishing reporting programs for this
new sector.
*/ (Question #7 from EPA's Production memo) The EPA seeks feedback on how to address
time series consistency in usin derived from Subpart W data—i.e., calculating activity
in years between the early 1990s base year and recent Subpart W-era years. As discussed
under "Time Series Considerations" the EPA might use the count of active production wells
as an activity data driver for major equipment and total pneumatic controller counts in
natural gas systems, and simple linear interpolation for petroleum systems. The EPA could
consider taking into account other factors (e.g., year to year production changes). The EPA
seeks stakeholder feedback on other factors that impact equipment counts and potential
methods to incorporate these factors into the GHGI calculations.
API Comment: API examined the Drillinglnfo (DI) Desktop data over the 1990-2014 period
to determine if there are any unusual peaks or valleys in oil or gas well counts or production
data. The trends for well counts and production data are generally the same, with no apparent
outliers. Therefore, it seems reasonable for EPA to use national well count and production data
to estimate emissions over the inventory time series.
However, API notes that obtaining accurate and replicable well counts is a complex issue. API
is engaged in ongoing discussions with EPA about how to estimate well counts using the
Drillinglnfo (DI) database. At a primary level, these discussions revolve around differences in
how the EPA accesses the DI data versus how API accesses the data. While EPA starts with
actual raw data files, API accesses the data through a desktop application of the data that only
allows for certain search parameters. This means that there are significant differences in how
users can access and search the data, which makes it very difficult to replicate well counts. For
example, because EPA has access to all raw well data, they are able to easily classify wells as
either "oil" or "gas" based on a GOR that they calculate. Through the desktop application
however, wells are classified as "oil" or "gas" based on state definitions that are not consistent
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across all wells. The following table illustrates the differences in well counts accessed by API
through the DI database, compared to well counts reported by EPA for 2013 in the previous
GHGI13
DI Database Well Counts for
2013 (accessed by API) EPA Reported 2013 GHGI Well Counts13*
Gas Wells
417,277
Non-associated gas wells
207,279
Gas wells with hydraulic fracturing
244,017
Gas and Oil Wells
70,679
Associated gas wells
477,023
Oil Wells
455,243
Heavy crude oil wells
38,682
Light crude oil wells
510,005
TOTAL
943,199
TOTAL
1,477,006
* Including 315,000 crude oil stripper wells (<15 Bbls per day); Reference 13 Table A-126
Unless one downloads all of the well data, which is not a feasible solution, the desktop
application does not allow a user to calculate a GOR and use it as a search parameter. API
urges EPA to be transparent in describing how EPA utilizes information in Drilling Info for the
GHGI in order to facilitate comparisons and ensure that there is no undercounting or
overcounting of wells.
We would also like to point out that the noted discrepancies in the well counts are not a new
issue. For example, the U.S. Energy Information Administration (EIA) reports 514,637
producing gas wells for 2011 (as compared to 604,681 in the GHGI published in 2013) and
536,000 producing oil wells (as compared to 220,787 crude oil wells and 315,213 crude oil
stripper wells in the GHGI published in 2013). For 2013, the EIA reports 484,994 producing
gas wells (with gas-oil ratio > 6000 scf/barrel) but does not furnish equivalent information for
oil wells.
The well counts provided in EPA's Production sector memo equal 1,315,196 (Table 4: 2013
wellheads for petroleum & natural gas combined). This value is different from the sum one
derives (per table above) from the respective petroleum and natural gas tables in Annex 3 of the
2013 GHGI. Since EPA is proposing to use the number of wellheads (well count) as the
normalization factor for scaling Subpart W data, it is imperative that the well count be accurate.
API is providing all of these examples to highlight the discrepancies in the data used to update
the emissions estimates for the production sector and the need to have them reconciled by a
transparent and structured process via a multi-stakeholders group, as previously stated.
Other Emission Sources
•S (Question #8 from EPA's Production memo) The EPA discusses potential revisions to the
GHGI production sector structure in a companion memo titled "GHGI of U.S. Greenhouse
Gas Emissions and Sinks: Revisions under Consideration for Natural Gas Gathering and
13 U.S. EPA, 2015, "Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2013", EPA 430-R-15-004, April
15, 2015; Tables A-126 and A-133.
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Boosting Emissions" (February 2016). Potential revisions would include updating some of
the production emission calculation methodologies based on Marchese et al (2015)
measurement data for centralized production and gathering-only facilities. With such
revisions, certain emission sources would overlap with the Marchese et al. facility-level EF
if current methodology were retained: dehydrator vents, Kinray pumps, and storage tanks.
The EPA seeks feedback on how to improve GHGI activity, emissions, and controls data for
sources located at non-gathering production sites based on available Subpart W data.
API Comment: EPA's memo on proposed revisions to the GHGI for Gathering and Boosting
focuses entirely on utilizing information from the Mitchell et al. and Marchese et al. studies.
However, the Mitchell et al. measurements are limited in their use because only downwind, site-
level short-duration "snapshot" measurements were conducted. This approach does not provide
sufficient information to properly characterize emissions at individual sites in gathering and
boosting operations, much less individual sources within the sites.
API recommends that EPA postpone major updates to the GHGI for gathering and boosting
emissions until GHGRP data are available. The GHGRP will provide additional activity data
for gathering operations and will enable EPA to properly characterize equipment populations
and distinguish between production and gathering. When this new information and
characterization become available, API recommends that EPA revise the GHGI to present,
separately, gathering emission estimates from production emission estimates, even if they
ultimately have to be combined for reporting under the IPCC categories. This will align the
inventory with the GHGRP, provide greater transparency, and enable trends to be evaluated. As
stated above, API requests that EPA delay making any significant changes to the methodology
until GHGRP data are available in 2017. At that time, EPA will have facility specific data for a
significant number of Gathering and Boosting facilities in the country, including population
information, activity data, and actual emission data for some sources.
*/ (Question #9 from EPA's Production memo) The EPA seeks stakeholder feedback on
production sector sources not discussed in this memorandum.
a. For sources where GHGRP data are currently available, the EPA seeks stakeholder
feedback on how GHG a may be used to revise current GHGI methodologies. For
example, the EPA seeks stakeholder feedback on whether similar methods to those
discussed in this memorandum could be used to scale up sub""*-4' w activity data for
sources such as liquids unloading and hydraulically fracture gas well completions
b. For sources where GHGRP data are not currently available, A seeks stakeholder
feedback on data sources available for updates to those methodologies. The EPA is
considering including emissions from hydraulically fractured oil well completions and
workovers in th -I, using information from the 2015 NS.PS OOOOa proposal. In
addition, the EPA seeks stakeholder feedback on any currently available or upcoming
activity and/or emissions data on abandoned wells.
API Comment: (a) For emission sources with data available through the GHGRP, API
recommends that EPA make use of GHGRP information to update the national inventory. As
mentioned in our responses above, the exception to this is where the GHGRP does not collect
new emissions data but utilizes default emission factors, such as for fugitive emissions in
production, pneumatic controllers, pneumatic pumps, compressors in production, and small
dehydrators.
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API previously commented on the use of GHGRP data for gas well completions and workovers
to update emission estimates in the GHGI.14 EPA incorporated updated emission factors for
these sources, although API continues to believe that the emissions data can be well represented
by only two emission factors (completions and workovers vented without REC, and all other
completions and workovers) rather than the four categories used by EPA. These two categories
maximize the use of GHGRP data, will be more straightforward to back cast for previous
reporting years in the GHGI, and are consistent with current practices.
API cautions EPA against using the ratio of well completions and workovers to overall well
counts in the GHGRP, in order to scale up completion and workover counts to the national
level. Completions, by definition, only apply to new wells, although not all new wells are
hydraulically fractured. Information on new wells should be available through EIA or DI
Desktop. Determining an appropriate method of scaling GHGRP data may be best achieved
through discussions and consideration by the multi-stakeholder group suggested by API.
(b) Although not currently required under the GHGRP, some companies have reported
emissions data for oil well completions and workovers with hydraulic fracturing. API
commented previously on the use of GHGRP data to derive emission factors for the GHGI.14
API previously identified 149 reported data sets, providing emissions data for 1675 completions
and 226 workovers for the years 2011 through 2013 combined (we have not examined the 2014
GHGRP data to update this analysis). API believes the GHGRP provides sufficient data to
include these emissions in the GHGI, and that much more information will be available in the
next few years to update the national emission estimates.
The DI database provides activity data for abandoned wells. A 2014 study (Kang et al.15)
provides information on emissions from abandoned wells in the Appalachia region. However,
many of these wells are very old, predate any abandonment criteria, were not properly
abandoned and were limited to a single geographic region. Therefore, while the study did
provide new information, the findings should not be considered as representative nor used as the
basis for national extrapolation. A proper data set is needed that reflects geographical
variability and well-age to represent emissions from abandoned wells on a national basis.
*/ (Question #10 from. EPA's Production memo) Recent production sector studies have
detected the presence of super emitters in the production sector. The EPA seeks stakeholder
feedback on how to incorporate information on super emitters into estimates for the
production sector. The EPA also seeks stakeholder feedback on which GHGI sources are
more likely than others to act as super emitters and whether and how to apply a super emitter
factor or other methodology to those sources.
14 Letter to Leif Hockstad and Melissa Weitz, API Expert Review Comments on EPA's Draft U.S. GHG Inventory:
1990-2013, January 9, 2015.
15 Kang et al. (2014) "Direct Measurements of Methane Emissions from Abandoned Oil and Gas Wells in
Pennsylvania". Proceedings of the National Academy of Sciences of the United States of America. Available at:
http://www.pnas.org/content/lll/51/18173.Ml.pdf]
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API Comment: Recent measurement studies have shown skewed "long tail" distributions for
source-level measurements, where a few emission sources may contribute a disproportionately
high fraction of emissions. This is a common and expected statistical distribution for random
events, such as fugitive emissions from process components and equipment malfunctions. A
combination of variability in production and non-steady state emissions may result in a 'fat-tail'
distribution even in the absence of operational upsets. Emission factors derived from such
measurements already account for the emission distributions throughout the range of
observations for each of the sources, including the emissions at the high range of the tail.
The approach raised by EPA, of potentially, separately adjusting the national inventory for the
so called 'super emitters,' is not appropriate. API contends that there should not be any
consideration of using downwind offsite measurements - especially those that depend on short
duration, snapshot measurements - to characterize emissions in the GHGI. Recent studies in the
Barnett Shale region indicate that there might be several order of magnitude differences in
repeated emissions from a given set of sites, probably due to stochastic variables that are
transient in nature. In particular, a study of 22 separate flights around the same compressor
station16 indicated that facility-level emissions ranged from 0.3 to 73 g CH4/sec with highly
skewed distributions (mean=14 g/sec and median = 7.4 g/sec). Again, API suggests that the
EPA inventory team consult with the EPA ORD's Eben Thoma regarding the adequacy of
downwind ambient concentration measurements in determining emissions.
All the studies aiming to quantify fugitive emissions indicate that the distribution of emissions
and the shape of its tail are not well understood. API insists that both EPA and the scientific
community do not have enough information to identify the reasons for the variability of some
emission sources. All measurements have some degree of uncertainty. This is especially true
for short duration snapshot measurements conducted offsite, which fail to differentiate between
routine episodes of high emissions, operating conditions, or operators errors that may lead to
17
periodic higher emissions. For example, one study focused on "super-emitter" quantification
in the Barnett Shale and relied on measurements of 1-5 minutes in duration at distances of up to
several kilometers downwind in a region with high oil and gas site density.
EPA's ORD research5 that was conducted with strict data quality control parameters, longer
sampling times, and nearer pad sampling, indicated that, at best, downwind measurements
provide screening level accuracy with ±60%. Insufficient research exists to validate high
downwind measurements with on-pad emission sources such that it could be used to
characterize national emission estimates for a program like the GHGI. API concurs with EPA's
ORD that in order to properly quantify emissions measurements, they should be taken over a
long period of time in order to capture the full range of variability, rather than rely on just peak
emissions. Assuming that peak emissions occur all the time would lead to biased results.
16 Nathan, B.J., Golston, L. M., O'Brien, A.S., Ross, K. Harrison, W. A., Tao, L., Lary, D. J., Johnson, D. R.,
Covington, A. N., Clark, N. N., and Zondlo, M. A., Near-field characterization of methane emission variability from a
compressor station using a model aircraft. Environmental Science & Technology, 49,7896-7903 2015
17 Yacovitch, T. I., Herndon, S.C., Petron, G., Kofler, J., Lyon, D., Zahniser, M. S. and Kolbacovitch, C. E. et al. Mobile
laboratory observations of methane emissions in the Barnett Shale region. Environmental Science and Technology. 49,
7889-7895, 2015
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In summary, API maintains that adjusting emissions for what EPA terms 'super emitters' may
lead to gross overestimation due to the unpredictable nature of such high emissions events and
may also lead to duplicative counting, since these events are already part of the emission
distribution that is used to derive emission factors. For example, if a connection failure is
posited as the cause of a theoretical site being deemed as a theoretical "super-emitter", emission
factors developed from in-fteld measurements of a population of connectors already account for
some of these components emitting at a high rate. Consequently, API insists that since EPA
does not have sufficient information to characterize and understand this then no such adjustment
to the GHGI inventory approach should be considered.
Responses to EPA Questions for Revisions under Consideration for Gathering and
Boosting Emissions
Data Availability
*/ (Question #1 from. EPA's Gathering and Boosting memo) The EPA is seeking stakeholder
feedback on additional data available to consider in revising G&B emission estimates at this
time. The EPA seeks stakeholder feedback on the proposed approach to use Marchese et al.
estimates for national activity data. Are additional data sources or approaches available to
estimate national G&B activity9
API Comment: The Marchese et al. study results are based on facility level, downwind short-
duration "snapshot" measurements conducted during the Mitchell et al. study. Marchese et al.
used that data to model the total methane emissions from approximately 120 facilities. The
modeled results are then "scaled" - using multiple assumptions - to a national level to represent
the methane emissions from over 4,500 Gathering and Boosting facilities.
As indicated in our general comments, API urges EPA to wait on any significant revisions to the
GHGI related to Gathering and Boosting until the GHGRP data are available. Significant
activity data will be reported through the GHGRP, including throughput volumes and equipment
counts. This information will be superior to the Marchese et al. study for developing national
Gathering and Boosting activity data.
*/ (Question #2 from EPA's Gathering and Boosting memo) Replacing current Gl s for
large reciprocating compressors and stations with the EF based on Marchese et al. G&B
station emissions may introduce double counting of the "mixed category" sources based on
current GHGI methodology. 1 updates under consideration for the G&B sector
(this memorandum) and production sector (Inventory of U.S. Greenhouse Gas Emissions
and Sinks: Revisions under Consideration for Natural Gas Production Emissions (February
2 i combination avoid potential double counting issues by calculating emissions for
each as distinct sectors. Please comment on the overall approach under consideration for
production and G&B.
API Comment: The Mitchell et al. study relies on offsite, downwind measurements, using
inverse flux methodology to derive emissions over short durations. These types of
measurements have significant uncertainty, which has been documented by EPA's ORD5.
EPA's proposed approach to segregate Gathering and Boosting emissions from Production is
specifically designed to utilize data from the Marchese et al. study4, which is a desktop
"3
modeling study based on the Mitchell et al. measurements but is inconsistent with the Mitchell
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et al study. API does not support the use of the emissions data from the Mitchell et al. or
Marchese et al. studies for updating the GHGI.
The API further cautions the EPA on the development of new national emissions factors based
on the Mitchell et al. study due to the large degree of variability and small sample size for the
study. For the 114 facilities, emission rates ranged more than 4 orders of magnitude (from 0.6
to 600 scf CH4/minute). Part of this variability is inherent in the short sample durations for the
plumes in the study (30-120 seconds). Given the wide variation in facility emission rates from a
study of 22 separate flights around the same compressor station16, which indicated that facility
level emissions ranged from 0.3 to 73 g CHVsec with highly skewed distributions (mean=14
g/sec and median = 7.4 g/sec), more context is needed for understanding emission rates in the
Mitchell et al. study before considering application to national emission estimates.
In attempting to avoid double counting of emissions sources, EPA is artificially defining
Production versus Gathering and Boosting equipment. For example, EPA is proposing to assign
emissions from all pneumatic controllers, chemical injection pumps, dehydrator vents, and
Kimray pumps to the Production sector. This will give the false impression that these sources
only occur in Production.
API recommends that EPA wait until data are available through the GHGRP for the Gathering
and Boosting sector. We believe this information will better represent the emission sources
associated with Gathering and Boosting (recognizing that some Gathering and Boosting
operations will continue to be reported under the Production sector due to the location of a well
at the Gathering/Boosting site). In addition, we recommend that EPA report emissions from
Gathering and Boosting separate from the Production sector, or as a subset of the Production
sector. This will provide greater transparency and comparison to the GHGRP than combining
Gathering as part of the Production sector, as is currently reported in the GHGI.
*/ (Question #3 from. EPA's Gathering and Boosting memo) As discussed in this
memorandum, G&B data will be available in 2017 through GHGRP. GHGRP data could
allow the EPA to calculate emissions for individual equipment types as opposed to using
emission factors and activity data at the station level The EPA seeks stakeholder feedback
on the two approaches. The EPA could considering using the station level approach for the
2 IGI, and then re-evaluating and potentially revising the approach with new GHGRP
data in the 2 "IGI, or could consider implementing updates to the G&B sector starting
with the 2017 GHGI and using GHGRP and/or the Marchese et al data at that time.
API Comment: API does not believe the Marchese et al. study results are appropriate for
updating the national inventory and encourages EPA to wait until the Gathering and Boosting
data are available through the GHGRP. As EPA indicates, the GHGRP data will allow the EPA
to calculate emissions for individual emission source types as opposed to using emission factors
and activity data at the station-level. Data for individual equipment types will be significantly
more useful and transparent than emission factors and activity data at the station level. There is
no need to introduce a significant revision to the GHGI now to accommodate the Marchese
study information, only to later have to significantly revise the methodologies again to utilize
the GHGRP data.
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*/ (Question #4 from. EPA's Gathering and Boosting memo) The EPA seeks feedback on
whether and how to use the Marchese et al data to reflect geographic variation of activity
factors and/or emission factors. In the current GHGI, emissions from G&B sources are
calculated separately for six NEM5 regions along with production sources. The update
under consideration would be applied at the national level. The EPA plans to explore options
to reflect geographic variation in future GHG inventories.
API Comment: The small population size of the underlying Mitchell et al. study, the lack of
emission source detail, and the numerous compounding assumptions made in the Marchese et al.
study to extrapolate the modeled results do not provide sufficient certainty to use the study
results to characterize the Gathering and Boosting Sector. Nor does the Marchese study provide
sufficient information to characterize geographic variability. As mentioned above, in response
to questions raised in the Production memo, API recommends that EPA discontinue breaking
out natural gas production data by NEMS region and instead report Production sector emissions
data at the national level only, as EPA does for the other sectors under Natural Gas Systems and
Petroleum Systems. Similarly EPA should not attempt to calculate emissions from the
Gathering and Boosting sector for individual NEMS regions.
Time Series Considerations
*/ (Question #5 from EPA's Gathering arid Boosting memo) The EPA seeks feedback on the
appropriateness of using the Marchese et al. based G&B station EF across all years of the
time series, or whether there are approaches that may be considered for reflecting changing
industry trends impacting emissions over time.
API Comment: The Marchese et al. study, which is based primarily on drive-by, snap-shot
measurements from the Mitchell et al. study, does not provide useful data for characterizing
current national emissions, nor does it provide sufficient information to reflect emission trends
over time.
*/ (Question #6 from EPA's Gathering and Boosting memo) The EPA seeks stakeholder
feedback on the activity driver (volume of marketed onshore gas production) under
consideration. Other options for the activity driver could include well count data or other gas
production categories. Please comment on which activity driver would be the most
appropriate to show trends in G&B.
API Comment: EPA will have significant activity data reported for the Gathering and
Boosting sector through the GHGRP starting in 2017. API recommends that EPA evaluate this
information when it's available to identify activity drivers for scaling Gathering and Boosting
emissions data to a national level. API also points out that it may take more than one reporting
cycle to work through data quality concerns associated with the first year of reporting for a new
sector.
*/ (Question #7 from EPA's Gathering arid Boosting memo) The EPA seeks stakeholder
feedback on trends in G&B activity data that would result in more or fewer stations per
volume of marketed onshore gas production during any point in the GHGI time series. The
EPA requests stakeholder feedback on how upcoming subpart W G&B activity data
(available in 2017) could be used to inform the time series activity data to reflect ongoing
trends.
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API Comments on Updates under Consideration for Natural Gas and Petroleum Production Emissions, and Gathering
and Boosting Emissions
API Comment: As noted in our comment to question #6, API expects the activity data reported
through the GHGRP for the Gathering and Boosting sector to provide significant information
for developing national scaling factors and similarly will be appropriate data for informing
activity data over the time series.
*/ (Question #8 from. EPA's Gathering and Boosting memo) Since the EI A does not publish
separate values for the onshore portion of marketed natural gas production prior to 1992, the
EPA is considering using the relationship of onshore marketed production to onshore gross
withdrawals in 1992 to estimate marketed onshore production in 1990 and 1991, based upon
onshore gross withdrawals for these two years. Are there alternatives to addressing this
missing AD9
API Comment: API supports EPA's proposal to relate onshore marketed production to
onshore gross withdrawals in 1992 in order to estimate marketed onshore production in 1990
and 1991.
*/ (Question #9 from EPA's Gathering arid Boosting memo) Although it is not possible to
directly compare the G&B emissions estimate developed with GM/EPA study data to the
Marchese et al. results, it is evident that the G&B emissions from Marchese et al. are
significantly higher than estimates in the current GHGI. The EPA seeks stakeholder
comment on this discrepancy.
API Comment: It is not appropriate to compare the Marchese et al. modeling information
which is based on short-duration, off-site ambient concentration measurements, which rely on
inverse flux methods to derive emissions; to source specific emission estimates. The site level
measurements conducted in the Mitchell et al. study significantly limit the use of the data for
updating the national inventory, which is compiled from source level emission estimates. API
urges EPA to delay revising the emission estimation methods for the Gathering and Boosting
sector until more data is available for this sector through the GHGRP.
Gas Processing
*/ Marchese et al. also measured the methane emissions from 16 natural gas processing plants
using a similar approach as described above for G&B stations. The results of the Marchese
et al. testing were scaled to the estimated 600 national gas processing plants using a similar
Monte Carlo simulation as was used for G&B stations. The results of the Marchese et al.
simulation was a national methane emission estimate for gas processing plants of 506 Gg.
As with the G&B stations, Marchese et al. estimated that the emission results were biased
low for several factors. The brief sampling period did not capture routine maintenance and
upset emissions. In addition the sampling method did not capture a significant portion of the
compressor exhaust emissions. Marchese et al. compared their findings to the
of 2012 emissions. The net ethane emissions for 2012 from processing plants were
891 Gg. The nc I emissions from processing plants, excluding compressor exhaust
and blowdown/venting emissions were estimated to be 666 Gg. EPA seeks stakeholder
comment on the potential use of Marchese et al. results for the processing sector.
API Comment: As mentioned previously, measurement data from the Mitchell et al. study are
not particularly useful for updating the GHGI because the data lack emission source detail.
Substantial new activity data and some measurement data are available for gas processing
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API Comments on Updates under Consideration for Natural Gas and Petroleum Production Emissions, and Gathering
and Boosting Emissions
facilities that report through Subpart W. EPA now has four years of fugitive emission surveys
and measurement data for specific emission sources and activity data that can be used to update
the GHGI. API encourages EPA to make use of the survey results and actual measurements
reported in GHGRP. In the November 2015 stakeholders' workshop, API presented a
preliminary comparative analysis of methane emissions from equipment leaks from natural gas
processing, showing that it is about six times larger in the GHGI as compared with the GHGRP.
Although the number of gas plants reporting to the GHGRP is different than the number of gas
plants in the GHGI, this difference cannot fully account for the emission differences. API would
welcome further collaboration with EPA to address these differences and develop a procedure
that incorporates the GHGRP measurement data in the GHGI.
API's comments above are based on our long term engagement in reviewing and providing
information for the U.S. GHG Inventory. It includes observations and recommendations for careful
QA/QC of data extracted from the mandatory GHGRP to improve the validity and
representativeness of data used for the U.S. GHG Inventory. API recognizes that emerging data
from recent field studies have raised concerns about measurements uncertainty, and recognizes the
need for a thorough discussion of means of improving the methodology to ensure collection of
robust measurement data. We reiterate our recommendation for EPA to form a multi-stakeholder
workgroup to discuss updating the national GHGI to incorporate information from recent
measurement study results and Subpart W data.
API appreciates the opportunity to provide comments on the proposed revisions to the U.S. national
GHG Inventory and EPA's willingness to work with industry to improve the data used for the
national inventory. API encourages EPA to continue these collaborative discussions and is
available to work with EPA to make best use of the information available under the GHGRP to
improve the national emission inventory. We look forward to continuing our collaborative work in
the GHGI development process.
Sincerely,
Karin Ritter
cc: Alexis McKittrick, Climate Change Division
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APPENDIX: API Comments on Updates under
Consideration for Natural Gas and Petroleum
Production Emissions, and Gathering and Boosting
Emissions
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fponH
ISei© ice&Technoogy
Assessment of Methane Emissions from Oil and Gas Production Pads
using Mobile Measurements
Halley L. Brantley, Eben D. Thoma,*'' William C. Squier/' Birnur B. Guveiv and David Lyon"
10ffice of Research and Development, U.S. Environmental Protection Agency, 109 T.W. Alexander Drive, Research Triangle Park,
North Carolina 27711, United States
'"Houston Advanced Research Center, The Woodlands, Texas 77381, United States
^Environmental Defense Fund, 301 Congress Ave., Suite 1300, Austin, Texas 78701, United States
0 Supporting Information
This is an open access article published under an ACS AuthorChoice License, which permits
copying and redistribution of the article or any adaptations for non-commercial purposes.
