Improving Characterization of

Anthropogenic Methane Emissions in

the U.S.

James W.C. White (Chair)

BOARD ON ATMOSPHERIC SCIENCES AND CLIMATE

BOARD ON AGRICULTURE AND NATURAL RESOURCES

BOARD ON EARTH STUDIES AND RESOURCES

BOARD ON ENERGY AND ENVIRONMENTAL SYSTEMS

BOARD ON ENVIRONMENTAL STUDIES AND TOXICOLOGY

1

Why measure, monitor, and track methane?

• Climate:

Potent GHG contributes to rise

in global average temperature

• Economy:

Capture from natural

gas/petroleum wells and

landfills

• Human health:

Precursor to ground-level ozone

pollution

• Safety:

Can be flammable and

dangerous to workers in mines

and landfills

2

Many Natural and Anthropogenic Sources

3

Measurements and emission estimates made along

spectrum of spatial and temporal scales

4

Bottom-up/Inventory Development

• Strength

– Provides information about magnitudes/patterns of emissions

from specific sources

• Limitations

– May not account for all sources

– May use uncertain/inaccurate activity data and emissions

factors

• Definition

– Measuring/modeling emissions

at scale of individual emitters

extrapolating results to

regional/national scales

– Emission factors, activity data,

process-based models

5

Top-down/Inversions

• Definition

– Uses observed atmospheric

methane concentrations

and models that simulate

transport from emitter to

observation location

• Strength

– Includes emissions from all sources

• Limitation

– May have difficulty attributing emissions to specific

sources

6

Inventories

• Greenhouse Gas Inventory

(GHGI)

– Main U.S. inventory of

anthropogenic emissions

– Relies on standardized methods

from IPCC (2006)

– National/annual resolution

• Built for specific purposes

• Can provide emissions estimates at many scales

– facility-level, urban, regional, state, national, global

• Track emissions over time and link to individual sources

7

• Methane 2nd most prevalent

GHG emitted in US and

worldwide; is increasing

• Concerns about expansion

of natural gas, leading to

methane emissions

• Numerous new analyses of

methane emissions

• Discrepancies between top-

down and bottom-up

approaches have fueled

discussion about how to

improve estimation approaches

Why this study?

Sponsors:

DOE, EPA, NASA, NOAA

8

• discuss how methane emissions

measurements, monitoring data, and

inventories are used

• assess scientific understanding with respect to

published inventories

• describe and evaluate approaches used to

measure and monitor methane emissions

• recommend how to present results of

methane emissions studies

• describe and evaluate approaches used to

develop inventories

• recommend best available approaches for

addressing key uncertainties, areas of

incomplete understanding, and technical

challenges in developing methane inventories

• recommend research needs

Statement of Task

9

Committee Members• James W.C. White, Chair, University of Colorado Boulder

• David Allen (NAE) , The University of Texas at Austin

• Praveen K. Amar, Independent Consultant

• Jean Bogner, University of Illinois, Chicago

• Lori Bruhwiler, NOAA Earth Systems Research Laboratory

• Daniel Cooley, Colorado State University

• Christian Frankenberg, California Institute of Technology

• Fiji George, Southwestern Energy

• Lisa Hanle, Independent Consultant

• Alexander Hristov, Pennsylvania State University

• Ermias Kebreab, University of California, Davis

• April Leytem, USDA-Agricultural Research Service

• Maria Mastalerz, Indiana University

• Steven Wofsy (NAS) , Harvard University

NASEM Staff:

• Katie Thomas

• April Melvin

• Michael Hudson

10

Effective interlinking

between atmospheric

measurements and inventory

estimates involves

strengthening both

measurement approaches

and developing a gridded

inventory to integrate

approaches

11

Recommendation #1

NOAA and NASA should continue and enhance

current atmospheric methane observations and

advance models and assimilation techniques

used by top-down approaches.

12

Expanding Atmospheric Methane

Observations

Limitation

• Measurements are currently

sparse:

– Spatially/temporally from

fixed ground networks and

aircraft

– Temporally for regional

emission fluxes

To strengthen observations:

• More frequent/denser network of observations

• Data collection strategies to account for temporal/spatial variability

• Observation system simulation experiments and intensive field

experiments

13

Strengthening Modeling

• Improvements to more accurately simulate observational data in

models:

– Develop/use more accurate prior estimates

– Higher spatial and temporal resolution transport models

– New techniques for model evaluation

– Freely share data so researchers can evaluate effects of using or not using

various data sets

Limitation:

• Inversion modeling based on different

combinations of observational data sets

• Atmospheric transport models cannot

adequately represent small scale processes

that affect measured concentrations

14

Multi-Scale Observational

Strategies

• High-quality, long-term, multi-scale (e.g. aircraft, surface,

tower, and satellite remote sensing) observational strategies:

– supply complementary information

– provide emissions flux estimates from facility through local/regional

scale, which can be compared with gridded inventories

– critical for quantifying and tracking changes in methane emissions on

regional scales

15

Recommendation #2

EPA, in collaboration with the scientific research

community, DOE, NOAA, USDA, and NASA, should establish

and maintain a fine scale, spatially and temporally

explicit (e.g. gridded) inventory of U.S. anthropogenic

methane emissions that is testable using atmospheric

observations and update it on a regular basis.

