IPCC Expert Meeting on
Use of Atmospheric Observation Data
in Emission Inventories

Report of IPCC Expert Meeting
5-7 September 2022, Geneva, Switzerland

Task Force on National Greenhouse Gas Inventories

1Supporting material prepared for consideration by the Intergovernmental Panel on Climate Change (IPCC). This
supporting material has not been subject to formal IPCC review processes.
IPCC Expert Meeting on Use of Atmospheric Observation Data in Emission Inventories was organised by the IPCC
Task Force on National Greenhouse Gas Inventories (TFI). It was held in a hybrid format at the World
Meteorological Organization (WMO) Headquarters in Geneva, Switzerland, from 5 to 7 September 2022.
This meeting report was prepared jointly by the Co-Chairs of the IPCC TFI (Eduardo Calvo Buendia and Kiyoto
Tanabe) as well as the Technical Support Unit (TSU) of the TFI (Sandro Federici, Baasansuren Jamsranjav, Pavel
Shermanau) and the IGES Fellow/TSU scientific advisor of the Institute for Global Environmental Strategies (IGES)(Takeshi Enoki), and subjected to review by the meeting participants.
Published by the Institute for Global Environmental Strategies (IGES), Hayama, Japan on behalf of the IPCC
© Intergovernmental Panel on Climate Change (IPCC), 2022
Please cite as:
IPCC (2022). IPCC Expert Meeting on Use of Atmospheric Observation Data in Emission Inventories. Eds: Calvo
Buendia, E., Tanabe, K., Enoki T., Federici S., Jamsranjav B., Shermanau P. - Report of the IPCC Expert Meetingon Use of Atmospheric Observation Data in Emission Inventories, Pub. IGES, Japan.
IPCC Task Force on National Greenhouse Gas Inventories (TFI)
Technical Support Unit
℅ Institute for Global Environmental Strategies
2108 -11, Kamiyamaguchi
Hayama, Kanagawa
JAPAN, 240-0115
https://www.ipcc-nggip.iges.or.jp

Image: NASA's Goddard Space Flight Center Scientific Visualization Studio, Microscopic image courtesy of James
Anderson (Arizona State University)

ISBN 978-4-88788-264-5
2

Table of Contents
Table of Contents .................................................................................................................................................... 3
Preface.................................................................................................................................................................... 4
List of Acronyms and Abbreviations ........................................................................................................................ 5
Executive Summary ................................................................................................................................................ 6
1. Introduction ..................................................................................................................................................... 7
2. Meeting discussion and conclusions .............................................................................................................. 9
2.1 Plenary discussions ............................................................................................................................... 9
2.2

CO2 emissions from fuel combustion ................................................................................................... 11

2.3

Fugitive CH4 emissions ........................................................................................................................ 13

2.4

AFOLU GHG emissions ....................................................................................................................... 16

2.5

F-gases ................................................................................................................................................ 20

Annex 1: Materials for the Meeting ....................................................................................................................... 22
Annex 2: Agenda .................................................................................................................................................. 25
Annex 3: List of Participants.................................................................................................................................. 28

3

Preface
We are pleased to present this report of the IPCC Expert Meeting on Use of Atmospheric Observation Data in
Emission Inventories held in a hybrid format at the World Meteorological Organization (WMO) Headquarters in
Geneva, Switzerland, from 5 to 7 September 2022.
There is significant interest in exploring how atmospheric measurements can be used as a tool to assess andguide improvements to national greenhouse gas inventories (NGHGI), including through inverse modelling. In the2006 IPCC Guidelines for National Greenhouse Gas Inventories (2006 IPCC Guidelines), the benefit of use of
atmospheric measurement data was referred to, but practical guidance on how to use could not be provided. Afterthe 2006 IPCC Guidelines were produced, there has been a move towards establishing dedicated national
greenhouse gas monitoring networks for this purpose in some countries, and also there has been advancement inscience and technologies relating to atmospheric measurements. Taking that into account, guidance on the use of
atmospheric measurements for verification of national GHG inventories was updated and elaborated in the 2019
Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories (2019 Refinement), Volume 1,
Chapter 6.
Research and monitoring activities involving the collection, archiving and distribution of data on atmosphericconcentration of GHGs, as well as of other Short-lived Climate Forces (SLCF), could in some cases provide
information of benefit to the improvement of national inventories.
This expert meeting aimed to discuss issues relating to the use of atmospheric observation data and models inverification of national GHG inventories building on guidance provided in the 2019 Refinement. The meetingbrought different communities together – experts on atmospheric observation of GHGs and inverse modelling andexperts on national emission inventories. The invitees were identified and selected by the Bureau of TFI (TFB) in
accordance with the Appendix A to the Principles Governing IPCC Work. Discussion and conclusions of this expert
meeting are described in this report.
This expert meeting report is not to pre-empt future IPCC work, but to support the development of IPCC materials
that will assist countries to make better estimates of emissions, for example the Methodology Report on SLCFs tobe produced during the IPCC 7th assessment cycle (AR7 cycle).
We would like to thank all those involved in this meeting, namely, the scientists and experts who participated, themembers of TFB and the TFI Technical Support Unit, for their contribution, that enabled to make this meeting a
success. We also extend our appreciation to the WMO for hosting this expert meeting.

