F-Gas Inventories and Comparisonswith Atmospheric Observations
IPCC Meeting on Use of Atmospheric Observation Data in Emission Inventories
Deborah Ottinger, US EPA

1

Acknowledgements
Thanks to the following for their work on the comparisons and input
into this presentation:• Stephanie Bogle, Dave Godwin, and Lauren Aepli, US EPA• Lei Hu, University of Colorado-Boulder• Steve Montzka, US NOAA

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Meeting Objectives• Assess and critique recent datasets as well as new and operational systems, platforms, instruments/sensors andmethods/models to derive, from atmospheric observations, representative emission rates from source categories overtime periods of interest.
• Assess and evaluate the usability of these recently available datasets as well as new operational systems, platforms,
instruments/sensors and methods/models to derive, from atmospheric observations, comparative data to verify IPCC
default factors and uncertainties as well as to allow inventory-compilers to verify their emission estimates throughapplication of IPCC good practice methods and approaches.
• Assess and evaluate useful examples of comparisons between atmospheric observations and national inventories thatare consistent with good practice provided in the 2019 Refinement to the 2006 IPCC Guidelines on National Greenhouse
Gas Inventories (e.g., following the steps provided in tables 6.3 and box 6.5 of Volume 1) that have led to implemented
or planned improvements in national inventories.
• Assess and evaluate available examples where emission estimates derived from atmospheric observations have been
incorporated into a bottom-up inventory framework, including the associated resources (technical, human, funds)
needed in their implementation.
• Assess and evaluate the usefulness of efforts (including resource implications) to grid (spatially and temporally) nationalemissions inventory and the use of these gridded products in comparisons with atmospheric observations.
By achieving these objectives, this Expert Meeting is expected to support the development of IPCC materials that will assist
countries to make better estimates of emissions, for example the Methodology Report on SLCFs to be produced during the
IPCC 7th assessment cycle (AR7 cycle).

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Key Question
What can we say in addition to the guidance in the2019 Refinement to reflect what we’ve learned sincethen about using atmospheric measurements to informor QA/QC F-GHG emissions inventories?

42019 Refinement on Using Atmospheric Measurements to Verify
F-GHG Inventories“Fluorinated gases and methane(CH4) are considered the mostsuitable greenhouse gases for which
inverse modelling could provide
verification of emission estimates(Rypdal et al. 2005, Bergamaschi etal. 2004). The fluorinated compounds
are considered good candidates forinverse modelling verification
because: they have virtually nonatural source interference in theatmospheric measurements, there
can be considerable uncertainties ininventory methods, they are longlived, and the loss mechanisms arewell known.”

Example: CF4 and C2F6

Source: Kim, J., et al. (2014), “Quantifying aluminum and semiconductor industry
perfluorocarbon emissions from atmospheric measurements,” Geophys. Res. Lett., 41,4787-4797, doi: 10.1002/2014GL059783.

Using Atmospheric Measurements to Verify andEnhance F-GHG Inventories: US Experience• Sulfur hexafluoride• HFCs• Conclusion: Long-term communication andcollaboration between inventory compilers andatmospheric scientists are key to making the most ofcomparisons.

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Using Atmospheric Measurements to Verify FGHG Inventories: US Emissions of SF6SF6 is most potent GHG, with 100-year GWP (AR5) of 23,500 andatmospheric lifetime of 3,200 years
Inventory methods• 1999-2019 emissions estimated based on facility reporting throughGreenhouse Gas Reporting Program (GHGRP), voluntary EPA-industry
Partnerships, and national activity data x estimated emission factors for
non-reporting facilities.
Atmospheric measurements• 2007-18 emissions estimated using measurements made from groundbased and airborne whole-air flask samples collected from the U.S.
National Oceanic and Atmospheric Administration (NOAA) Global
Greenhouse Gas Reference Network and a regional inverse model.
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US SF6 Sources
US GHGI: Emissions of SF6 by Source Since 1990
35
30

Magnesium Prod. & Processing

25
MMTCO2e• Uses/sources include (bold=currently
in US GHGI):• Insulator and arc quencher inelectrical transmission anddistribution (ET&D) equipment• Source of fluorine for electronics
manufacturing• Cover gas for magnesium
production and processing• Through 2010: Emissions from SF6
production facility• Military uses (e.g., AWACs, torpedo
propellant)• Insulator in research and medical
accelerators• Other medical applications• Tracer gas and others

20
15

Semiconductor Prod.

10

Electrical T&D

5
0
1990

1995

2000

2005

2010

Source: Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2019.
U.S. Environmental Protection Agency. April 2021.

8

2015

Comparison Between Activity-Based andAtmosphere-Based Estimates of US Emissions of SF6• Both GHG Inventory andatmospheric measurements show
a declining trend in US SF6emissions.
• US EPA GHGI emissions lower thanemissions inferred fromatmospheric measurements• Gap especially large before
2011.
• Gap smaller in 2011 and later
years, after the GHGRP
began.

