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Natural Gas Methane Emissions in 

the United States Greenhouse Gas 

Inventory: 

Sources, Uncertainties, and 

Opportunities for Improvement

NREL/PR-6A20-65424

Garvin Heath, Ph.D.

Ethan Warner, Daniel Steinberg: NREL

Adam Brandt: Stanford University

NREL is a national laboratory of the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, operated by the Alliance for Sustainable Energy, LLC.
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JISEA Report

With a focus on methane emissions from the natural gas 

(NG) sector, the purpose of this report is to:

1. Summarize methods and results of the U.S. 

Greenhouse Gas Inventory (GHGI)

2. Identify potential gaps and barriers to improvement

3. Identify opportunities to improve accuracy.

Observations and suggestions in this presentation focus 

on providing an overview of recommendations. 

- Additional detail on these recommendations can be 

found in the report. 

This report is one of several recent JISEA studies on 

natural gas, including:

- Potential Cost-Effective Opportunities for Methane 

Emission Abatement (natural gas, oil, and coal)

- Controlling Methane Emissions in the Natural Gas 

Sector: A Review of Federal & State Regulatory 

Frameworks.

http://www.nrel.gov/docs/fy16osti/62820.pdf
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The U.S. Environmental Protection Agency publishes the 

U.S. GHGI; many agencies, organizations, and researchers 

rely on its results for analyses and decision making. 

The U.S. GHGI is a critical resource for:

• Understanding the U.S. contribution to global climate change 

• Tracking trends in GHG emission sources and sinks 

• Identifying and prioritizing abatement opportunities within the 

United States

• Informing policy and investment decision making. 

The U.S. GHGI: A Critical Resource
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Source Prioritization is Affected by Accuracy 

of Source-Level Emission Estimates

Even when the sum of measured emissions from different sources is 

equivalent to the inventory, is it due to compensating errors? 

(Allen et al. 2013) 

0

200

400

600

800

1000

1200

1400

Completion

Flowback

Chemical

Pumps

Pneumatic

Controllers

Equipment

Leaks

National

Subtotal

Methane Emissions (Gg/ yr)

Allen et al. (2013)

EPA 2013 GHG

Inventory

Gg = gigagrams or thousand metric tonnes
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Both top-down (TD) and bottom- up (BU) studies have uncertainty 

and potential for inaccuracy; 

neither is “truth.”

Both have roles to improve 

inventory, e.g.:

• TD: Useful as comparison to 

inventory estimates, any 

differences could help generate 

hypotheses

• BU: Measurement studies can 

update outdated emission 

factors (EFs).

Top-Down and Bottom-Up Studies: Roles to 

Improve Inventory

POTENTIAL 

IMPROVEMENT:

Improve capability of TD 

measurements to verify 

inventory, e.g.:

• Improve source 

attribution to better align 

TD and BU study system 

boundaries

• Improve understanding 

of non-O&G methane 

sources, especially ones 

that confound current 

attribution methods

• Improve ability to align 

measurements across 

scales, e.g., from 

regional to facility.
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Inventory Improvement Through BU 

Measurement Studies

Challenges with currently 

used EFs:

• Not representative

– Outdated

– Sampling bias

– Sample size

– Mean emission factors 

(EFs) capture fat tail?

– All salient dimensions of 

emission variability 

captured?

POTENTIAL IMPROVEMENTS:

• Update EFs for prioritized 

emission sources categories

• Focus effort of new studies on 

ensuring robust sample size, 

strong sampling design to 

capture source variability and 

minimization of self-selection bias

• Leverage available evidence to 

explore how to characterize 

emission variability within the EF 

metric

• Explore regional variability and 

along other dimensions.
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Inventory Improvement for Activity Factors

Most efforts to improve the 

inventory have focused on 

EFs; activity factors (counts) 

also need attention: 

• Data sources

– GHGRP or new ones

• Methods – transparency, 

simplicity, and accuracy

• Balance the need for 

consistent time series with the 

need to improve current 

accuracy.

POTENTIAL 

IMPROVEMENTS:

• Develop new data 

sources to improve 

accuracy, completeness, 

and methodological 

simplicity

• Develop methods for 

quantification of activity 

factor uncertainty.
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Inventory Improvement: Completeness and 

Structure

Prioritized gaps in current knowledge, e.g.:

• Abandoned wells

• Measurements on gathering pipelines

• “After the meter” leaks at site of end use

• Well work-overs that are not recompletions*

Inventory structure

• Currently organized sectorally, which 

creates challenges when comparing to a 

measurement representative of a certain 

spatial domain

• Oil and gas wells in the same area

• Associated gas

• Certain segments are grouped, e.g., 

gathering with production.

POTENTIAL 

IMPROVEMENTS:

• Fill prioritized source 

gaps in GHGI

• Align future studies to 

the structure of the 

GHGI for easier 

incorporation OR

• Consider restructuring 

the inventory to better 

capture robust results 

of recent studies

• Gridded inventory to 

enhance measurementbased validation.

*Work-overs are included in the GHGI, but are defined as recompletions. Other work-over activities can also be performed in the industry.
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Uncertainty Quantification

Uncertainty quantification is critical 

for informed decision making, 

communication, and verification 

with measurements. Currently, the 

GHGI:

• Uses Monte Carlo parametric 

uncertainty quantification, with 

lognormal distributions assumed in 

almost all cases

• Reports an uncertainty range that 

hasn’t changed since 2010

• Uses expert judgment to assign 

uncertainty for activity factors.

POTENTIAL 

IMPROVEMENTS:

• Ensure sponsored 

studies robustly 

quantify uncertainty 

• Strengthen uncertainty 

quantification methods 

and efforts

• Develop methods and 

empirical foundation for 

activity factor 

uncertainty 

quantification.
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New Research Efforts in the Context of Many 

Other Studies 

POTENTIAL IMPROVEMENTS: Coordination amongst studies could be enhanced.

Confidence in inventory accuracy can be potently increased if measurements are paired 

with inventory contemporaneously and systematically. 10

Source: Heath et al. 2015
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Garvin Heath: garvin.heath@nrel.gov

JISEA report: 

http://www.nrel.gov/docs/fy16osti/

62820.pdf

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