Eduardo Calvo Buendia
Co-ChairTask Force on National Greenhouse Gas Inventories
Intergovernmental Panel on Climate Change

Kiyoto Tanabe
Co-ChairTask Force on National Greenhouse Gas Inventories
Intergovernmental Panel on Climate Change

4List of Acronyms and Abbreviations
AFOLU

Agriculture, Forestry, and Other Land Use

AR6

Sixth Assessment Report

AR7

Seventh Assessment Report

BOG

Break-Out GroupCH4

MethaneCO2

Carbon Dioxide

EF

Emission Factor

EFDB

Emission Factor Database

F-gases

Fluorinated greenhouse gases, including hydrofluorocarbons (HFCs), perfluorocarbons(PFCs), Sulphur hexafluoride (SF6), Nitrogen trifluoride (NF3), etc.

GHG

Greenhouse Gas

GWP

Global Warming Potential

IPCC

Intergovernmental Panel on Climate Change

N2O

Nitrous Oxide

NGHGINational Greenhouse Gas Inventory

SLCF

Short-Lived Climate Forces

TFB

Task Force Bureau

TFI

Task Force on National Greenhouse Gas Inventories

TSU

Technical Support Unit

UNFCCC

United Nations Framework Convention on Climate Change

WG

Working Group

WMO

World Meteorological Organization

5

Executive Summary
The IPCC, at its 54th (bis) Session (December 2021), decided that the TFI hold an Expert Meeting on Use of
Atmospheric Observation Data in Emission Inventories (Decision IPCC-LIV(bis)-2, according to the document
IPCC-LIV(bis)/Doc.2, Add. 1). The IPCC Expert Meeting on Use of Atmospheric Observation Data in Emission
Inventories was held in a hybrid format at the World Meteorological Organization (WMO) Headquarters in Geneva,
Switzerland, from 5 to 7 September 2022.
At the opening plenary, informative presentations were made to provide participants with background information
on atmospheric observation, covering topics such as comparison of greenhouse gas (GHG) inventories andinversions, space-based measurements, carbon balance, uncertainties, discriminating anthropogenic and natural
fluxes, case studies, remote observations, etc. After the plenary session, experts split up into four break out groups(BOGs) to discuss the following:• Potential of using atmospheric observations to verify GHG inventories.
• Examples of comparisons between atmospheric observations and national inventories that have led to
implemented or planned improvements in inventories or where emission estimates derived fromatmospheric observations have been incorporated into a bottom-up inventory.
• Emerging datasets from atmospheric observations could be used to test and verify particular IPCC default
values and associated uncertainties.
• Spatial and temporal gridding of NGHGIs to allow comparison with atmospheric observation data.
• Terminology and classifications of sources/sinks and associated natural and anthropogenic GHG fluxes.
The BOG discussions and conclusions were presented and discussed at the closing plenary. Some of the key
findings of the BOG discussions were as follows:• There is potential for atmospheric observations to be used for verification of national GHG inventories,
depending on sector/category. Verification of inventories using data derived from atmospheric observationand inverse models is not necessarily leading to direct changes in the emission estimates, but rather as astarting point for further improvement of the inventory.
• Inverse analysis systems are not yet standardized; therefore, there is room for additional progress andrefinement of emission estimates and uncertainties derived from atmospheric observation and inverse
models. Identifying robust signals and robust differences between an inverse analysis and inventory datarequires judicious expert review of sources/sinks to assure that comparisons are based on valid
comparisons of the elements that are actually included in the estimates and assessment of results.
• In addition to inverse models, direct measurement of the flux from a GHG sources, forward models, processmodels, and others could contribute to the verification of national GHG inventories.
• Atmospheric observation is a rapidly maturing science and future work is planned and underway that will
advance further the capabilities for atmospheric observations to help verification of national GHG
inventories. Ongoing dialogue and development of capacity between GHG inventory compilers andatmospheric observation researchers is critical to advance the understanding of the contents of the productsof the two communities and enhancing their consistency in verification exercises.
• There are some examples of where the comparison between atmospheric observations and national
inventories have been carried out effectively.
The Co-Chairs concluded that a forum for exchange of information among inventory compilers and atmosphericobservation researchers is useful, and a long-term interaction may be beneficial. Atmospheric measurements have
proved useful in verifying national GHG inventory data in specific cases, and examples were presented at themeeting. These case studies and the lessons learned should be shared with other countries to further promote theinteraction between atmospheric observation and national GHG inventories. This expert meeting was not intended
to produce specific methodological guidance, but the discussion and conclusions documented in this report are
expected to inform future work of TFI.

