Methane Emissions from United States Natural Gas Gathering and

Processing

Anthony J. Marchese,*,† Timothy L. Vaughn,† Daniel J. Zimmerle,‡ David M. Martinez,†

Laurie L. Williams,§ Allen L. Robinson,∥ Austin L. Mitchell,∥ R. Subramanian,∥ Daniel S. Tkacik,∥

Joseph R. Roscioli,⊥ and Scott C. Herndon⊥

†

Department of Mechanical Engineering, Colorado State University, Fort Collins, Colorado 80523, United States

‡

The Energy Institute, Colorado State University, Fort Collins, Colorado 80523, United States

§

Fort Lewis College, Durango, Colorado 81301, United States

∥

Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, United States

⊥Aerodyne Research Inc., Billerica, Massachusetts 01821, United States

*S Supporting Information

ABSTRACT: New facility-level methane (CH4) emissions measurements obtained from 114 natural gas gathering facilities and 16

processing plants in 13 U.S. states were combined with facility counts

obtained from state and national databases in a Monte Carlo simulation

to estimate CH4 emissions from U.S. natural gas gathering and

processing operations. Total annual CH4 emissions of 2421 (+245/−

237) Gg were estimated for all U.S. gathering and processing operations,

which represents a CH4 loss rate of 0.47% (±0.05%) when normalized by

2012 CH4 production. Over 90% of those emissions were attributed to

normal operation of gathering facilities (1697 +189/−185 Gg) and

processing plants (506 +55/-52 Gg), with the balance attributed to

gathering pipelines and processing plant routine maintenance and upsets.

The median CH4 emissions estimate for processing plants is a factor of

1.7 lower than the 2012 EPA Greenhouse Gas Inventory (GHGI) estimate, with the difference due largely to fewer reciprocating

compressors, and a factor of 3.0 higher than that reported under the EPA Greenhouse Gas Reporting Program. Since gathering

operations are currently embedded within the production segment of the EPA GHGI, direct comparison to our results is

complicated. However, the study results suggest that CH4 emissions from gathering are substantially higher than the current EPA

GHGI estimate and are equivalent to 30% of the total net CH4 emissions in the natural gas systems GHGI. Because CH4

emissions from most gathering facilities are not reported under the current rule and not all source categories are reported for

processing plants, the total CH4 emissions from gathering and processing reported under the EPA GHGRP (180 Gg) represents

only 14% of that tabulated in the EPA GHGI and 7% of that predicted from this study.

■ INTRODUCTION

Since 2005, domestic production of natural gas (NG) in the

United States has increased by 26%.1 Much of this increase is a

consequence of major new resources that have become

accessible for commercial production due to advances in

hydraulic fracturing and horizontal drilling. During this same

period, the U.S. has seen an increased demand for NG in the

stationary electricity generation and transportation sectors.2,3

Since NG has lower carbon per unit of energy than other fossil

fuels, the potential exists for decreased greenhouse gas

emissions when NG is substituted for coal or liquid fossil

fuels because less carbon dioxide (CO2) is emitted when NG is

combusted in comparison to other fossil fuels. However, since

NG is composed primarily of methane (CH4)a much more

potent greenhouse gas than CO2

4

a certain amount of NG

emitted throughout the entire supply chain can reduce the

greenhouse gas benefits of lower CO2 emissions. For example,

recent studies suggest that substitution of new coal fired power

plants with new NG plants would result in short-term climate

benefits only if the total net CH4 emission rates were less than

3 to 4%,5,6 while substitution of heavy-duty diesel vehicles with

compressed NG would require a net CH4 emission rate of less

than roughly 1% from well-to-wheels to ensure net short-term

climate benefits.5,7,8

The NG supply chain consists of a vast network of

operations (exploration, production, gathering, processing,

transmission, and distribution) with a variety of CH4 emission

sources including: fugitive emissions from leaking valves,

fittings, and compressors; venting from normal operations

Received: May 6, 2015

Revised: July 2, 2015

Accepted: July 6, 2015

Published: August 18, 2015

Article

pubs.acs.org/est

© 2015 American Chemical Society 10718 DOI: 10.1021/acs.est.5b02275

Environ. Sci. Technol. 2015, 49, 10718−10727

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.
such as NG powered pneumatic devices; venting from periodic

maintenance and upsets; and combustion emissions (uncombusted CH4 released through the exhaust of devices fueled

by NG). The Environmental Protection Agency (EPA) 2014

Greenhouse Gas Inventory (GHGI) estimates total net 2012

CH4 emissions of 6,186 Gg/yr for the U.S. NG supply chain.9

With the addition of an estimated 408 Gg/yr of CH4 emissions

from the production of associated gas in 2012, the EPA GHGI

estimate represents a total rate of CH4 loss of 1.3% from the

U.S. NG supply chain (Supporting Information, SI, Section

S.1.1). However, the EPA GHGI estimate remains uncertain,5,10,11 as it is based largely on activity data and emission

factors that were developed in the early 1990s.12 Moreover,

many studies suggest that CH4 emission rates from the NG

supply chain are dominated by a relatively small fraction of

highly emitting components, and it is therefore inaccurate to

assume a normal distribution for all emission sources.11

To improve our understanding of CH4 emissions from the

U.S. NG supply chain, a series of comprehensive studies have

been organized in recent years focusing on CH4 emissions from

specific sectors of the NG industry: exploration and

production;10,13,14 gathering and processing,15,16 (this study);

transmission and storage;17,18 distribution19 and NG vehicles.

In this study, recent facility-level CH4 emissions measurements15,16 obtained from 130 facilities (owned by five

companies and located in 13 U.S. states) were combined

with facility counts obtained from state and national databases

in a Monte Carlo simulation to produce an estimate of total

annual CH4 emissions from all U.S. NG gathering and

processing operations.

The gathering and processing sectors are defined as all NG

industry assets and operations that take place between two

custody transfer points: the well site delivery meter and the

receipt meter to the transmission sector (or local distribution)

(SI Section S.1.2). Gathering and processing systems include

gathering pipelines, gathering facilities, and processing plants.