ACS AuthorChoice
pubs.acs.org/est
ABSTRACT: A new mobile methane emissions inspection wind Direction
approach, Other Test Method (OTM) 33A, was used to V
quantify short-term emission rates from 210 oil and gas
production pads during eight two-week field studies in Texas,
Colorado, and Wyoming from 2010 to 2013. Emission rates
were log-normally distributed with geometric means and 95%
confidence intervals (CIs) of 0.33 (0.23, 0.48), 0.14 (0.11,
0.19), and 0.59 (0.47, 0.74) g/s in the Barnett, Denver-
Julesburg, and Pinedale basins, respectively. This study focused
on sites with emission rates above 0.01 g/s and included short-
term (i.e., condensate tank flashing) and maintenance-related
emissions. The results fell within the upper ranges of the
distributions observed in recent onsite direct measurement
studies. Considering data across all basins, a multivariate linear
regression was used to assess the relationship of methane emissions to well age, gas production, and hydrocarbon liquids (oil or
condensate) production. Methane emissions were positively correlated with gas production, but only approximately 10% of the
variation in emission rates was explained by variation in production levels. The weak correlation between emission and
production rates may indicate that maintenance-related stochastic variables and design of production and control equipment are
factors determining emissions.
¦ INTRODUCTION
Environmentally responsible development of oil and gas assets
requires an understanding of atmospheric emissions of methane
(CH4) and other organic pollutants as well as their potential
impact on local and regional air quality and greenhouse gas
budgets. Emissions are associated with many different processes
in upstream (well development and production) and midstream
(transportation and storage) oil and gas activities.1,2 Although
differing in profile, emissions occur in all phases of well
construction, drilling, and completion, and continue as part of
the ongoing production processes.3 Oil and gas production
pads (pads) typically consist of well heads, separation units, and
storage tanks. Emissions from pads can be difficult to measure
and model due to temporal variability and the large number of
potential sources.4,3 Pad emission profiles depend on a variety
of factors including the geological formation, equipment design
and maintenance state, and on operational procedures. For
example, depending on engineering and control strategies,
atmospheric-pressure condensate storage tanks are a significant
potential source of emissions and can be challenging to
measure.6" Pad emissions can also vary over time as wells age
and production levels and pressures change. Improving our
understanding of emissions from production sites requires a
combination of approaches, including estimating emissions
using engineering calculations for inventories,2,8,9 direct
measurements for refinement of emission and activity factors,10
and new inspection techniques to inform departures from
routine operations and support compliance activities.11
Direct (onsite) measurements can provide information on
component-level emissions, but are resource intensive,
requiring site access and special safety considerations.
Furthermore, the high site-to-site variability decreases the
probability of obtaining a representative sample from a small
number of sites. To complement direct measurement
approaches, a number of research groups are investigating the
use of mobile inspection techniques to locate and assess
emissions from off-site observing locations.4,12-14 These
emerging approaches vary with respect to execution require-
ments and emission estimation techniques; however, their
mobile nature facilitates identification of unknown emission
sources (e.g., pipeline leaks) and anomalous operating
Received: June 24, 2014
Revised: September 23, 2014
Accepted: November 6, 2014
Published: November 6, 2014
ACS Publications © 2014 American Chemical Society
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conditions (e.g., malfunctions). Unlike direct measurements,
mobile approaches typically cannot isolate specific emitting
components and are generally less precise than direct measures
but are comparatively easier to implement, enabling emission
assessments to be made at a greater number of locations on a
more routine basis.
This paper describes a novel mobile inspection approach,
EPA Other Test Method (OTM) 33A,17 and its use to generate
CH4 emission rate data from oil and gas production sites in the
Denver-Julesburg (Dj) Basin, the Barnett Shale, Pinedale, and
Eagle Ford from 2010 to 2013. OTM 33A uses a combination
of mobile sampling to identify sources and stationary
measurements to quantify emissions. In addition to the analysis
of repeated measurements at nine sites, the emission estimates
from the OTM 33A field studies were compared with recent
on-site studies led by the Eastern Research Group (ERG)15 and
Allen et al.16 The ERG study,15 conducted for the City of Fort
Worth, TX, used both direct measurement and source
estimation methods to characterize CH4 and volatile organic
compound emissions at 388 production sites containing wells,
produced water storage tanks, separators, and compressors.
Component-level source identification in the ERG study15 was
accomplished by infrared camera observations and direct source
measurements were conducted using Hi Flow samplers
(Bacharach Inc., New Kensington, PA), toxic vapor analyzers,
and evacuated canisters. The measurements were used by the
City of Fort Worth to evaluate the adequacy of setback
provisions for pads and compressor stations. The results of the
ERG study15 indicated that compressors, leaking tank thief
hatches, and pneumatic valve controllers are the most
frequently encountered and significant emissions sources of
CH4. Using similar on-site measurement techniques, Allen et
al.16 measured CH4 emissions from 150 production sites in four
regions of the United States to evaluate engineering estimates
of CH4 emissions from natural gas production that are used in
national inventories. Their results indicated that emissions from
pneumatics and equipment leaks were higher than estimated in
the EPA greenhouse gas (GHG) emissions inventory.16
ATERIALS AND METHODS
OTM 33A17 is a mobile inspection approach used to locate
sources and determine real-time emission rates with screening-
level accuracy (±60%), without the need for site access or
location-specific modeling. The technique is applicable to select
oil and gas sources such as roadway proximate pads located in
relatively open areas. In addition to downwind vehicle access
and favorable plume transport conditions required for all
mobile assessment methods, the emission characterization
portion of OTM 33A relies on relatively consistent
meteorological conditions, obstruction-free line of sight
observation, and a knowledge of the distance to the source.17
Sampling Platform Design and Protocol. The OTM
33A equipment configuration, further described in OTM33A
Appendix A,17 used either a G1301-fc cavity ring-down
spectrometer (Picarro, Inc., Santa Clara, CA) or a GG-24-r
ofF-axis integrated cavity output spectrometer (Los Gatos
Research Inc., Mountain View, CA) as CH4 concentration
measurement instruments (CMIs). The mobile measurement
platforms were sports utility vehicles containing the CMI,
computer control system, and battery systems allowing engine-
ofF instrument operation during stationary observations to
prevent self-sampling of vehicle exhaust. The vehicles were
fitted with rotatable front-mounted masts with a height of 2.7 m
allowing the CMI probe and meteorological instruments to be
located away from the body of the vehicle. Primary wind field
data were acquired using a model 81000 V Ultrasonic
Anemometer (R.M. Young, Inc., Traverse City, Ml). A
collocated compact weather station (model AIO 102780,
Climatronics Corp., Bohemia, NY) provided secondary wind
data along with temperature, atmospheric pressure, and relative
humidity measures. Location was recorded using a Hemisphere
Crescent R100 Series GPS system (Hemisphere GPS, Calgary,
AB Canada). A LabView (National Instruments, Inc., Austin
TX) computer program time-aligned the data stream while
allowing user control of the system.
The accuracy, linearity, and range of the CH4 CMIs were
confirmed in predeployment testing with in-field accuracy
verified to be within ±5% of actual using nominal 20 ppm CH4
(air balance) gas standard challenges as per OTM 33 Section
9.4.17 The CMI readings were not corrected for atmospheric
water vapor (OTM 33A Appendix A)17 which introduces an
approximate 1.5% average negative bias to CH4 emission
determinations for the conditions encountered in this study.
For a typical pad assessment, emissions were located through
downwind, drive-by inspection, keying on sharply elevated CH4
spikes indicative of proximate source plumes. Maximizing real-
time CH4 concentrations measured by the CMI, the vehicle was
positioned in the plume at a safe and appropriate downwind
observing location with the probe facing the source, and the
engine was turned off. Distance from the measurement vehicle
to the emission source ranged from 10 to 200 m with an
average distance of 57 m. Data were acquired for a 15 to 20 min
time period with the vehicle remaining stationary. Auxiliary data
from infrared cameras (FLIR Systems, Inc., Boston MA), when
available, helped identify the source location, facilitating laser
rangefinder measurements of the distance from the mobile
platform to the source. Distances were later confirmed through
Google Earth images coupled with wind-concentration rose
data. The vehicle was positioned to minimize line-of-sight wind
flow obstructions.
Emission rate estimates were calculated using a point source
Gaussian (PSG) approach with a custom MATLAB (Math-
Works, Natick, MA) analysis program (OTM 33A Appendix
Fl).17 This approach relies on variations in wind direction to
move the plume around the observation location in three
dimensions; further assumptions include a point source and
Gaussian plume dispersion. The analysis software time-aligned
the measurements to correct for sampling line delay, rotated
the 3-D sonic anemometer data to polar coordinates centered
on the predominant wind direction, and binned the CH4
concentrations by wind direction data in ten degree increments.
The results were fitted with a Gaussian function to determine
the average peak CH4 concentration in the plume. Background
concentrations were determined by the program during time
periods with no plume-probe overlap (OTM 33A Section
8.7).17 The program calculated the representative atmospheric
stability indicator (ASl) from an average of the turbulence
intensity (Tl), measured by the 3D-sonic anemometer and the
standard deviation in 2-D wind direction (nO), acquired by the
compact meteorological station. By defining a seven unit ASI
scale with steps of equal increments (TI = 0.025, a0 = 4.0°), an
ASI value for each measurement was assigned which ranged
from 1 (TI > 0.205, 27.5°) to 7 (TI < 0.08, oO < 7.5°),
roughly corresponding to the Pasquill stability classes A
through D.18 For the PSG emission estimate, the values of
horizontal (try) and vertical (
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Environmental Scienc inology
from an interpolated version of point source dispersion tables
using the measured source distance and the ASI (OTM 33A
Section 12, Appendix Fl).17 The PSG emission estimate (q) is
a simple 2-D Gaussian integration (no reflection term)
multiplied by mean wind speed (u) and the peak concentration
(c) determined by the Gaussian fit: (q = In-cy-GZ-u-c)}7
Method Validation Using Controlled Release Experi-
ments. A set of 107 controlled CH4 release experiments were
conducted to investigate data quality indicators and the
expected accuracy range for the PSG approach in relatively
obstruction-free, open areas as encountered in this study
(OTM 33A Section 9).17 The experiments used single point
releases from slightly dispersed, mass flow-controlled cylinders
of 99.9% CH4, performed at a variety of site locations,
observation distances, and under a range of atmospheric
conditions. Release rates ranged from 0.19 g/s to 1.2 g/s with
60% at approximately 0.6 g/s. Based on these experiments, a
primary set of three data quality indicators was identified: (l)
fitted peak CH4 concentration centered within ±30 degrees of
the source direction; (2) an average in-plume concentration
greater than 0.1 ppm; and (3) a Gaussian fit with an R2 > 0.80.
The plume centering indicator helps ensure the identity of the
upwind source and can protect against off-axis interfering
sources and poor plume advection conditions. The concen-
tration limit helps protect against insufficient plume transport
and the R2 indicator helps identify interfering sources and
obstructed wind flow conditions (non-Gaussian transport).
The percent error ([estimated emission rate-release rate]/
[release rate]) of the controlled release experiments that met
the data quality criteria ranged from —60% to 52% with 72% of
the measurements within ±30%. Without application of the
data quality indicators, the set of release experiments produced
accuracy values ranging from —87% to 184% of actual. The
184% overestimate was believed to be due to pooling and
release under partially stagnant conditions and a trial wind
variance indicator was developed for this case (not observed in
field trials). Factors affecting accuracy can include insufficient
plume advection and nonrepresentative concentration profiles
caused by near-field obstructions or poor plume-probe overlap.
Potential data quality indicators such as wind speed and plume
concentration statistics are being investigated as part of OTM
33A method development.17 For the current analysis, only
measurements that met the three primary criteria were included
(representing 77% of the controlled release measurements and
71% of the field measurements).
Description of Field Studies and Production Data.
OTM 33A was used in eight two-week field campaigns in four
oil and gas production basins: Colorado DJ Basin, July 2010
and 2011; Texas Barnett shale, September 2010 and 2011;
Texas Eagle Ford Shale, September 2011; and Wyoming
Pinedale, which includes the Pinedale Anticline and Jonah
fields, June 2011, July 2012, and June 2013. Data sets for each
individual basin were combined as the methods of data
collection were similar, although there were some software and
hardware improvements in later studies. All measurements were
collected in the daytime on days with no significant
precipitation.
Oil and gas production information for the counties sampled
was obtained from DI Desktop (Drillinginfo, Austin, TX).
Included in the data set were well type, operator, first
production date, spatial coordinates of the well, and annual
and monthly hydrocarbon liquids, gas, and water production
levels. OTM 33A measurements were spatially matched with
production data using aerial imagery (Google Earth19 and
ArcGIS20 base maps). When coordinates did not align with
aerial imagery, additional data sets provided by the State of
TX21 and State of CO22 ' were used to cross-reference location
information. Monthly production values were available for 81%
of the measurements. When monthly production was not
available, annual values were converted to monthly estimates.
The matched data set was analyzed using R23 and ArcGIS 10.20
Both emissions estimates and production values were log-
normally distributed and for this reason, data in figures are
shown on a log scale. The mean and 95% CI of the log-
transformed data were calculated using a nonparametric
bootstrap24'25 and then transformed back into the original
scale. The nonparametric bootstrap involved resampling with
replacement 1000 times, the mean of each of the samples was
taken and the 95% CIs were calculated from the resulting
normally distributed means. The nonparametric bootstrap was
chosen because it does not assume the underlying data comes
from a normal distribution. To compare OTM 33A emissions
estimates with the direct measurement studies conducted by
ERG15 and Allen et al.,16 direct measurements were converted
from CH4 scfm into g/s using a molar volume of 40.87 mol m~3
and summed by site. Measurements from the ERG study15
were matched with the corresponding monthly production
values from DI Desktop (Drillinginfo, Austin, TX) based on the
recorded Entity ID. Production values for the sites measured by
Allen et al.16 were reported by the well operators to the study
team.
¦ RESULTS AND DISCUSSION
Description of Sites with Repeat Measurements. The
OTM 33A mobile inspection approach was used to identify and
assess CH4 emissions from roadway proximate well pads with
an average in-plume concentration enhancement over back
ground >0.1 ppm. No attempt was made to measure or
statistically account for well pads with apparently low (and thus
difficult to measure) emissions. In many cases, infrared camera
videos (examples in Supporting Information (Si) Supplemental
B) acquired from off-site observing locations, simultaneously
with the CH4 measurements, helped to identify specific
emission sources. Storage tank-related emissions were
frequently observed. The emission rates and video examples
presented here may not be representative of current conditions
due to engineering advancements, changes in work practices,
and the implementation of new state regulations.
To improve understanding of both technique and source
variability, repeat measurements (three or more) were made at
nine sites in the Pinedale Basin, with the number of
measurements per site ranging from 3 to 21 (SI Table Si).
The consistent winds and lack of obstructions in the Pinedale
Basin create favorable conditions for OTM 33A Measurements
were made in different years at four of these sites (Figure l),
and the time between measurements ranged from <1 day to
732 days (SI Table Si). For sites A—G, the 95% CI for the
geometric mean was less than 1 g/s while at sites H and I, large
variations in emissions were observed, resulting in a CI > 2 g/s
(SI Table Si).
The results indicate that while relatively low emissions (<2
g/s) frequently persist over time, the larger emissions observed
using OTM 33A are likely episodic in nature. One source of
persistent low-level emissions observed with the infrared
camera is believed to be a vented produced water tank at Site
C (SI Video Si). Previous studies have shown that flashing
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10-
ST
s
i
O 5-
0-
Figure 1. CH4 emission rates (g/s) measured at repeated sites in
Pinedale, WY by year.
from a condensate tank after a separator dump can result in
episodic large emissions.6 CH4 emissions greater than 2 g/s
were observed at 13% of the 210 unique sites measured. The
variability of emission rates at sites H and I indicates that these
larger emissions may be episodic events that cannot be used to
infer annual emission rates without a greater understanding of
their frequency and duration (Figure l).
Site I was measured on four separate days in 2012. On each
of the days, the emissions appeared to originate from the same
tank. Infrared videos indicate that all of the emissions >3.0 g/s
occurred during the time period that a thief hatch on a
condensate tank was open (SI Video S4, Video S5, and Video
S6). On the last day the site was measured, the thief hatch was
closed and the measured emissions seemed to originate from a
pressure relief device and were <3.0 g/s (SI Video S7).
Another potential cause of variation in emissions levels is the
variability in plume capture. Depending on meteorological
conditions, the plume measured can include all of the sources
on the pad or only some of the sources (Figure 2).
Measurements were made at Site H on 3 days in 2012 and 1
day in 2013 (four and two independent emission measure-
ments, respectively). The higher emissions observed were only
present on one of the days in 2012 and originated from the
tank on the north side of the pad (SI Video S2), whereas the
smaller emissions seemed to originate from the southern edge
of the pad (SI Video S3).
Comparisons of CH4 Emissions by Basin and with
Direct Measurement Studies. A total of 318 OTM 33A
measurements that met the data quality criteria were collected.
Of these measurements, 31 were excluded from the analysis
because the measured emissions either did not originate from
routine pad operations (e.g., evidence of active pad
maintenance, pipeline leaks, gas processing plants, etc.) or no
current production data were available, resulting in a total of
210 unique sites. The sites were classified into gas or oil pads
based on the TX Railroad Commission definition of a gas
well25 (>100 Mscf of gas per barrel of hydrocarbon liquids).
Gas pads constituted 93%, 2%, 75%, and 84% of the sites
measured in the Barnett, DJ, Eagle Ford, and Pinedale basins,
respectively. Methane emissions were averaged by site and
month, resulting in a total of 228 combinations of emission and
production values. Due to the small sample size in the Eagle
Ford (n = 4), these measurements were excluded from the
basin comparison (Figure 3). CH4 emissions were log-normally
distributed with geometric means and 95% confidence intervals
(CIs) of 0.33 (0.23, 0.48), 0.14 (0.11, 0.19), and 0.59 (0.47,
0.74) g/s in the Barnett, Denver-Julesburg, and Pinedale basins,
respectively. Emissions by basin were compared using a
Kruskal—Wallis one-way analysis of variance test and pairwise
Wilcoxson rank-sum tests and were found to be significantly
different (p < 0.05). The differences in emissions between
basins are likely a result of a combination of factors, including
but not limited to variations in gas and oil production,
emissions control devices, and natural gas and oil composition.
The OTM 33A measurements were compared with the
results of the direct measurement studies of routine pad
operations conducted by ERG15 and Allen et a!."' (Figure 3).
The studies encompass a range of pads that vary with respect to
oil and gas composition, production levels, amount and type of
production equipment, age, and emission control measures,
resulting in a broad distribution of emissions. The mean of the
CH4 emissions measured using OTM 33A in the Barnett Shale,
0.33 (0.23, 0.48) g/s, is more than twice the mean of the
emissions measured by ERG 0.14 (0.11. 0.18) g/s. Never-
theless, the interquartile range of the OTM 33A measurements
in the Barnett falls within the interquartile range of the ERG
emissions estimates despite the differences in the measurement
methods and the bias toward higher-emitting sites in the OTM
33A measurements.
Both onsite and remote measurement techniques can
provide important information on emissions. Whereas direct
measurements can accurately quantify component-level emis-
sions, they are less amenable to locating and assessing
malfunction-related or large short-term emissions such as
condensate tank flashing. The measurements by Allen et al.16
were limited primarily to equipment leaks, pneumatic
controllers, and chemical injection pumps. Condensate tank
emissions were measured at some sites but rarely could all of
the emission points be accessed. In the ERG study, 5 due to
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Figure 2. Map of repeated measurements at sites H and I. The directions of the colored arrows indicate mean wind directions and the locations
indicate the locations of the mobile platform during the measurement.
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1.0000'
w
ci3
CL
"g 0.0100'
LU
g 0.0001
n = 43
Allen etal. (2013)
0.1'
n = 58
0.13*
I
n = 21
0.15^
n = 17
0.03j
ERG (2011)
n = 295
0.14»
I I I I
Appalachian Gulf Coast MidcontinentRocky Mountain Barnett
Basin
This study (OTM 33A)
n = 43
t
n = 74 n = 107
0.33*
Barnett
DJ
¦
i
0.59*
0.14»
l
Pinedale
Figure 3. Comparison of measured CH+ emissions per pad (g/s) from Allen et a].,16 ERG,13 and OTM 33A by basin. Boxes represent the 1st and
3rd quartiles of the data, while whiskers extend to the largest measurement that is within 1.5 times the interquartile range (IQR). Means and 95% CIs
are shown in black and were calculated using a nonparametric bootstrap.
lack of condensate production, flash emissions were not
represented. Although both studies measured fugitive compo-
nent leaks, neither identified or measured potentially larger
maintenance-related emissions (e.g., open thief hatch or failed
pressure relief value). In contrast, OTM 33A measurements
generally represent an integrated plume including all potential
sources on a pad. Supporting infrared camera footage from the
OTM 33A studies indicated that emissions often originate from
condensate storage tanks which have previously been shown to
comprise a significant source6'"1 (SI Supplemental B). OTM
33A is also more likely to capture malfunction-related CH4
releases than direct measurement methods because of its
mobile and off-site measurement capabilities.
However, the remote nature of the OTM 33A method and
its application in these studies to only sites with downwind
average in-plume concentrations greater than 0.1 ppm result in
an effective lower sampling limit of approximately 0.010 g/s,
compared with <0.001 g/s limits for the on-site measurement
techniques (Figure 4a). As a result, the OTM 33A measure-
ments only represent the upper end of the distribution in this
comparison (Figure 4b).
Comparison of Measurements with Production
Values. CH4 emissions from the direct measurement studies
and OTM 33A were compared to monthly gas production
using a linear regression on the log transformed data (Figure
5). Sites with gas production <1 Mscf/day or CH4 emissions
<0.0005 g/s were excluded from the analysis (five sites in the
ERG study15). Gas production values explained more of the
variation in the OTM 33A measurements than the measure-
ments from the on-site studies, although variation in gas
production still accounted for only 8.396 of the total variation in
emissions (R1 = 0.083) (Figure 5).
The OTM 33A CH4 emission estimates were also compared
with hydrocarbon liquids and water production and the
(arithmetic) mean age of active permitted wells on the site
using Pearson correlation coefficients (Table l) and a
multivariate linear regression.
Approximately 23% and 15% of the pads measured using
OTM 33A reported no hydrocarbon liquids or water
production, respectively. To use these pads in the log-
transformed model, pads with no reported oil or water
production were assigned 0.01 bbl/day. Several values were
Allen etal. (2013)
ERG (2011) — This study (OTM 33A)
0.0 -
0.001
-| 1 r
0.010 0.100 1.000 10.000
1.00
'en
c
0
o
0
>
iS
=5
E
zs
o
0.75
0.50
0.25
0.00
-i 1 r
0.001 0.010 0.100
CH4 Emitted Per Site (g/s)
l r
1.000 10.000
Figure 4. Density (a) and cumulative density (b) of measurements of
CH4 emission rates (g/s) from this study (OTM 33A), Allen et al.,16
and ERG.13 Note the logarithmic x-axis.
tested and the choice of this value did not significantly affect
the results. When considering the correlation between
production and emissions individually, CH4 emissions were
most strongly correlated with gas production (R = 0.29). CH4
emissions were also positively correlated with water production,
negatively correlated with mean age, and not correlated with
hydrocarbon liquids production (Table l).
A multivariate linear regression was conducted to determine
the effect of gas and hydrocarbon liquids production and age of
the well on CH4 emissions simultaneously. Water production
was not included in the model because it was so highly
correlated with gas production (R > 0.7) that the effects could
not be separated. The following model was used:
l°g(CH4) = /^log (gas) + /?2log(oil) + /?3age
(1)
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Environmental Science & Technology
Article
~a
0)
E
LU
v
I
o
1.00-
0.01 -
Allen etal. (2013)
ERG (2011)
This study (OTM 33A)
R2 = 0.055
R2 = 0.031
R2 = 0.083
* . • »-*2
V +\\
* • \ • •
# «• • •
» • • • ••
* * #
• • —•
•
V*V" • •
I •
10
1000 100000 10 1000 100000 10
Gas Production (Mscf/day)
1000
100000
Figure 5. CH4 emissions (Mscf/day) versus reported monthly gas production (Mscf/day). Blue lines represent the linear regression lines.
Table 1. Pearson Correlation Coefficients (R) of Emissions
and Production
ch4
emissions
(Mscf/
day)
gas
production
(Mscf/ day)
hydrocarbon
liquids
production
(bbl/day)
water
production
(bbl/day)
CH4 emissions
(Mscf/ day)
1.00
gas production
(Mscf/ day)
0.29
1.00
hydrocarbon
liquids
production
(bbl/day)
-0.01
0.44
1.00
water production
(bbl/day)
0.22
0.77
0.40
1.00
mean age (years)
-0.20
-0.59
-0.34
-0.57
where CH4 represents measured emissions in g/s, gas is total
reported production in Mscf/day, oil is total reported
hydrocarbon liquids production in bbl/day, and age is the
mean age of the wells in years. Age was not significantly
correlated with CH4 emissions, while gas production was
significantly positively correlated, and oil production was
significantly negatively correlated (SI Table S2). The negative
correlation with oil production is consistent across the basins
(SI Figure Si). This negative correlation with oil production is
likely due to the lower fraction of CH4 in wet gas compared to
dry gas. Furthermore, emissions from condensate tanks, which
are more prevalent in wet gas areas, typically contain a lower
fraction of CH4 and higher fraction of heavier hydrocarbons
such as VOCs when compared with produced gas.6 The
inclusion of hydrocarbon liquids and age in the model did not
explain much more of the variation in emissions resulting in an
adjusted R1 of only 0.096, in contrast to an R1 of 0.083 when
only gas production was included (Figure 5).
Other important sources of variation not accounted for in
this analysis include emissions controls and equipment present
on the pads. Further uncertainty is introduced by the
production data: daily or hourly production levels may not
be consistent with monthly production.
Although the OTM 33A CH4 emissions data include episodic
features (e.g., flash emissions), it is instructive to compare
emission rates as a ^percent of production with the measure-
ments by Allen et al. and ERG. 5 The differences between the
CH4 emissions estimates of the three studies are amplified
when emissions are considered as a percentage of total
production rather than in mass emission rate (SI Figure S2).