6

1. Introduction• Background and relevant IPCC decision for the Expert Meeting
There is significant interest in exploring how Atmospheric measurements can be used as a tool to assess andguide improvements to national greenhouse gas inventories (NGHGI), including through inverse modelling. In the2006 IPCC Guidelines, the benefit of use of atmospheric measurement data was referred to, but practical guidanceon how to use could not be provided. After the 2006 IPCC Guidelines were produced, there has been a movetowards establishing dedicated national GHG monitoring networks for this purpose in some countries, and there
has been advancement in science and technologies relating to atmospheric measurements. Taking that into
account, guidance on the use of atmospheric measurements for verification of NGHGI was updated and elaborated
in the 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories (2019 Refinement),
Volume 1, Chapter 6.
Research and monitoring activities involving the collection, archiving and distribution of data on atmosphericconcentration of GHGs, as well as of other Short-lived Climate Forces (SLCF), could in some cases provide
information of benefit to the improvement of national inventories. Development and improvement of source-specificemission factors are becoming increasingly important to keep enhancing the quality of GHG estimates, especiallyfor those sectors and categories where development and application of new technologies impact the associatedrate of emissions.
With this background and context, and considering rapid advancement in science and technologies relating toatmospheric measurements, the IPCC, at its 54th (bis) Session (December 21), decided that the TFI hold an Expert
Meeting on Use of Atmospheric Observation Data in Emission Inventories (Decision IPCC-LIV(bis)-2, according to
the document IPCC-LIV(bis)/Doc.2, Add. 1).
The objectives of the expert meeting were of the following:
I.
II.

III.

IV.
V.

Assess and critique recent datasets as well as new and operational systems, platforms,
instruments/sensors and methods/models to derive, from atmospheric observations, representativeemission rates from source categories over time 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 through application of IPCC good practice methods and approaches.
Assess and evaluate useful examples of comparisons between atmospheric observations and national
inventories that are 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 andbox 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 atmosphericobservations have been incorporated into a bottom-up inventory framework, including the associatedresources (technical, human, funds) needed in their implementation.
Assess and evaluate the usefulness of efforts (including resource implications) to grid (spatially andtemporally) national emissions inventory and the use of these gridded products in comparisons withatmospheric observations.

By achieving these objectives, this expert meeting is expected to support the development of IPCC materials thatwill 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).
• Organization of the IPCC Expert Meeting on Use of Atmospheric Observation Data in Emission
Inventories
The IPCC Expert Meeting on Use of Atmospheric Observation Data in Emission Inventories was held in a hybrid
format on 5-7 September 2022 at the World Meteorological Organization (WMO) Headquarters in Geneva,
Switzerland, and virtually via ZOOM and MS Teams platforms. Prior to the meeting, TSU together with TFB
7

elaborated the guiding note (see Annex 1) to the meeting participants and the agenda for the meeting (see Annex
2).
At the opening plenary (5 September), following the welcome address and explanation of background of the expert
meeting by TFI Co-Chairs, presentations were delivered to inform the discussion at this meeting. After the opening
plenary session, the meeting split into break out groups (BOGs) and held in parallel in the second day (6September) and in the morning of the third day (7 September).
Four BOGs were formed on the following topics:••••

BOG 1: CO2 emissions from fuel combustion
BOG 2: Fugitive CH4 emissions
BOG 3: AFOLU GHG emissions
BOG 4: F-gases

At the closing plenary, each of four BOGs reported on its discussion, which was followed by a brief plenary
discussion on the BOG topics. The expert meeting was closed by expression of appreciation by TFI Co-Chairs to
all the participants and TSU. (See List of Participants in Annex 3).
• Outcome of the IPCC Expert Meeting on Use of Atmospheric Observation Data in Emission Inventories
Discussion and conclusions of the expert meeting are summarized in Chapter 2 of this meeting report. In addition,
the outcomes of BOGs work are published on the IPCC TFI website at this same page.