Gathering facilities collect NG from multiple wells (typically 10

to 100), compress the gas to a higher pressure and discharge

the gas toward its next destination, which could be another

gathering facility, a transmission line (if no further processing of

the gas is needed) or a processing plant. At gathering facilities,

compressors are powered by reciprocating engines and/or gas

turbines that operate on NG. In some cases, compressors are

electrically powered. Gathering facilities also often include inlet

separators (to remove liquid H2O and/or hydrocarbon

condensate), dehydration systems (to remove gaseous H2O)

and amine treatment systems (to remove CO2 and/or

hydrogen sulfide [H2S]). Produced water and/or liquid

hydrocarbon condensate are often stored in tanks onsite.

Processing plants typically include all of the above operations/

equipment but also include systems to remove ethane and/or

natural gas liquids (NGLs).

Prior to the recent field campaign,15,16 relatively little data

had been published on CH4 emissions from processing plants

and even less for gathering facilities.20−22 Shorter et al.20

reported facility-level CH4 emissions from seven processing

plants and two gathering facilities, and two additional

studies21,22 reported CH4 emissions from nine processing

plants. While processing is reported as a distinct sector within

the EPA GHGI, gathering is currently embedded within the

EPA GHGI production inventory and therefore a national

inventory of CH4 emissions from gathering facilities does not

exist. Moreover, unlike processing plants, for which national

facility counts are available,23,24 there are no national databases

available on gathering facilities in the U.S. Accordingly, the

objectives of this study were as follows: (1) compile facility data

(count and NG throughput) for U.S. processing plants; (2)

compile facility data (state counts and installed compressor

engine power) for gathering facilities; (3) combine the facility

data with new CH4 emissions data15,16 in a Monte Carlo

simulation to estimate total annual CH4 emissions from all U.S.

gathering facilities and processing plants; and (4) compare the

model results against the EPA GHGI and EPA Greenhouse Gas

Reporting Program (GHGRP).25

■ METHODS

Field Campaign. As detailed in Mitchell et al.,16 a 20-week

field campaign was conducted from October 2013 through

April 2014 during which total facility-level emission rates

(FLER) of CH4 were measured from 114 NG gathering

facilities and 16 processing plants located in 13 U.S. states. The

CH4 FLER were measured using a dual gas downwind tracer

flux technique,15 which attempts to capture all CH4 emissions

from a facility (fugitive, vented, and uncombusted). The 114

gathering facilities were selected by the study team from

randomly ordered lists of 738 such facilitiessubject to

constraints such as road access and wind directionprovided

by four industry study partners (SI Section S.2). The 16

Figure 1. (a) Measured facility-level emission rates (FLER) of CH4 (kg/h) and (b) throughput-normalized facility-level emission rates (tnFLER) of

CH4 (%) for 114 gathering facilities and 16 processing plants as a function of natural gas throughput (MMscfd) for each facility.16 The blue shaded

regions demonstrate the population of facilities from which CH4 FLER would be drawn (and the associated tnFLER for the same population of

facilities) for a 10 MMscfd facility in the Monte Carlo simulation. The red, green, and blue boxes highlight the differences in emissions for small (0.1

to 1 MMscfd), midsize (1 to 100 MMscfd), and large (>100 MMscfd) facilities.

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sampled processing plants represented all accessible processing

plants operated by two industry study partners and one

randomly selected plant provided by another company who

provided site access but did not provide funding for the study.

Emissions from gathering pipelines were not measured. The

dual tracer gas methodology and data analysis techniques

employed in the field campaign are described in detail by

Roscioli et al.15 A detailed description of sampling strategy,

facility selection process, analysis of CH4 FLER data, and

description of the effects of facility type and operating

conditions on measured CH4 FLER are presented by Mitchell

et al.16 and summarized in SI Section S.2.

Gathering facilities were defined as compression only (C);

dehydration only (D); compression/dehydration (C/D);

compression/dehydration/treatment (C/D/T); or dehydration/treatment (D/T). Processing plants (P) were defined in

accordance with Title 40, Code of Federal Regulations, Part 60,

Subpart KKK (“Subpart KKK processing plants”). Facilities

exclusively dedicated to fractionation were omitted from the

study since the process of fractionation of NGLs was

considered to be outside the natural gas supply chain. Several

of the processing plants sampled in the study did, however,

have fractionation systems on site and any CH4 emissions from

these operations would have been captured as part of the CH4

FLER.

Figure 1(a) is a plot of the CH4 FLER from all sampled

gathering facilities and processing plants as a function of NG

throughput in MMscfd (1 MMscfd = 0.328 m3

/s). The CH4

FLER data in Figure 1(a) represent weighted average results

from multiple CH4 plumes (2 to 42 plumes) acquired from

each facility.15,16 Figure 1(b) is a plot of throughput-normalized

facility-level emission rates (tnFLER) for the same facilities,

where tnFLER is defined as the measured CH4 FLER divided

by the facility CH4 throughput, which was calculated from the

total NG throughput and inlet CH4 content (vol %),

respectively. The data are tabulated in SI Section S.3 and are

the focus of a recent paper by Mitchell et al.16 The tnFLER

represent the percentage of CH4 handled by a given facility that

is emitted on a particular day of sampling. Measured tnFLER

were as low as 0.01% for some gathering facilities, but greater

than 1% for 25 facilities and greater than 10% for four facilities.

Five facilities had measurable CH4 FLER with zero NG

throughput. The median tnFLER was much lower for

processing plants (0.08%) in comparison to gathering facilities

(0.42%) and none of the 16 processing plants sampled had

tnFLER greater than 0.80%. A discussion on the field campaign

sample size and capture of “super-emitters” is included in SI

Section S.3.1.