For the sites measured using OTM 33A, approximately 0.72
14513
(0.44, 1.17)%, 1.36 (0.97, 1.95) %, and 0.58 (0.39, 0.86) % of
production was emitted on average (with 95% CI) in the
Barnett, DJ, and Pinedale basins, respectively, compared with
0.11 (0.09, 0.16)% of production measured by ERG15 in the
Barnett shale and 0.01 (0.01, 0.01) % and 0.09 (0.04, 0.20)%
measured by Allen et al.16 in the Appalachian and Rocky-
Mountain basins, respectively (SI Figure S2). As evidenced in
the statistical analysis, differences in production rate explain
only a fraction of the variation in emissions. The percentages
from this study only represent emissions from routine well pad
operations and thus cannot be directly compared to other
estimates of total CH4 emitted as a percent of production such
as those by Brandt et al.5 that include emissions from many
other processes.
Mean gas production at the OTM 33A sites was significantly
lower than mean gas production at the sites measured in the
direct measurement studies (SI Figure S4). Gas production at
the OTM 33A sites ranged from 3.7 (Mscf/day) to 9021
(Mscf/day) with 37% of the sites producing <100 Mscf/day. In
contrast, Allen et al.16 reported a gas production range of 20 to
47 690 (Mscf/day) with only 10% of the sites producing <100
Mscf/day and with approximately 20% of the measured sites
producing >10,000 Mscf/day. The gas production values of the
ERG15 sites ranged from 0.06 to 9085 Mscf/day in the Barnett
with 10% of the sites producing <100 Mscf/day (SI Figure S4).
The OTM 33A results indicate that sites with very low gas and
oil production can emit a much greater fraction of the gas
produced than sites with higher production levels. Maintenance
issues (e.g., fugitive leaks, open or leaking thief hatches, failed
pressure relief devices, malfunctioning separator dump valves)
could be more prevalent at smaller older production sites than
at higher producing sites that are potentially better maintained
and may have fundamentally different engineering designs (e.g.,
use of buffer tanks to suppress flash emissions). Furthermore,
many of the fugitive processes can emit at levels that are not
linearly associated with production rates as is evidenced by the
lack of correlation between emissions and production and the
finding by Allen et al.16 that equipment leaks are under-
estimated by the 2011 EPA national inventory.
In summary, the OTM 33A mobile inspection method can
be used to complement direct measurement techniques and
expand our knowledge of the upper range of the distribution of
CH4 emissions. OTM 33A was successfully applied to quantify
CH4 emissions at 210 oil and gas well pads with an accuracy of
±60% determined by controlled release tests. Well pad
emissions were log-normally distributed and differed signifi-
cantly by basin with geometric means ranging from 0.14 g/s in
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Environmental Scienc inology
the Denver-Julesburg to 0.59 g/s in the Pinedale basin. Repeat
measurements at 9 sites indicated consistent low emission rates
at seven sites and highly variable emissions at two sites, one a
documented malfunction. The production rates accounted for
approximately 10% of the variation in sampled emission rates in
a multivariate linear regression on age, hydrocarbon liquid and
gas production. Normalizing emissions by gas production
amplified the differences between the remote and onsite
measurements. Compared to the direct measurements in the
Barnett, the mean of the remote measurements was
approximately twice as large in terms of mass emissions rate,
but approximately seven times as large when considered as a
percentage of production, indicating that sites with lower
production levels can emit a much greater percentage of
production. Infrared camera videos indicate that emission rates
may be strongly affected by stochastic variables. In particular,
equipment malfunctions or operator error may cause emission
rates to increase substantially compared to routine operating
conditions. Accurately estimating site emissions on a regional
scale likely will require determining the average magnitude and
frequency of these stochastic events.
CONTENT
Q Supporting Information
Supplemental figures, tables, and IR videos are supplied. This
material is available free of charge via the Internet at http://
pubs.acs.org.
10ft INFORMATION
Corresponding Author
*Phone: 1-919-541-7969; fax: 1-919-541-0359; e-mail: thoma.
eben(S>epa.gov.
Notes
The authors declare no competing financial interest.
#On Oak Ridge Institute of Science and Education Fellowship.
te? aCKNOWLEDGMS 1
We thank Shahrooz Amin and Mark Modrak with ARCADIS,
Inc., for field and data analysis support for this project. We
would like to thank EPA colleagues Bill Mitchell, Adam Eisele,
Mike Miller, Jason DeWees, Robin Segall, and Ken Garing and
his team for ongoing support in development of OTM 33.
Special thanks to Eric Crosson, Chris Rella, and Tracy Tsai
with Picarro for ongoing collaboration on mobile measure-
ments. Primary funding for this effort was provided by U.S.
EPA ORD's Air, Climate, and Energy (ACE) and Regional
Applied Research Effort (RARE) programs. Funding for the
Environmental Defense Fund's methane research series,
including this work, is provided for by Fiona and Stan
Druckenmiller, Heising-Simons Foundation, Bill and Susan
Oberndorf, Betsy and Sam Reeves, Robertson Foundation,
Alfred P. Sloan Foundation, TomKat Charitable Trust, and the
Walton Family Foundation. The views expressed in this article
are those of the authors and do not necessarily represent the
views or policies of the U.S. Environmental Protection Agency.
¦ REFERENCES
(1) Moore, C. W.; Zielinska, B.; Petron, G.; Jackson, R. B. Air
impacts of increased natural gas acquisition, processing, and use: A
critical review. Environ. Sci. Technol. 2014; DOI: 10.1021/es4053472.
(2) Roy, A. A.; Adams, P. J.; Robinson, A L. Air pollutant emissions
from the development, production, and processing of Marcellus Shale
natural gas. /. Air Waste Manage. Assoc. 2014, 64 (l), 19—37
DOI: 10.1080/10962247.2013.826151.
(3) CenSARA, 2011 Oil and Gas Emission Inventory Enhancement
Project for CenSARA. States prepared for: Central States Air Resources
Agencies 2011. http://www.censara.org/filedepot_download/S6064/
14 (accessed September 17, 2014).
(4) Field, R. A.; Soltis, J. J.; Murphy, S. Air quality concerns of
unconventional oil and natural gas production. Environ. Sci.: Processes
Impacts 2014, 16, 954-969 DOI: 10.1039/C4EM00081A.
(5) Brandt, A.; Heath, G.; Kort, E.; O'Sullivan, F.; Petron, G.;
Jordaan, S.; Tans, P.; Wilcox, J.; Gopstein, A; Arent, D. Methane leaks
from North American natural gas systems. Science 2014, 343 (6172),
733-735 DOI: 10.1126/science.l247045.
(6) Hendler, A.; Nunn, J.; Lundeen, J.; McKaskle, R. VOC Emissions
from Oil and Condensate Storage Tanks-, Houston Advanced Research
Center, 2006; http://files.harc.edu/Projects/AirQuality/Projects/
H051C/H051 CFinalReport.pdf.
(7) Gidney, B.; Pena, S. Upstream Oil and Gas Storage Tank Project
Flash Emissions Models Evaluation Final Report; Texas Commission on
Environmental Quality: Austin, TX, 2009; http://www.bdlaw.com/
assets/htmldocuments/
TCEQ_%20Final%20Report%200il%20Gas%20Storage%20Tank%20
Project.pdf.
(8) U.S. EPA. Greenhouse Gas Reporting Rule Subpart W, Petroleum
and Natural Gas Systems; Public Law 78 FR 71904, 2013; http://www.
gpo.gov/fdsys/pkg/FR-2013-ll-29/pdf/2013-27996.pdf.
(9) U.S. EPA. Inventory of U.S. Greenhouse Gas Emissions and Sinks:
1990-2011; EPA 430-R-13-001, 2013; http://www.epa.gov/
climatechange/Downloads/ghgemissions/US-GHG-Inventory-2013-
Main-T ext.pdf.
(10) U.S. EPA. EPA Needs to Improve Air Emissions Data for the Oil
and Natural Gas Production Sector; Report No. 13-P-0161; U.S.
Environmental Protection Agency Office of Inspector General:
Washington DC, 2013; http://www.epa.gov/oig/reports/2013/
20130220-13-P-0161.pdf.
(11) Snyder, E. G.; Watkins, T. H.; Solomon, P. A; Thoma, E. D.;
Williams, R. W.; Hagler, G. S.; Shelow, D.; Hindin, D. A; Kilaru, V. J.;
Preuss, P. W. The changing paradigm of air pollution monitoring.
Environ. Sci. Technol. 2013, 47 (20), 11369-11377 DOI: 10.1021/
es4022602.
(12) Caulton, D. R.; Shepson, P. B.; Santoro, R. L.; Sparks, J. P.;
Howarth, R. W.; Ingraffea, A. R.; Cambaliza, M. O.; Sweeney, C.;
Karion, A.; Davis, K. J. Toward a better understanding and
quantification of methane emissions from shale gas development.
Proc. Natl. Acad. Sci. U. S. A. 2014, 111 (17), 6237-6242
DOI: 10.1073/pnas.l316546111.
(13) Karion, A; Sweeney, C.; Petron, G.; Frost, G.; Michael
Hardesty, R.; Kofler, J.; Miller, B. R.; Newberger, T.; Wolter, S.; Banta,
R. Methane emissions estimate from airborne measurements over a
western United States natural gas field. Geophys. Res. Lett. 2013, 40
(16), 4393-4397 DOI: 10.1002/grl.50811.
(14) Thoma, E.; Squier, B.; Olson, D.; Eisele, A.; DeWees, J.; Segall,
R.; Amin, M.; Modrak, M. Assessment of methane and voc emissions
from select upstream oil and gas production operations using remote
measurements, interim report on recent survey studies. In Proceedings
of 1 OSth Annual Conference of the Air & Waste Management Association,
Control No. 2012-A-21-AWMA, 2012, 298-312.
(15) ERG. City of Fort Worth Natural Gas Air Quality Study Final
Report; Fort Worth, TX, 2011. http://fortworthtexas.gov/gaswells/
?id=87074.
(16) Allen, D. T.; Torres, V. M.; Thomas, J.; Sullivan, D. W.;
Harrison, M.; Hendler, A; Herndon, S. C.; Kolb, C. E.; Fraser, M. P.;
Hill, A D. Measurements of methane emissions at natural gas
production sites in the United States. Proc. Natl. Acad. Sci. U. S. A.
2013, 110 (44), 17768-17773 DOI: 10.1073/pnas.l304880110.
(17) U.S. EPA Other Test Method (OTM) 33 and 33A Geospatial
Measurement of Air Pollution-Remote Emissions Quantification-
Direct Assessment (GMAP-REQjDA). 2014. (http://www.epa.gov/
ttn/emc/prelim.html).
14514
dx.doi.org/10.1021/es503070q I Environ. Sci. Technol. 2014, 48, 14508-14515
26 of 75 38 of 87
-------
Environmental Scienc i no logy
(18) Golder, D. Relations among stability parameters in the surface
layer. Bound.-Lay. Meteorol 1972, 3 (l), 47-58 DOI: 10.1007/
BF00769106.
(19) Google Inc. Google Earth Pro (Version 7.1.2.2041), 2014.
(20) ESRL ArcGIS Desktop: Release JO; Environmental Systems
Research Institute: Redlands, CA, 2011.
(21) Public GIS Map Viewer for Oil, Gas, and Pipeline Data, http: //
wwwgisp.rrc.state.tx.us/GISViewer2/ (April 22, 2014),.
(22) COGCC GIS Online, http://dnrwebmapgdev.state.co.us/
mg2012app/ (accessed April 22, 2014).
(23) R Core Team R: A Language and Environment for Statistical
Computing; R Foundation for Statistical Computing: Vienna, Austria,
2013.
(24) Wickham, H. ggplot2: Elegant Graphics for Data Analysis;
Springer: New York, 2009.
(25) Harrell Jr, F. E.; Dupont, C. Hmisc R package version 3.14-1.
2007.
(26) TX RRC. Texas Administrative Code. Title 16 Part 1 Chapter 3
Rule §3.79, Railroad Commission of Texas, Oil and Gas Division:
Austin, TX, http://info.sos.state.tx.us/pls/pub/readtac$ext.
TacPage?sl=R&app=9&p_dir=&p_rloc=&p_tloc=&p_ploc=&pg=
1 &p_tac=&ti=16&pt= 1 &ch=3&rl=79.
14515
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CSIRO ENERGY TECHNOLOGY
www.csiro.au
Field Measurements of Fugitive
Emissions from Equipment and
Well Casings in Australian Coal
Seam Gas Production Facilities
Report to the Department of the Environment
Stuart Day, Mark Dell'Amico, Robyn Fry and Hoda Javanmard Tousi
June 2014
28 of 75 40 of 87
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Day, S., Dell'Amico, Fry, R., Javanmard Tousi, H., (2014). Field Measurements of Fugitive Emissions from
Equipment and Well Casings in Australian Coal Seam Gas Production Facilities. CSIRO, Australia.
© 2014 CSIRO To the extent permitted by law, all rights are reserved and no part of this publication
covered by copyright may be reproduced or copied in any form or by any means except with the written
permission of CSIRO.
CSIRO advises that the information contained in this publication comprises general statements based on
scientific research. The reader is advised and needs to be aware that such information may be incomplete
or unable to be used in any specific situation. No reliance or actions must therefore be made on that
information without seeking prior expert professional, scientific and technical advice. To the extent
permitted by law, CSIRO (including its employees and consultants) excludes all liability to any person for
any consequences, including but not limited to all losses, damages, costs, expenses and any other
compensation, arising directly or indirectly from using this publication (in part or in whole) and any
information or material contained in it.
29 of 75 41 0f 87
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Contents
• ¦ ¦¦¦ ' iii
1 Introduction 1
2 ¦¦¦¦¦¦::¦; ¦ 4
3 : /
3.1 ^ /
3.2 ¦. : 8
3.3 ¦¦¦¦¦:¦ • 9
3.4 ' : 10
3,'j : 12
4 ¦ 14
4.1 : :: ¦¦¦.:.¦¦ 14
4.2 : ¦ 14
4.3 : 2B
lJ ¦ •¦ ¦¦ : 30
lJ,l ' 34
{> 36
. 3/
Field Measurements of Fugitive Emissions from Equipment and Well Casings in Australian Coal Seam Gas Productio^a^'i^es
-------
Acknowledgements
We gratefully acknowledge the CSIRO Energy Flagship and Department of the Environment for providing
financial support for this project. The project would not have been possible without the cooperation of the
CSG industry and the numerous company staff who provided assistance and advice. In particular we would
like to thank Sally Oelerich, Tom Lawler and Aaron Clifton of AGL, Jenny Bright and Ben McMahon of Arrow
Energy, Graeme Starke of QGC, Liz Beavis, Michael Boyle, Mark Rider and Dan O'Sullivan of Origin Energy,
and Anshul Jain, Michael Roberts, and Rob Dunsmuir of Santos.
ii | Field Measurements of Fugitive Emissions from Equipment and Well Casings in Australian Coal Seam Gas Production Facilities f7E.
ji or 43 of 87
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Executive Summary
The Australian coal seam gas (CSG) industry has developed rapidly over the last decade and as several
liquefied natural gas (LNG) plants currently under construction in Queensland are completed, gas
production will increase significantly over the next few years. Fugitive emissions of methane from gas
production and processing have the potential to diminish the greenhouse benefits of CSG utilisation
compared to other fossil fuels but at present the extent of fugitive emissions from the CSG industry and
unconventional gas production more generally is not well understood. Recent reports from the United
States have suggested that fugitive emissions from unconventional gas production, especially shale and
tight gas, are much higher than previously estimated. However, because of significant differences in
production methods and other factors, it is unlikely that emission estimates from U.S. shale and tight gas
production are indicative of emissions from Australian CSG operations. To provide quantitative information
on emissions from CSG operations, CSIRO and the federal Department of the Environment initiated a
project to measure emissions from a range of production wells in Queensland and NSW.
Methane emissions were measured at 43 CSG wells - six in NSW and 37 in Queensland. Measurements
were made by downwind traverses of well pads using a vehicle fitted with a methane analyser to determine
total emissions from each pad. In addition, a series of measurements were made on each pad to locate
sources and quantify emission rates.
Of the 43 wells examined, only three showed no emissions. These were two plugged and abandoned wells
and one suspended well that had been disconnected from the gas gathering system. The remainder had
some level of emission but generally the emission rates were very low, especially when compared to the
volume of gas produced from the wells. The principal methane emission sources were found to be:
• venting and operation of gas-powered pneumatic devices,
• equipment leaks and
• exhaust from gas-fuelled engines used to power water pumps.
The median methane total emission rate (from all sources) for the 43 wells was approximately 0.6 g min"1,
and the mean about 3.2 g min"1. Thirty seven wells had total emissions less than 3 g CH4 min"1 and 19 less
than 0.5 g min"1. There were however, a number of instances where much higher emission rates were
found. The highest emission rate of 44 g min"1 was from a vent on a water line at one well although this
represented a very minor proportion of gas production. These emission rates are very much lower than
those that have been reported for U.S. unconventional gas production.
Gas operated pneumatic devices were installed at some well sites and were occasionally found to be
emitting small amounts of methane. These emissions were small (mean emissions rate of 0.12 g min"1) and
may reduce even further as gas operated pneumatic systems are replaced by air or electrically operated
devices.
Equipment leaks were found on 35 wells with emission rates ranging from less than 1 mg min"1 up to about
28 g min"1. The median and mean emission rates from these wells were 0.02 g min"1 and 1.6 g min"1, which
correspond to emission factors of about 0.1 kg C02-e t"1 and 2.4 kg C02-e t"1, respectively. This range is
consistent with the current emission factor of 1.2 kg C02-e t"1 commonly used throughout the CSG industry
to account for equipment leaks for the purposes of reporting emissions under the National Greenhouse and
Energy Reporting legislation.
Several of the larger equipment leaks were found at seals on water pump shafts on some wells. However,
once identified, well maintenance staff were able to repair some of these leaks on site, which effectively
eliminated methane emissions.
Fifteen of the well sites had gas fuelled engines operating at the time measurements were made. The
exhaust from most of these engines was found to be contributing to the well site emissions, in several cases
Field Measurements of Fugitive Emissions from Equipment and Well Casings in Australian Coal Seam Gas Production^cjlitigs | ^
-------
comprising the bulk of methane emissions. From a greenhouse gas accounting perspective, methane in
exhaust is not considered to be a fugitive emission but is counted as a combustion emission.
During the field measurements, no evidence of leakage of methane around the outside of well casings was
found at any of the wells included in this sample.
Although the well pad emissions were low, a separate, larger source of methane was found on a gas relief
vent on a water gathering installation close to one of the wells examined during this study. An indicative
estimate of the emission rate from this vent suggested that the source was at least three times higher than
the largest well pad emission rate. Similar installations are widespread through the Queensland gas regions
and hence further examination is needed to determine the extent of this potential emission source.
The results obtained in this study represent the first quantitative measurements of fugitive emissions from
the Australian CSG industry; however, there are a number of areas that require further investigation.
Firstly, the number of wells examined was only a very small proportion of the total number of wells in
operation. Moreover, many more wells are likely to be drilled over the next few years. Consequently the
small sample examined during this study may not be truly representative of the total well population. It is
also apparent that emissions may vary over time, for instance due to repair and maintenance activities. To
fully characterise emissions, a larger sample size would be required and measurements would need to be
made over an extended period to determine temporal variation.
In addition to wells, there are many other potential emission points throughout the gas production and
distribution chain that were not examined in this study. These include well completion activities, gas
compression plants, water treatment facilities, pipelines and downstream operations including LNG
facilities. Emissions from some of these sources are often estimated for reporting purposes using
methodology based on emission factors largely derived from the U.S. gas industry. However, reliable
measurements on Australian facilities are yet to be made and the uncertainty associated with some of
these estimates remains high.
iv | Field Measurements of Fugitive Emissions from Equipment and Well Casings in Australian Coal Seam Gas Production Facilities _____
jj or /b 45 of 87
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Coal seam gas (CSG) production is a major and rapidly expanding industry in Australia. During 2011-2012,
Australian CSG production was around 247 PJ, which represented about 12 % of total gas production in
Australia (BREE, 2013). Since then, production in Queensland alone has increased to more than 264 PJ in
2012-2013 (DNRM, 2014) with production likely to increase even further as several liquefied natural gas
plants under construction come on stream. Most Australian CSG is currently produced in Queensland with
only one operational project in NSW; however, there are a number of other projects planned for NSW at
various stages of approval.
One of the key drivers of increased demand for gas is that greenhouse gas emissions from gas utilisation
are usually lower than other fossil fuels (Day et al., 2012). However, because of the much higher global
warming potential of methane compared to C02, even relatively small proportions of fugitive methane
released during the production, processing and distribution of natural gas can reduce this advantage
relative to other fuels (e.g. Wigley, 2010; Alvarez et al., 2012).
In the natural gas industry, fugitive emissions are considered to include all greenhouse gas emissions from
exploration, production, processing, transport and distribution of natural gas, except those from fuel
combustion (IPCC, 2006). However certain combustion processes like flaring and waste gas incineration are
also counted as fugitive emissions.
At present the level of fugitive emissions from the Australian CSG industry is not well defined, although
individual companies estimate and report their annual emissions under the requirements of the National
Greenhouse and Energy Reporting Act 2007 (NGER, see Section 2). These data are used for compiling the
Australian National Greenhouse Gas Inventory which currently estimates fugitive emissions from the
Australian oil and gas industry to be around 12 Mt C02-e per annum (DIICCSRTE, 2013a). About 60 % of
these emissions are attributed to venting and flaring, which are in principle amenable to direct
measurement; hence the uncertainty on this component may be relatively low. However, other sources
such as equipment leaks are frequently difficult to measure so are usually estimated by methodology
characterised by very high uncertainty. Despite significant differences in production methods, the national
inventory does not at present distinguish between conventional gas production and unconventional
sources like shale gas and CSG.
In 2012, the CSIRO reviewed the available scientific and technical literature to assess the current state of
knowledge relating to fugitive emissions from unconventional gas production, especially for CSG production
in Australia (Day et al., 2012). Most of the information in the public domain at the time was concerned with
shale and tight gas production in the United States with virtually none specific to CSG. Up until then, only
one study based on actual measurements had been published (Petron et al., 2012). This group measured
methane emissions in the Denver-Julesburg Basin in Colorado and depending on the method used,
estimated that the emission rate from the gas field was equivalent to 1.7 to 7.7 % of the gas produced in
the region.
Since 2012, several other studies, also from the United States, have been published. Karion et al. (2013)
conducted an airborne survey of ambient methane in an unconventional gas field in the Uintah Basin in
Utah in the United States. The Karion et al. study yielded emission estimates of between about 6 and
almost 12 % of gas production of the region. In a detailed examination of atmospheric methane data from
airborne and fixed monitoring stations, Miller et al. (2013) determined the spatial distribution of methane
emissions throughout the United States. This study considered all sources of anthropogenic methane
emissions, including fugitive emissions from oil and gas production. For the Texas/Oklahoma region
emissions from oil and gas production were estimated to be 3.7 ± 2.0 Tg C y"1, which is 4.9 ± 2.6 times
higher than the current estimate of 0.75 Tg C y1 in the European Commission's Emissions Database for
Global Atmospheric Research (EDGAR).
Field Measurements of Fugitive Emissions from Equipment and Well Casings in Australian Coal Seam Gas Production^cijit^s |
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Both the Miller et al. (2013) and Karion et al. (2013) studies used top-down methodology and did not
attempt to determine the specific sources of the methane emissions. Petron et al. (2012) also used top-
down methods which yielded the higher estimates (i.e. ~7.7 % of production) although the bottom-up
methodology used by that group gave much lower emission estimates (1.7 %). A bottom-up approach was
used by Allen et al. (2013) who examined emissions at the facility level to determine both the rate and
route of methane emission. In that study, methane emissions were measured at 190 onshore natural gas
sites within the United States, which included 489 production wells (all of which had been hydraulically
fractured), 27 well completion flowbacks, nine well unloadings, and four well workovers. One of the key
findings of this work was that the measured emissions were generally comparable to the most recent
USEPA estimates of emissions from the sources examined, although the relative proportion of emissions
from individual categories differed somewhat. For example, emissions from pneumatic devices were
significantly higher than current estimates while emissions from well completions were much lower than
estimates in the U.S. inventory. Overall, the emissions estimated from the unconventional gas industry
corresponded to about 0.42 % of production.
This bottom-up estimate contrasts with the much higher top-down estimates discussed above. The lower
emission rate estimated by Allen et al. (2013) may be explained in part by the fact that only production
facilities were considered. Emissions from downstream processing, transport and distribution were not
included so any emissions from these facilities would be expected to increase this proportion. Another
reason for the discrepancy between bottom-up and top-down estimates has been proposed by Brandt et
al. (2014) who suggested that a large proportion of emissions may be due to a small number of 'super
emitters'. If true, facility level bottom-up measurements may sometimes miss these large emission sources.
In addition to gas production facilities, other sources may be contributing to overall emissions, which are
not captured by the bottom-up methods. Tait et al. (2013), for example, proposed that drilling and
associated activity may induce fracturing of overlying strata thus providing pathways for methane to reach
the surface and escape to the atmosphere. Such landscape-scale emissions would be detected by many
top-down methods but may be difficult to measure using the bottom-up methodology applied by Allen et
al. (2013). However, the Tait et al. (2013) model was based on ambient radon measurements; methane
emission rates were not measured so this emission route remains speculative at this stage. Other possible
emission sources that could account for the apparent discrepancy between the reported top-down and
bottom-up methods are geological sources such as seeps that are often associated with oil and gas fields
(Klusman, 1993) or abandoned boreholes (Etiope et al., 2013; Day et al., 2013).