8

2. Meeting discussion and conclusions
2.1

Plenary discussions

In the opening plenary, the TFI Co-Chairs explained that the expert meeting aimed to discuss issues relating to
the use of atmospheric observation data and models in verification of national GHG inventories building on
guidance provided in the 2019 Refinement. The meeting is not aiming to revise existing guidance or to add
additional guidance, but to provide opportunities for experts in the GHG inventory and atmospheric measurement
communities to share an understanding of the activities in the communities.
The participants took stock of the 2019 Refinement which states that, “comparisons with atmosphericmeasurements are not established as a standard tool for verification to be applied by an inventory compiler. Still,
considerable scientific progress in this area needs to be noted and inventory compilers may wish to take advantageof the potential of this approach, as it gives independent data for verification.” It also outlines five steps to allow
comparison of atmospheric measurements with NGHGI’s sources/sinks: Confirm that observation-based andinventory estimates represent the same time period and sources/areas (temporal and spatial gridding of theinventory and observation-based estimates); determine what data were used and how this data can be comparedto the emission inventory (categories’ definitions); Assess how the estimation procedure treats anthropogenic andnatural emissions, to confirm that the estimates compare with emissions included in the inventory; confirm thatseasonal variability of the emissions and other effects have been considered in the comparison; and assess theuncertainties of the estimated emissions, and note whether the discrepancy is statistically significant.
During the opening plenary session, ten presentations were made to provide participants with backgroundinformation on atmospheric observation, covering topics such as comparison of GHG inventories and inversions,space-based measurements, carbon balance, uncertainties, discriminating anthropogenic and natural fluxes, casestudies in New Zealand and Mongolia, remote observations, etc.
At BOGs, meeting participants were asked to discuss the following five issues:• Assess and critique recent estimation techniques that utilise atmospheric observations as well as
operational systems, platforms, instruments/sensors and methods/models for their potential use forverification of national inventory sectoral emission estimates, consistent with the guidance provided in the2019 Refinement.
• Assess and evaluate successful examples of: (i) comparisons between atmospheric observations andnational inventories that are consistent with good practice provided in the 2019 Refinement that have led to
implemented or planned improvements in national inventories; and (ii) available examples where emission
factors derived from atmospheric observations have been incorporated into a bottom-up inventory
framework.
• Assess the possibility that emerging datasets from atmospheric observations could be used to test andverify particular IPCC default values (emission factors) and associated uncertainties;• Discuss the use of gridding (spatial and temporal) of NGHGIs to allow comparison with atmosphericobservation data.
• Discuss terminology and classifications of sources/sinks and associated natural and anthropogenic GHG
fluxes to find a common understanding of consistency and differences in atmospheric observation data and
GHG inventory estimates.
At the closing plenary, BOG representatives presented their response to the five issues. A summary of findings ofthe BOGs were of the following:• There is potential for atmospheric observations to be used for verification of GHG inventories, depending
on sector/category. Verification of inventory emissions using inversion data is not necessarily leading todirect changes in the inventory-based emissions, but rather as a starting point for further improvement of
the inventory.
• Inverse analysis systems are not yet standardized; therefore, there is room for additional progress andrefinement of emission estimates and uncertainties. As a result, identifying robust signals and robust
differences between an inverse and inventory estimates require expert judicious review of sources/sinks
actually included in the estimates and assessment of results.
9• Use of atmospheric observations for assessing emission inventories is a rapidly maturing science and future
work is planned and underway that will advance further the capabilities for atmospheric observations toprovide more accurate verification of regional- and national-scale emission magnitudes. Ongoing dialogue
and development of capacity between GHG inventory compilers and researchers is critical for continued
progress.
• There are some examples of where the comparison between atmospheric observations and national
inventories have been carried out. In some countries, atmosphere-derived emission estimates for F-gases
are included in their NGHGIs.
• There is a need to gain more experience using atmospheric observations and inversions to evaluate AFOLU
sectoral GHG inventories.
• Successful examples of comparisons occur when there is respectful communication between both
atmospheric and inventory-focused communities to better understand emission estimates, trends, and theiruncertainties. Also, a dedication to continuous and long-term engagement in this collaborative process iscritical for success.
• It may be difficult to use atmosphere-based estimates to gain insights into specific default emission factors
because current inverse systems provide total emissions from the sum of all emissive processes -including
natural sources- while the default EF may be based on carbon content of specific fuels or be for a specificprocess among many.
• Geographically or temporally gridded NGHGI information can facilitate more accurate comparisons withatmosphere-based emission estimates to identify areas of improvement. There is a need to determine theappropriate spatial and temporal scales for comparing inversion and inventory-derived emissions.
• Very useful to have interactions between inventory compilers and atmospheric observation researchers toenhance the common understanding of issues and also to develop a glossary of terms, as some terms may
have different meanings in the two communities.
The Co-Chairs concluded that a forum for exchange of information among inventory compilers and atmosphericobservation researchers is useful, and a long-term interaction may be beneficial. Atmospheric measurements areuseful to verify GHG inventories, and examples were presented at the expert meeting. By sharing these casestudies and the lessons learned with other countries it is hoped that the interaction between atmosphericobservation researchers and the GHG inventory community will be advanced so that ultimately our understandingof GHG emissions magnitudes and source contributions will be improved. There is no methodological guidance
newly developed as a result of the expert meeting, but the findings will be documented for future TFI to benefit
from the rich discussions held between all experts.

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2.2

CO2 emissions from fuel combustion

The following experts participated in the Combustion CO2 BOG: Philippe Ciais, Richard Engelen, Rebecca
Garland, Veronika Ginzburg, Michel Alexandre Grutter de la Mora, Chia Ha, Miao Lang, Bundit Limmeechokchai,
Zhu Liu, Greg Marland, Batouli Said Abdallah, Marko Scholze, Steven J. Smith, Hiroshi Suto, Jocelyn Turnbull,
Yogesh K. Tiwari, Masataka Watanabe, Jung-Hun Woo, Yousuke Yamashita
Facilitator:
Dario Gómez
Rapporteur:
Ole-Kenneth Nielsen
TSU:
Takeshi Enoki
1. Assess and critique recent estimation techniques that utilise atmospheric observations as well as
operational systems, platforms, instruments/sensors and methods/models for their potential to be
used for the verification of national inventory sectoral emission estimates, consistent with theguidance provided in the 2019 Refinement.
 Examples of utilising land-based, airborne and satellite data to estimate CO2 emissions all yielding
useful results in terms of verification
 Examples of both national and subnational applications
 No examples of estimates based on atmospheric observations that has the level of sectoral detail thatis required in national emission inventories
 More potential for verification in countries with less developed statistical systems
 Can be used to identify gaps or areas for future improvements in the inventories
 While it may not be possible to significantly improve fossil CO2 emission estimates for all countries,
estimates derived using atmospheric observations can be used to build trust Challenge to distinguish between fossil and biogenic CO2 – need to measure additional chemical orisotopic markers
 Probably a need to combine satellite data with land-based measurements
 Verifying emission trends might be easier than the emission level depending on the national
circumstances Not clear what the uncertainties are of the estimates based on atmospheric observations – uncertainties
need to be smaller or comparable to the inventory estimate for it to make sense for verification
 A lot of future work is planned and underway that will advance further the capabilities for atmosphericobservations to provide more accurate verification
2. Assess and evaluate successful examples of: comparisons between atmospheric observations andnational inventories that are consistent with good practice provided in the 2019 Refinement thathave led to implemented or planned improvements in national inventories; available examples
where emission factors derived from atmospheric observations have been incorporated into abottom-up inventory framework
 Some examples of good consistency between national inventories and estimates based on atmosphericobservations – no known examples of where national inventories have been improved based on
atmospheric measurements
 No known examples of atmospheric observations having been used to derive CO2 emission factors forfuel combustion and applied in a national inventory Difficult for atmospheric observations to be used to derive emission factors for fuel combustion – could
be different for other CO2 emission sources, e.g. in connection with fugitive emissions from fuels Atmospheric observations could be used to identify incorrect fuel information, e.g. the share of biofuelsin road fuels Atmospheric observations could be used to verify emissions from large point sources11