16

GHGI Challenging to Verify

• GHGI used by diverse communities

– for array of scientific and policy purposes

– Including for purposes for which it was not designed

• Challenging to test the GHGI against top-down estimates due

to high degree of spatial (national) and temporal (annual)

aggregation

– aircraft campaigns quantify local to regional-scale emissions and report

daily or hourly averages

• Verifiability is bedrock upon which inventories should be built

if they are to be widely applicable to policy needs

17

Recommended Gridded Methane

Emissions Inventory

• Spatial and temporal resolution at as fine a scale as

possible

• GHGI and gridded inventory meet needs of

different users should be viewed as

complementary

• Sufficient documentation to allow scientific/policy

communities interested in regional methane

emissions to adapt inventory to meet their needs

18

Examples Gridded Methane

Emissions Inventories

• EDGAR: estimates global

emissions on per country

basis– 0.1°×0.1° spatial resolution

– 1 month temporal resolution

• Maasakkers et al. (2016):

disaggregated 2012 GHGI– 0.1°×0.1° spatial resolution

– 1 month temporal resolution

– uses data from various sources

• Recent top-down studies construct “downscaled” inventory

to compare bottom-up inventory results to their

atmospheric observations

19

Recommendation #3

EPA, DOE, NOAA, and USDA should promote a

sustainable process for incorporating the latest

science into the United States Greenhouse Gas

Inventory and regularly review U.S. methane

inventory methodologies.

20

Incorporating New Science into

Inventory Methodologies

• Many inventory methodologies do not reflect current

scientific understanding and engineering practice

• The need to back-cast to 1990 for UNFCCC reporting should

not be a constraint in implementing new methods that

improve emission estimates for current and future

applications • An advisory group could help guide

how new science should be

incorporated into improving GHGI

– Could be facilitated by EPA/NOAA and

comprised of experts from academia,

industry, policymaking, federal agencies,

NGOs

21

Updating Emissions Estimation

Approaches for Specific Sources

Should prioritize inventory categories with greatest uncertainties

Committee’s

confidence in GHGI

uncertainty estimates:

High

Medium

Low

22

Primary reasons for

uncertainties in most

source categories are

sparse activity data

and limited emission

measurements

Enteric Fermentation

• Uncertainties:

– Lack of activity data for cattle

numbers, feed intake, feed composition

– Emission factors aggregated by

state/region may be inaccurate on local

scale

• To reduce uncertainty:

– Update/simplify existing Tier 2 equations, emission factors, based

on recent studies

– Improve inventory of cattle numbers by category

– Better document feed composition and intake, particularly for

cattle on pasture

– Expand research on predicting dry matter intake estimates for

cattle on pasture/rangeland based on animal and feed

characteristics23

Manure Management

• Uncertainties:

– Lack of activity data on distribution of manure in different

management systems

– Emission factors and estimation equations

• To reduce uncertainties:

– Gain better understanding of

distribution of different

manure management systems

– Increase access/use of on-

farm data to validate present

GHGI equations for different

management systems

24

Petroleum & Natural Gas Systems

• To reduce uncertainty:

– Better characterize high-emitting events through field measurement studies

– Supplement GHGRP data with public records to develop more robust activity

data for all petroleum and natural gas systems, including • unaccounted for sources

• facilities not required to report their emissions

– Update characterization of emissions from key sources that still rely on

emission factors from 1996 Gas Research Institute/EPA study

• Uncertainties:

– Temporal variability (>±50% on daily basis)

– Sparse activity data despite abundance of

emission sources

– Wide ranges in measured emissions for

individual sources

– Presence of unaccounted for emission sources

25

Landfills

• Uncertainties:

– Uncertain national activity data (annual landfilled waste)

– Current IPCC methodology does not consider primary drivers of emissions• site-specific soils/climate and operational factors

– Dynamic climate effects on soil gas methane transport and oxidation rates

high spatial/temporal variability of emissions

• To reduce uncertainty:

– Improve collection/statistical analysis of

national/state data for waste generation,

recycling/diversion, treatment, disposal

– Improve and use process-based field-

validated model linked to site-specific soils

and climate

– Minor adjustments to data collected under

GHGRP could facilitate initial national trial

for process-based emission model

26

Coal Mining

• Uncertainties:

– Underground mine ventilation measurements are not confirmed by

emission measurements at surface

– Abandoned underground mines and surface mines emissions are

calculated based on coal gas content

• Gas content often not representative of specific mines

– Emission factors are state/region based and may not be accurate on

mine scale

• To reduce uncertainty:

– For underground mines, measure at all

entries and monitor emissions at surface

– Update and increase reliability of gas

content data

– For abandoned mines, improve monitoring

including pressure build-up and methane

concentration at surface27

Unaccounted for Sources

• Known sources that may not be fully

accounted for in inventories

– Residential/commercial operations, electric power plants, refineries,

and high-emitting sources

• Previously unknown sources that have been unrecognized

because of their scale, complexity of attribution, or other

factors and are not currently incorporated in GHGI

• To reduce uncertainty:

– Increase measurements of sources ignored

or assumed negligible based on screening

studies

– Integrated top-down and bottom-up

assessments

28

High-Emitting Sources

• “super emitters”, “heavy tails”

• Small number of sites or equipment with

much higher than expected emissions;

common element in many recent

natural gas methane emission studies

• Factors that cause certain sub-populations

to become high emitters are not well known

• Difficult to incorporate into GHGI

– GHGI represents annual average

– High-emitting sources have significant temporal variability

• Increase research to gain a mechanistic understanding of high-emitting

sources and establish appropriate estimation methods

• Conduct campaigns in coordination with owners and operators of

facilities to help ensure availability of contemporaneous information

about operations

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Recommendation #4

The U.S. should establish and maintain a

nationwide research effort to improve accuracy,

reliability, and applicability of anthropogenic

methane emissions estimates at scales ranging

from individual facilities to gridded

regional/national estimates.

30

Emission Inventory Improvement Studies

Should incorporate multiple key features: – Multiple, contemporaneous, multi-day top-down

and bottom-up measurement campaigns

conducted in a variety of source regions for

anthropogenic methane emissions

– Sampling strategies to account for infrequent or

rare high emitting sources

– Operator participation to provide site access

and knowledge of operational details

– Data collection strategies to account for

temporal and spatial variability of emissions

– Comprehensive, up-to-date spatially/temporally

resolved emission estimates from all source

categories including those that are unaccounted

for in inventories

31

Presenting Methane Emissions Data and Results

• Common approaches to facilitate presentation of study results

for multiple uses:

– Research networks that help standardize project design

– Clarity on scope, and spatial and temporal boundaries

– Providing data on absolute mass/time basis and other intensity metrics

– Increased data transparency by making underlying report data publicly

available in machine-readable formats and improved documentation

and archiving of GHGRP data

• Methane emissions data generated

by various entities

• Diverse stakeholder community

using these data is even broader

32

Way Forward• US should take bold action now

• Progress is required on each

interlinked recommendation to

address the challenge

• Implementation will:

– improve quantification and

attribution of emissions and

trends

– help identify knowledge gaps

and guide avenues for

improvement

33

For additional information:Katie Thomas, kcthomas@nas.edu, 202-334-3860

April Melvin, AMelvin@nas.edu, 202-334-2684

Join the conversation on twitter: #methanestudy

Report available at:

http://nas-sites.org/dels/studies/methane-study/

and

https://www.nap.edu/

34

Extra slides

35

Natural Sources of Methane

Emissions

• Accurate knowledge of spatio-temporal distribution of natural methane

emissions is required to accurately attribute observed methane emissions

to source categories and processes

– especially in regions with spatial overlap between different source categories

Wetlands and Lakes

• Largest/most uncertain natural source of

methane

• In US (including Alaska), estimated emissions

are comparable to petroleum/natural gas

emissions

• Particularly difficult to quantify because

their emissions depend on both details of

microbial production and distribution of

wetlands

• Can be affected by human activities such as

climate feedbacks, agriculture, and development

36

Improving Attribution Methods

• Molecular and isotopic tracers can be helpful for source

attribution

• Limitations:

– Many sources do not have unique molecular/isotopic fingerprints

– Some sources require multiple species that may not be sufficiently

inert or useful for robust atmospheric identification

• Additional isotopic and chemical approaches needed:

– carbon monoxide, ethane,13CH4, CH3D, 14CH4, clumped methane

isotopes

37

Recalculations in the GHGI

• In general, recent revisions to GHGI are more accurate than previous estimates

and are encouraged

• Challenge of recalculating emissions back to 1990 should not be a barrier for

utilizing most up-to-date methodologies and information in GHGI

• Consider adoption of an alternative base year or period for reporting of national