In Australia, limited investigations into fugitive methane emissions from CSG production have been
undertaken over the last couple of years. In an initial study that was widely reported, Santos and Maher
(2012) surveyed a CSG production region near Tara in Queensland using an instrumented vehicle to
measure the spatial distribution of ambient methane concentrations. They measured elevated methane
concentrations within the gas field that they suggested may be indicative of fugitive methane release from
production activities. More recently, a study of ambient methane levels in the vicinity of CSG production
facilities south of Sydney was reported (Pacific Environment Limited, 2014). This study also found elevated
methane concentrations near CSG facilities although they concluded that on average, ambient methane
concentrations within the gas field were comparable to those in a nearby urban area. However, neither
study attempted to measure emission flux and in any case, the presence of other potential methane
sources such as cattle feedlots, abandoned boreholes and landfill sites complicated the interpretation of
the results. Consequently attempts to attribute sources based on these results remain inconclusive.
Despite the level of recent activity aimed at quantifying emissions from unconventional gas production, the
situation remains unclear. The Australian studies reported to date only considered ambient methane
concentrations near gas production sites and provide no information on emission flux. While the U.S.
studies measured emission rates, widely varying estimates were reported. Moreover, they were concerned
with shale and tight gas operations, which are unlikely to be indicative of emissions from Australian CSG
production facilities. Due to the lack of quantitative emission data specific to Australian operations, the
CSIRO review recommended, among other things, that a series of measurements at CSG production
facilities was required to better understand the actual level of fugitive emissions from the Australian CSG
2 | Field Measurements of Fugitive Emissions from Equipment and Well Casings in Australian Coal Seam Gas Production Facilities f 7J- A £ ->-7
OO OT (D 47 Qf g J
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industry (Day et al., 2012). A similar recommendation for emissions measurements was made by Saddler
(2012) when reviewing methodology for estimating emissions from CSG production.
As a result of these recommendations, CSIRO initiated a project with the principal aims of (1) developing
atmospheric top-down methodology for monitoring and quantifying methane fluxes from CSG production
facilities and (2) measuring methane emission fluxes from operational CSG production sites. Shortly after
this project commenced, the federal Department of the Environment (then the Department of Climate
Change and Energy Efficiency) requested that CSIRO to extend the scope of the field measurements to
include an investigation of gas leakage from well casings and equipment located on individual well pads.
In this report we present the results of field measurements made at well sites throughout NSW and
Queensland. The specific objectives of these measurements were to:
• quantify methane emissions from individual well pads,
• identify the primary routes of these emissions,
• measure leak rates from individual items of equipment located on well pads and
• determine whether or not methane was leaking from around the outside of well casings and if so,
measure the leakage rate.
While wells represent a major segment of the CSG production infrastructure, it is important to note that
there are many other components downstream of the wells which have the potential to release
greenhouse gases. These include processing and compression plants, water treatment facilities, gas
gathering networks, high pressure pipelines and several LNG production facilities currently under
construction near Gladstone. In the study reported here, we have only examined emissions from a small
sample of CSG wells; none of the other downstream infrastructure has been considered at this stage.
However, the ongoing CSIRO research into atmospheric top-down method methodology is aimed at
developing techniques for monitoring emissions across the CSG industry more broadly.
Field Measurements of Fugitive Emissions from Equipment and Well Casings in Australian Coal Seam Gas Production^acijit^s |^Sg
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2 National Greenhouse Gas leporting Practices
Before discussing the experimental results of the field measurements it is instructive to consider the
methodology currently used to estimate greenhouse gas emissions from CSG wells.
Australian CSG gas producers (along with conventional gas operators) are required to estimate and report
their annual greenhouse emissions in accordance with the National Greenhouse and Energy Reporting Act
2007 using methodology prescribed in the National Greenhouse and Energy Reporting (Measurement)
Determination 2008. The scope of the Act covers all sectors of the gas industry i.e. production and
processing, transmission and distribution, and includes emissions from fuel combustion (e.g. stationary
engines at well sites and compression plants) and fugitive emissions (leaks from equipment, venting and
flaring).
According to the definition used in the Determination, fugitive emissions associated with natural gas
production and processing comprise:
• Emissions from venting and flaring
o the venting of natural gas
o the venting of waste gas and vapour streams at facilities that are constituted by natural gas
production or processing
o the flaring of natural gas, waste gas and waste vapour streams at those facilities
• Emissions other than venting and flaring which include
o a gas wellhead through to the inlet of gas processing plants
o a gas wellhead through to the tie-in points on gas transmission systems, if processing of
natural gas is not required
o gas processing plants
o well servicing
o gas gathering
o gas processing and associated waste water disposal and acid gas disposal activities
The Determination specifies methodology for estimating emissions from all of these sources; the 'Methods'
are broadly classified into four generic categories of varying complexity, which are briefly described below.
• Method 1 is the simplest approach and relies on activity data and an emission factor for the
process. The emission factors used in Method 1 are generic and are usually specified in the
NGER Determination.
• Method 2 is more specific and uses emission factors based on more detailed data.
• Method 3 is very similar to Method 2 except that the methods are based on internationally
accepted standards.
• Method 4 is the direct measurement of emissions.
Some emissions can be directly measured (i.e. Method 4) but often emissions cannot be readily measured
so instead, simpler methodology based on the concept of emission factors is used.
Emission factors are average emission rates of a particular gas (i.e. methane but also C02 and N20 if
applicable) from a given source. Emissions, E, are calculated by multiplying the emission factor, EF, by the
activity of the process producing the emissions, A (Equation 2.1).
E = EF X A Equation 2.1
Examples of activity are the amount of fuel consumed or the amount of gas produced.
This methodology can yield accurate emission estimates for processes such as fuel combustion where both
the emission factor (which is based on the chemical composition of the fuel) and the activity data (i.e.
consumption rate of fuel, which is often known to a high level of accuracy) can be well defined. However,
4 | Field Measurements of Fugitive Emissions from Equipment and Well Casings in Australian Coal Seam Gas Production Facilities f 7J- Ar. £ ->-7
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for some fugitive emissions sources such as equipment leaks, emission factors may be subject to very high
uncertainty. For instance, the American Petroleum Institute's Compendium of Greenhouse Gas Emissions
Methodologies for the Oil and Natural Gas Industry which provides emission factors for calculating
emissions from gas production and processing operations, estimates that uncertainties on some emission
factors may be as much as 1000 % (API, 2009). One of the reasons for this high level of uncertainty is that
emission factors are often based on very limited experimental data.
CSG well pads may release greenhouse gases from a range of sources, all of which are estimated for annual
reporting purposes. These sources include fuel combustion in well site engines used to drive water pumps,
and fugitive emissions from vents, gas operated pneumatic devices and leaks in equipment. Occasionally,
during maintenance operations for example, gas may be flared and this too counts as a fugitive emission
that is accounted for. Combustion emissions from engines or flaring are predominantly C02 although small
amounts of methane (unburnt fuel) and N20 (produced in the combustion process) may also be emitted.
Most of the other non-combustion emissions are methane.
Some emissions from vents can be measured according to Method 4 but because of its simplicity, many
CSG operators use the Method 1 approach for estimating most of the other greenhouse gas emissions from
well pads. The methods are summarised in Table 2.1.
Table 2.1. Summary of NGER estimation methods for various well pad sources
Classification Source Method
Fuel Combustion Exhaust emissions from Emission factor to account
well site engines for C02, CH4 and N20
emissions:
51.2 kg C02-e GJ1 (C02)
0.1 kg C02-e GJ"1 (CH4)
0.03 kg C02-e GJ1 (N20)
Fugitive Emissions Flare Emissions factor to account
for C02, CH4 and N20
emissions:
2.71 C02-e t1 (C02)
0.11 C02-e t1 (CH4)
0.03 t C02-e t1 (N20)
Fugitive Emissions
Equipment leaks
Emission factor of 1.2 kg
C02-e t"1 gas produced
Fugitive Emissions
Gas driven pneumatic
Emission factors specified
equipment
in the API Compendium
(API, 2009)
Fugitive Emissions Cold process vents In some cases these can be
measured directly (i.e.
Method 4). Otherwise
estimated using emission
factors in API Compendium.
Although most of the methods shown in Table 2.1 are based on the use of emission factors, the level of
uncertainty associated with the estimates is quite variable. In the case of emission from engines, the
uncertainty is likely to be relatively low provided the amount of fuel consumed is known accurately (which
is usually the case). Similarly emissions from flaring can be estimated with reasonable accuracy if the gas
Field Measurements of Fugitive Emissions from Equipment and Well Casings in Australian Coal Seam Gas Production^cijit^s g~J
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flow to the flare is measured. Emissions from vents are often measured using process instrumentation so
these too should be known with a high degree of certainty. Emissions from equipment leaks, pneumatic
equipment and vents estimated by emission factors, on the other hand, have higher levels of uncertainty.
However, the overall uncertainty of emission inventories is also influenced by the relative contribution of
various sources. Hence if a source with high uncertainty comprises only a small proportion of total
emissions from a particular sector, the overall level of uncertainty is not greatly influenced by the minor
component.
6 | Field Measurements of Fugitive Emissions from Equipment and Well Casings in Australian Coal Seam Gas Production Facilities
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3 Experimental Methods
3.1 Selection of Wells
Five CSG companies provided access to wells in various gas fields throughout NSW and Queensland, which
are summarised in Table 3.1. Each company usually provided CSIRO with a list of their wells from which
CSIRO staff selected a subset of wells for examination. Because individual companies agreed to participate
in the project at different times during the course of the project it was not possible to make a properly
randomised selection of wells at the start of the project. Instead, wells were selected on an ad hoc basis in
the order that companies agreed to participate. In addition, access to sites due to weather and agreements
with landholders determined the selection of wells to some extent.
Factors considered when selecting wells included:
• The production region
• The age of the well, i.e. old to new
• The gas production rate, i.e. from low to high rates
• Whether or not the well had been hydraulically fractured
• The type of surface equipment installed at the well, i.e. pumped or free flowing.
Table 3.1. Participating CSG producers and the gas fields where emission measurements were made.
Company Name Project Name Basin Locality
AGL Energy Limited Camden Sydney MacArthur region, NSW
Arrow Energy Limited
Daandine
Surat
Dalby area, Qld
Kogan North
Surat
Dalby area, Qld
Tipton
Surat
Dalby area, Qld
Origin Energy Limited
Talinga
Surat
Chinchilla area, Qld
QGC Pty Limited
Bellevue
Surat
Chinchilla area, Qld
Berwyndale
Surat
Chinchilla area, Qld
Berwyndale South
Surat
Chinchilla area, Qld
Codie
Surat
Chinchilla area, Qld
Kenya
Surat
Chinchilla area, Qld
Lauren
Surat
Chinchilla area, Qld
Santos Limited
Fairview
Bowen
Injune area, Qld
Scotia
Bowen
Wandoan area, Qld
For the purpose of this report, we consider the well pad to be the (usually) fenced area around a well head
that contains the surface equipment associated with gas production. This includes the well head,
dewatering pump (if fitted), separator, pipework and associated valves and fittings. Also included are vents,
(including those installed on water gathering system components on the well pad) and engines used to
power dewatering pumps.
Field Measurements of Fugitive Emissions from Equipment and Well Casings in Australian Coal Seam Gas Production^cijit^s 1^^ ^ gy
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The 43 wells selected represent less than 1 % of the 5,000 CSG wells across Australia and therefore may not
be representative of the total well population. Nevertheless, it provides a reasonable cross section of the
industry covering a range of different producers and geographic locations within the main gas production
regions. For comparison, a recent study of well emissions in the U.S. where emissions measurements were
made at 489 wells represented only about 0.01 % of U.S. unconventional gas wells (Allen et al., 2013).
3.2 Methane Analysis System
Methane measurements were made using a Picarro Model 2301 Cavity Ring-down Spectrometer
CH4/C02/H20 analyser coupled with a Picarro Mobile Measurement Kit. The resolution of this analyser is < 1
ppbv CH4 and has very low drift characteristics (Crosson, 2008) so that very small CH4 perturbations can be
reliably detected against the background concentration. Both instruments were mounted in a 19" rack in
the rear of a 4WD vehicle (Figure 3.1).
Figure 3.1. Photographs of the field vehicle where the GPS antenna and sonic anemometer are visible on the top of
the vehicle (left hand photograph). The methane analyser and a calibration gas cylinder are shown in the rear of the
vehicle (right hand photograph).
The Mobile Kit included a GPS receiver and software that allows the spectrometer output to be processed
and displayed in GIS software. A two-dimensional sonic anemometer (Climatronics Sonimometer) was also
fitted for measuring local wind speed during plume traversing measurements (Section 3.3).
For mobile surveys, the spectrometer was operated continuously as the vehicle was driven. Air was
sampled via a %" nylon tube from the front of the vehicle about 1 m above ground level. The normal flow
rate of sample air to the spectrometer is approximately 100 mL min however, to minimise the lag time
between air entering the inlet tube and reaching the analyser, an auxiliary pump in the Mobile Kit was used
to increase the flow rate to about 5 L min '. When used for flux chamber measurements (Section 3.5), the
auxiliary pump was bypassed using a three-way valve.
Initially, the instrument was configured to measure CH4, C02 and H20 simultaneously; however, the
sampling rate in this mode was relatively slow with measurements made approximately every 3 s. To
increase the spatial resolution during plume traverses, the sampling rate was increased to about 2 Hz by
reconfiguring the analyser to measure CH4 only.
8 i Field Measurements of Fugitive Emissions from Equipment arid Well Casings in Australian Coal Seam Gas Production Facilities .. f7i-
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The analyser was calibrated against a reference air sample containing 1.732 ppm CH4 prepared by the
CSIRO Marine and Atmospheric Research GASLAB (Francey et al., 2003). Additional standard gas mixtures
of 10.2 and 103 ppm CH4 in air (BOC Gases Australia) were used for multipoint calibrations.
Although the nominal range of the analyser is 0-20 ppm CH4, we found that the instrument could reliably
measure concentrations well in excess of this level. In one experiment, an Ecotech GasCal dilution system
was used to generate gas flows with known CH4 concentrations up to about 280 ppm. The results of this
experiment are shown in Figure 3.2 where the analyser output is plotted against the actual methane
concentration.
Actual [CH4] (ppm)
Figure 3.2. Calibration curves obtained for the methane analyser. Open circles correspond to points made using gas
mixtures generated with a gas diluter. Red circles represent a multipoint calibration made using reference gases
several months later.
The response of the instrument remained linear at least to 280 ppm CH4. One of the routine multipoint
calibration curves using the three reference gases made several months later (red markers) is also plotted
to demonstrate the low drift characteristics of the instrument.
Multipoint calibrations were performed before and after each field campaign and single point calibration
checks were made periodically in the field.
3.3 Plume Traverses
Methane emissions from well pads were estimated using a plume dispersion method. In this method, the
CH4 concentration profile in a plume originating from CH4 emission sources on the pad is measured at some
distance downwind of the pad by performing traverses across the plume. Since the plume comprises all CH4
released from the pad, it yields total emissions from each pad. The technique is illustrated in Figure 3.3.
Field Measurements of Fugitive Emissions from Equipment and Well Casings in Australian Coal Seam Gas Productiongcijit^s
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Plume Characteristics
z
x
Emission Source
y
Wind Direction
Figure 3.3. Schematic representation of the plume traversing experiments.
The field vehicle with the CH4 analyser was driven 15 to 50 m downwind of each well to measure the
ground level CH4 concentration across each plume. The emission flux, F, over each traverse was estimated
by integrating the CH4 concentration enhancement (i.e. the measured concentration minus background CH4
concentration), c, of the plume in the horizontal and vertical directions and multiplying by the average wind
velocity, u, measured at each site (Equation 3.1). Background CH4 concentrations were measured by
performing upwind traverses of the well pad.
Since the traverse measurements were made at ground level only, the vertical extent was estimated by
reference to the Pasquill-Gifford curves of az (i.e. the standard deviation of the distribution of CH4
concentration in the vertical direction) as a function of downwind distance under given atmospheric
turbulence conditions (Hanna et al., 1982). The vertical concentration profile of CH4, within the plume was
assumed to decrease from the ground level concentration with height according to a Gaussian distribution
across the traverse plane. For each well, an average emission rate was determined from up to 10 traverses
made over about a 20-minute period,
One of the primary sources of uncertainty with the plume traversing method is associated with determining
the height of the plume because it must be estimated rather than measured. To assess the level of
uncertainty in the plume traversing results, we performed a number of experiments where CH4 was
released from a cylinder of compressed gas at a known rate while traverses were made downwind of the
source. The results of the traverses were then compared with the actual rate of CH4 release. These
controlled release measurements were made at a site near the CSIRO laboratories in Newcastle where
there were no other sources of CH4 present and to simulate field conditions, traverses were made between
15 and 50 m downwind of the controlled release point. The results of these experiments are discussed in
Section 4.1.
At each well site an initial survey for elevated CH4 concentrations was made by performing vehicle
traverses as described above to determine if CH4 emissions were present. The presence of elevated CH4
concentrations indicated some type of leak, venting or engine exhaust emission from the pump power
pack. Where CH4 was detected, more detailed examination of the facility was undertaken using a probe
connected to the vehicle mounted CH4 analyser to locate the source or sources of CH4 (Figure 3.4). On
Equation 3.1
3.4 Leak and Vent Testing
10 i Field Measurements of Fugitive Emissions from Equipment arid Well Casings in Australian Coal Seam Gas Production Facilities , 7i-
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some occasions, leaks were located by spraying a leak detection solution (Snoop, Swagelok Company) onto
individual components.
Figure 3.4. Locating equipment leaks at a CSG well pad.
When the source of the leak was identified, the leak rate was measured. During the first set of field
measurements, leak rates were measured in accordance with the USEPA Protocol for Equipment Leak
Emission Estimates (USEPA, 1995). In this procedure, the leaking component is enclosed in a plastic bag or
sleeve and an air stream is passed through the bag at a known rate while the outlet stream is analysed for
CH4 concentration. Although this is a proven method for quantifying leak rates, it was found to be very slow
and labour intensive. For later measurements (and the majority of the results reported here) we
constructed a high-flow apparatus, similar in principle to the 'Hi-Flow' device reported by Kirchgessner et
al. (1997). In this system, a high capacity fan attached to a 100 mm diameter flexible tube was used to
provide an air stream around the leak point to entrain the leaking CH4. A variable power supply was used to
allow the fan speed to be varied up to a maximum flow rate of approximately 80 L s 1 (4.8 m3 min"1).
During leak tests, the inlet of the hose was held within about 150 mm of the apparent leak point while the
CH4 concentration in the outlet air stream was measured with the CH4 analyser in the field vehicle. The leak
rate, /?,, was calculated from the volumetric flow rate of the air stream, V, and the steady state CH4
concentration, c, according to Equation 3.2
Rl = V X c Equation 3.2
A schematic diagram of the apparatus is shown in Figure 3.5.
Field Measurements of Fugitive Emissions from Equipment and Well Casings in Australian Coal Seam Gas Production ^iH^i^j |_lg _ ^ g_
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m
To Methane Analyser <
[1
{ (Fan)'
Flow FlexibleTube
Straightener
n
Figure 3.5. Schematic diagram of the leak testing apparatus. Methane leaking from a component (red arrow) is
entrained in the airstream drawn into the tube by the fan.
Occasionally emission rates from some sources (e.g. vents and pneumatic devices) were amenable to a
simple measurement technique where the exhaust point was sealed in a plastic bag of known volume and
measuring the time required to fill the bag. In a few cases where the emission rate was reasonably
constant, emission rates were measured by attaching a flow calibrator (DryCal DR2) to the emission outlet.
3.5 Surface Emissions
Measurements were made on the ground surface near well heads to determine if CH4 was migrating
around the outside of well casings or through casing walls. These measurements were made using a surface
flux chamber, a technique frequently used to measure emission rates of soil gases. For these
measurements, a plastic cylindrical chamber 37.5 cm in diameter and 40 cm high with a total volume of
about 45 L and an area of coverage of 0.11 m2 was placed on the ground at each sampling point. A small
solar powered fan mounted in the chamber ensured that the sample within the chamber was well mixed
during each experiment. The chamber was connected to the CH4 analyser in the field vehicle via a %" nylon
tube and the CH4 concentration within the chamber, C, continuously measured over a period of several
minutes. The flow rate of the sample stream from the flux chamber to the analyser was approximately 100
mL min"1.
The CH4 emission flux, F, was calculated according to Equation 3.3
U - dC s/ V
r — X — Equation 3.3
dt A
where V is the volume of the chamber, dC/dt is the rate of change in the CH4 concentration over time, t,
and A is the area of surface covered by the chamber.
A schematic diagram of the chamber system is shown in Figure 3.6
12 | Field Measurements of Fugitive Emissions from Equipment and Well Casings in Australian Coal Seam Gas Production Facilities
4b ot ft 57 of 87
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Analyser
A
Return Flow
Flux
Chamber
fttf
CH„ Flux
Figure 3.6. Schematic diagram of the flux chamber system used for well casing leak determinations
Typically, chamber measurements were made at four or more points within about 1 m of the well casing. In
many cases, the chamber was placed adjacent to the casing, depending on access. Occasionally, additional
measurements were made at distances up to about 20 m from the well head.
Field Measurements of Fugitive Emissions from Equipment and Well Casings in Australian Coal Seam Gas Production ^cilip^.1
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4 Results
4.1 Controlled Release
Controlled release experiments were conducted on several occasions with CH4 release rates of between 0.7
and 0.8 g min1 and traversing distances between 15 and 30 m downwind of the release point. Figure 4.1
shows the results of the controlled release experiments. The black markers represent the mean value
determined by the traverses while the error bars show the minimum and maximum results determined
over each set of traverses. The red markers represent the actual release rate.
g
'E
O)
59 Of 87
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measurements due to maintenance or other activities. Two of the wells examined were plugged and
abandoned and one well had been 'suspended' where the well head was still in place but had been
disconnected from the gathering network and most of the surface equipment had been removed.
Twenty-nine wells were producing gas during the measurements, flowing at rates ranging from less than
1000 m3 day"1 to more than 186,000 m3 day"1. Eleven of the sampled wells were hydraulically fractured. The
selection also included a mix of free-flowing wells (water was not pumped from the well) and pumped wells
(water was pumped from the well to allow gas flow). Pumped wells used on-site engines to power hydraulic
pumps or generators to drive down-hole water pumps. In all but one case (which used diesel), these
engines were fuelled from gas supplied from the well. A summary of the wells is shown in Table 4.1. To
maintain commercial confidentiality, the well locations and operators of individual wells are not identified
in this report.
Table 4.1. Details of wells examined during this study.
Well Number
Completion
Date
Production Rate
(m3 day"1)
Fracture
Stimulated
Type
Pump with Engine
Wells on Pad
A1
11/10/1999
1,470
Yes
Vertical
No
1
A2 - Suspended
1/05/2003
0
Yes
Vertical
No
1
A3
1/07/2007
0
Yes
Vertical
Yes - not running
1
A4
20/04/2010
18,400 (total of all
4 wells on pad)
No
Horizontal
No
4
A5
8/06/2011
14,900
No
Horizontal
Yes
2
A6
11/12/2007
13,700
No
Horizontal
No
1
B1
24/09/2006
38,880
No
Vertical
Yes
1
B2
11/01/2008
0
No
Vertical
No
1
B3
06/08/2011
9,360
No
Vertical
Yes - not running
1
B4
21/09/2010
26,400
No
Vertical
Yes - not running
1
B5
08/12/2010
0
No
Vertical
No
1
B6
27/04/2003
23,760
Yes
Vertical
Yes
1
B7
09/08/2007
26,400
No
Vertical
Yes
1
B8
26/01/2008
62,400
No
Vertical
No
1
B9
23/06/2008
7,680
No
Vertical
Yes
1
B10
07/04/2007
55,200
No
Vertical
No
1
Bll
23/06/2011
94,602
No
Vertical
Yes - not running
1
B12
28/06/2011
0
No
Vertical
Yes - not running
1
B13
21/02/2005
0
No
Vertical
No
1
B14
30/08/2007
75,360
No
Vertical
No
1
Field Measurements of Fugitive Emissions from Equipment and Well Casings in Australian Coal Seam Gas Production ^ili^i^.|
-------
B15
08/04/2009
70,800
No
Vertical
No
CI
15/05/2001
76,101
No
Vertical
Yes
C2
2/08/2003
853
No
Vertical
Yes
C3
4/10/2007
0
No
Vertical
Yes - not running
C4
29/03/2007
52,458
No
Vertical
Yes
C5
29/03/2007
58,594
No
Vertical
Yes - not running
C6
28/01/2008
186,464
No
Vertical
Yes
C7
17/09/2009
0
Yes
Vertical
No
C8
22/05/2010
0
No
Horizontal
No
C9
16/10/2003
78,731
Yes
Vertical
No
C10
1/10/2003
85,556
Yes
Vertical
No
Cll
27/08/2004
0
Yes
Vertical
No
D1 - Abandoned
8/11/2003
0
No
vertical
No
D2
1/09/2005
93,400
Yes
vertical
No
D3 - Abandoned
29/11/2003
0
Yes
vertical
No
D4
19/04/2004
0
Yes
vertical
Yes (x2 - not
running)
D5
7/11/2009
7,900
No
vertical
Yes (x2)
D6
28/11/2009
0
No
vertical
Yes (x2)
El 16/3/2008 43,843 (total of No vertical Yes 2
both wells on pad)
E2 7/9/2008 26,847 No vertical Yes 1
E3 16/3/2007 3,707 No vertical Yes - not running 2
E4 31/5/2009 6,598 No vertical Yes 1
E5 31/5/2005 14,498 (total of all No vertical Yes 3
3 wells on pad)
Downwind plume traverses were made at all wells sites except Wells B7 and C3 where the wind was too
light to produce stable plumes. Of the well sites where traverses were made only three did not exhibit any
CH4 emissions. These were the two plugged and abandoned wells (D1 and D3) and the suspended well (A2).
All of the other wells examined exhibited some level of CH4 emissions although in most cases the amount
was relatively small. The plume traversing results for all wells are presented in Table A1 in the Appendix.
On-pad measurements were made at most wells except in a few cases where high ambient CH4 levels from
major leaks or vents made locating minor leak points difficult. In one case at Well B2, CH4 released from a
vent on a water gathering line was drifting over the pad components so it was not possible to determine if
16 | Field Measurements of Fugitive Emissions from Equipment and Well Casings in Australian Coal Seam Gas Production Facilities .. ,7C
49 0T 'b 61 of
-------
there were other leaks against the high background. Similar conditions were encountered at Wells C3 and
E4 where variable plumes from leaks around the water pump shaft seals precluded reliable leak detection.