While the tnFLER is a useful metric to assess the rate of CH4

loss on a facility-by-facility basis, a more effective metric to

characterize emissions from a population of facilities is the

sampled CH4 loss rate (SMLR), defined as Σ(CH4 FLER)/

Σ(CH4 throughput) for the population of facilities. For

gathering facilities and processing plants sampled in this

study, the SMLR were 0.20% ± 0.01% and 0.078% ± 0.01%,

respectively. However, these SMLR values cannot be

extrapolated to the national population of gathering and

processing facilities because a fraction of NG flows through

multiple gathering facilities and the CH4 emissions (both FLER

and tnFLER) were found to be dependent on facility NG

throughput.

Monte Carlo Model. The colored boxes in Figure 1

highlight the result that low throughput facilities (<1 MMscfd)

exhibited lower FLER (2 to 75 kg/h) and higher tnFLER (1%

to >10%) than high throughput facilities (>100 MMscfd),

which had higher FLER (8 to 606 kg/h) but lower tnFLER

(<0.8%). The midsize facilities (1 to 100 MMscfd), which

represent the largest number of facilities, exhibited a wide

spread in emissions. While the CH4 FLER was found to vary

with facility throughput (R2 = 0.38), the wide spread in

emissions observed for a given throughput range suggests that

CH4 emissions from some sources are independent of gas

throughput. Indeed, CH4 emissions are a function of facility

type, facility design (e.g., number of pneumatic devices, prime

mover types), facility size/complexity (e.g., number of fugitive

leaks), facility operating pressures (e.g., magnitude of fugitive

leaks), facility pressure ratio (e.g., number of stages of

compression), total facility throughput (e.g., number of

compressors; combustion emissions), and operating state

(e.g., normal, maintenance, etc.). Mitchell et al.16 includes a

detailed discussion on how the CH4 FLER was found to vary

with facility type, equipment and facility operations. The

modeling approach employed in this study accounts for both

the throughput dependence and variability in CH4 emissions

for a given throughput range. To account for the variation in

observed CH4 FLER for a given throughput range, a Monte

Carlo model was developed whereby CH4 FLER values were

randomly drawn from the measurement data set and assigned

to “similar” facilities as compiled in partner, state and national

inventories (SI Section S.4). The CH4 FLER values were

randomly drawn based on facility type and average daily NG

throughput (for all processing plants and partner gathering

facilities) or installed compressor engine power (for nonpartner

gathering facilities). The experimental uncertainty for each

sampled facility was accounted for by drawing a CH4 FLER

value from a normal distribution centered on the weighted

average FLER given the unbiased weighted standard deviation

for each measurement.

The modeling framework integrates multiple data sources:

measured CH4 FLER data, operating data and equipment

inventory from each sampled facility (N = 130); operating data

and equipment inventory from all study partner facilities (N =

766); gathering facility counts from eight U.S. states and

national processing plant counts from the Energy Information

Administration (EIA) and the Oil and Gas Journal23,24 (SI

Section S.4). State-level counts of gathering facilities were

developed by analyzing publically available air permit data

obtained from Arkansas, Colorado, Louisiana, New Mexico,

Oklahoma, Pennsylvania, Texas, and Wyoming. These states

accounted for 83.5% of all U.S. NG gathered (and 82.2% of

marketed production) in 2012.1 The process by which facilities

in the air permit data sets were identified as gathering facilities

and the quantification of confidence intervals for this process is

detailed in SI Section S.4. The confidence intervals for the

number of gathering facilities in each state were used to

randomly vary the state facility counts for each iteration in the

simulation. Table S13 (SI Section S.9) contains a list of the

state facility data sets used in the simulation. For seven of the

eight states, the gathering facility counts identified in each state

data set were adjusted based on the fraction of known partner

gathering facilities found in each data set (SI Section S.4.3). For

Texas, the total number of gathering facilities was estimated by

extrapolating the gathering facility count identified in a recent

study26 on the Barnett Shale (N = 259) based on the fraction of

Texas NG produced in the Barnett Shale over the period 2009

through 2014 (SI Section S.4.3). For processing plants, national

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facility data were available23,24 resulting in the identification of

578 unique Subpart KKK processing plants with NG

throughput available for 512 of these plants (SI Section S.4.1).

The Monte Carlo simulation consists of three submodels

(Figure S10, SI Section S.4.5): a partner gathering facility

submodel, a nonpartner gathering facility submodel and a

processing plant submodel. All three submodels employ a

“nearest neighbors”

27 Monte Carlo scheme to account for the

throughput dependence and variation in measured CH4 FLER

for a given throughput range. In the gathering facility

submodels, facilities are drawn from each state database and

identified as a partner facility or nonpartner facility. If identified

as a partner facility, then the gathering facility type is identified

along with its 2012/2013 average daily NG throughput (as

provided by the partner companies). A measured CH4 FLER

value is then randomly drawn from one of the 10 sampled

facilities of that type that are closest in NG throughput (i.e., the

“nearest neighbors”). The blue shaded region in Figure 1(a)

indicates the region of population from which CH4 FLER

would be drawn for a 10 MMscfd throughput facility. The

nonpartner gathering facility submodel is used when the facility

is not identified as a partner facility. In this case, the 10 “nearest

neighbors” are identified based on installed compressor engine

horsepower and no distinction is made between gathering

facility types. The observed variation in CH4 FLER with facility

throughput is taken into account through the use of installed

compressor engine power, which was found to correlate well

with throughput (R2 = 0.71) for sampled partner facilities

(Figure S8, SI Section S.4.2).

For the processing plant submodel, a total Subpart KKK

processing plant count of 592 ± 14 was used, which accounted

for the discrepancy between the 606 processing plants as

compiled in the EPA GHGI9,23 and the 578 plants identified in

this study as Subpart KKK plants (SI Section S.4.1). For each

iteration of the Monte Carlo simulation, the processing plant

count is randomly varied (between 578 and 606) and that

count is populated using the NG throughput distribution from

the national data set of 512 Subpart KKK processing plants for

which NG throughput was found.23,24 For each plant in the

national list, a measured CH4 FLER value is randomly drawn

from one of the seven sampled plants and C/D/T facilities that

are closest in NG throughput. The CH4 FLER measured at C/

D/T gathering facilities were integrated into the processing

plant submodel because the throughput distribution of sampled

processing plants had a much lower percentage of low

throughput plants in comparison to the national distribution.