3. Assess the possibility that emerging datasets from atmospheric observations could be used to test
and verify particular IPCC default values (emission factors) and associated uncertainties
 In terms of fuel combustion, it is unlikely that atmospheric observations could be used to verify IPCC
default emission factors as the emission factors are based on carbon content in specific fuels
4. Discuss the use of gridding (spatial and temporal) of NGHGIs to allow comparison with atmosphericobservation data Very useful – not necessarily just for atmospheric observation researchers(e.g. local authorities andfeedback to inventory compilers of gaps in knowledge)
 Lots of ongoing activities – important to share knowledge and data Requires a lot of data handling Balance between cost and benefit Important with close collaboration between inventory compilers and modellers
5. Discuss terminology and classifications of sources/sinks and associated natural andanthropogenic GHG fluxes to find a common understanding of consistency and differences inatmospheric observation data and GHG inventory estimates Has not observed major issues at this meeting for CO2 from fuel combustion
 International transport is only included as a memo item in the national emission inventories
 Different methodological tiers – relevant for atmospheric observation researchers to know, e.g. if using
Tier 1 default EFs where full oxidation is assumed, If national or plant-specific EFs are used (Tier 2 orTier 3), full oxidation may or may not be assumed
 Useful with a glossary Important to be clear on the difference between concentrations and emissions
 Very useful to have interactions between inventory compilers and modellers to enhance the common
understanding of the issues
6. Additional relevant publications
 On uncertainties related to latitude longitude coordinates of emissions from point sources: A spatial
uncertainty metric for anthropogenic CO2 emissions (Woodard et al. 2014), Uncertainty in gridded CO2
emissions estimates (Hogue et al. 2016), Large Uncertainties in Urban-Scale Carbon Emissions (Gately& Hutyra 2017) For energy data changes: Hoesly R.M. and S.J. Smith. 2018. “Informing energy consumption
uncertainty: an analysis of energy data revisions.” Environ. Res. Lett. 13 124023.
https://doi.org/10.1088/1748-9326/aaebc3

12

2.3

Fugitive CH4 emissions

The following experts participated in the Fugitive CH4 BOG: Dominique Blain, Steven Hamburg, Matthew Johnson,
Bryce Kelly, Zhou Lingxi, Bram Maasakkers, Prabir Kumar Patra, Cynthia A. Randles, Steve Smyth, Rob Sturgiss,
Oksana Tarasova, Irina Yesserkepova, Daniel Varon, Felix Vogel.
Facilitator:
Melissa Weitz
Rapporteur:
Anna Romanovskaya
TSU:
Baasansuren Jamsranjav
1. Assess and critique recent estimation techniques that utilise atmospheric observations as well as
operational systems, platforms, instruments/sensors and methods/models for their potential to be
used for the verification of national inventory sectoral emission estimates, consistent with theguidance provided in the 2019 Refinement
 A lot of potential for use of these techniques for assessment of GHG inventories for CH4 fugitive
emissions Rapidly maturing science Ongoing dialogue and development of capacity between GHG inventory compilers and researchers is
critical (design of studies and appropriate interpretation of results)
 Appropriate technique depends on question being asked:- particular target: verification of the national inventory for fugitive CH4 or development of Tier 3 EFsor conduction of Tier 3 measurement for inventory reporting- specific source in question: level of detail required- scale: time and space (source level, facility level, basin level, national), (e.g., snap shot through longterm measurements) versus annual inventories and time series considerations- approach to upscaling/downscaling of measurements (representativeness)- relevance of single technique or to use the combination of techniques- trace gases (isotopes, stoichiometry, etc.) for precise interpretation
 Idea from the group: to develop a matrix (set of matrixes) for use in collaboration between inventory
compilers and atm. researchers to assess available different techniques for different scales and different
purposes (e.g., level versus trend) (Table 6.2, Volume 1)
QUESTION (inventory-relevant)⇔TECHNIQUES (atmospheric-based)⇔IMPLEMENTATION- could include mass balance, spectroscopy, long-term observation, simple inversion, modelling, etc.
and different vehicles: cars, towers, aircrafts, satellites- “living” list of techniques – to be updated periodically taking into account rapid developments in thatscience, including information on uncertainty
 The matrix (set of matrixes) referred to in the previous bullet can be developed, but time is needed- Recommendation for future work of TFI
2. Assess and evaluate successful examples of: comparisons between atmospheric observations andnational inventories that are consistent with good practice provided in the 2019 Refinement thathave led to implemented or planned improvements in national inventories; Examples discussed from Annex I (lack for non-Annex I):- Canada:
 aircraft used to compare emissions totals and source-level breakdown for the area
 planned to measure EFs for specific provinces- Australia: aircraft QA process for CH4 inventory in total and for coal seam gas particularly- US: satellite (e.g., TROPOMI datasets) and aircraft used for comparison for production anddistribution (oil/gas)- China: in situ comparison for coal CH4 emissions
13