Source: Lei Hu, et al, “Atmosphere-based US emission estimates of SF6 for 2007 – 2018”, eGMAC (April
2021)

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Bottom-up Estimates Sensitive to Assumed Emission Rateof Non-Reporting Facilities
Estimated Emissions from Electric Power Systems Based on
Different Assumptions Re: Emission Rates of Non-Reporting
Systems
0.70

Non-reporting systems' EF assumed HIGHER thanreporting systems (1990-2010 Inventory)

0.60
0.50

SF6 Emissions (Gg)

• Facilities reporting under both Partnershipand GHGRP reduced emissions significantly,
especially in first few years of reporting.
• In US GHG Inventories published before
2013, non-reporting facilities wereassumed NOT to have reduced theiremissions from the 1999 emission rate ofPartners.
• In US GHG Inventories published in 2013and later, non-reporting facilities wereassumed to have reduced their emissions
at the SAME rate as reporting facilities
throughout the time series.
• In fact, new GHGRP reporters may haveacted to reduce emission rate only afterdraft GHGRP published in 2009.

0.40
0.30
0.20

Non-reporting systems' EF assumed SAME asreporting systems (1990-2019 Inventory)

0.10
0.00

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

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Regional Comparison: Gridding US GHGI SF6
Emissions• Used EPA’s 2021 state-by-state breakout of national GHG Inventory (1990-2019).
• For years after 2011, able to precisely locate point sources that report through
GHGRP (semiconductor manufacturing, magnesium production).
• ET&D more challenging (even after 2011) because reporting “facilities” (ET&D
networks) often span multiple states. In 2021 state-by-state breakout, only able
to allocate 20 – 30 % of ET&D emissions to a single state by facility location (i.e.
when the facility was only in one state). The remaining emissions were
distributed based on the transmission miles in each state.
• Limited regional resolution of SF6 emissions data for current study.
• Improving now—37-49% of emissions allocated by state in 2022 state-by-state inventory.

• Before 2011, ET&D and semiconductor emissions allocated to states based on
activity data (transmission miles for ET&D; area x layers for semiconductors).
Magnesium emissions allocated to states based on emissions reported byPartners.

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Atmosphere-Based Regional Emissions
Distribution in 2007/8 vs 2011-17/18
2011-2018 Mean

Difference

2007/08 Mean

2011-2017 Mean

Difference

STILT

HYSPLIT

2008 Mean

Source: Lei Hu et al., submitted, 2022.

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Regional SF6 Trends
Central North

50

Electronics

ETD OEMElectronics

ETD OEMNOAA (stilt)

Southeast

20
2019

2017

2015

2013

0
2011

2019

2017

0

40

2009

50

60

2007

100

80

2005

150

100

2003

200

120

2001

250

SF6 emissions (metric tons)

300

2001

2019

2017

2015

2013

2011

2009

Magnesium

Central SouthSF6 Emissions (metric tons)

2007

2003

0
2001

SF6 Emissions (metric tons)

2017

2015

2013

2011

2009

2007

2019

100

Electrical T&D

West
SF6 Emissions (metric tons)

150

NOAA (stilt)

NOAA (stilt)

180
160
140
120
100
80
60
40
20
0

200

Electrical T&D

2015

ETD OEM

250

Magnesium

2013

Semi

0

2011

EPS

50

2009

Magnesium

2017

2015

2013

2011

2009

2007

2005

2003

2001

0

100

2005

20

150

2007

40

200

2003

60

250

2005

80

300

2003

100

Northeast

350

2001

SF6 Emissions (metric tons)

SF6 Emissions (metric tons)

120

2005

Mountain

Source: Source: Lei
Hu et al.,submitted, 2022.
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Seasonal SF6 Trends• Atmospheric measurements show
persistent seasonal variations, withthe highest emissions in the winter.
• SF6 use and emissions not expected
to vary seasonally for magnesium orelectronics production.
• Based on discussions with ET&D
sector, higher winter SF6 may be due
to increased servicing of electricalequipment during off-peak (cooler)months. In addition, leaks may belarger in the winter due tohardening of seals during cold
weather.
• Seasonal variation is mostpronounced in regions of thecountry where the majority of SF6emissions are from ET&D, as is thecase in the South.
14Seasonal variation apparently grew between
2006-8 and 2011-18.

Source: Source: Lei Hu et al., submitted, 2022.

• Also see changes in seasonal variation
over the time series.
• Largest variation seen in 2009, whenGreat Recession reduced semiconductor
and magnesium production but didn’t
affect ET&D.
• Observe statistically significant
difference between 2007-2008 variationand 2011-2018 variation.
• Challenge: This contradicts our
hypothesis that underestimate fromET&D sector is primarily responsible for2007-2010 overall underestimate.