The use of C/D/T facilities as a proxy for low throughput

Subpart KKK plants is discussed in detail in SI Section S.4.1. A

discussion on use of seven nearest neighbors in the processing

plant simulation is included in SI Section S.5.

■ RESULTS

The Monte Carlo simulation results for gathering facilities in

the eight states are shown in Figure 2. The figure contains

cumulative distribution functions (CDFs) of the predicted total

CH4 emissions (Gg) from each state from 50 000 iterations of

the simulation. The slope of each CDF curve is indicative of the

confidence intervals in facility count, which were estimated as

described in SI Section S.4.4. For example, the model

predictions for Colorado suggest that the total annual emission

of CH4 from gathering facilities in Colorado is 69 Gg (+25/−

21 Gg). The former value represents the median value at 50%

probability from the model predictions, while the latter values

represent the confidence intervals in the model results. The

confidence intervals are defined as the difference between the

median prediction and the prediction at 2.5% and 97.5%

probability, respectively. The magnitude of the confidence

intervals is influenced primarily by the uncertainty in the facility

counts and, to a lesser extent, by the experimental uncertainty

in each individual CH4 FLER measurement. Incorporating the

experimental uncertainty in the model resulted in widening of

the state level confidence intervals by 5 to 15%. A similar

process was performed for all eight states in the model and the

predicted CH4 emissions for each state ranged from a low of 53

Gg (+20/−15 Gg) for Arkansas to a high of 616 Gg (+124/−

118 Gg) for Texas. The results are summarized in Table 1.

The predicted annual total emission of CH4 from gathering

facilities in the eight states explicitly included in the model is

1417 (+158/−154) Gg. Normalizing this value by the total

CH4 gathered in 2012 from these eight states (351 Tg) yields a

modeled CH4 loss rate (MMLR) from gathering facilities of

0.40% (+0.05%/-0.04%), which is substantially higher than the

SMLR (0.20% ± 0.01%) from the 114 gathering facilities

sampled in this study. The higher model predictions are

indicative of the fact that a percentage of NG is handled by

more than one gathering facility as it travels from the well to

the transmission (or distribution) sector. It should also be

noted that the SMLR for gathering facilities was heavily

influenced by the presence of five very high throughput/low

tnFLER facilities; indeed, the remaining 109 gathering facilities

had an SMLR of 0.41%. The total amount of CH4 gathered in

the eight states included in the model represents 83.5% of the

421 Tg of CH4 gathered in the U.S. 2012. Assuming that the

CH4 emissions from facilities that gather the remaining 16.5%

of CH4 occur at the same CH4 loss rate (0.40%), a total of 1697

(+189/−185) Gg of CH4 emissions is predicted for all U.S.

gathering facilities.

Table 1 also includes the total number of gathering facilities

as derived from the eight state data sets (3797 +768/−587) and

an extrapolated estimate of total U.S. gathering facilities (4549

+921/−703), which was developed by assuming that the total

number of gathering facilities scales linearly with CH4 gathered

(SI Section S.4.3 and S.4.4). Since accurate gathering facility

counts were not available prior to this study, a comparison was

Figure 2. Cumulative distribution functions (CDFs) of predicted

annual emission of methane (Gg) from gathering facilities in the states

of AR, CO, LA, NM, OK, PA, TX, and WY and U.S. Subpart KKK

processing plants (N = 592 ± 14) from the Monte Carlo simulation.

The median values and confidence intervals are indicated by the

intersection between the CDFs and the solid (50%) and dashed lines

(2.5%, 97.5%), respectively.

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made between the facility counts derived from the state air

permit databases to the known partner facility count. The

partner companies reported handling a total of 5.9 Tscf of NG

in 2012, which represents 103 Tg of CH4 (assuming an average

of 90 vol % CH4) or 24% of the total 421 Tg of CH4 gathered

during the same period. The 738 partner facilities would

therefore extrapolate to a total of 3022 gathering facilities

nationally. However, the total amount of CH4 handled by the

partner facilities is calculated from the sum of the annual CH4

throughput from each facility and is not directly equivalent to

the “CH4 gathered” by the partner companies since NG can be

handled by multiple gathering facilities in transit through the

gathering sector.

Since the gathering facility submodel draws CH4 FLER data

from the same set of 114 sampled facilities for all states in the

model, the variation in predicted MMLR among the eight states

is driven primarily by the ratio of gathering facility count to

CH4 gathered for each state. Oklahoma, with a ratio of 32.2

facilities per Tg CH4 gathered, exhibited the highest MMLR

(0.94%). Conversely, states such as LA, CO, and PA all have

less than 7.3 facilities per Tg CH4 gathered and MMLRs less

than 0.25%. Figure S12 (SI Section S.5), which is a plot of

MMLR as a function of the ratio of facility count to CH4

gathered (Tg−1) for each state in the model, shows that the

MMLR varies linearly (R2 = 0.84) with this ratio and that the

0.40% national estimated MMLR falls along this same line.

The Monte Carlo simulation results for all U.S. Subpart KKK

processing plants are also shown in Figure 2. The results

suggest that the total annual emission of CH4 from Subpart

KKK processing plants is 506 (+55/−52) Gg for 2012.

Normalizing this value by the total CH4 processed in 2012 (287

Tg, SI Section S.8) yields a modeled CH4 loss rate (MMLR)

from processing plants of 0.18% (±0.02%).

Potential Sources of Bias in Model Predictions. Several

sources of uncertainty exist that potentially bias the CH4

emissions results as predicted by the Monte Carlo simulation.