In one case we attempted to measure emissions from a well about 500 m downwind of a gas compression
plant but the CH4 emissions from the plant prevented any measurements being made at this site.
Most of the CH4 emissions were found to be derived from equipment leaks and venting but we also found
that exhaust from the engines used to drive the water pumps on some wells was frequently a significant
source of methane. Fifteen of the pumped wells had the engines operating during the measurements and
in most cases the exhaust was found to contain CH4 that contributed to total emissions. In a few cases, the
plume from the engine exhaust was sufficiently spatially separated from other sources of CH4 to quantify
the sources separately using the traverse method (Figure 4.2).
~
¦ 11
Engine
Separator
20 m
Wind
Direction
Q Well
Figure 4.2. Methane concentration profile at Well C2 showing the separate plumes associated with the engine and
equipment leaks elsewhere on the pad.
However, in most cases the plumes were coincident and the exhaust component could not be separated.
To attempt to estimate the magnitude of engine emissions, we measured the CH4 concentration in the
exhaust outlet of the engine where this was possible. The range of CH4 concentration varied considerably;
from only a few ppm to more than 1500 ppm. The exhaust gas flow rate was estimated from the nominal
fuel consumption (often stated on the engine nameplate) or power rating and assuming a 33 % efficiency
and 17:1 air fuel ratio.
In the example for Well C2 shown in Figure 4.2, the plume traverse yielded an emission rate from the
engine of 0.8 g min"1 compared to the estimate based on the fuel consumption and exhaust CH4
concentration of 0.9 g min'1. In another example, engine emissions from Well B7 were estimated using the
exhaust method to be 0.2 g min"1. A separate measurement made by the well operator using a stack testing
method also gave 0.2 g min"1. While these two examples suggest that this method provides a reasonable
approximation of exhaust CH4 emissions, in many cases the CH4 concentration measured was well above
Field Measurements of Fugitive Emissions from Equipment and Well Casings in Australian Coal Seam Gas Production ^iii^i^j 1,J'0 ^ _
-------
the calibrated range of the CH4 analyser (i.e. > 280 ppm) and hence the results can only be considered
indicative.
Although on-pad measurements provided reasonably accurate leak rate results for individual leak points,
the large number of possible emission sources including equipment leaks, vents, pneumatic devices and
engine exhaust presented a risk that some emission points on each pad would be missed during the surveys
(Figure 4.3).
Figure 4.3. CSG well pad showing some of the surface equipment and potential emission points. Note the engine in
the background for supplying hydraulic power to the water pump.
To check this we compared the emission rates determined from the on-pad measurements to those
calculated from the downwind traverses, which capture all emissions from the pad. Ideally therefore, if ali
the emission sources have been accounted for, on-pad measurements should equal emission rates
determined from traverse data. Apart from one result, there was generally good agreement between the
two methods, which is shown in Figure 4.4 where the emission rate determined for each well by the on-pad
methods is plotted as a function of the traversing results. The outlier (red marker in Figure 4.4) corresponds
to Well B2 where the traverses were made under very light and variable conditions, which make accurate
quantification difficult. The mean traverse result for this well was approximately 17 g min"1 but this result
exhibited the greatest variably of all the traverses, ranging from 1 to 66 g min"1. If this result is omitted from
the plot, the slope of the line is close to 1 (0.94) confirming that the on-pad measurements generally
accounted for the main emission points i.e. there were no major sources that were missed during the leaks
surveys.
18 i Field Measurements of Fugitive Emissions from Equipment arid Well Casings in Australian Coal Seam Gas Production Facilities f7i-
51 or 'b 63 Of 87
-------
70
g
E
<1)
"CO
Od
c
o
C/)
C/)
E
LU
~C5
05
Q_
¦
c
o
60 -
50
40 -
Traverse Emission Rate (L min )
Figure 4.4. Correlation of total CH4 emissions determined by traverses with on-pad measurements
The well site results from individual companies are discussed in more detail in the following sections.
4.2.1 COMPANY A
Figure 4.5 summarises the total emissions measured at Company A's well sites using the traversing method.
At the time of the measurements only four wells were producing gas - Well A2 was suspended and Well A3
was shut-in for maintenance.
Field Measurements of Fugitive Emissions from Equipment and Well Casings in Australian Coal Seam Gas Production ^ g-j
-------
3.0
2.5 -
Company A
g
E
CD
<1)
"CO
Qd
c
o
if)
c/)
E
LU
x
o
2.0
1.5 -
1.0
0.5 -
0.0
Suspended
A1
V
A2
Max = 13.4
Avg = 7.3
A3 A4
Well Number
A5
A6
Figure 4.5. Total CH4 emission rates estimated at Company A's well sites using the traversing method.
Apart from the suspended well (A2) emissions were detected at each site. Generally emissions were very
low rwith five of the wells having emissions below about 0.1 g min"1. On-pad measurements made at the
well sites showed that in two cases (Wells A1 and A5) the emissions were due to the operation of
pneumatic devices with emission rates of ~75 mg min"1 and 55 mg min"1, respectively.
Two other wells (A3 and A6) were also found to have minor emissions but at the time the measurements
were made, venting from pneumatic equipment was not contributing (i.e. these devices did not operate
over the few hours we were on site at each well). In the case of A6, CH4 was leaking slowly from a loose
plug on a branch pipe at a rate of 22 mg min"1. This leak was repaired by gas company personnel shortly
after it was identified and further measurements on site showed that the leak had been eliminated. At Well
A3, a leak was found in the gathering line, but again, this was very small amounting to less than 1 mg min"1.
The largest emissions were found at Well A4. Two separate sets of traverses yielded an average emission
rate of 7.3 g min"1. Methane leaks were detected at a valve and pipe joint on the well pad but the combined
emission rate from these was about 7 mg min"1 so the bulk of the methane release was from another
source. This well was on a pad with three other wells within close proximity, which were not examined in
detail during this campaign, so it is possible that some of the observed methane in the plume may have
originated from these other wells. However, the bulk of the source was traced to a buried gathering line
adjacent to the pad that serviced all four wells. We attempted to measure the emission rate using the
surface flux chamber method; however, because of the diffuse nature of the emissions through the gravel,
this was not successful.
Although the average emission rate of 7.3 g min"1 (15.5 m3 day"1 at 15 °C) determined by the traverses was
by far the largest emission source found at Company A, it represented only about 0.1 % of the indicated gas
flow of 18,400 m3 day"1 from the four wells on the pad.
A summary of the emissions determined by on-pad measurements at Company A is provided in Table 4.2.
20 | Field Measurements of Fugitive Emissions from Equipment and Well Casings in Australian Coal Seam Gas Production Facilities
txs or /b g5 of 87
-------
Table 4.2. Summary of on-pad emission rates measured at Company A sites; nf denotes 'not found'. Note the leak
rate shown for Well A6 was determined from the traverses.
Well Number Leaks (g min"1) Vents (g min"1) Pneumatics (g min"1]
A1
A2
A3
A4
A5
A6
3.3 x 10"
0
4.5 x 10"'
7.3
0
2.2 x 10
-2
nf
nf
nf
nf
nf
nf
7.5 x 10"'
nf
nf
nf
5.5 x 10";
nf
4.2.2 COMPANY B
Methane emissions estimates based on the traverses for the Company B wells are summarised in Figure
4.6.
c
E
CD
<1)
05
CY.
c
o
if)
-------
meant that it was not possible to identify any other sources on the pad because the plume was engulfing
the surface equipment.
Well B2 was not flowing at the time of the measurements, but assuming the normal flow rate is 26,400 m3
day"1 (i.e. the median production rate of the Company B wells examined), fugitive emissions from this vent
represent about 0.4 % of the well's production.
Emissions at the other Company B well sites were much lower than B2, with emission rates generally less
than 2 g min"1. Most of the well sites exhibited a small level of leakage from certain items of equipment and
especially a particular brand of pressure regulator. These regulator leaks however, were quite low with the
maximum measured less than 25 mg min"1. Most of the CH4 emissions were, like Well B2, from vents
present on many of this company's wells. Vent emissions were significantly higher than the equipment
leaks, typically more than 1 g min"1, with the maximum of 44 g min"1.
The on-pad measurements for Company B are summarised in Table 4.3.
Table 4.3.Summary of on-pad emission rates measured at Company B sites; nf denotes 'not found'.
Well Number
Leaks (g min"1)
Vents
(g min"1) Pneumatics
¦
B1
2.4 x
10"3
2.9
nf
B2
nf
43.8
nf
B3
2.1 x
10"4
nf
nf
B4
1.5 x
10"3
nf
nf
B5
nf
nf
nf
B6
6.4 x
10"3
1.0
nf
B7
9.6 x
10"4
1.1
nf
B8
2.1 x
10"2
6.2
nf
B9
2.4 x
10"3
nf
nf
BIO
2.3 x
10"2
3.6 x 10"2 nf
Bll
2.5 x
10"2
1.2
nf
B12
X
o
ro
10"4
nf
B13
o
X
10"3
< 10"4
nf
B14
3.94
x 10"3
0.9
nf
B15
2.4 x
10"3
3.3
nf
In addition to the emissions from the well pads, we found a significant CH4 emission point from a water
gathering line installation near Well B13 (Figure 4.7).
22 | Field Measurements of Fugitive Emissions from Equipment and Well Casings in Australian Coal Seam Gas Production Facilities „
SS OT (5 QJ of 8/
-------
Figure 4.7. Methane emission sources on a water gathering line.
Methane was being released from the two vents shown in Figure 4.7 at a rate sufficient to be audible a
considerable distance from the vents. It was not possible at the time to the site visit to directly measure the
emission rate from the vents due to restricted access, however, the CH4 concentration 3 m downwind of
the vents was 15 % of the lower explosive limit of CH4 (i.e. 7,500 ppm). Based on the prevailing wind speed,
we estimate that the CH4 emission rate from the two vents was at least 200 L min"1 (130 g min"1) or almost
300 rrr day"1, This is a factor of three more than the highest emitting well examined during this study.
4.2.3 COMPANY C
Figure 4.8 summarises the CH4 emission rates estimated by the traversing method for Company C.
Emissions were generally estimated to be below 1.5 g min"1, except for Wells CI and C4, with emission rates
of about 8.7 and 11.8 g min \ respectively. The bulk of the emissions from wells CI and C4 were due to CH4
in the engine exhaust rather than venting or equipment leaks. Similarly, emissions from Wells C2 and C6
comprised mainly CH4 in engine exhaust although the emissions rates were much lower than CI and C4.
On-pad measurements at each of the wells showed that emissions from the wells were generally relatively
low when the engine exhaust is excluded (Table 4.4). In this case, leaks were mostly less than 0.3 g min"1.
Most of these leaks were found to be from vent pipes on equipment such as pressure relief valves or
pressure regulators similar to those on Company B's well sites. In one case (Well C10), a pneumatic device
was found to be venting at an average rate of 0.5 g min"1 in addition to the equipment leak rate of 0.3 g
min"1 to give a total emission of 0.8 g min \
Field Measurements of Fugitive Emissions from Equipment and Well Casings in Australian Coal Seam Gas Production igciii^^. j JJ,3g _ ^ g_
-------
g
'E
O)
0)
TO
on
c
o
'(/)
w
'E
HI
f
o
30
25 -
20 -
15 -
10 -
5 -
i
03
03
Q
I
03
Max = 34.8
4-1
Company C
{
C1 C2 C3 C4 C5 C6 C7 C8 C9 C10 C11
Well Number
Figure 4.8. Total CH4 emission rates estimated at Company C's well sites using the traversing method.
Traverses were not made at Well C3 due to lack of wind, however, on-pad inspections revealed a significant
gas leak was on the seal of the water pump shaft. The emission rate from this leak was approximately 28 g
min"1 (measured using the high-flow apparatus), which was the second largest well emission (after B2) and
the largest equipment leak of the 43 sites examined. Since this well was shut-in at the time of
measurement, it was not flowing but using the median flow rate of Company C's wells (52,500 m3 day"1) the
leak rate corresponds to about 0.1 % of the well's production.
The water pump shaft seal was also found to be the source of CH4 leakage at Well C5 but in that case, the
emission rate was about 0.3 g min"1, about 100 times less than C3.
Table 4.4. Summary of on-pad emission rates measured at Company C sites; nf denotes 'not found'.
Well Number
Leaks (g min"1)
Vents
(g min"1) Pneumatics
¦
CI
5.3 >
< 10"2
nf
nf
C2
0.2
nf
nf
C3
28.
nf
nf
C4
8.0 >
< 10"2
nf
nf
C5
0.3
nf
nf
C6
0.2
nf
nf
C7
0.1
nf
nf
C8
2.1 >
< 10"3
nf
nf
C9
8.9 >
< 10"3
nf
nf
24 | Field Measurements of Fugitive Emissions from Equipment and Well Casings in Australian Coal Seam Gas Production Facilities „
5/ or gg of 87
-------
CIO
Cll
0.3
7.4 x 10"'
nf
nf
0.5
nf
4.2.4 COMPANY D
Two of the wells at Company D were plugged and abandoned with all surface equipment removed. Detailed
traverses and flux chamber measurements made on the well sites revealed no sign of any residual
emissions from these wells. The traversing results for Company D are shown in Figure 5.9.
c
'E
-------
Methane leaking from
damaged actuator
diaphragm
Figure 4.10. Methane leak from a valve actuator. Note the soap solution bubbles around the emission point.
Table 4.5 shows a summary of the on-pad results from Company D.
Table 4.5. Summary of on-pad emission rates measured at Company D sites; nf denotes 'not found'.
Well Number
Leaks (g min"1)
Vents
(g min"1) Pneumatics
¦
Dl
0
nf
nf
D2
5.7 >
< 10"2
nf
nf
D3
0
nf
nf
D4
6.4 >
< 10"2
nf
1.4x 10"2
D5
1.5
nf
nf
D6
0.9
nf
See note
Note: Although the emissions from the actuator shown in Figure 4.10 were from a pneumatic device, it appeared that this was due to a leak rather
than normal operational emissions. Hence we have classified this as a leak in Table 4.5
4.2.5 COMPANY E
The traverse results obtained for Company E are shown in Figure 4.11. The lowest emitting well of the five
examined was E5. This well was located on a pad of three wells, with a single engine providing power to all
three water pumps. Emissions from ali three wells were less than 60 mg min most of which were
26 i Field Measurements of Fugitive Emissions from Equipment and Well Casings in Australian Coal Seam Gas Production Facilities ,7i-
by°r ft 71 of 87
-------
probably associated with engine exhaust. We did not find any equipment leaks or venting emissions at this
site.
c
'E
O)
0)
TO
on
c
o
'(/)
w
'E
HI
f
o
25
20 -
15
10 -
5 -
Max = 56.8
Company E
*
•
1
M
\-1
1—•—1
m
E1
E2 E3
Well Number
E4
E5
Figure 4.11.. Total CH4 emission rates estimated at Company E's well sites using the traversing method.
The other wells, however, showed higher emissions, the largest of which was on Well E4 with an emission
rate of about 15 g min"1. This was traced to a leak on the water pump shaft seal. Like a number of other well
sites examined during this study, the seal was repaired on site once the leak had been identified and
subsequent measurements confirmed that CH4 leakage was completely eliminated.
Well site El was also found to be leaking CH4 from the water pump shaft seal. This site had two wells on the
pad and both were found to be leaking from the seal. The combined rate of leak from this source was 0.7 g
min"1. These wells also showed significant leakage from two pressure regulators, similar to those used at
various other well pads examined, with a combined emission rate of 1.7 g min"1. Total emissions from leaks
at El were 2.5 g min"1 (Table 4.6).
The next highest emitting well from Company E was E2 but most of these emissions were apparently from
the engine exhaust. For E3, a very slight leak was detected from the pump shaft seal (about 40 mg min"1)
but most of the CH4 emissions were from a leak in a filter attached to the engine fuel line (0.6 g min"1).
Table 4.6. Summary of on-pad emission rates measured at Company E sites; nf denotes 'not found'.
Well Number
Leaks (g min"1)
Vents
(g min"1) Pneumatics
¦
El
2.5
nf
nf
E2
nf
nf
nf
E3
0.6
nf
nf
E4
15
nf
nf
E5
0
nf
nf
Field Measurements of Fugitive Emissions from Equipment and Well Casings in Australian Coal Seam Gas Production ^:ili^i^| ^7^ ^ g-j
-------
4.3 Casing Leaks
CSG wells are designed so that gas is extracted from the seam through a well casing but if the casing is
damaged or improperly sealed into the surrounding strata, it is possible that gas can migrate to the surface
outside the casing (Figure 4.12). To determine if CH4 was escaping from the well casing, the flux chamber
method was applied at each well site to measure the emission rate of any leakage from around the outside
of the casing.
Possible leak
around casing
Gas to processing plant
~ ~ ~
Typically
300 to 1000 metres
BOTTOM HOLE PUMP
Figure 4.12. Schematic representation of a CSG well showing a possible route for CH4 leaking outside a casing.
We anticipated that leakage from this source may be quite low, so it was important to ensure that the
measurement technique had sufficient sensitivity to detect low level seepage. Therefore, prior to making
field measurements a series of preliminary experiments were performed to determine the lower limit of
detection of the method. Several experiments were made using a controlled release of CH4 into the flux
chamber system. Figure 4.13 (a) shows a plot of the CH4 concentration within the chamber over about 5
minutes. The actual flow rate of CH4 into the chamber was 7.76 x 1CT5 g min'1 whereas the measured rate
was 7.42 x 105 L min1 or a difference of about 4 %. While this is a very low emission rate (cf. the smallest
well leak rates of ~3 I 10~4 g min1) the ultimate sensitivity was several orders of magnitude lower.
Measurement of CH4 emissions from natural surfaces showed that emission rates less than 1 x 10 g min 1
could be reliably quantified (Figure 4.13 b).
28 i Field Measurements of Fugitive Emissions from Equipment arid Well Casings in Australian Coal Seam Gas Production Facilities f 7S- __ .
oi or <3 / 3 of 87
-------
Figure 4.13. Methane concentration as a function of time in the flux chambers (a) controlled release experiment; (b)
natural surface emission.
At the well sites, even with the very high sensitivity of the chamber method, we did not detect any
emissions from around the well casing. Because the flux chamber measurements were applied at discreet
points around the well it is possible that leak points were missed, however we believe that this was very
unlikely since any significant emissions would have been detected during the mobile plume traverses and
leak detection measurements made near the well heads.
Field Measurements of Fugitive Emissions from Equipment and Well Casings in Australian Coal Seam Gas Production E,
?4 of 87
-------
5 Discussion
Overall, the emission rates measured at the well sites were quite low, especially when compared to the
volume of gas produced. Of the 43 sites examined, 19 had emission rates less than 0.5 g min"1 and 37 less
than 3 g min"1; however, there were a number of wells with substantially higher emission rates up to 44 g
min"1 (Figure 5.1).
10 20 30
CH. Emission Rate (g min"1)
Figure 5.1. Histogram of emission rates from all sources measured at the 43 well sites.
Well pad emissions were found to be derived from several sources:
• exhaust from engines used to power dewatering pumps,
• vents and the operation of pneumatic devices and
• equipment leaks.
The mean emission rate of all of these sources for all wells is 3.2 g min"1 whereas the median (middle value)
is 0.6 g min"1.
Engine exhaust is not considered to be a fugitive emission for the purposes of greenhouse accounting since
it is counted separately as a combustion source. Nevertheless, exhaust represented a significant proportion
of the total CH4 emissions at some well sites. The wide range of CH4 concentrations present in the exhaust
meant that the contribution of exhaust to overall emissions was highly variable. Some engines appear to
have very low CH4 emissions such as that at Well A5. Similarly, an unidentified well in Queensland was
found to have no detectable CH4 in the exhaust within close proximity to the pad (Day et al., 2013). On the
other hand, engine exhaust was by far the primary source of CH4 emissions at some wells (e.g. Wells CI and
C4).
As noted in Section 2, methane emissions from combustion are estimated for NGER reporting using an
emission factor of 0.1 kg C02-e GJ"1 (DIICCSRTE, 2013b), which is equivalent to 4.8 g CH4 GJ"1 using a global
warming potential for CH4 of 21. Assuming that the fuel consumption of the well site engines was 594 MJ
30 I Field Measurements of Fugitive Emissions from Equipment and Well Casings in Australian Coal Seam Gas Production Facilities __ , __
63 of 75 75 of 87
-------
h"1 (indicated on the nameplate fitted to one make of engine commonly used throughout the industry), this
equates to a CH4 emission rate of 0.05 g min"1, which lower than some of the estimates made during the
study. Well C4 for example was estimated to be emitting CH4 at a rate of 11.8 g min"1.
Pneumatic devices, which are potential emission points, were installed at many wells, although during the
measurement campaign, only seven of these were releasing CH4 at the time of the site visits. Emissions
from the these pneumatic devices ranged from 3.8 x 10"2 to 0.47 g min"1 with a mean emission rate 0.12 g
min"1 and standard deviation of 0.18 g min"1. This is somewhat lower than the emission rate for pneumatic
devices recently reported by Allen et al. (2013). They found that the average emission rate from
intermittent pneumatic devices at U.S. unconventional gas well was 5.9 ± 2.4 g min"1. The result obtained
for the Australian CSG wells is also lower than the production average emission factor for pneumatic
devices provided in the API Compendium (API, 2009) of 345 ± 49.5 scf d"1 (4.6 ± 0.66 g min"1).
It is not clear why these emission rates are lower than the U.S. estimates; however, it should be borne in
mind that the results of our study represent only a very small sample. The Allen et al. (2013) study
examined 305 devices compared to only seven in our study. Another reason for the difference may be due
to the intermittent operation of the devices. Most of the CH4 emission apparently occurs when the devices
operate and hence the frequency of operation has a strong influence on the emission rate so a longer
period of sampling may have yielded different results.
Despite the uncertainty of the results for pneumatic devices, it is probable that emissions from these
systems will tend to decrease in the future. Some Australian CSG companies are now installing compressed
air operated or electrical actuators on newer well pads which will eliminate pneumatic CH4 emissions from
these pads.
Vents installed at various points on some well pad equipment were frequently found to be sources of CH4
emissions. Of the 43 well sites examined, ten had vents, all from Company B, that were emitting CH4 at the
time measurements were made. The rate of emissions varied substantially from less than 10"4 g min"1 up to
44 g min"1, which was the highest rate of emissions measured from any source measured during this
project. The mean vent emission rate was 6.1 g min"1 with a standard deviation of 13.4 g min"1, reflecting
the large range of values.
The third main source of well pad CH4 emissions was from equipment leaks. Most of the wells examined
were found to have some degree of leakage from equipment on the pad. Minor leaks (usually less than 60
mg min"1) were found on various items such as fuel lines to engines, valves, sight gauges on separators and
other equipment. However, there were some leak points that were consistently found across the well sites.
The first of these was a particular type of pressure regulator installed at many wells (Figure 5.2). This device
was apparently associated with the separator and was usually found to be leaking a small amount of CH4.
Mostly, these leaks were less than 150 mg min"1 but in one case (Well El) the emission rate was about 1.5 g
min"1.
Field Measurements of Fugitive Emissions from Equipment and Well Casings in Australian Coal Seam Gas Production ^ili^i^l ^Lg ^
-------
Figure 5.2. Pressure regular that was a common source of CH4 leakage.
The other common leak point was the seal around water pump shafts on pumped wells (Figure 5.3). The
two largest equipment leaks detected were due to leaking seals at Wells C3 and E4. At the time of the site
visit, Well C3 was shut-in for maintenance and as a result the pressure on the seal was almost 2 MPa, which
was much higher than normal operating pressure and this is likely to have contributed to the high leak rate
from the well. This is consistent with a study of leaking wells in Queensland made in 2010 where high CH4
concentrations (up to 6 % CH4) due to leaks were often found on shut-in wells that were under high
pressure (DEEDI, 2010).
32 i Field Measurements of Fugitive Emissions from Equipment arid Well Casings in Australian Coal Seam Gas Production Facilities f7i-
OS OT id / / Of O7
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Figure 5.3. Well head showing the location of the water pump shaft and seal which was found to be a common leak
point.
At Well E4, the seal had apparently 'dried out' since the previous inspection and was allowing CH4 to leak
around the rotating pump shaft at almost 15 g min After the leak was identified, however, maintenance
staff applied more grease to the seal and tightened the gland around the shaft, which effectively eliminated
the leak. A smaller leak of around 1.5 g min 1 on the shaft seal on Well D5 was also repaired on site by
simply tightening the gland.
Although the water pump shaft seal is a potentially large source of CH4 emissions, it is clear that in many
cases these leaks can be easily repaired. Regular inspection of these seals, especially during shut-ins when
the well pressure may increase substantially, is therefore likely to be important for minimising well site
emissions.
None of the wells examined during this study exhibited any sign of CH4 emissions around the well casing so
this does not appear to be a common route for CH4 release. Methane leaks have been detected at ground
level adjacent to well casings on Australian CSG wells previously but these were traced to leaks in the
threaded connection between the casing and well head base (DEEDI, 2010) rather than gas leaking around
the outside of the casing.
Despite this, it has been suggested that 6 to 7 % of well completions in the United States are subject to
integrity failure that could lead to CH4 leakage (Ingraffea, 2013). Given that we surveyed less than 1 % of
Field Measurements of Fugitive Emissions from Equipment and Well Casings in Australian Coal Seam Gas Production ^iii^i^j ^ g_
-------
Australian CSG wells, it is possible that the small sample size is not sufficiently representative to assess the
true extent of well leakage. Further work would be required to conclusively determine the extent of casing
leaks.
Four of the wells surveyed were horizontal; the remainder were vertical. The range of emissions from the
four horizontal wells was 0.05 to 7.3 g min"1 compared to 0 to 44 g min"1 for the vertical wells. It is not
possible based on only four wells to determine if horizontal wells have different emission characteristics
compared to vertical; however, it seems unlikely that this would be the case. The emission routes were
always associated with surface equipment, some of which was common to both horizontal and vertical well
pads.