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What source(s) other than ET&D contributed
to 2007-2010 underestimate?

• Uses/sources other than ET&D
include (bold=currently in US GHGI):• Source of fluorine for electronics
manufacturing• Cover gas for magnesium
production and processing• Through 2010: Emissions from SF6
production facility• Military uses (e.g., AWACs, torpedo
propellant)• Insulator in research and medical
accelerators• Other medical applications• Tracer gas and others

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Leading Candidate: SF6 Production Facility• Uses/sources other than
ET&D include(bold=currently in US GHGI):• Source of fluorine forelectronics manufacturing• Cover gas for magnesium
production and processing• Through 2010: Emissions
from SF6 production facility• Military uses (e.g., AWACs,
torpedo propellant)• Insulator in research andmedical accelerators• Other medical applications• Tracer gas and others

Once we account for (1) higher 2007-10 emissions from nonreporting ET&D facilities, and (2) 2007-10 emissions from theSF6 production facility, mix of sources is consistent withseasonal variation seen in 2007 and 2008.
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Using Atmospheric Measurements to Verify
Country-Level Estimates of US HFC Emissions• Latest USEPA GHGI report includes comparisons of
HFC-32, HFC-125, HFC-134a, and HFC-143a derived
in the Inventory and from atmosphericmeasurements and inversion models• Results combined with knowledge of the ODS
Substitutes industry highlight areas for future
research that could improve Inventory estimates,
such as:Figure 4-4: U.S. Emissions of HFC-32, HFC-125, andHFC-143a• Changes in the refrigeration market away from blends
like R-404A or success in lowering emission rates• Use of “dry-charge” residential AC equipment in lieu of
R-410A• Uncertainty estimates by species would aid incomparisons to atmospheric data.

• EPA will explore Monte Carlo analysis to differentiate
between species

Source: Inventory of US Greenhouse Gas
Emissions and Sinks, 1990-2020, 2022, p. 4147.

Using Atmospheric Data to Enhance Regional HFC
Emissions Estimates
Approach• National emissions were initially allocated to states based only on population, as state-level activity and emission
factor data are limited.
• Subsequently, state-level estimates were adjusted based on NOAA atmospheric measurements.
• The emissions distribution was modified with data from Hu et al. (2017), which used atmosphericmeasurements to estimate emissions from 6 regions in the contiguous states• Data for four HFCs were available: HFC-125, HFC-134a, HFC-143a (2008-2014), and HFC-32 (2010-2014).
• Regional emissions were then divided into states by population.
• For the other HFCs, population alone was used to estimate emissions.
g/year/personpico mole/m2/s

g/year/person pico mole/m2/s

Source: Hu, L., et al.
(2017), Considerable
contribution of theMontreal Protocol todeclining greenhouse gas
emissions from theUnited States, Geophys.
Res. Lett., 44, 8075–
8083,
doi:10.1002/2017GL0743
19
88.

Reminder: Atmosphere-Based Estimates Are
Also Uncertain
CFC-11 Emissions (Gg/yr)

Chinese Emissions of CFC-11 Derived from Four Inverse
Modelling Frameworks

Measurement or modelinguncertainties or errors can resultin under-estimates, overestimates, or incorrect regional
attribution of emissions.

Source: Rigby, M., Park, S., Saito, T. et
al. Increase in CFC-11 emissions from eastern
China based on atmosphericobservations. Nature 569, 546–550 (2019).
https://doi.org/10.1038/s41586-019-1193-4

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Consider Enhancing Comparisons Using
Additional Sources of Independent Data
• Can also compare F-GHG consumption reported by/inferred
for users and emitters of F-GHGs to F-GHG supplies reported
by producers, importers, and exporters.
“[W]hen considered along with estimates of actual emissions, thepotential emissions approach can assist in validation ofcompleteness of sources covered and as a QC check by comparing
total domestic consumption as calculated in this ‘potential
emissions approach’ per compound with the sum of all activity
data of the various uses” (IPCC, 2006 Guidelines).

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SF6 Consumption (metric tons)

U.S. SF6 Supply vs. Consumption
1600
1400
1200
1000
800
600
400
200
0
2011

2012

2013

2014

Net Supply of SF6 (Upstream Reporting Method)

2015

2016

2017

2018

2019

2020

SF6 Consumption by Users (Downstream Reporting Method)
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Take-aways• Long-term communication and collaboration between inventory compilers andatmospheric scientists are key to making the most of comparisons.
• Plan on a lively back-and-forth process.
• Consider bringing in additional expertise, e.g., from emitting industry.