The potential sources of bias include: multiple episodic CH4

emission events captured during maintenance/blowdowns at

gathering facilities that were not included in the CH4 FLER

data,16 incomplete capture of uncombusted CH4 entrained in

lofted exhaust plumes16 and uncertainty in electric compressor

station facility counts. As discussed in detail in SI Section S.5.1,

the bias from the missing episodic CH4 emissions events and

incomplete capture of CH4 entrained in lofted plumes were

quantified and the results suggest that the model predictions

are biased slightly low. To estimate the impact of the missing

episodic emission events (10 plumes out of 1442 plumes

acquired during the field campaign) on the gathering facility

model predictions, a separate Monte Carlo model was

constructed that showed that these events yield an additional

169 (+426%/−96%) Gg/yr of CH4 emissions, which is less

than 10% of the total predicted CH4 emissions from gathering

facilities. In terms of incomplete capture of lofted emissions,

Mitchell et al.16 estimated that the CH4 FLER data were biased

low by a maximum of 15% for processing plants and 17% for

gathering facilities, respectively. It is unclear how the

uncertainty in electric compressor station facility counts biases

the model predictions. In summary, the effects of the missed

episodic emissions, incomplete capture of lofted plumes, and

electric compressors were not incorporated into the model, and

it is therefore likely that the model predictions are overall

biased slightly low.

■ DISCUSSION

The total estimated annual CH4 emissions from U.S. gathering

facilities and processing plants as predicted by the Monte Carlo

simulation were compared to the 2012 CH4 emissions as

reported in the 2014 EPA GHGI (SI Section S.6) and reported

under the EPA GHGRP (SI Section S.7).

Comparison to EPA GHGI. Processing. Since the EPA

GHGI explicitly includes NG processing as a separate sector in

the U.S. NG supply chain, a reasonably direct comparison can

be made with our results (506 +55/−52 Gg). In the 2014 EPA

GHGI, the 2012 total net U.S. CH4 emissions from NG

processing are estimated to be 892 Gg, which includes 851 Gg

of emissions during normal operations and 40 Gg of emissions

from routine maintenance (see SI Section S.6.1).

The results of this study suggest that CH4 emissions from

processing plants during normal operations are lower (by a

median factor of 1.7) than the EPA GHGI estimate. The

discrepancy can be largely attributed to differences in

compressor activity data in the GHGI in comparison to that

observed during the field campaign. The EPA GHGI lists 5624

reciprocating and 906 centrifugal compressors among 606

plants, which yields a value of 9.3 reciprocating compressors per

plant and a ratio of 6.2 reciprocating to centrifugal compressors

(SI Section S.6.1). During the field campaign, for the 16

sampled plants we observed fewer reciprocating compressors

Table 1. Total Annual Emission of CH4 (Gg) and Modeled CH4 Loss Rate (MMLR %) from Gathering Facilities in 8 U.S.

States, which Account for 83.5% of U.S. Natural Gas Gathered

state number of gatheringfacilities

annual emission of CH4 from gathering facilities (Gg)

2012 CH4 gatheredb

(Gg) modeled CH4 loss rate (%)

AR 214 (+43/−38) 53 (+20/−25) 19 723 0.27% (+0.10%/−0.08%)

CO 193 (+46/−35) 69 (+25/−21) 28 261 0.25% (+0.09%/−0.07%)

LA 364 (+62/−124) 104 (+42/−36) 50 207 0.21% (+0.08%/−0.07%)

NM 282 (+82/−82) 96 (+40/−33) 20 215 0.47% (+0.20%/−0.16%)

OK 1103 (+132/−132) 322 (+56/−52) 34 263 0.94% (+0.16%/−0.15%)

PA 247 (+22/−7) 70 (+16/−14) 37 676 0.19% (+0.04%/−0.04%)

TX 1012 (+304/−101) 616 (+124/−118) 126 552 0.49% (+0.10%/−0.09%)

WY 382 (+77/−66) 86 (+25/−22) 34 414 0.25% (+0.07%/−0.06%)

total states in model 3797 (+768/−587) 1417 (+158/−154) 351 310 0.40% (+0.05%/−0.04%)

total U.S.a 4549 (+921/−703) 1697 (+189/−185) 420 906 0.40% (+0.05%/−0.04%)

a

Total number of gathering facilities and total predicted CH4 emissions scaled linearly by total natural gas gathered in the U.S. in 2012. bNatural gas

gathered for each state was calculated by subtracting lease fuel from the total marketed production.1 CH4 gathered was calculated from natural gas

gathered assuming an average CH4 content of 90 vol %.

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per plant (6.4) and a smaller ratio of reciprocating to

centrifugal compressors (2.6). Including field observations for

the C/D/T facilitieswhose CH4 FLER values were part of

the Monte Carlo processing plant simulationwe also

observed fewer reciprocating engines per plant (5.4) and a

smaller ratio of reciprocating to centrifugal compressors (3.3)

(SI Section S.6.1, Table S6). Mitchell et al.16 found that CH4

FLER at facilities with centrifugal compressors driven by gas

turbines was 75% lower than at facilities with engine-driven

reciprocating compressors. Similar observations were found in

recent studies of CH4 emissions from the U.S. transmission and

storage sector.17,18 Since 90% of all CH4 emissions in the EPA

GHGI processing inventory are from compressor fugitives and

engine/turbine exhaust emissions (SI Section S.6.1, Table S5),

it is likely that the GHGI’s assumed activity factors for

reciprocating and centrifugal compressors lead to an overestimate of CH4 emissions from processing plants.