Eleven wells examined had been hydraulically fractured and as shown in Table 5.1, average emissions from
these wells were lower (0.42 g min"1) than those measured on the unfractured wells (4.2 g min"1). Because
the data are heavily skewed and it is unlikely that the sample size is statistically representative, it is
misleading to draw conclusions about the relative emission rates based on a comparison of means alone.
Methane emissions were observed from both fracture stimulated and unfractured wells but in all cases,
emissions were from surface equipment that would not be expected to be affected by the stimulation
method. Therefore, the observed difference between the emission rates of the fractured and unfractured
wells in this sample is probably unrelated to the stimulation method.
Table 5.1. Comparison of emission rates measured on hydraulically fractured and unfractured wells.
Fractured
Unfractured
Number of Wells
11
32
Mean (g min"1)
0.42
4.2
Median (g min"1)
0.07
1.0
Std Deviation (g min"1)
0.66
14.3
Another parameter that was initially thought to possibly contribute to differences in emission rates was the
well production rate. The range of gas production from the wells varied substantially but there was no
observable correlation between production and leak rate. The highest emissions were from wells that were
not producing gas at the time of the measurements. In the case of one of the non flowing wells (C3) at
least, it may have been that the high well pressure due to the shut-in was contributing to the high leakage.
Conversely, Well C6, which was producing about 186,000 m3 day"1 (cf. the median production rate of 13,700
m3 day"1) had relatively low emissions, most of which were derived from the exhaust from the engine on
the well pad.
Despite the rather low well pad emissions measured during this study, a much higher emission source was
identified on a water gathering line installation. Unfortunately accurate measurements could not be made
at this site but indicative estimates suggested that the emission rate from this source was at least three
times higher than the largest emission rate measured on any of the wells. Similar installations are
widespread through the Queensland gas regions and occasionally, gas can be heard escaping from vents on
these systems. It is possible that these may be a significant source of CH4 and is an area that needs further
investigation.
5.1 Emission Factors
As discussed in Section2 emissions from equipment leaks are often estimated for NGER reporting according
to Method 1 using a generic emission factor of 1.2 kg C02-e t"1, which is equivalent to 57 g CH41"1. It is
therefore instructive to compare this emission factor to the leak emission data measured in the field. The
field measurements yielded a median leak rate 0.02 g min"1 and mean rate of 1.6 g min"1 from the 35 wells
34 | Field Measurements of Fugitive Emissions from Equipment and Well Casings in Australian Coal Seam Gas Production Facilities R7 f7E.
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where leaks were found. The median production rate of the wells was 13,700 m3 day"1 or 9.3 t CH4 day"1
(referenced to 15 °C). Dividing the median daily leak rate by the median production rate gives an emission
factor of approximately 4 g CH41"1 or 0.1 kg C02-e t"1 (based on a global warming potential of 21). Using the
mean leak rate of 1.6 g min"1 and mean production rate of 29,600 m3 day"1 yields an emission factor of 115
g CH41"1 or 2.4 kg C02-e t"1. This range is consistent with the current NGER emission factor for general
equipment leaks and tends to confirm that equipment leaks comprise only a very small proportion of
greenhouse gas emissions from CSG production.
Similar calculations may be made to develop emission factors for vents and pneumatic equipment. A
summary of the emission data for leaks, vents and pneumatic equipment and the corresponding emission
factors calculated from these data are shown in Table 5.2.
Table 5.2. Summary of emission data from leaks, vents and pneumatic equipment. Emissions factors calculated
from the mean emission rate for each category are also shown in units of kg C02-e t1 (GWP of 21 used in this
calculation).
Equipment Leaks
Vents
Pneumatic
Equipment
Mean (g min"1)
1.59
6.05
0.12
Median (g min"1)
0.02
1.14
0.06
Std Dev
5.36
13.40
0.18
N
35
10
7
Calculated Emission Factor from
Mean Emission Rate (kg C02-e t"1)
2.4
9.1
0.2
Although these averaged emission factors are low it should be remembered that firstly, the number of
wells examined was less than 1 % of wells in operation so may not be representative of the total well
population and secondly, there were several equipment leaks that were much higher than the average
values (Figure 5.1). The maximum leak rate measured in this study was about 28 g min"1 on Well C3 and
although this well was not flowing at the time, based on the median production rate for all wells, is
equivalent to 91 kg C02-e t"1. A high leak rate of 15 g min"1 was also found at Well E4 and based on its
production rate, equates to 102 kg C02-e t"1. These leak rates are about two orders of magnitude higher
than the current NGER emission factor for equipment leaks.
Another important point with regard to the reliability of emission factors is that they may change due to
operating conditions or maintenance. For instance, the leak from Well E4 discussed above was repaired
during the site visit and completely sealed. Several other leaks were effectively repaired during the course
of the visits once they were identified. However, since wells operate largely unattended, there may be
some time between when the leak forms and when it is repaired.
With regard to well casing leaks there is currently no emission factor representative of Australian
operations for estimating emissions. The current Method 2 emission factor is based on measurements
made at some Canadian wells during the mid 1990s (CAPP, 2002). While there have been suggestions that
well leakage may be a significant source of emissions (Somerville, 2012), the wells examined in this study
showed no evidence of emissions via this route. But again, this needs to be considered in the context of the
small number of wells examined.
Field Measurements of Fugitive Emissions from Equipment and Well Casings in Australian Coal Seam Gas Production ^:ili^i^| ^
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Fugitive CH4 emission rates were measured at 43 CSG well sites in Queensland and NSW. A range of
methods was applied including downwind traverses of CH4 plumes originating from well pads, and on-pad
measurements to determine leak rates from individual items of equipments and well casings.
Emission rates from production sites ranged from zero to a maximum of about 44 g min"1. The highest
emission rate was due to CH4 released from a vent on the well pad while the lowest emitters were two
plugged and abandoned wells and a suspended well. All of the producing wells were found to have some
level of emissions, although in all cases these were very low compared to overall production. Emissions
were found to comprise equipment leaks, venting, pneumatic device operation and engine exhaust. The
wells examined in this study did not show any evidence of CH4 migration outside the well casing.
Overall, the median CH4 emission rate from all sources for the wells examined was approximately 0.6 g
min"1 while the mean emission rate was about 3.2 g min"1 or about 7 m3 day"1. This compares to a mean
production rate of the 43 wells of 29,600 m3 day"1 and represents about 0.02 % of total production. This is
very much lower than recent estimates of CH4 emissions from unconventional gas production in the United
States.
Apart from vents, highest emissions were due to CH4 leaking from seals on water pump shafts. On several
occasions, these leaks were repaired on site once they were identified. The median emission rate of all the
equipment leaks identified was 0.02 g min"1 and the mean was 1.6 g min"1, which yield emission factors of
about 0.1 kg C02-e t"1 and 2.4 kg C02-e t"1, respectively. This range is consistent with the emission factor
currently used in the National Energy and Greenhouse Reporting Method 1 methodology for estimating
equipment leaks.
Although well pad emissions were generally found to be low, one significantly higher emission source was
found on a vent associated with a water gathering line. This source appeared to be at least three times
higher than the highest emission rate from any well examined.
The results obtained in this study represent the first quantitative measurements of fugitive emissions from
the Australian CSG industry; however, there are a number of areas that require further investigation.
Firstly, the number of wells examined was only a very small proportion of the total number of wells in
operation. Moreover, many more wells are likely to be drilled over the next few years. Consequently the
small sample examined during this study may not be truly representative of the total well population. It is
also apparent that emissions may vary over time, for instance due to repair and maintenance activities. To
fully characterise emissions, a larger sample size would be required and measurements would need to be
made over an extended period to determine temporal variation.
In addition to wells, there are many other potential emission points throughout the gas production and
distribution chain that were not examined in this study. These include well completion activities, gas
compression plants, water treatment facilities, pipelines and downstream operations including LNG
facilities. Emissions from some of these sources are often estimated for reporting purposes using
methodology based on emission factors largely derived from the U.S. gas industry. However, reliable
measurements on Australian facilities are yet to be made and the uncertainty surrounding these some of
these estimates remains high.
36 | Field Measurements of Fugitive Emissions from Equipment and Well Casings in Australian Coal Seam Gas Production Facilities cn
by or /b gi of 87
-------
Allen, D.T. Torres, V.M., Thomas, J., Sullivan, D.W., Harrison, M., Hendler, A., Herndon, S.C., Kolb, C.E.,
Fraser, M.P., A. Daniel Hill, A.D., Lamb, B.K., Miskimins, J., Sawyer, R.F., Seinfeld, J.H., 2013.
Measurements of methane emissions at natural gas production sites in the United States.
Proceedings of the National Academy of Science 110,18023-18024.
Alverez, A.A., Pacala, S.W., Winebrake, J.J., Chameides, W.L., Hamburg, S.P., 2012. Greater focus needed on
methane leakage from natural gas infrastructure. Proceedings of the National Academy of Science,
109, 6435-6440.
API, 2009. Compendium of greenhouse gas emissions methodologies for the oil and natural gas industry.
American Petroleum Institute, Washington DC.
Brandt, A.R., Heath, G.A., Kort, E.A., O'Sullivan, F., Petron, G., Jordaan, S.M., Tans, P., Wilcox, J., Gopstein,
A.M., Arent, D., Wofsy, S., Brown, N.J., Bradley, R., Stucky, G.D., Eardley, D., Harris, R., 2014.
Methane leaks from North American natural gas systems. Science 343, 733-735.
BREE, 2013. Energy in Australia 2013. Bureau of Resources and Energy Economics, Canberra
(
, accessed 12 February 2014).
CAPP, 2002. Estimation of flaring and venting volumes from upstream oil and gas facilities. The Canadian
Association of Petroleum Producers, Calgary.
(http://www.cappxa/library/publications/sourGasl-laringVenting/pages/publnfo.aspx?Docld 3H23
4, accessed 30 May 2014).
Crosson, E.R., 2008. A cavity ring-down analyzer for measuring atmospheric levels of methane, carbon
dioxide, and water vapor. Applied Physics B 92, 403-408.
Day, S., Etheridge, D., Connell, N., Norgate, T. (2012). Fugitive greenhouse gas emissions from coal seam gas
production in Australia. CSIRO Report EP128173. 28 pp.
Day, S., DeN'Amico, M., Fry, R., Javanmard, H. (2013). Preliminary field measurements of fugitive methane
emissions from coal seam gas production in Australia. Proceedings of the 14th International
Conference on Coal Science and Technology, Pennsylvania State University 29 Sept-3 Oct 2013,
1445-1455.
DEEDI, 2010. Leakage testing of coal seam gas wells in the Tara 'rural residential estates' vicinity.
Department of Employment, Economic Development and Innovation, Brisbane.
(
accessed 21 February 2014).
DIICCSRTE, 2013a. Australian national greenhouse accounts. National inventory report 2011, Volume 1.
Department of Industry, Innovation, Science, Research and Tertiary Education, Canberra.
(
, accessed 23 February, 2014).
DIICCSRTE, 2013b. Australian national greenhouse accounts. National greenhouse account factors.
Department of Industry, Innovation, Science, Research and Tertiary Education, Canberra.
(
, accessed 17 May 2014).
DNRM, 2014. Queensland's coal seam gas overview, January 2014. Queensland Department of Natural
Resources and Mines, ( ,
accessed 11 February 2014).
Field Measurements of Fugitive Emissions from Equipment and Well Casings in Australian Coal Seam Gas Production ^ili^i^.|
of 87
-------
Etiope, G., Drobniak, A., Schimmelmann, A., 2013. Natural seepage of shale gas and the origin of the
'eternal flames' in the Norther Appalacian Basin, USA. Marine and Petroleum Geology 43, 178-186.
Francey, R.J., Steele, L.P., Spencer, D.A., Langenfelds, R.L., Law, R.M., Krummel, P.B., Fraser, P.J., Etheridge,
D.M.,Derek, N., Coram, S.A., Cooper, L.N., Allison, C.E., Porter, L., Baly, S., 2003.The CSIRO
(Australia) measurement of greenhouse gases in the global atmosphere, report of the 11th
WMO/IAEA. Meeting of Experts on Carbon Dioxide Concentration and Related Tracer Measurement
Techniques, Tokyo, Japan, September 2001, S.Toru and S. Kazuto (editors), World Meteorological
Organization Global Atmosphere Watch 97-111.
Hanna, S.R., Briggs, G.A., Hosker Jr., R.P., 1982. Handbook on atmospheric diffusion. U.S. Department of
Energy, Technical Information Center (page 29).
Ingraffea, A.R., 2013. Fluid migration mechanisms due to faulty well design and/or construction: an
overview and recent experiences in the Pennsylvania Marcellus play. Physicians, Scientists &
Engineers for Healthy Energy.
, accessed 24 February 2014).
IPCC, 2006. 2006 IPCC Guidelines for National Greenhouse Gas Inventories, Prepared by the National
Greenhouse Gas Inventories Programme, Eggleston H.S., Buendia L., Miwa K., Ngara T. and Tanabe
K. (eds). Published: IGES, Japan.
Karion, A., Sweeney, C., Petron, G., Frost, G., Hardesty, R.M., Kofler, J. Miller, B.R., Newberger, T., Wolter,
S., Banta, R., Brewer, A., Dlugokencky, E., Lang, P., Montzka, S.A., Schnell, R., Tans, P., Trainer, M.,
Zamora, R., Conley, S., 2013. Methane emissions estimate from airborne measurements over a
western United States natural gas field. Geophysical Research Letters 40, 4393-4397.
Kirchgessner, D.A., Lott, R.A., Cowgill, R.M., Harrison, M.R., Shires, T.M., 1997. Estimate of methane
emissions from the U.S. natural gas industry. Chemosphere 35, 1365-1390.
Klusman, R.W., 1993. Soil gas and related methods for natural resource exploration. Wiley, Chichester, UK.
Miller, S.M., Wofsya, S.C., Michalak, A.M., Kort, E.A., Andrews, A.E., Biraude, S.C., Dlugokenckyd, E.J.,
Eluszkiewicz, J., Fischerg, M.L., Janssens-Maenhouth, G., Miller, B.R., Miller, J.B., Montzka, S.A.,
Nehrkorn, T., Sweeney, C., 2013. Anthropogenic emissions of methane in the United States.
Proceedings of the National Academy of Science, 110, 20018-20022.
Pacific Environment Limited, 2014. AGL fugitive methane emissions monitoring program - technical report.
(http://www.agl.aim.au/'Vmedia/AGI /About%/!0AGI /Docurnerrt;s/How%20We%20Source%20tner
..«, accessed 15 February 2014).
Petron, G., Frost, G., Miller, B. R., Hirsch, A. I., Montzka, S. A., Karion, A., Trainer, M., Sweeney, C., Andrews,
A. E., Miller, L., Kofler, J., Bar-llan, A., Dlugokencky, E.J., Patrick, L., Moore Jr., C.T., Ryerson, T.B.,
Siso, C., Kolodzey, W., Lang, P.M., Conway, T., Novelli, P., Masarie, K., Hall, B., Guenther, D., Kitzis,
D., Miller, J., Welsh, D., Wolfe, D., Neff, W., Tans, P., 2012. Hydrocarbon emissions characterization
in the Colorado Front Range: A pilot study. Journal of Geophysical Research-Atmospheres, 117.
D04304.
Saddler, H., 2012. Review of literature on international best practice for estimating greenhouse gas
emissions from coal seam gas production. Report prepared for the Department of Climate Change
and Energy Efficiency. Pitt & Sherry.
(
, accessed 26 February 2014).
Santos, I., Maher, D., 2012. Submission on estimation of fugitive methane from coal seam gas operations.
38 | Field Measurements of Fugitive Emissions from Equipment and Well Casings in Australian Coal Seam Gas Production Facilities 71 f7E.
n 0T 83 Of 87
-------
, accessed 15
February 2014).
Somerville, W., 2012. Submission on estimation of fugitive methane from coal seam gas operations.
(
, accessed 31 January, 2014).
Tait, D.R., Santos, I. Maher, D.T., Cyronak, T.J., Davis, R.J., 2013. Enrichment of radon and carbon dioxide in
the open atmosphere of an Australian coal seam gas field. Environmental Science and Technology
47, 3099-3104.
USEPA, 1995. Protocol for Equipment Leak Emission Rates. U.S. Environmental Protection Agency,
Washington DC.
Wigley, T., 2011. Coal to gas: the influence of methane leakage. Climatic Change, 108, 601-608.
Field Measurements of Fugitive Emissions from Equipment and Well Casings in Australian Coal Seam Gas Production
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Appendix
Table Al. Results of the downwind traverse measurements for each well. The average results shown for Wells B2,
B7 and C3 were measured on each well pad. All units are g min1.
Al 0.04 0.03 0.11 0.03
A2-Suspended 0.00 0.00 0.00 0.00
A3 0.04 0.02 0.08 0.02
A4 7.28 2.75 13.42 3.38
A5 0.10 0.08 0.20 0.06
A6 0.05 0.04 0.05 0.01
B1 1.50 0.01 3.60 1.22
B2 43.8 (on pad) 1.09 66.5 22.5
B3 0.07 0.01 0.28 0.08
B4 0.04 0.01 0.22 0.06
B5 0.01 0.01 0.02 0.00
B6 1.66 0.77 3.10 0.74
B7 1.27 (on pad)
B8 1.31 0.10 2.85 0.98
B9 0.83 0.14 2.95 0.81
B10 0.15 0.07 0.28 0.07
Bll 1.79 0.09 3.65 1.07
B12 0.05 0.01 0.12 0.03
B13 0.02 0.01 0.06 0.02
B14 0.61 0.01 3.23 0.98
B15 1.61 0.11 7.78 2.35
CI 8.69 2.73 15.9 4.77
C2 1.10 0.33 2.45 0.66
40 | Field Measurements of Fugitive Emissions from Equipment and Well Casings in Australian Coal Seam Gas Production Facilities
<¦i of '=> 85 Of 87
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C3 28.0 (on pad)
C4 H.8 0.46 34.8 12.4
C5 0.93 0.21 1.82 0.56
C6 1.17 0.07 2.38 0.71
C7 0.54 0.04 0.99 0.35
C8 0.10 0.02 0.27 0.08
C9 0.05 0.01 0.10 0.03
CIO 1.75 0.76 3.52 0.82
Cll 0.07 0.05 0.10 0.02
D1 Abandoned 0.00 0.00 0.00 0.00
D2 0.12 0.03 0.16 0.04
D3 Abandoned 0.00 0.00 0.00 0.00
D4 0.32 0.17 0.57 0.13
D5 1.07 0.11 2.18 0.71
D6 2.52 0.44 5.00 1.42
El 2.17 0.63 4.08 1.19
E2 0.99 0.50 2.17 0.55
E3 0.60 0.22 1.13 0.33
E4 14.8 1.89 56.8 18.8
E5 0.06 0.01 0.19 0.06
Field Measurements of Fugitive Emissions from Equipment and Well Casings in Australian Coal Seam Gas Production
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CONTACT US
t 1300 363 400
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e enquiries@csiro.au
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-------
Clean Air Task Force comments on US EPA's
Draft US Greenhouse Gas Inventory Report 1990-2014
23 March 2016
Clean Air Task Force supports EPA's efforts to update the US GHG Inventory with the most
appropriate measurements and scientific information. We are pleased to submit comments on EPA's
February 2016 memos on Revisions Under Consideration for Natural Gas and Petroleum Production
Emissions, and Gathering and Boosting Emissions.
A. Petroleum and Natural Gas Production
The comments in this section focus closely on EPA's February 2016 memo on Revisions Under
Consideration for Natural Gas and Petroleum Production Emissions. We have provided answers to a
number of questions EPA raised in that memo.
The approach that EPA has laid out for incorporation of GHGRP data for Petroleum and Natural Gas
Production into the US GHG Inventory is sound and we encourage EPA to move ahead with this
approach in the 2016 Inventory. While GHGRP data must be used with care, it contains a very large
"sample" of activity data, representing a very significant portion of nationwide production activity. No
third-party study of oil and gas production activity would ever obtain data from such a large sample
(roughly 33%) of the industry, and GHGRP data is available rapidly and on an annual basis. It is very
clear that activity counts based on GHGRP will be far more accurate than those from the GRI study,
which was based on a much smaller sample of facilities and is more than two decades old. While
GHGRP reporters are not fully representative of all oil and gas production firms (they are certainly the
larger firms), the large number of firms that report makes it a very valuable data source for nationwide
emissions estimation.
Question 1. EPA's approach of scaling equipment counts for pneumatic controllers, separators, etc., to
wellhead counts is sound, and moreover it follows the approach of scaling equipment counts to
wellhead counts that the Inventory has used for many years. We believe that EPA's "Approach 2" for
apportioning activity between oil production and gas production is an appropriate methodology and
EPA should move forward with the Approach 2 methodology. We do not know of any other data
source that could be used to scale emissions to account for the non-reporting population.
We strongly urge EPA to directly report net emissions data by pneumatic controller type for years
when Subpart W data is available. If this data (ie, from 2011) can be interpolated back to the 1990s
base year for the GRI study, so that historical data is available by controller type, this might be
interesting but it would be somewhat academic, as only overall emissions are likely to be of interest for
pre-2011 data.
To our knowledge the estimate of emissions from completion of gas wells with hydraulic fracturing
and liquids unloading in the 2015 and 2014 Inventories analyzed GHGRP data to prepare emissions
estimates for each NEMS region, without adjusting data to account for the non-reporting population.
EPA should derive a methodology for accounting for the non-reporting population for gas well
completions, as it is considering doing so for the equipment counts in the 2016 Inventory. We believe
that such adjustments can be performed using data available in the DI database and the like. (Question
9a).
1
-------
Question 2. We agree that Allen (2015) is not appropriate for development of emissions factors for
pneumatic controllers, because Allen (2015) systematically underestimates emissions from pneumatic
controllers that are designed to release gas intermittently - and are thus counted in the inventory as
"intermittent-bleed" controllers.1
Question 5. While the variation between NEMS regions can be of interest, it is not clear that it is
always real and accurate. EPA should prioritize accurate national-level data as the Inventory is
developed; if this requires giving only national-level data for certain source types, as opposed to data
by NEMS region, EPA should do so.
Question 8. As discussed below in Section B, we believe the approach EPA is considering for
updating activity and emissions data for Gathering & Boosting facilities is sound and appropriate.
Marchese et al. has demonstrated that the current Inventory greatly underestimates emissions from
these facilities and it is important that EPA address this underestimate.
If the approach described in the Gathering and Boosting memo is taken, and EPA retains the approach
used in previous years for activity data for Production condensate tanks, Kimray pumps, and
dehydrator vents, there will be a small double counting issue: a small portion of these sources are
located at G&B facilities and emissions from them were included in the overall facility emissions
measurements used by Marchese et al. to calculate G&B sector emissions.
This overlap is small, as EPA has described on p. 4 of the G&B memo. Using calculations from
Marchese et al., about 31 Gg is emitted from these sources at G&B stations. Marchese et al. calculated
the portion of "production" equipment that is located at gathering facilities using a straightforward
comparison of the total activity data in the US GHG Inventory for "Natural Gas Production" to
nationally scaled activity data from counts at the facilities they studied. For Condensate tanks, Kimray
Pumps, and Dehydrator Vents, 31 Gg is emitted at G&B facilities. Note: EPA apparently calculates
that 44 Gg is emitted from overlapping sources on p. 4 of the G&B memo, but this includes Chemical
Injection Pumps (CIPs); EPA is proposing to use Well Production Facility GHGRP data for CIPs, so
there will not be overlap with G&B for CIPs). When CIPs are removed, the figure is 31 Gg.
Using this activity data (in Tables S7 and S8 of the Supporting Information section of Marchese et al.)
one can calculate appropriate factors to reduce the current "Production" Activity data for these
equipment types. For example, EPA's activity figure for condensate tanks (both controlled and
uncontrolled) in "Natural Gas Production" is 88 MMBbl/yr; Marchese et al. report that 3 MMBbl/yr of
that is in condensate tanks at G&B facilities. Therefore, EPA should reduce the activity data for
condensate tanks at Well Production Facilities by 3.4% (3/88) to correct for double counting. Using
the same logic, activity data for Kimray pumps and dehydrator vents should be decreased by 7.9%.
If EPA feels that this approach is not logical or is otherwise not appropriate, the inventory should
clearly note the sources that are subject to potential double counting and the estimated magnitude of it,
so that the issue is handled transparently.
1 See D. McCabe and L. Fleischman, "Average Emissions from Intermittent-Vent Pneumatic Controllers
as Reported by Allen et al. (2015)," Attached as Appendix A.
2
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Question 10. One of us (DM) recently co-signed a letter submitted by D.T. Allen to EPA concerning,
inter alia, the proper handling of super-emitters in oil and gas production. We reference those
comments in regard to this question.
Final note - we urge EPA to incorporate data from the GHGRP and elsewhere for two other sources
not discussed in the February memo. First, EPA should add a category for "oil well completions after
hydraulic fracturing" and use methods consistent with the emissions estimates prepared to support the
proposed NSPS Subpart OOOOa to calculate nationwide emissions. Second, EPA should incorporate
data from GHGRP on venting of natural gas from oil wells. Reported methane emissions for
"Associated Gas Venting" from GHGRP are far higher than the estimate of "Stripper Well" methane
emissions in the Inventory, as CATF has documented in our comments on Inventory Drafts in 2014
and 2015. EPA should update these two categories with the more accurate data it already has for the
final 2016 GHG Inventory. If this cannot be done, or EPA concludes that this would be inappropriate
now or in general, EPA should explain the reasoning in the text of the inventory. The 2016 Inventory
should not remain silent on these two emissions sources.
B. Gathering and Boosting
The comments in this section focus closely on EPA's February 2016 memo on Revisions Under
Consideration for Gathering and Boosting Emissions. We have provided answers to a number of
questions EPA raised in that memo.
Question 1. As stated above, the approach that EPA is considering for Gathering and Boosting (G&B)
is sound and appropriate. The papers EPA describes have identified a very significant issue with the
Inventory: Activity Data for G&B is significantly underestimated.