- Poland and Romania: aircraft spectrotechnics, large subnational scale – fugitive emissions for coalmines (Poland) oil and gas (Romania) A lot of examples of EFs however subnational scale: California, Canada Improvements in the industrial reporting Idea from the group: encourage submission of new developed EFs in the IPCC EFDB
3. Assess the possibility that emerging datasets from atmospheric observations could be used to test
and verify particular IPCC default values (emission factors) and associated uncertainties
 Opinion of the group: testing and verification of Tier 1 default EFs may not be worth the effort due tovariability (geographically, practices, etc), complexity of measurements, costs, level of disaggregationof data obtained- Other potential uses include informing decision by country to use or not use Tier 1 EF, developmentof Tier 2 EF
 New default EFs from atmospheric observation would not necessarily lower the associated uncertainties
compared to 2019 Refinement: different features\specific of different individual sources Uncertainties of measurements and inventory estimates are different (sampling size, equipment,
modelling versus IPCC uncertainties of estimates)
4. Discuss the use of gridding (spatial and temporal) of NGHGIs to allow comparison with atmosphericobservation data Gridding is critically important step for inverse modelers- Gridded versions of national GHG inventories (consistent with sectors, sources in GHG inventories)
improve our ability to compare GHG inventory results with atmospheric observations- Note that uncertainty is impacted with spatial, temporal, allocations etc.
 Spatial resolution needed:- depends on the individual sources and could be different, depends on types of observation
 Temporal gridding:- for fugitive emissions is difficult to obtain- fugitive emissions can vary greatly over time
- limited data to grid temporal variability for fugitives
 Additional value of gridding:- Information to local communities (including environmental justice information, mitigation)- Improved priors for atmospheric studies
 Connected to the question of capacity of inventory teams in different countries- is a barrier to wide use atmospheric observation across reporting countries under the Paris
Agreement (only few countries have a such experience) Some countries could resist of doing gridding- e.g. confidential (or lack of) information
 Idea of the group: to develop recommendations on the gridding of the national GHG inventory data
- further work for TFI
5. Discuss terminology and classifications of sources/sinks and associated natural andanthropogenic GHG fluxes to find a common understanding of consistency and differences inatmospheric observation data and GHG inventory estimates constrain1 – Atmospheric observation: “what we have information on.” Inventory: “not be able”
 scale 2 - how different scales are matching inventory
1 Atmospheric observation community uses this term to mean: “what we have information on.” Inventory often interprets the term tomean: “not be able”
2 The temporal and spatial scales may differ between atmospheric observations and inventories and this should be taken into
consideration for comparisons14 fugitive - Atmospheric observation: general understanding. Inventory: according to IPCC definition
 validation/verification - Atmospheric observation: validation of models. Inventory: defined verification in
IPCC Guidelines natural versus anthropogenic - provide list of sources from IPCC Guidelines to atmospheric observation
community
 biogenic and thermogenic and pyrogenic - and how it does and does not relate to natural versus
anthropogenic
 uncertainty 3 - Atmospheric observation: scientific interpretation of measurements conducted.
Inventory: IPCC methodology related to the total calculated emission
 concentrations versus emissions (fluxes) - measured atmospheric concentrations versus emissions ininventories
 upscaling/downscaling - how national totals are obtained from measurements
 time frames – how annual data are obtained for the inventory
 completeness - Atmospheric observation: all sources covered in measurements. Inventory: IPCC
definitions
 individual source versus source category - measured individual source versus defined source categories
in inventories
 time series consistency - how possible to ensure using atmospheric observation in line with IPCC
Guidelines
 Inventory development requirements versus research needs to get a result4

3 Uncertainty information provided in inventories and in atmospheric observation research may have different meanings. Uncertainty inthe inventories should be estimated in accordance with the agreed IPCC methodology and based on the uncertainty of activity data andemission factors. Uncertainty for research could include uncertainty in the modelization, uncertainties in the sources/sinks contributing to
the measured flux and trend as well as uncertainty in the actual boundaries of the territory to which measured fluxes and trends pertainetc.”
4 Inventory and atmospheric observation community may use the term “requirement” different--Inventory considers requirements of
IPCC/UNFCCC and research considers it to mean what is needed to get a result (the specifics of which may not be a requirement for
inventories)