Comparison to EPA GHGI. Gathering. For gathering

facilities, a direct comparison with the EPA GHGI is

complicated because gathering systems (gathering pipelines,

facilities, and associated equipment) are embedded within the

GHGI production inventory. Some of the source categories in

the EPA GHGI production inventory (e.g., gathering pipelines)

can be assigned solely to gathering and in these cases it is

reasonable to assign 100% of the activity and emissions data for

those categories to the gathering sector. Other categories, such

as gathering compressors, engine exhaust, pneumatic devices,

dehydration units, chemical pumps, and condensate tanks are

common to both production sites and gathering facilities10,13,14

and assumptions must be made to assign a percentage of the

activity data and emissions to each sector. Table S7 (SI Section

S.6.2) is a compilation of 2012 CH4 emission source categories

from the 2014 EPA GHGI production inventory that are

present at both production sites and gathering facilities. Sources

common to both production and gathering systems (which

would constitute an absolute upper bound on gathering

emissions in the GHGI) account for 1,431 Gg of 2012 CH4

emissions in the 2014 EPA GHGI, which is less than the model

prediction of 1697 (+189/−185) Gg for gathering facilities

alone.

We apportioned the fraction of activity data for each source

category in SI Table S7 that could be assigned to the gathering

sector using equipment data from the 738 partner gathering

facilities, detailed equipment surveys of the 114 sampled

gathering facilities (which included pneumatic device counts,

inlet separator counts, condensate/water tank counts, dehydrator counts, installed/operating compressor engine power,

etc.) and the estimated total count of 4549 U.S. gathering

facilities (SI Section S.6.2). Given these assumptions, a total of

404 Gg of CH4 emissions were assigned to gathering, which

represents 20% of the total net 2012 CH4 emissions (1992 Gg)

in the 2014 EPA GHGI production inventory.9 For the

gathering facilities (i.e., subtracting out the GHGI estimated

178 Gg of gathering pipeline emissions), a total CH4 emission

of 226 Gg is estimated (Table S8, SI Section S.6.2) in

comparison to our model results of 1697 Gg for gathering

facilities. While there is uncertainty in determining gathering

facility emissions from the EPA GHGI, the results of this study

suggest that the GHGI substantially underestimates emissions

from gathering facilities.

Comparison to EPA GHGRP. The EPA GHGRP requires

annual reporting of GHG emissions from large direct emission

sources and suppliers of certain fossil fuels and industrial gases

in the United States. Processing plants are required to report

CH4 emissions from multiple source types under 40 CFR Part

98 Subparts W and C if their total greenhouse gas emissions

from these sources are in excess of 25 000 t per year of CO2e.

Gathering facilities are required to report CH4 emissions only

from stationary combustion sources (under 40 CFR Part 98

Subpart C) and only if their total greenhouse gas emissions

from these sources are in excess of 25 000 t per year of CO2e.

28

A detailed discussion of GHGRP reporting requirements for

processing plants and gathering facilities is included in SI

Section S.7 and elsewhere.28

Comparison to EPA GHGRP. Gathering. In 2013, 404

gathering facilities reported a total of 0.53 Gg of CH4 emissions

under the GHGRP Subpart C, which represents a very small

fraction (0.03%) of the total national CH4 emissions from

gathering facilities predicted in this study. This large difference

is mainly because the total number of reporting gathering

facilities represents less than 10% of the national facility count

and only combustion emissions from those facilities are

reported. Also, a recent study on CH4 emissions from the

NG transmission and storage sector suggests that the emission

factor used in the GHGRP to estimate CH4 combustion

emissions for reciprocating engines is unrealistically low.17,18

The EPA has proposed a revision to the GHGRP rule that

would require the gathering sector to begin reporting CH4

emissions from numerous additional sources under Subpart W

(SI Section S.7.1).29

Comparison to EPA GHGRP. Processing. The estimate of

processing plant emissions from this study is also larger than

that reported under the GHGRP. Figure 3 is a comparison of

measured annualized CH4 FLER (Mg) and the 3-year average

(2011 to 2013) of CH4 emissions reported under the GHGRP

for the 16 processing plants sampled in this study. The total

emission of CH4 based on the FLER measurements from the

16 sampled processing plants when extrapolated to an annual

value represents a total of 23.7 ± 4.0 Gg. The total annualized

CH4 emissions reported under the GHGRP for those same

Figure 3. Comparison of cumulative distribution functions for the

measured annual equivalent methane FLER (Mg, CH4) for the

processing plants sampled in this study (N = 16; blue circles), average

annual emissions reported under the 2011 to 2013 EPA Greenhouse

Gas Reporting Program25 for the same processing plants (N = 16;

white circles) and all processing plants that reported emissions under

the GHGRP from 2011 through 2013 for which average daily natural

gas throughput was available (N = 246).25

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Environ. Sci. Technol. 2015, 49, 10718−10727

10723
plants was 12.6 Gg, which is 47% lower than the measurements.

Normalizing by total CH4 throughput for these 16 plants, the

GHGRP-reported CH4 loss rate from the 16 plants is 0.043% in

comparison to the SMLR of 0.078% for these same plants.

A comparison was also made between the results of the

Monte Carlo simulation for all U.S. plants and the total CH4

emissions from all processing plants that reported to the

GHGRP from 2011 to 2013 for which annual NG throughput

was obtained (N = 246). The reported annualized average CH4

emissions from these facilities are also plotted in Figure 3. The

total reported annual CH4 emissions from these 246 plants

(computed as the average of 2011 through 2013) was 104 Gg.

The total annualized NG processed by these plants was 14.5

Tscf. Assuming an average inlet CH4 content of 85 vol % for

these processing plants yields a total reported rate of CH4 loss

of 0.044%, which is less than 1/4 of our 0.18% MMLR. As

shown in Figure 3, approximately 50% of the reported CH4

emissions in both the larger GHGRP (N = 246) and the study

plant data set (N = 16) were less than 200 Mg, whereas only

two of 16 annualized CH4 FLER measurements were below this

value. One reason for the discrepancy between measured and

reported GHGRP CH4 emissions is that not all sources of CH4

emissions at processing plants are required to be reported

under the GHGRP. For example, CH4 emissions from

pneumatic controllers, pneumatic pumps, tanks and compressor fugitives during some operating modes are not reported,

and for acid gas removal vents, only CO2 emissions (and not

CH4) are reported (SI Section S.7). Also, as mentioned above,

a recent study suggests that the emission factor used in the

GHGRP to estimate CH4 combustion emissions for reciprocating engines is unrealistically low.17,18

Total CH4 Emissions and Loss Rate from U.S.