CATF urges EPA to incorporate the results of Marchese et al. and Mitchell et al. using the approach
discussed in the memo. These papers are based on large number of measurements at facilities carefully
chosen to represent G&B, and using an accurate methodology to capture all non-exhaust emissions
from the facility. We are not aware of any similar data sources that can be used to develop these
estimates. Note that CATF has worked in the past to develop improved activity data for G&B, which
we shared with EPA and the authors of Marchese et al. and Mitchell et al., so we have direct
knowledge of the available data.
Question 2. First, we urge EPA to present data on G&B as a distinct segment of the industry in the
2016 inventory. This will allow researchers and other stakeholders to compare measurements, activity
research results, etc., to the inventory with far greater accuracy (and ease).
EPA should make certain revisions to the equipment source type descriptions, etc., to carry this out.
For example, the approach EPA is considering effectively treats "small reciprocating compressors" as
wellpad compressors, while large recips are effectively compressors at G&B stations. EPA should re-
designate these sources as such, for clarity. Other sources would be clarified well simply by being
classified as "production" or "G&B" - for example, "Meters and Piping" which is a generic term but
apparently applies specifically to wellpads.
This is particularly important since these types of equipment do exist at G&B facilities, but under the
approach to Production and G&B presented in the memos, these lines in the inventory will only
3
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account for emissions at wellpads. It's really important that that be made clear to users who have not
studied these memos!
Second, EPA's proposed approach of using the Marchese et al. data for G&B stations, in tandem with
using scaled GHGRP activity data for many sources for production facilities, eliminates most of the
concern about double counting for overall emissions from natural gas production and G&B. A few
sources (condensate tanks, dehydrators and Kimray pumps) would still have some double counting. As
we describe above in response to Question 8 in the Production Memo, the quantity of double counting
is small, and EPA can correct for it by modestly reducing production segment activity data for these
sources, based on data compiled by Marchese et al.
It is not apparent how EPA will present data on G&B in the Inventory. The Marchese et al. emissions
estimate for G&B facilities includes emissions from a number of specific sources within those facilities
(compressor seal emissions, leaks from static components, pneumatic devices, etc.), but does not
apportion emissions to those sources. CATF supports the approach of using the Marchese data because
it will produce a far more accurate figure for overall emissions. However, we urge EPA to provide as
much information as possible about the individual sources of emissions within those facilities. Even if
information about the breakdown of individual sources within the larger category of "G&B Station
Emissions" cannot be made quantitatively consistent with the overall emissions from those stations,
best estimates of the breakdown of emissions would be valuable.
Question 3. CATF strongly supports moving forward with the approach to G&B emissions described
in the Memo for the 2016 Inventory. It would be inappropriate for EPA to delay updates for G&B
while waiting for the new GHGRP data from G&B. First, this data will not be available to EPA in time
for 2017 inventory, since facilities are not required to report emissions for 2016 (the first year for
which G&B is subject to GHGRP) until 31 March 2017, far too late for EPA to consider GHGRP data
for the 2017 Inventory. Thus, the update would be delayed by two full years from the present. Second,
operators of G&B stations are allowed to use Best Available Monitoring Methods for G&B stations in
2016, inevitably degrading the accuracy of the G&B data for 2016. Third, due to the reporting
threshold, many G&B facilities will not report to GHGRP, so direct GHGRP data will be an
underestimate of total G&B emissions, and as shown by the analysis undertaken by Marchese et al
summarized in the Memo, it is challenging to scale G&B measurements due to the lack of clear
nationwide activity data for G&B.
When G&B reports to GHGRP become available in 2017, they will provide valuable additional
information. This should be examined and possibly used to inform the 2018 Inventory (as stated above,
this can't happen in time for the 2017 Inventory). However, we are somewhat troubled that EPA is
considering "potentially revising the approach with new GHGRP data in the 2017 GHGI." While we
recognize that the Marchese approach based on emissions from the entire facility (less exhaust) is not
as useful for some purposes as an approach based on emissions from each type of equipment, the
measurements-based approach in Marchese et al. is more accurate than the GHGRP data will be. In
the GHGRP, many if not most emissions sources are estimated based on population emissions factors,
not actual measurements, and many of these emissions factors have been shown to be inaccurate and
highly variable between facilities. In contrast, Marchese et al. is based on actual measurements, so it is
much more accurate than the GHGRP will be.
4
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Question 4. CATF questions the usefulness of presenting geographic variability by NEMS region. In
the past we have raised questions about the usefulness and accuracy of breaking down data for liquids
unloading by NEMS region, for example. Because there is more variability within a single NEMS
region, which will typically contain conventional formations and many types of unconventional
formations, than between regions, the extrapolation of smaller data sets taken within a single NEMS
regions (which may be skewed to facilities handling gas from only certain formation types) to the
whole NEMS region is probably less accurate than using all available data to calculate national
emissions.
However, it would be very helpful to have more granular estimates of emissions - we just don't believe
the NEMS region breakdown is helpful. EPA should explore classification of production, and possibly
G&B, emissions by formation type. For example, G&B requirements may be very different for shale
gas and coal-bed methane (CBM), because the pressures of these formations are very different.
Question 5. Time series - CATF believes that the findings of Marchese et al. are generally applicable
to emissions over the whole time period of the Inventory (1990 - present). There is no reason to
believe that G&B emissions, per volume of gas produced, would have been vastly lower in the 1990s
than they are today. If anything, modern unconventional tight gas - produced at relatively high
pressures - requires less G&B equipment per unit of production than gas in the 1990s, which was
largely conventional and CBM.
Question 6. CATF believes that volume of marketed onshore natural gas production is the most
appropriate activity driver for G&B.
Question 7. Above we suggest breaking down activity / emissions were by formation type that G&B
stations serve, instead of NEMS regions. If this approach appears to have merit, it would probably be
the best way to estimate historical emissions.
Question 9. The activity data in past Inventories for G&B was clearly far too low: as demonstrated by
Marchese et al, working directly from State data and partner company data, there are thousands of
G&B stations nationwide, in contrast to the estimate of a few dozen in the Inventory, based on the GRI
study. We have not examined the GRI methodology but the result is clearly a gross underestimate of
G&B activity. We commend EPA for re-examining this data in light of the Mitchell et al. and
Marchese et al. results, and we urge EPA to move ahead with the approach suggested in the Memo for
the 2016 Inventory.
C. Natural Gas Distribution
CATF submitted comments to EPA in January, 2016, on the December 2015 memo, "Inventory of U.S.
Greenhouse Gas Emissions and Sinks: Revisions under Consideration for Natural Gas Distribution
Emissions." In those comments we raised several issues with the calculation of the number of
underground pipeline and service leaks proposed in the December 2015 memo. Briefly, these issues
are:
• The methodology and data for calculating the number of underground pipeline leaks is taken
from Lamb et al (2015). This methodology is logically flawed: the algebra is not consistent
with the approach operators take to surveying distribution systems for leaks. Furthermore, the
5
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underlying data for leak counts presented in Lamb et al (2015) are not consistent with the
definitions used by Lamb et al. It appears that some of the partner companies misinterpreted
survey questions, so the underlying data is also flawed.
• Lamb et al. assume that operators surveying distribution systems find 85% of leaks, based on
the same assumption in the 1990s GRI study. The GRI study attributed that assumption to
information from a single partner company; no data or explanation is provided to substantiate
the claim. Recent data presented by PG&E at a recent Gas Star meeting contradicts this
assumption and shows that less than 85% of leaks are found using typical surveys.
• The leak per mile frequencies that EPA proposed in the December 2015 memo are inconsistent
with the results from vehicle-based leak surveys that have been published in recent years.
These surveys found significantly higher leaks in cities with significant amounts of outdated
pipelines than the leak-per-mile frequencies EPA proposed would predict.
We further noted that top-down analyses have shown that emissions from natural gas distribution in
two urban areas, Boston and Los Angeles, are considerably higher than EPA's 2015 GHG Inventory
implied. The proposed changes to the Inventory will substantially reduce the estimate of emissions
from Distribution, exacerbating the gap between what was measured in those cities and what the
Inventory predicts.
Considering these internal flaws and inconsistencies with recent observations, CATF recommends
against the proposed updates for underground pipeline leaks. If EPA concludes that the Inventory
should be updated for this section as proposed, then EPA should clearly note these issues in the text of
the inventory.
Concluding Remarks
Thank you for considering these comments. Please contact us if you would like to discuss or clarify
any of the information we have presented.
Sincerely,
David McCabe
Scientist
Clean Air Task Force
18 Tremont St, Ste. 530
Boston, MA 02108
626 710 6542
dmccabe @ catf. us
6
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Appendix A
Average Emissions from Intermittent-Vent Pneumatic Controllers
as Reported by Allen et al. (2015)
David McCabe
Lesley Fleischman
Clean Air Task Force
December 2015
Allen et al. (2015) reports the results of a new set of measurements of emissions from 377 pneumatic
controllers at 65 oil and natural gas production sites (largely natural gas sites).1 Allen et al. (2015)
reports that the average whole gas emission rate from all pneumatic controllers they sampled was 5.5
standard cubic feet per hour (scfh). This emissions factor is lower than the average emissions factor for
all pneumatic controllers reported from earlier measurements of 305 pneumatic controllers by Allen et
al. (2013), 11.2 scfh.2 Allen etal. (2015) attribute the lower emissions per controller (as compared to
Allen et al. (2013)) primarily to the large number of controllers they observed that did not emit.3 Allen
et al. (2015) also reports that the wellsites they surveyed had 2.7 pneumatic controllers per well, a
much higher figure than the activity ratio used by the USGHGI of 1.0 pneumatic controller per well.
As Allen et al. (2015) discuss, it is possible that well site operators are often not counting intermittent-
bleed pneumatic controllers that rarely actuate, such as controllers for emergency shut-off devices, in
their counts of pneumatic controllers for purposes such as greenhouse gas reporting.4 Previous research
efforts may have similarly undercounted these controllers. When these controllers are included,
average emissions per controller decrease.
Notably, Allen etal. (2015) reports that the average emissions rate from "intermittent-vent" pneumatic
controllers in their sample was 2.2 scfh. This is considerably lower than the emissions factor for
"intermittent-bleed pneumatic devices" in EPA's Greenhouse Gas Reporting Program, 13.5 scfh,5 or
reported by Allen et al. (2013), 17.4 scfh.
However, the average emissions for intermittent-vent controllers from Allen etal. (2015) is not directly
comparable to the emissions factors from those other sources. Allen etal. (2015) labeled controllers
empirically, "based on the pattern observed during measurement."6 In cases where controllers that were
designed to bleed intermittently were functioning improperly and continuously bleeding gas, Allen et
al. (2015) labeled the controller as "continuous bleed" if the continuous bleed constituted the dominant
source of emissions. As an example, the time trace of controller LB07-PC02 is shown below in Figure
1. Functionally, this device is clearly an intermittent-bleed pneumatic controller. However, Allen et al.
(2015) treat this device as a continuous-bleed controller.7 This controller is not unique in the Allen et al.
1 Allen D.T. et al. (2015), "Methane Emissions from Process Equipment at Natural Gas Production Sites in the United
States: Pneumatic Controllers," Environ. Sci. Technol. 49, 633-640.
2 Allen, D.T., et al. (2013), "Measurements of methane emissions at natural gas production sites in the United States," Proc.
Natl. Acad. Sci. USA 110(44): 17768-17773.
3 Allen et al. (2015) at 638.
4 Ibid.
5 See Table W-1A to Subpart W of 40 C.F.R. Part 98.
6 Allen etal. (2015) at 634.
7 Allen et al. (2015) at table S4-2 (page S-24).
7
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(2015) dataset. A total of seven controllers (including LB07-PC02)8 are labeled as continuous-bleed by
Allen etal. (2015), but were observed to actuate (actuations listed in table S4-5).
i 1 1 r
0 5 10 15
Elapsed Time (Minutes)
Figure 1. Time trace of controller LB07-PC02 from Allen et al. (2015).
Source: Allen et al. (2015), supporting information, section S8 (page S-86).
Two of these controllers are very high emitters, with emission rates over 35 scfh whole gas. All but one
of these seven controllers emit more gas than the 2.2 scfh reported as the average for intermittent-vent
controllers by Allen et al. (2015). The average emission rate for these 7 controllers was 18.0 scfh.
As discussed by Allen et al. (2015) and elsewhere, pneumatic controllers frequently function
improperly and as a result bleed more natural gas than they are designed to emit. Intermittent-bleed
controllers will typically malfunction by emitting continuously, while it would be very unusual for a
continuous-bleed controller to malfunction by emitting intermittently. As a result, the approach taken
by Allen et al. (2015) systematically biases low their results for "intermittent-vent controllers," relative
to average emissions for functional intermittent-bleed controllers, by labeling intermittent-bleed
controllers that are high-emitting due to continuous leaks as continuous-vent controllers.
Simply combining the seven controllers discussed above with the 320 controllers that Allen et al.
(2015) have labeled as "intermittent-vent" yields an average emissions factor for the combined set of
8 Controller IDs OF07-PC01, LB07-PC02, AA02-PC07, XQ01-PC04, GZ03-PC01, AA02-PC06, and CW02-PC33.
8
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327 controllers, 2.55 scfh, that is 15% higher than Allen et al. (2015)' s result for "intermittent-vent
controllers."
However, it is very likely that additional pneumatic controllers that are functionally intermittent-bleed
are classified as continuous-vent controllers. This is because if an intermittent-bleed controller did not
actuate during the observations, but (improperly) leaked gas, Allen et al. (2015) probably classified it
as continuous-vent. Since a large portion (75%) of the controllers that were classified as intermittent-
vent did not actuate during the observations, this scenario is very likely. Indeed, there are twelve non-
actuating controllers that operators classified as intermittent-bleed and Allen et al. (2015) classify as
continuous-vent. Emissions from these devices range from 2.9 - 111.4 scfh, with all but one emitting 6
or more scfh. The average from this set of controllers was 29.5 scfh. It is likely that most or all of these
devices were actually functional intermittent-bleed controllers that were classified as continuous-vent
devices due to improper continuous emissions.
If we assume that all of these devices are in fact intermittent-bleed controllers, as the operators
classified them, and combine this set with the set of 327 controllers described above, the average
emissions for the combined set (n = 339) is 3.5 scfh, 58% higher than the intermittent-vent emissions
factor reported by Allen et al. (2015).
There are probably other devices in the dataset that were non-actuating intermittent-bleed controllers
that were improperly emitting continuously. 29 controllers that were not classified as either
intermittent-bleed or continuous-bleed by operators were classified as continuous-vent in the dataset.
These devices also have high emissions (average 17.8 scfh). Given the high proportion of intermittent-
bleed devices in the dataset, and the fact they often improperly emit continuously, it is probable that a
number of these are also functionally intermittent-bleed controllers. Inclusion of those devices in the
dataset would further increase the average emissions for intermittent-bleed controllers in the dataset.
In conclusion, the reported average emissions for "intermittent-vent" pneumatic controllers from Allen
et al. (2015) is not representative of functional intermittent-bleed pneumatic controllers, that is,
pneumatic controllers that are designed to bleed natural gas intermittently.
9
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NACWA
A ¦. l< ,r Commitment to America** Waters
EXECUTIVE COMMITTEE
PRESIDENT
Adel H, Hagekhalil
Assistant Director
City of Los Angeles -
LA Sanitation
Los Angeles, CA
VICE PRESIDENT
Raymond J. Marshall
Executive Director
Narragansett Bay Commission
Providence, Rl
TREASURER
Cathy Gerali
District Manager
Metro Wastewater
Reclamation District
Denver, CO
SECRETARY
David St. Pierre
Executive Director
Metropolitan Water
Reclamation District of
Greater Chicago
Chicago, IL
PAST PRESIDENT
Karen L. Pallansch
Chief Executive Officer
Alexandria Renew Enterprises
Alexandria, VA
CHIEF EXECUTIVE OFFICER
Adam Krantz
March 23, 2016
Leif Hockstad
U.S. Environmental Protection Agency
Climate Change Division
1200 Pennsylvania Ave, NW
Washington, DC 20460
Via Email: Hockstad.Leif@epa.gov
Re: NACWA Comments on Wastewater Treatment Emissions Estimates in EPA's
Draft Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2014
Dear Mr. Hockstad:
The National Association of Clean Water Agencies (NACWA) appreciates this
opportunity to comment on the U.S. Environmental Protection Agency's (EPA) draft
Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2014 (Inventory), and
specifically Section 7.2, Wastewater Treatment (IPCC Source Category 5D). NACWA
represents the interests of nearly 300 publicly owned wastewater treatment agencies
nationwide, serving the majority of the sewered population in the U.S. NACWA
members want to ensure that greenhouse gas (GHG) emissions from wastewater
treatment facilities be characterized correctly in the Inventory, since the Inventory is a
frequently-cited reference for GHG information.
NACWA has submitted comments on each of the previous nine Inventories, and we
appreciate the clarifications that EPA has made to clarify the emissions calculations
and the factors that are used in the calculations. Although the wastewater treatment
section has not yet been updated for the 2014 Inventory, EPA states that the same
methodology will be used as in the previous Inventory. NACWA previously stated its
concern that potentially outdated data was used in the emissions calculations (e.g.,
the 2004 Clean Watershed Needs Survey). If the same data is used in the 2014
Inventory, our concern remains that the calculations may not accurately reflect
current wastewater utility practices. NACWA also believes that more specific
emissions factors could be developed for U.S. wastewater treatment.
NACWA understands that EPA will be looking at possible improvements for the
wastewater treatment calculations in the next year. NACWA is willing to assist EPA
National Association of
Clean Water Agencies — _
1816 Jefferson Place, NW
Washington DC 20036-2505 www.nacwa.org • info^nacwa.org
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NACWA Comments on 2014 GHG Inventory
March 23, 2016
Page 2 of 2
in any way with these improvements, such as providing general information about current wastewater practices
or collecting specific data from our member utilities.
Please contact me at 202-533-1836 or cfinley@nacwa.org if you have any questions.
Sincerely,
Cynthia A. Finley, Ph.D.
Director, Regulatory Affairs
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ncasi
NATIONAL COUNCIL FOR AIR AND STREAM IMPROVEMENT, INC.
West Coast Regional Center
720 SW Fourth Street, Corvallis OR 97333
Phone: (541)752-8801 Direct: (541) 368-7707 Fax: (541)752-8806
Brad Upton
Principal Research Engineer
bupton@ncasi.org
March 23, 2016
Via email to Leif Hockstad
United States Environmental Protection Agency
Climate Change Division, Office of Atmospheric Programs
RE: Comments on Public Review Draft US Inventory of Greenhouse Gas Emissions and Sinks:
1990-2014
Dear Mr. Hockstad:
Thank you for the opportunity to provide input on the public review draft Inventory of US
Greenhouse Gas Emissions and Sinks: 1990-2014. We submit the following technical
comments.
Land Use, Land Use Change, and Forestry
The estimated forest ecosystem carbon stock changes reported in the draft 1990-2014 national
inventory are significantly different than those reported previously. The text in the report
explains that this is due, at least in part, to new estimation methods (described in Woodall et al.
20151) and reclassification of land in Alaska. It is our understanding that the new estimates rely
more heavily on measured data (compared to model-generated data) than earlier estimates and,
as a result, are likely to be more accurate. It would be helpful for the text in the report to
elaborate on the benefits of greater reliance on measured vs. modeled data in the updated
estimates.
While the report contains a summary of the recalculations of forest ecosystem carbon, it is
unfortunate that the annexes have not been updated to provide a full explanation of the sources of
the difference between the new and previous estimates. We encourage the agency, in future
years, to make the annexes available for comment at the same time the report is made available.
Changes in carbon stocks in products-in-use are also significantly different than in previous
inventories, but this is not acknowledged or explained in the report or the annexes. This should
be discussed in the report and examined in more detail in the annexes.
1 Woodall CW, Coulston JW, Domke GM, Walters BF, Wear DN, Smith JE, Anderson H-E, Clough BJ, Cohen
WB, Griffith DM, Hagan SC. Hanou IS, Nichols MC, Perry CH, Russell MB, Westfall JA, Wilson BT. 2015.
The US Forest Carbon Accounting Framework: Stocks and Stock change 1990-2016. Gen. Tech. Rep. NRS-154.
Newtown Square, PA: US Department of Agriculture, Forest Service, Northern Research Station. 49 pp.
. environmental research for the forest products industry since 1943
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Comments on Public Review Draft US Inventory of Greenhouse Gas Emissions and Sinks: 1990-2014
page 2
March 23, 2016
Waste
In Chapter 7 Waste on page 7-11, line 1, EPA states that the degradable organic carbon (DOC)
value for landfilled pulp and paper waste was revised from 0.20 to 0.15 based on a literature
review and data reported under 40 CFR Part 98 (referred to as the Greenhouse Gas Reporting
Program, GHGRP, the new DOC value is also discussed in Chapter 9 Recalculations and
Improvements on page 9-1, line 39, and in Annex 3.14 on page A-391, line 38). The new value
of 0.15 corresponds to a weighted average of all DOC values reported to the GHGRP within
subpart TT by pulp and paper facilities in 2013. It is stated in a reference supporting the draft
inventory (RTI2015 ) that 72% of the pulp and paper facilities that reported to subpart TT used
only the default DOC values from Table TT-1 and that 49% of the reported waste quantities were
associated with the default DOC value for general pulp and paper industry waste other than
industrial sludge (0.20). Therefore, the new DOC value used in the draft inventory (0.15) is
heavily influence by use of the default value of 0.20 in Table TT-1.
The current default DOC for general pulp and paper industry waste other than industrial sludge
in Table TT-1 (0.20) is based on an erroneous interpretation of IPCC guidance, as documented
by NCASI in prior communications with EPA (NCASI20113). Therefore, it is inappropriate to
include data elements corresponding to the default value of 0.20 when developing a new DOC
value for use in the inventory. As noted in RTI 2015, 28% of pulp and paper facilities that
reported to subpart TT developed DOC values specific to their landfilled waste streams by
analysis using methodologies specified by EPA. It is more technically appropriate (and accurate)
to develop a DOC value for pulp and paper industry waste from a weighted average of these
waste stream-specific DOC values reported to the GHGRP, as these values represent the
characteristics of the actual waste placed in industrial landfills at pulp and paper mills and would
not be influenced by the erroneous general DOC value of 0.2. RTI 2015 presents such a
weighted average DOC value for pulp and paper industry wastes, which is 0.10. EPA should use
a DOC value of 0.10 rather than 0.15 in developing estimates of methane emissions from
industrial landfills at pulp and paper mills.
In Annex 3.14 on page A-391. line 38. EPA incorrectly associates the new DOC value for pulp
3 3
and paper industry waste (0.15) with an Lo value of 49 m /MT. An Lo value of 49 m /MT
correlates with a DOC value of 0.10, which is the technically appropriate DOC value to use in
the agency's top down analysis as explained above. On line 47 the agency states that "data were
available through the GHGRP to warrant a change to the L0 (DOC) from 99 to 49 m3/MT..."
Note that the previous DOC (0.20) is correlated with an L0 of 99 m3/MT, and further note that
"3
DOC is directly proportional to Lo. Therefore, halving Ln (from 99 to 49 m /MT) would result in
DOC also being halved (i.e.. from 0.20 to 0.10).
As conveyed in our comments on the public review Draft US Inventory of Greenhouse Gas
Emissions and Sinks: 1990-2013 (included herein as Appendix A), production statistics
developed by EPA for use in waste-related GHG emissions calculations for the pulp and paper
2 Research Triangle Institute (RTI). 2015. Investigate the potential to update DOC and k values for the Pulp and
Paper industry in the US Solid Waste Inventory. Memorandum prepared by K. Bronstein and M. McGrath for R.
Schmeltz (EPA). December 4, 2015.
3 National Council for Air and Stream Improvement, Inc. (NCASI). 2011. Errors in EPA GHG rule industrial
landfill methane calculation method parameter. Memorandum from B. Upton to S. Hogan (EPA). July 20.
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Comments on Public Review Draft US Inventory of Greenhouse Gas Emissions and Sinks: 1990-2014
page 3
March 23, 2016
sector are too high. Table 7-12 lists 2013 production of the pulp and paper sector at
131.5 million metric tons, based on data from the Food and Agriculture Organization of the
United Nations (FAO), and includes a note that this figure represents the sum of woodpulp
production plus paper and paperboard production. The same production figures are presented in
RTI20064, which describes EPA's method for estimating industrial landfill emissions.
Summing woodpulp, paper, and paperboard production results in double counting, because the
majority of woodpulp production is used to produce paper and paperboard at integrated mills (an
integrated mill includes both pulping and papermaking at the same facility).
A more appropriate method for characterizing total pulp and paper sector production would be to
sum paper production, paperboard production, and market pulp production. For 2013, the
American Forest and Paper Association reported total production of paper and paperboard to be
approximately 73 million metric tons and total production of market woodpulp to be
approximately 8 million metric tons (AF&PA 20146). Based on these statistics, total pulp and
paper sector production in 2013 was approximately 81 million metric tons.
EPA's method of using the FAO statistics overstates the pulp and paper industrial sector's
production, which in turn results in estimates of pulp and paper sector industrial wastewater
treatment and landfill methane emissions being far too high. On page 7-28 of the Draft US
Inventory of Greenhouse Gas Emissions and Sinks: 1990-2014, lines 42-47, EPA notes that the
agency is evaluating new approaches to estimating industry-level production (and other values)
used in estimating industrial wastewater treatment GHG emissions. The agency should use
production data from AF&PA's Statistical Summary reports in calculating both wastewater
treatment and landfill emissions from the pulp and paper sector, which will result in more
accurate characterization of industrial waste-related methane emissions from this sector.
Please feel free to contact me for clarifications or with questions.
Brad Upton, Ph.D.
National Council for Air and Stream Improvement, Inc.
720 SW Fourth Street
Corvallis OR 97333
telephone: 541-368-7707 (direct); 541-752-8801 ext 309 (office)
bupton@ncasi. org
Best Regards,
Brad Upton
Principal Research Engineer
4 Research Triangle Institute (RTI). 2006. Methane Emissions for Industrial Landfills. Memorandum prepared by
K. Weitz and M. Bahner for M. Weitz (EPA). September 5.
5 Market pulp is produced at a pulp mill and then sold rather than being used at the same mill to produce paper or
board.