15

2.4

AFOLU GHG emissions

The following experts participated in the AFOLU GHG BOG: Antonio Bombelli, Pep Canadell, Frank J. Denten,
Savitri Garivait, Giacomo Grassi, Werner Leo Kutsch, Toshihiro Kuwayama, Douglas MacDonald, Sara MikaloffFletcher, Sini Niinistö, Wolfgang Alexander Obermeier, Riitta Kristiina Pipatti, Lucia Perugini, Ana, Maria Roxana
Petrescu, Lars Peter Riishojgaard, Yasna Rojas, Wanqi Sun, Rona Louise Thompson, Luciana Vanni Gatti, Sara
Venturini, Yohanna Villalobos Cortes, Thomas Charles Wirth.
Facilitator:
Maria Jose Sanz Sanchez
Rapporteurs:
Stephen Ogle
TSU:
Sandro Federici
1. General Comments
 Focused on atmospheric observations that are used in inversion frameworks to estimate fluxes Verification of inventory using inversion data is not necessarily leading to direct changes in theemissions reporting (i.e., directly using the inversion results for reporting), but rather as a starting point
for further investigation of the inventory methods as well as the inversion framework
 Goal is to reduce uncertainty by identifying issues with underlying data
 Inventories may also be useful for improving atmospheric inversions
 In general, developing country parties to the UNFCCC face more challenges to use atmosphericobservations for evaluating inventories- Global inversions may provide some insights into key categories- Not clear that inversions can be used directly in evaluating inventories in developing countries,
particularly smaller countries
 Questions that can be asked in these comparisons:- Is the inventory accurate?
- Is the inversion accurate?
- What are the drivers of the stock changes or GHG fluxes?
- Are trends and spatial patterns consistent between the inventory and inversion?
2. Assess and critique recent estimation techniques that utilise atmospheric observations as well as
operational systems, platforms, instruments/sensors and methods/models for their potential to be
used for the verification of national inventory sectoral emission estimates, consistent with theguidance provided in the 2019 Refinement
 Overarching conclusion: Need to gain more experience using atmospheric observations and inversions
to evaluate AFOLU sectoral GHG inventories.
- Best examples from evaluation of CH4 and N2O emissions in AFOLU sector
 Considerations for conducting an informative analysis based on recent inversion and inventory
comparisons Scale of inversion is important- Regional inversions critical for small countries, and to evaluate subnational fluxes in larger countries- Global inversions may be useful for large countries- Estimates of fluxes should be consistent across scales, as such regional inversions need to beconsistent with the global inversions and with rates of emissions measured at the local scale Prior fluxes for inversions is a large source of uncertainty- Could use the inventory as a prior if adequate for purposes but will likely need data beyond theinventory to estimate the full flux, particularly for CO2- In AFOLU, lateral fluxes associated with harvested woody products, crop harvest and transport,
indirect N2O emissions, and hydrological flows contribute to the uncertainty in the estimates Transport is another large source of uncertainty in inversion frameworks- May contribute to mismatch in inversion fluxes compared to inventory16

- Depends on topography and complexity of atmospheric structure Atmospheric observations of concentrations have considerably less uncertainty, but quality and quantityof atmospheric observations are another consideration- Interpretation of tall tower and aircraft observations are a more direct inference on theconcentrations, and need to be expanded in some regions (initiative led by WMO)
- Satellite data provide additional information on atmospheric concentrations to support the inversions- In turn, satellite data are providing opportunities for inversion analysis in regions where this was notpossible in the past
 Inventory compilers need to be actively involved in these comparisons- Providing context about the inventory analysis- Expressing needs for improving the inventory- Evaluating differences and unexplained inconsistencies from the comparison
3. Assess and evaluate successful examples of: comparisons between atmospheric observations andnational inventories that are consistent with good practice provided in the 2019 Refinement thathave led to implemented or planned improvements in national inventories; Comparison 1: New Zealand Example- Inversion system applied to evaluate CO2- Inversion System: Surface measurements and Langragian Bayesian inversion system- Finding C sink in the inversion analysis that has not been identified in the inventory along coastal
areas May be associated with lateral flows of sediment and/or water New studies initiated to investigate these possibilities- Publications: Steinkamp et al. 2017, ACP; Geddes et al. 2020, Report to Ministry of Primary
Industries
 Comparison 2: Australia Example- Inversion system applied to evaluate CO2- Inversion System: OCO-2 Satellite data with Data Assimilation- Finding a sink in rangelands that has not been identified in the inventory
 Maybe associated with precipitation patterns, woody encroachment, and/or management
 Planning to further investigate these differences with inventory team
- Publications: Villalobos et al. 2020, ACP; Villalobos et al. 2021, ACP; Villalobos et al. 2022, ACP Comparison 3: United States Example- Inversion system applied to investigate impact of freeze-thaw process on soil N2O emissions- System: Tower observations and observations made from aircraft were interpreted with
Carbontracker Lagrangian Bayesian Inversion system- Findings showed that freeze-thaw periods coinciding with large emission pulses consistent with thesmall set of experimental data.
- Inversion informed model development leading to an improvement in the inventory that has been
incorporated into UNFCCC reporting- Publication: Nevison et al. 2018, GBC; Del Grosso et al. 2022, PNAS Comparison 3: Subnational Example from US State of California- Inversion system applied to emissions from dairy operations- Inversion System: Lagrangian Bayesian Inversion System- Inversion suggested that they were under-estimated- Mobile and airborne measurements confirmed that the inventory emission factors were accurate andthe inversion was not accurate in this case.
- Publication: Amini et al. 2022, ES&T