Gathering and Processing. In this section the Monte

Carlo simulation results are used to estimate the total annual

CH4 emissions (Gg) and rate of CH4 loss (%) from all U.S. NG

gathering and processing operations (SI Section S.8). Figure 4

summarizes the modeled estimate of total annual CH4

emissions from U.S. gathering facilities (1697 +189/−185

Gg) and processing plants under normal operation (506 +55/−

52 Gg) along with comparisons against the EPA GHGI and

2013 GHGRP. Methane emissions from gathering pipelines

and processing plants under routine maintenance (i.e.,

blowdowns, which entail the venting of high pressure vessels

and pipe sections) were not measured in this study and, for the

purposes of a national estimate, the estimated 2012 CH4

emissions in the EPA GHGI were assumed for these source

categories (178 Gg and 40 Gg, respectively). On the basis of

the results of this study, the total annual CH4 emissions from

U.S. natural gathering and processing are estimated at 2421

(+245/−237) Gg in comparison to 1,296 Gg of CH4 emissions

derived from the EPA GHGI and 180 Gg of CH4 emissions

reported under the 2013 EPA GHGRP, respectively. The 2013

GHGRP value includes 154 Gg of CH4 emissions from 433 NG

processing plants under normal operating conditions, 25 Gg

from these same plants during routine maintenance and only

0.53 Gg from the 404 gathering facilities that reported in 2013.

While CH4 emissions from processing plants appear to be

substantially lower than that tabulated in the EPA GHGI, CH4

emissions from gathering facilities appear to be substantially

higher than current EPA GHGI estimates and it can be

concluded from this study that gathering systems are a

substantial contributor to total CH4 emissions from the U.S.

NG supply chain. Indeed, the total CH4 emissions from

gathering systems (facilities and pipelines) as predicted in this

study (1875 +189/−185 Gg) are greater than that estimated for

the transmission and storage sector in a recent study (1503 Gg

+30%/−19%)18 and are equivalent to 30% of the total net 2012

CH4 emissions for the entire NG supply chain in the 2014 EPA

GHGI (6186 Gg). Moreover, the predicted CH4 emissions are

most likely biased low as discussed above and in SI Section

S.5.1.

Figure 4 also shows that the total CH4 emissions from

gathering and processing reported under the EPA GHGRP

(180 Gg) represents only 14% of that tabulated in the EPA

GHGI and 7% of that predicted from this study. As noted

above and in the SI (Section S.7), the large discrepancies are

due to reporting requirements (e.g., reporting threshold of

25 000 t CO2e per facility) that capture very little CH4

emissions from gathering (0.53 Gg total) as well as multiple

source categories that are not reported for processing plants

under the GHGRP.

Figure 4. National estimate of total CH4 emissions (Gg) from U.S. natural gas gathering systems (facilities and pipelines) and processing plants

(normal operation and routine maintenance) from this study in comparison to that derived from the 2014 EPA GHGI9 and reported under the 2013

EPA GHGRP,9 respectively. CH4 emissions from processing plant routine maintenance (blue wedges) are 40 Gg for the study results and EPA

GHGI and 25 Gg for the EPA GHGRP.

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The results of the Monte Carlo simulation were used to

estimate the MMLR (%) from all U.S. NG gathering and

processing operations, and the individual subcategories of

gathering facilities, gathering pipelines and processing plants

(routine operations and blowdowns). The subsector MMLR

for gathering facilities, gathering pipelines, processing plant

normal operations, and processing plant blowdowns (retaining

the EPA GHGI estimate for gathering lines and processing

plant blowdowns) were estimated to be 0.40%, 0.042%, 0.18%,

and 0.014%, respectively (SI Section S.8). These values

represent the percentage of CH4 lost during handling by each

of those subcategories but cannot be added together to develop

an estimate for the total rate of CH4 loss from gathering and

processing. Normalizing the CH4 emissions from each

subcategory by the total net CH4 production of 513 Tg for

2012 (SI Section S.8), yields a supply chain MMLR of 0.33%,

0.035%, 0.099%, and 0.008% for gathering facilities, gathering

pipelines, processing plant normal operations and processing

plant blowdowns, respectively, and an overall MMLR of 0.47%

for all U.S. gathering and processing. The MMLR is 87% higher

than the 2012 CH4 loss rate of 0.25% for all gathering and

processing operations derived from the 2014 EPA GHGI. The

results are summarized in Table S11 (SI Section S.8).

The results of the Monte Carlo simulation were also used to

develop “facility-level emission factors” for gathering facilities

and processing plants, respectively (SI Section S.8.1). For

processing plants, the national estimate of 546 (+55/−42) Gg

of CH4 emissions from 592 ± 14 Subpart KKK processing

plants, yields an estimated facility-level emission factor of 105

(+11/−10) kg/h-plant in comparison to 168 kg/h-plant as

derived from the EPA GHGI. Similarly, for gathering facilities,

the national estimate of 1697 (+189/-185) Gg of CH4

emissions from 4549 (+921/−703) gathering facilities yields

an estimated facility-level emission factor of 43 (+10/−8) kg/hfacility in comparison to 5.7 kg/h-facility as derived from our

analysis of the EPA GHGI production inventory (SI Section

S.6.2). These results are summarized in Table S12 (SI Section

S.8.1).

In the context of evaluating the greenhouse gas emission

implications of NG substitution into various energy sectors

(e.g., coal power plants, heavy duty diesel vehicles, and light

duty gasoline vehicles), an overall rate of CH4 loss of 0.47%

from gathering and processing is not trivial, particularly with

respect to those applications with the lowest tolerance for CH4

emissions in terms of net short-term climate benefits (i.e., heavy

duty diesel vehicles).5,7,8 However, the results also show that

CH4 emissions from NG processing plants during normal

operation (506 +55/−52 Gg, 0.099% loss rate when

normalized by production) represent a relatively small fraction

of the CH4 emissions from the overall NG supply chain. While

emissions from gathering facilities (1697 +189/−185 Gg;

0.33% loss rate when normalized by production) represent a

substantially higher fraction of the total U.S. CH4 emissions in

comparison to processing, observations from the field

campaign15,16 suggest that further reductions in CH4 emissions

can be realized by incorporating systems and/or practices to

quickly identify and repair the high emitting gathering facilities.