• Useful comparisons take time; important to prioritize gases/sources.
• Insight into what is driving emissions can be gained by combining on-the-groundknowledge of sources with analysis of• temporal and spatial patterns in emissions (e.g., seasonality in emissions) and• emissions of different F-GHGs that may be emitted separately or together in characteristic ratios.

• If possible, establish a regular, predictable schedule for updated comparisons (ideallyannually, but at least every few years). This avoids having to reassemble the relevant
expertise and data on a case-by-case basis.
• Consider using additional sources of independent data to further QA/QC bottom-up
inventories.
• Comparisons have added benefit of reminding us of the uncertainties in both activitybased and atmosphere-based estimates.

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Additional Background24

2019 Refinement: AtmosphericMeasurements“Atmospheric measurements are being used to provide useful quality
assurance of the national greenhouse gas emission estimates (Manning
et al. 2011; Fraser et al. 2014; Henne et al. 2016). Under the rightmeasurement and modelling conditions (discussed further in thissection), they can provide a perspective on the trends and magnitudeof greenhouse gas (GHG) emission estimates that is largely
independent of inventories.”25

2019 Refinement• Operational verification systems exist in• Switzerland• UK• Australia

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BOX 6.5: COMPARISON – VERIFICATIONACTIONS ON INVENTORY COMPILER SIDE
1. In cases where there are discrepancies between the two estimates, the effort to reduce this discrepancy should
be taken by both the inverse modelling and inventory compiling groups. On the inventory compiler side, following
steps are suggested to take:2. Confirm that the observation-based emission estimates and the inventories represent the same time period,
areas.
3. Determine what emission dataset was used as a prior, and how it compares to the emission inventory.
4. Assess how the estimation procedure treats anthropogenic and natural emissions, to confirm that the estimatescompare with anthropogenic and natural emissions included in the inventory.
5. Confirm that seasonal variability of the emissions and other effects have been considered in the comparison.
6. Assess the uncertainties of the estimated emissions, and note whether the discrepancy is statistically significant.
7. For sub-national scale regions with the larger discrepancies, determine which emissions activities are occurring
there, based on the gridded or regional GHG inventory:
a. Recheck inventory activity data in that region;b. Assess factors that may make the regional emission rates different from the national inventory average (e.g.
different regulations, different technologies), and assess the extent to which these have been taken into account in
the national inventory and in its gridding/disaggregation.

8. In the national inventory improvement plan, prioritize emission sources/regions with larger discrepancies.

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TABLE 6.3: IMPLEMENTATION STEPS AND SHARE OFRESPONSIBILITIES BETWEEN PARTNERS
Step
1

Work package
Acquisition of GHG observations from a surface network (andwhen available from aircraft and satellites) that has sufficient
coverage of the country's emissions. The observation data haveto be linked to the same calibration scale and be processed by
the compatible routines across the network.

Responsible group
Observation /atmosphericmodelling2

Preparing gridded (spatially and temporally disaggregated) prioremissions data.
Preparing and operating the inverse model other observationbased emission estimation methods.
Quality Assurance / Quality Control to the inverse model
output.
Comparison verification and reporting. Production of final
outputs and update of the GHG inventory improvement plan.

Gridded inventory

3
4
5

Atmospheric modelling
Atmospheric modelling
Inventory/ Atmospheric modelling28

Scope of GHGRP and Partnership SF6 Data
Percentage of SF6 Emissions Accounted for by Facilities Reporting to EPA By Source Category
Estimated Percentage
of Partnership
Emissions Coverage(1999-2009/2010)

Estimated Percentage of
GHGRP GHG Emissions
Coveragea(2010/2011+)

Electronics Manufacturing~69-81%

96-97%

Magnesium Production and Processing

88-95%

67-92%

Use of Electric Transmission and Distribution (ET&D)
Equipment

60-65%

66-78%

Manufacture of Electric Transmission and Distribution(ET&D) Equipment

N/A

~50%

N/A

>95%

N/A

100%

SourceSF6 Users / Emitters

SF6 Suppliers
Importers / Exporters

Draft Deliberative - Do Not Cite or Quote

Production of Fluorinated Gasesa Coverage estimates include both F-GHGs and other GHGs emitted from these sources and show the range incoverage from 2011-2019.

Seasonal Variation Also Seen for HFCs in US• HFC emissions also foundto vary seasonally.
• In contrast to SF6emissions, HFC emissions
peak in the summer.
• Potential drivers include• Increased servicing of
A/C&R equipment insummer, and• Higher pressuresinside A/C&R
equipment in summer.

Figure S4: Derived monthly fluxes plotted relative to annual totals
during 2008 to 2014.

Source: Hu, L., et al. (2017), Considerable
contribution of the Montreal Protocol todeclining greenhouse gas emissions from theUnited States, Geophys. Res. Lett., 44, 8075–
8083, doi:10.1002/2017GL074388.