6 American Forest and Paper Association (AF&PA). 2014. 2013 Statistical Summary: Paper, Paperboard: Pulp.
August.
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PC/k
America's Cement Manufacturers™
Portland Cement Association
1150 Connecticut Avenue NW, Suite 500
Washington, DC 20036-4104
202.408.9494
www.cement.org
Michael Schon
Vice President and Counsel,
Government Affairs
mschon@cement.org
Via Electronic Mail and Regulations.gov
March 23, 2016
Leif Hockstad
Climate Change Division
Office of Atmospheric Programs (MC-6207S)
U.S. Environmental Protection Agency
hockstad.leif@epa. gov
Re: Comments on EPA's Draft Inventory of U.S. Greenhouse Gas Emissions and Sinks:
1990-2014, Docket No. EPA-HQ-OAR-16-000-4157
Dear Mr. Hockstad:
The Portland Cement Association (PCA)1 appreciates the opportunity to comment on the
Draft Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2014 (hereinafter Draft
Inventory). See 81 Fed. Reg. 8713 (Feb. 22, 2015). PCA recognizes the importance of
understanding greenhouse gas (GHG) emissions at the domestic and international levels.
The Draft Inventory's approach to accounting for emissions associated with cement
production does not consider available data, however, or determine whether those data are
consistent with the conclusions reached by the Draft Inventory. In addition, the Draft Inventory
does not present a comprehensive and easily discernible estimate of the industry's total GHG
emissions. This issue makes verification of the total emissions associated with cement
production impossible and also masks efficiency improvements by the sector. In these
comments, PCA suggests areas for improvement to address these concerns.
As the Draft Inventory acknowledges, GHG emissions are released at two points in the
production of cement—an essential component of concrete. First, the combustion of fuel to heat
1 PCA represents more than 92% of U.S. cement manufacturing capacity. PCA members
operate manufacturing plants in 33 states, with distribution terminals in all 50 states, servicing
nearly every Congressional district. Founded in 1916, PCA is the widely-recognized authority
on the technology, economics, and applications of cement and concrete. The association
advocates for sustainability, economic growth, sound infrastructure investment, and overall
innovation and excellence in construction.
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EPA-HQ-OAR-16-000-4157
March 23, 2016
Page 2 of 3
cement kilns and to enable necessary chemical reactions produces GHG emissions. Thanks to
efficiency improvements, including use of carbon-neutral alternative fuels, cement production
plants reduced combustion-related emissions per unit of production in recent years.2 Second,
emissions are generated through calcination, a chemical reaction that produces calcium oxide—a
foundational component of cement. Calcium carbonate is converted to calcium oxide and carbon
dioxide: CaCCte CaO + CO2. There is little opportunity to reduce the calcination process-
related CO2 emissions per unit of production.
EPA developed a Greenhouse Gas Reporting Program (GHGRP) for cement plants to
inventory both of these types of emissions on a facility-specific basis. Under Subpart H to 40
C.F.R. Part 98, all cement production plants in the United States must report both their
combustion-related and process-related emissions. 40 C.F.R. §§ 98.80, 98.82. EPA now has
five years of reported data from those facilities on file. In 2010, an Intergovernmental Panel on
Climate Change (IPCC) task force encouraged the consideration of GHGRP data in the
development of the annual inventory of domestic GHG emissions that EPA submits to the United
Nations in accordance with the United Nations Framework Convention on Climate Change
(UNFCCC).3
Yet this year's draft domestic inventory, like its predecessors, still does not consider the
GHGRP data for cement production, including whether those data points are in line with the
GHG estimations presented in the Draft Inventory. Rather, EPA punts on considering those data.
This is a missed opportunity to evaluate facility-specific data, as EPA itself acknowledges.4
In the Draft Inventory, EPA also misses an opportunity to analyze emissions associated
with cement production in a comprehensive manner. While the process-related emissions of
cement production are addressed in the Industrial Processes and Product Use chapter of the Draft
Inventory, the combustion-related emissions of cement production are not disaggregated from
2 See Gale Boyd & Gang Zhang, Measuring Improvement in the Energy Performance of
the U.S. Cement Industry (May 2011),
https://www.enereYStar.eov/sites/defaiilt/files/biiildines/tools/Diike%20Report.%20on%20Cemen
t%20EPI%20Update.pdf.
3 See Intergovernmental Panel on Climate Change (IPCC) Task Force on National
Greenhouse Gas Inventories, Use of Models and Facility-Level Data in Greenhouse Gas
Inventories, Report of the IPCC Expert Meeting on Use of Models and Measurements in GHG
Inventories at 115-16 (Aug. 9-11, 2010), http://www.ipcc-
neeip.iees.or.ip/pubtic/Mtdocs/pdfites/1008 Model and Facilm j ^ I 1! <>a Report.pdf
(hereinafter IPCC Task Force Report).
4 Draft Inventory at 4-9.
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EPA-HQ-OAR-16-000-4157
March 23, 2016
Page 3 of 3
other industries' combustion-related emissions in the Energy chapter.5 The Draft Inventory
estimates total process-related cement production emissions at 38.8 MMT CChe in 2014,6 but
presents no equivalent figure for the combustion-related cement production emissions. This
makes it impossible to determine the total emissions generated by the industry.
Thus, PC A cannot comment on whether the Draft Inventory's accounting of cement
production emissions is defensible or accurate. We encourage EPA to calculate and present an
overall emissions figure associated with cement production so that it can be compared to the total
reported cement production emissions of 67.6 MMT CChe in 2014 under the GHGRP.7
PCA also encourages EPA to consider cement production emissions not only on a total
mass basis but also on a production rate basis so that efficiency improvements are apparent. As
economic conditions have improved, demand for cement has increased, resulting in an increase
in the total tons of emissions. Importantly, however, significant efficiency improvements, on an
emissions per unit of production basis, have also occurred.
PCA recognizes that development of the annual inventory is an iterative process. We
appreciate your attention to these comments and would welcome the opportunity to further
discuss cement production GHG emissions with you, especially as EPA develops future
inventories. Please let me know your availability for a meeting in April.
5 Id. at 4-6. The IPCC task force highlighted the GHGRP's disaggregation of emissions
by industry as one of its strengths and as an area for improvement in the U.S. domestic
inventory. IPCC Task Force Report at 116.
6 Draft Inventory at 4-7.
7 EPA, GHGRP 2014: Minerals, https ://www. epa. gov/ eh greporting/ eh Minerals.
Regards,
Michael Schon
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Reassessing the EPA's Alternative GWP Analysis - Inventory Chapter 6.1
March 22, 2016
Mr. Leif Hockstad
U.S. Environmental Protection Agency
1200 Pennsylvania Avenue, N.W.
Washington, DC 20460
Dear Mr. Hockstad,
We respectfully submit these comments on the Draft U.S. Greenhouse Gas Inventory
Report: 1990-2014. Our comments are intended to encourage EPA to examine gross U.S.
greenhouse gas (GHG) emissions using the most updated values of the Global Warming
Potential (GWP) of methane and nitrous oxide. Given recent international news on
China's underreporting of its coal consumption and, accordingly, GHG emissions (a
November 3, 2015 New York Times article estimates the undercounting at over 900
million metric tons), we believe that the U.S. should place additional importance on
accurately quantifying its own GHG emissions.
Our comment states that the Inventory Report, in Annex 6.1, uses an alternative set of
GWPs [from the Intergovernmental Panel on Climate Change's 5th Assessment Report
(AR5)] that exclude carbon cycle feedbacks, resulting in emissions estimates lower than
if EPA were to include these feedbacks. While we understand that EPA excludes these
feedbacks to align methodology with the GWPs used in the main text of the Inventory
Report, we believe that these higher emissions estimates, which represent the full climate
impact of methane and nitrous oxide, must be presented to the public.
It is our goal to increase the transparency by which the EPA reports U.S. GHG emissions
to the global community. We believe that using GWPs inclusive of carbon cycle
feedbacks accomplishes this goal.
Thank you for your consideration.
Sincerely,
Evan Weber, Executive Director
U.S. Climate Plan
William Snape, Senior Counsel
Center for Biological Diversity
Lydia Avila, Executive Director
Energy Action Coalition
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Colette Pichon Battle, Director
Gulf Coast Center for Law & Policy
Joan Brown, Executive Director
New Mexico Interfaith Power and Light
Andres Restrepo, Staff Attorney
Sierra Club
Alan Journet, Co-facilitator
Southern Oregon Climate Action Now
Erik Schlenker-Goodrich, Executive Director
Western Environmental Law Center
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In Section 6.1 of the U.S. GHG Inventory, Table A-282 presents alternative scenarios of
greenhouse gas emissions estimates if EPA used GWPs from the IPCC Fifth Assessment
Report (AR5), rather than the Fourth Assessment Report (AR4). However, this analysis
underestimates the GWP of CH4 and N2O, based on Table 8.7 (page 714) of the AR5
Working Group I report. This underestimation results from excluding "carbon cycle
feedbacks" previously not quantified in AR4. Table 1 shows that by including these
feedbacks for AR5 100-year GWPs, the emissions increase (relative to AR4 values) is far
higher than EPA presents. While EPA reports this increase to be 22.6 (0.3% higher than
AR4 total emissions) MMTCChe, the true value is 238.0 (3.5% higher) MMTCChe.
According to WRI's CAIT tool, this additional 215.4 MMTCChe is roughly equal the
gross emissions of Norway, Sweden, Denmark, and Finland—combined.
Our analysis does not include the following factors, which we believe indicate that our
upward adjustments are actually conservative:
# IPCC indicates that the GWP of biogenic methane is 34, whereas fossil methane is
36, over a 100-year time horizon. Given that over one-third of U.S. methane
emissions are fossil (from natural gas systems, coal mining, and petroleum
systems), the change in methane from AR4 to AR5 should be greater than our
value of 254.8.
# EPA's also underestimates the GWP of HFC-134a, which represents 40% of
Emissions from Substitution of Ozone Depleting Substances - the AR5 value EPA
uses is 1,300, whereas IPCC, including carbon cycle feedback, uses 1,550. Other
high-GWP gases, whose carbon cycle feedbacks are not quantified in Table 8.7,
very likely have higher GWPs than EPA uses in Annex 6.1, though the lack of
IPCC data prevents us from quantifying this.
These emissions must be presented to the public. We do understand that EPA has chosen
not to include the carbon cycle feedbacks from CH4 and N2O for the AR5 GWPs in order
to align methodologies with AR4. However, given that the GWPs highlighted yellow in
Table 1 below are the "true" values, we see no reason to keep the lower AR5 numbers, as
changes in methodology to quantify carbon cycle feedbacks are precisely the goal of
updated scientific research. If consistency between methodologies really is necessary
(though again, this shouldn't be a reason not to use the higher values), then we
recommend communicating these findings in addition to the previous ones. Table 2
presents the GHG emissions totals by gas, for further transparency as to how we
calculated the differences between emissions for each GWP accounting method.
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Table 1 - Changes in Emissions using AR4 GWPs, AR5 GWPs Excluding Climate Feedbacks, and AR5 GWPs
Including Climate Feedbacks
GHG
AR4 GWP
Inventory
AR5 GWP
Inventory
2014 Change
from AR4 to
AR5 - no
Carbon Cycle
Feedback
%
Change
AR5
GWP -
IPCC
2014 Change
from AR4 to
AR5 - Carbon
Cycle Feedback
Included
%
Chang
e
C02
1
1
0.0
0%
1
0.0
0%
ch4
25
28
84.9
12.0%
34
254.8
36%
n2o
298
265
-45.6
-11.1%
298
0.0
0%
HFCs
MIXED
MIXED
-16.4
-9.3%
MIXED
-16.4
-9.3%
PFCs
MIXED
MIXED
-0.6
-9.6%
MIXED
-0.6
-9.6%
SF6
22,800
23,500
0.2
3.1%
23,500
0.2
3.1%
nf3
17,200
16,100
0.0
-6.4%
16,100
0.0
0%
Total 22.6 0.3% 238.0 3.5%
Table 2 - GHG Emissions Totals by Gas using IPCC's AR4, EPA's AR5, and IPCC's AR5 GWPs
GHG
2014 Emissions
(AR4)
2014 Emissions (AR5, excluding
carbon cycle feedbacks)
2014 Emissions (AR5, including
carbon cycle feedbacks)
CO 2
5,564.3
5,564.3
5564.3
CH4
707.9
792.8
962.7
N20
411.4
365.8
411.4
HFCs
175.8
159.4
159.4
PFCs
5.8
5.2
5.2
SF6
6.9
7.1
7.1
NF3
0.6
0.6
0.6
Total
6,872.7
6,895.3
7,110.7
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March 22, 2016
Via Electronic Transmission: hockstad.leif@epa.gov
Schmeltz. rachel@epa. go v
Mr. Leif Hockstad
Ms. Rachel Schmeltz
Office of Atmospheric Programs, Climate Change Division
U.S. Environmental Protection Agency (MC-6207S)
1200 Pennsylvania Ave., NW
Washington, DC 20460
Re: Draft Inventory of U.S. Greenhouse Gas (GHG) Emissions and Sinks: 1990-2014
Dear Leif and Rachel:
The undersigned organizations representing both private and public landfill owners and
operators, solid waste consultants, and industry trade and professional organizations
(hereinafter referred to as the landfill sector), are pleased to offer the following comments on
the United States Environmental Protection Agency's (EPA) Draft Inventory of U.S. Greenhouse
Gas (GHG) Emissions and Sinks: 1990-2014 (hereinafter referred to as the Draft Inventory)
published February 22, 2016 (81 FR 8713). We have gained considerable experience by
implementing the Mandatory GHG Reporting Rule (GHG MRR) since 2010, reporting emissions
for active and closed Municipal Solid Waste (MSW) landfills and associated renewable energy
projects. The landfill sector has significant interest in the Draft Inventory since EPA, for the first
time has used annual waste disposal data reported by MSW landfills under Subpart HH of the
GHG MRR, in its Draft Inventory emissions estimates. We very much want to work with you to
ensure that GHG MRR data are used correctly to refine the Draft Inventory for MSW landfill
emissions.
We commend EPA for using GHG MRR data to refine the inventory estimates of emissions. As
EPA states in Chapter 7 -Waste, of the Draft Inventory (at 7-7), the EPA rigorously verifies data
provided by reporters subject to the GHG MRR. Moreover, reporters certify the data as true
and accurate before submitting it to the Agency, and must collect data and ensure its quality in
accordance with GHG MRR requirements and the facility's GHG Monitoring Plan. Thus, data
developed for the GHG Reporting Program (GHGRP) is of known quality and has far greater
certainty than other databases EPA has relied upon. Using reporting data and emissions
calculations prepared for the GHGRP should enhance the quality and validity of the nationwide
inventory.
Because of the emphasis on accuracy and verification with GHG MRR data, we were surprised
with the changes to MSW landfill emissions estimates in the Draft Inventory. We believe that
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thorough evaluation of the databases must be undertaken before EPA can confidently express
2015 emissions using the GHG MRR data. The changes in net emissions, and amounts of
methane flared and used for energy appearing in the draft inventory are very significant and
negative. The 24-year methane reduction performance achieved by MSW landfills working to
comply with EPA control standards dropped from a projection of 38% reduction to a mere 1.4%
reduction. We could not replicate the Agency's calculations, and they appear to be in
contravention with other data all agree to be reliable.
Specifically, there appears to be a fundamental disconnect between the estimated emissions
reported by MSW landfills subject to the GHGRP and the estimated emissions reported in the
Draft Inventory. The GHGRP emissions from MSW Landfills in 2014 were 91.5 MMT CC^e1.
EPA designed the GHGRP to obtain the highest possible percentage of emissions from each
reporting sector, while minimizing the total number of facilities that would be required to
report. EPA selected a reporting threshold for MSW landfills based on estimated methane
generation of 25,000 MT C02e or greater, and estimated that the MSW landfills reporting
under GHGRP comprise 82% of total national emissions of MSW landfills for both active and
closed landfills.2
The inconsistency in the emissions reported becomes evident when comparing the 2014
emissions from the GHGRP to those estimated in the Draft Inventory for the same year. If 91.5
MMT represents 82% of MSW landfill emissions, then logically, the total from all MSW landfills
will be approximately 111.5 MMT C02e. Instead, total emissions from MSW landfills are 167
MMT C02e, and emissions for the landfill sector (both MSW and industrial landfills) are 181.8
MMT C02e.
The landfill sector representatives appreciated your meeting with us to describe the process
used to integrate GHGRP annual waste disposal figures into the Draft Inventory. Since we first
reviewed these estimates, we have been attempting to discover what factors led to a total
methane generation of almost twice as much as what was in the GHGRP data. This is a
challenging exercise because the database has been structured in such a way to make accessing
all of the relevant information very difficult.
We found a significant source of error in the use of GHGRP annual waste disposal figures in the
Draft Inventory because the waste was not properly differentiated between degradable waste
and inert materials. Since only degradable waste produces methane, applying the degradation
factor (or DOC) for bulk MSW to all waste disposed (even separate inert waste streams that do
not degrade) significantly over predicts methane generation.
We looked first at the public database for the GHGRP (Envirofacts) to assess how many
reporters in 2014 characterized their annual waste receipts to identify inert materials. Because
1 www.epa.gov/ghgreporting/ghgrp-2014-waste
2 U.S. EPA, OAR, February 4, 2009, Technical Support Document for the Landfill Sector: Proposed Rule for
Mandatory Reporting of Greenhouse Gases
_
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Envirofacts does not capture the waste type descriptor provided by reporters, one must query
the database to identify reporters using various DOC values for different waste streams and
sum those fractions to one. For 2014, 944 landfill sites reported accepting waste. Of those 944
reporting annual waste receipts, 42% reported receiving inert waste, using the waste
composition option to delineate inert wastes (DOC=0), and combining separate C&D waste
streams with MSW under the bulk waste category, or by using the modified bulk waste option
showing (MSW DOC=0.31 C&D DOC=0.08, Inert DOC=0).
In fact, because it is so difficult to identify reported waste types in Envirofacts, we turned to the
SCS Engineers database, which contains all required reporting elements from 2010-2014 for
544 MSW landfill GHGRP reporters, or 44% of the total number of reporters, and 50% of the
annual waste receipts. The landfills in this database include both private and municipal sites
located across the country. Looking at GHGRP annual disposal amounts for the 544 sites in
2014, 23% of waste disposed was reported as inert. The prior reporting years 2010-2013, had
similar percentages of waste reported as inert (ranging from 17% in 2010 to 22.5% in 2013),
with the amount of inert waste growing in each year. This is consistent with the current
emphasis on diversion of organic wastes from landfills, and efforts by landfills to make up the
difference with inert waste streams such as ash and soils.
We also evaluated the GHGRP waste disposal history for these 544 sites (including total waste
in place - WIP). Of the total WIP, 8.1% is inert. However, WIP data is far less definitive than
annual waste disposal information because most reporters did not have historical data, or
chose to estimate historical waste in place as MSW and did not characterize the different waste
streams (MSW, C&D, inert) disposed in the landfill.
Waste Management did report well-characterized waste back to 1999 for most sites. A review
of this information showed that from 1999 through 2015, there has been a 21.5% drop in the
amount of MSW waste disposed in landfills, a 21% increase in inert wastes, and an 11%
increase in C&D waste. These findings comport with the experience of public and private
landfills across the country. Increased recycling and organics diversion initiatives have resulted
in a decline in MSW landfill disposal, yet for many landfills receipt of inert waste streams has
steadily increased.
Based on our analysis of the three datasets, we believe the annual waste disposal volumes used
in the Draft Inventory to calculate methane generation were likely assigned inappropriately
high DOC values, resulting in an over prediction of methane generation. This in turn led to
inflated estimates of methane emissions from MSW landfills.
We know that you share our interest in assuring the final Inventory is as accurate as possible.
The information in the Draft Inventory presents major, adverse policy implications for the
Administration and EPA. The current draft could be interpreted to contradict White House and
Agency regulatory statements, plans and documents with regard to methane controls, vitiate
the effectiveness of the EPA's twenty-year old New Source Performance Standards (NSPS) and
Emission Guidelines (EG) Rules, and undermine the accomplishments of the Landfill Methane
3
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Outreach Program (LMOP). These very serious impacts must certainly be avoided if they result
from a misinterpretation of GHGRP waste disposal data because the inventory database simply
does not fully characterize waste types and their potential to generate methane over time.
The landfill sector wants to work with you to ensure that the GHGRP data are appropriately
used, and the resulting estimated emissions are representative of MSW landfill disposal and gas
collection and control practices. We are concerned that there is limited time for the Agency to
conduct a thorough reevaluation of the data and make the necessary changes. If the Agency
were to publish the Draft Inventory results as they appear in the current draft, public officials
and community residents would be misinformed about landfill emissions, and there could be
significant policy and economic repercussions for the sector.
To allow sufficient time for correction of the draft estimate, in the short-term, we urge EPA to
use the 2015 Inventory data and protocols for estimating MSW landfill emissions. For future
inventories, we encourage the Agency to make use of the emissions calculations developed and
certified by GHGRP reporters under the force of law. The Agency has been proactive in
improving the estimation of landfill methane emissions by updating GHGRP protocols. Use of
these verified emissions data could only enhance the U.S. Inventory, while reducing
administrative burdens on Agency staff. We urge EPA to work with the landfill sector to
develop a methodology to incorporate GHGRP results and the growing body of measured
methane emissions into the nationwide inventory - much as you are doing with the natural gas
sector. We believe this is a wise practice, and we commit to do everything possible to assist
your review.
The undersigned organizations appreciate the opportunity to comment on the Draft Inventory,
and look forward to working with you as you continue to refine inventory practices for the
future. If you have any questions, please feel free to contact Kerry Kelly at (202) 639-1218 or
kkelly5@wm.com.
Sincerely,
Waste Management
Republic Services
The Sanitation Districts of Los Angeles County
SCS Engineers
Weaver Consultants Group
National Waste & Recycling Association
Solid Waste Association of North America
Cc: Paul Gunning
Bill Irving
4
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Dear Mr. Hockstad,
I am submitting some comments on the EPA's draft 1990-2014 Inventory. Since I am interested in helping the lay-person
understand the U.S. total energy/C-intensity/C02 picture, which is about 76% of total US GHG emissions, I have reserved
my comments to the keywords "energy" and "carbon intensity". In the table below, I list my comments/suggestions in blue
font with the quoted EPA statement and keywords italicized.
Feel free to contact me by email at chadwickb09@amail.com or by phone (215)287-6088 if my points are not clear.
keyword = "energy" and "non-energy"
page
EPA Statement with My Comments/Suggestions Below
3-4
Clarify the definition of energy as "the capacity for doing work as measured by the capability of doing work
(potential energy) or the conversion of this capability to motion (kinetic energy)" [EIA Monthly Energy Review,
MER\ and identify the types of energy sources: fossil fuels, nuclear, and renewables. Emphasize that some fossil
fuels are consumed for non-energy purposes (e.g. feedstock, reducing agents and non-energy products) but are
inventoried separately in Section 3-2.
3-7
Figure 3-4: U.S. Energy Consumption (Quadrillion Btu)
(1) change the scale of the graph to provide more detail; (2) add gridlines so that energy consumption can be
read more easily from the graph; (3) It appears that data for energy consumption + consumption of fossil fuels
for non-energy use have been graphed with a peak of about 100 qBtu in 2007. From my estimates, using
fossil fuel energy data provided in Table A-18 of EPA's draft Inventory and nuclear and renewable energy
provided in the ElA's MER, total energy consumption in 2007 peaked at about 93.5 qBtu.
ES-19, 3-6
to 3-7
"In the United States, 82 percent of the energy consumed in 2014 was produced through the combustion of fossil
fuels..." (page 3-6).
From my estimates, in 2014, total fossil fuel energy amounted to 73.6794 qBtu (using data in Table A-11 of the
EPA's Inventory). Nuclear and renewable energy (including geothermal energy) and imported electricity amounted
to 18.143 qBtu (using data in ElA's February 2016 MER Tables 1.3 and 2.6). So fossil fuel energy was about
80% of total energy consumed in 2014. My calculation of energy consumption for specific energy sources will
differ from EPA's calculation, too.
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keyword = "energy" and "non-energy"
page
EPA Statement with My Comments/Suggestions Below
2-11
Figure 2-5: 2014 Energy Chapter Greenhouse Gas Sources (MMT C02 Eq.)
The scale of the bar chart deemphasizes the significance of fossil fuel combustion. The scale should be expanded
so that readers can see fossil fuel combustion produces the greatest portion (about 92%) of energy-chapter
emissions. Furthermore, the adjacent piechart should show the breakdown of fossil fuel combustion in the energy
chapter "slice".
keyword = "carbon intensity" and "C-intensity"
page
EPA Statement with My Comments/Suggestions Below
2-3
"Energy-related C02 emissions also depend on the type of fuel or energy consumed and its carbon (C) intensity.
Producing a unit of heat or electricity using natural gas instead of coal, for example, can reduce the C02
emissions because of the lower C content of natural gas".
(1) Explain that the carbon intensity of an energy mix (e.g. electricity) is the energy-weighted average of the C02
emission factors of the energy sources in the mix; (2) Provide a table of C02 emission factors for all energy
sources including nuclear and renewable energy and/or refer readers to Table A-39.
3-14
(a) "Recently an increase in the carbon intensity of fuels consumed to generate electricity has occurred due to an
increase in coal consumption, and decreased natural gas consumption and other generation sources", (b) "Total
U.S. electricity generators used natural gas for approximately 27 percent of their total energy requirements in
2014 (EIA 14 2015b)".
Please correct the above statements: (a) Using the EPA Inventory for fossil fuel data (Table A-11) and the EIA
MER (Table 2.6) for C-free/neutral energy data, the c-intensity of electricity has DECREASED steadily since
2005, from 60.579 MtC02/qBtu in 2005 to 52.785 MtC02/qBtu in 2014. (b) In 2014, natural gas was 22% of the
total primary energy consumed for generating electricity and C-free/neutral energy was 35% of the total primary
energy.
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