Two areas of future work are recommended. First, as

mentioned above, the EPA GHGI does not include gathering as

a separate sector in its NG systems inventory. However, the

results of this study indicate that CH4 emissions from gathering

facilities represent a sizable fraction of CH4 emissions from the

NG supply chain. The results of this study in conjunction with

the results of recent studies on production sector emissions10,13,14 can provide input to the EPA for a separate

gathering sector inventory in future versions of the GHGI. A

proposed rule change to the EPA GHGRP that would require

reporting of CH4 emissions from gathering and boosting

stations (SI Section S.7.1) would provide further input for a

separate GHGI gathering inventory. Second, emissions from

gathering pipelines were not measured as part of this study.

The 445 135 miles of gathering pipeline in the 2014 EPA

GHGI is based solely on extrapolations from rough estimates of

pipeline miles per well made in the early 1990s12 and the

emission factors (CH4 emissions per mile) have never been

accurately quantified for gathering pipelines. Accordingly, it is

recommended that future studies be conducted to more

accurately survey the length of and quantify the CH4 emissions

from the U.S. national gathering pipeline network.

■ ASSOCIATED CONTENT

*S Supporting Information

S.1 Background Information; S.1.1 EPA GHGI Estimate of

Methane Emissions and Methane Loss Rate; S.1.2 Gathering

and Processing Sector Definitions; S.2 Description of the Field

Campaign; S.2.1 Definition of Facility Types; S.2.2 Natural Gas

Compressor Engine Types and Uncombusted Methane; S.3

Facility-Level CH4 Emissions Results; S.3.1 Field Campaign

Sample Size and Frequency of Super-Emitters; S.4. Model

Description; S.4.1 Processing Plant Data; S.4.2 Facility Natural

Gas Throughput and Engine HP Relationship; S.4.3 Estimation

of State Gathering Facility Counts; S.4.4 Estimation of

Confidence Intervals for State Gathering Facility Counts;

S.4.5 Monte Carlo Simulation Scheme for Gathering Facilities;

S.4.6 Monte Carlo Simulation Scheme for Processing Plants;

S.5 Model Results; S.5.1 Potential Sources of Bias in Model

Predictions; S.6 Comparisons with EPA Greenhouse Gas

Inventory; S.6.1 Natural Gas Processing; S.6.2 Natural Gas

Gathering; S.7 Comparison with EPA Greenhouse Gas

Reporting Program; S.7.1 Proposed Rule Changes to EPA

GHGRP for Gathering and Boosting; S.8. National Estimate of

CH4 Emissions and Loss Rate from G&P Systems; S.8.1

Facility-Level Emission Factors; S.9 State Gathering Facility

Data; Data Tables in excel format: SI-Tables20150615.xlsx;

Gathering and processing facility lists: facility-list20150615.xlsx

This material is available free of charge via the Internet at

http://pubs.acs.orgThe Supporting Information is available free

of charge on the ACS Publications website at DOI: 10.1021/

acs.est.5b02275.

■ AUTHOR INFORMATION

Corresponding Author

*Phone: (970) 491-2328; fax: (970) 491-3827; e-mail:

marchese@colostate.edu (A.J.M.).

Author Contributions

The manuscript was written through the contributions of all

authors. All authors have given approval to the final version of

the manuscript.

Funding

Environmental Defense Fund (EDF), Access Midstream,

Anadarko Petroleum Corporation, Hess Corporation, Southwestern Energy, and Williams Companies.

Notes

The authors declare no competing financial interest.

Environmental Science & Technology Article

DOI: 10.1021/acs.est.5b02275

Environ. Sci. Technol. 2015, 49, 10718−10727

10725
■ ACKNOWLEDGMENTS

This work was financially supported by the Environmental

Defense Fund (EDF), Access Midstream, Anadarko Petroleum

Corporation, Hess Corporation, Southwestern Energy and

Williams Companies. Subsequent to the field sampling

campaign of this study, the Williams Companies purchased

controlling interest in Access Midstream Partners L.P.

(“Access”) by acquiring 100% of the general partnership

interest of Access. A merger between Access and Williams

Partners L.P. was finalized on February 3, 2015. In addition to

financial support, the sponsors provided valuable technical

advice, operating data, and site access. Funding for EDF’s

methane research series, including this work, is provided 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. DCP Midstream,

while not a financial sponsor, provided site access for one of

their processing plants selected at random. The authors also

acknowledge Ramon Alvarez, David Lyon, and Drew Nelson at

EDF for their contributions both technical and logistical; Ann

Batchelor at Colorado State University for her role as Project

Manager; Jean Opsomer at Colorado State University for

advice on statistical analysis; and David McCabe at the Clean

Air Task Force for guidance on the state datasets used in this

study. The authors acknowledge the valuable advice and input

of the Science Advisory Panel, which included David T. Allen,

Garvin Heath, Michael Levi, and James McCarthy. The views

and opinions expressed are those of the authors and do not

necessarily reflect those of the sponsors or the Science Advisory

Panel.

■ ABBREVIATIONS

FLER Facility-level emission rate (weighted average of

multiple plumes) [kg/h]

MMLR Modeled methane loss rate [%]

MMscfd Million cubic feet per day of natural gas at standard

conditions (60 °F and 1 atm)

SMLR Sampled methane loss rate [%]

tnFLER Throughput normalized facility-level emission rate

[%]

Tscf Trillion cubic feet of natural gas at standard

conditions (60 °F and 1 atm)

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