GHG inventories consistent with more recent national and international policies

and commitments

• Technical challenges

– Updated activity data/emission factors may

not be available for entire time series or

applicable to earlier years due to changes in

technology and/or practices in industry

• Communication-related challenges

– Use of updated data can result in significant

revisions in estimates for any given year

– Drawing inferences related to changes in

emissions from prior years should be done

with caution

38

Projecting Future Methane Emissions

• Accurate projections are critical for planning national policies or goals

• Extremely challenging to do

– Diversity of methane sources that are influenced by many distinct factors

– Climate change

– Projections dependent on factors that are difficult to predict (e.g., future energy

and agriculture policies, population migration)

• Current methods for projecting emissions from key categories may not

be best predictor of future emissions

• Activity data and emission factors that serve as proxies for projecting

future methane emissions need to be robustly investigated regarding

correlations to measured emissions from key categories

– Update EPA Report Methodologies for U.S. Greenhouse Gas Emissions Projections:

Non-CO2 and Non-Energy CO2 Sources

• Future climate projections need to be factored into future emission

estimates for sources where methane is generated, transported, and

oxidized in soils and sediments

39

Updating Emissions Estimation

Approaches for Specific Sources Primary reasons for uncertainties in most source categories are

sparse activity data and limited emission measurements

Petroleum/natural gas: Numerous emissions sources, yet relatively

sparse activity data. Many emission factors rely on comprehensive

study conducted in ‘90s.

Enteric fermentation: Lack of activity data for cattle numbers, feed

intake, feed composition. Emission factors aggregated by state/region

may be inaccurate on local scale.

Manure management: Lack of data on distribution of manure in

different management systems. Most equations in IPCC (2006)

methodologies were developed using >30 years old data.

Landfills: Current methodology relies on 20-40 year old assumptions

and excludes major drivers for emissions: site-specific climate and

operational factors.

• Reducing these uncertainties requires collecting and reporting activity and

emissions data in consistent and comprehensive manner challenging because of cost, time, technical limitations

40

Updating Emissions Estimation

Approaches for Specific Sources

• Update/simplify equations &

emission factors based on

recent studies

• Gain better understanding

of distribution of

different manure

management systems

• Update emission factors

from 1996 Gas Research

Institute/EPA study

Landfills:

Improved monitoring• Underground mines: at all entries and surface

• Abandoned mines: pressure build-up and methane concentration at surface

• Expand use of public records to develop

more robust activity data

• Better characterize high-emitting events

through field measurement studies

Petroleum/Natural Gas:Enteric fermentation:

• Improve emission estimates for cattle

on rangeland and pasture

Manure management:

• Increase access/use of on-farm data

to validate GHGI equations

• Improve collection/analysis of

national/state data for waste

• Improve and broaden use of process-

based model linked to site-specific soils

and climate

generation, recycling/diversion,

treatment, disposal

Coal mining:

41

“Unaccounted for” and

High-Emitting Sources

• Unaccounted for Sources:

– Known but may not be fully

accounted for in inventories

– Previously unrecognized and

not currently incorporated in

GHGI

• To reduce uncertainty:

– Increase measurements of

sources ignored or assumed

negligible based on screening

studies

– Integrate top-down and

bottom-up assessments

• High-Emitting Sources

– Small number of sites or

equipment with emissions much

higher than expected

• To reduce uncertainty

– Increase research to gain

mechanistic understanding of

high-emitting sources and

establish appropriate estimation

methods

– Conduct campaigns coordinated

with facility owners/operators

to ensure availability of

contemporaneous operations

information

42

Information Gathering

• 2 Scoping Meetings held in 2014 to develop the

study objectives

• 5 in-person committee meetings

• 3 field trips

43

Stakeholder Engagement• NGOs: EDF, CATF, WRI, Carnegie Endowment for International

Peace, Environmental Research and Education Foundation,

California Farm Bureau Federation

• Industry: Dairy Cares, WM Waste Management, AECOM, Aerodyne,

Gas Technology Institute, Innovation Center for US Dairy

• Academia: Stanford, Washington State, CSU, Purdue, UC Irvine,

California Polytechnic State, CU Boulder

• State and City Governments/Agencies: LA County Sanitation

District, Bay Area Air Quality Management District, CARB, CO. Dept.

of Public Health & Environment

• National Labs: NETL, NREL, LBNL

• Federal Agencies: EPA, USDA, DOE, NOAA, NASA, USGCRP,

USGS, DOT

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