17

4. Assess the possibility that emerging datasets from atmospheric observations could be used to test
and verify particular IPCC default values (emission factors) and associated uncertainties
 Tier 1 Emission Factor Evaluation: Soil N2O emissions- Inversion system applied to estimate N2O fluxes in Brazil, United States, China, South Asia, andEurope- Estimated implied emission factors based on N inputs (i.e., dividing the emissions by the inputs)
combining direct and indirect emissions- Found that Tier 1 factors from the 2006 GL were lower than implied emission factors from theinversion analysis and that implied emission factors increased over time, or with higher applications
rates. The study did not consider the differentiation between direct and indirect emissions or naturalemissions- Note: 2019 Refinement has updated these factors so could be further investigation- Regardless, example of how atmospheric data could be used to evaluate default factors- Publication: Thompson et al. 2019, NCC
5. Discuss the use of gridding (spatial and temporal) of NGHGIs to allow comparison with atmosphericobservation data
 Inventory compiler needs sufficient resources and time to participate in the gridding of inventory data
- Compiler has the detailed understanding of these data and should be involved in this process even
if the compiler is not gridding the data Need to determine the appropriate spatial and temporal scales for comparing the inversion and inventory
before gridding the inventory data
- e.g., comparisons at finer scales may not be informative if uncertainties are large Need to determine where uptake and release are occurring, particularly the lateral flows of materials
that may lead to processes that drive uptake and release of the GHGs occurring in different locations
that are not easily identified.
6. Discuss terminology and classifications of sources/sinks and associated natural andanthropogenic GHG fluxes to find a common understanding of consistency and differences inatmospheric observation data and GHG inventory estimates Anthropogenic GHG Emissions- Managed land proxy leads to inconsistency between inversion and inventory estimates Differences in application of inventory methods- Particularly differences among inventory Tier methods- Tier 1 v. Tier 3 for soil N2O has a different level of estimation and can lead to inconsistencies
 Missing sources in the inventory- Some sources may not be estimated depending on policy relevance but leads to inconsistencies incomparisons with the inversion- e.g., Herbaceous biomass and dead organic matter Attribution of inversion flux to individual source categories- Fluxes are based on gases but source categories are often further subdivision of gases into
categories such as direct and indirect soil N2O emissions- Inversions may provide some information on emissions if separation of activities across the country(e.g., pixels dominated by forest, cropland etc., rice fields, may provide some insight on sources
categories)- However, more heterogeneous land use patterns and mobile sources on the landscape such as
livestock systems in this sector will be difficult to disaggregate and also evaluating livestock systems
in this sector which are more mobile across the landscape Interannual variability

18

- Not always addressed in the inventory whereas this is part of the inversion, leading toinconsistencies- Longer term climate change is imposed on these patterns, but may not be addressed in the inventory- May be able to extract interannual variability out of the atmospheric data as the time series increasein length
 Inversions may only capture short term trends that may not result in longer-term changes in stocks
consistent with fluxes observed in inversions

19

2.5

F-gases

The following experts participated in the Fgas BOG: Peter Brown, Philip L. DeCola, Fatma Betül Demirok, Mark
Hunstone, Alistair James Manning, Stephen Montzka, Anita Ganesan, Kokou Sabi, Bo Yao
Facilitator:
Jongikhaya Witi
Rapporteur:
Deborah Ottinger
TSU:
Pavel Shermanau
1. Assess and critique recent estimation techniques that utilise atmospheric observations as well as
operational systems, platforms, instruments/sensors and methods/models for their potential to be
used for the verification of national inventory sectoral emission estimates, consistent with theguidance provided in the 2019 Refinement
 Both atmospheric scientists and inventory compilers should be aware of the uncertainties in theemissions derived from atmospheric observations.
 For the most commonly used inverse modelling approach, these uncertainties may result from any of
the components of the modelling system, including gas abundance measurements, priors, weather
prediction models, transport models, inverse systems, and concentrations upwind of the region ofinterest.
 One way to better understand these uncertainties is to calculate results based on multiple versions ofthese components.
 Priors are supplied as inputs to inversions, and priors with a range of detail (from uninformed toextensively informed) supply different but useful emissions estimates (an entirely independent estimate
vs. a refinement of the inventory estimate) to the inventory community for the purpose of verification (asdefined in the 2019 Refinement) of national emission estimates.
 Recognize that inverse analysis systems are not yet standardized; therefore, there is room for additional
progress and refinement of emission estimates and uncertainties derived using these systems. As aresult, identifying robust signals and robust differences between an inverse and inventory result requires
expert judicious review and assessment of results. Robust signals are best identified or confirmed
through consideration of multiple configurations of inversion models and observations.
2. Assess and evaluate successful examples of: comparisons between atmospheric observations andnational inventories that are consistent with good practice provided in the 2019 Refinement thathave led to implemented or planned improvements in national inventories; available examples
where emission factors derived from atmospheric observations have been incorporated into abottom-up inventory framework Atmosphere-derived emission estimates for F-gases are included in NIRs to the UNFCCC for four
different countries.
 These successful examples all include ongoing respectful communication between both atmosphericand inventory-focused communities to better understand emission estimates, trends, and theiruncertainties. The best examples include those where there was a dedication to continuous and longterm engagement in this collaborative process.
 Useful outcomes have resulted from:- A sustained and consistent back-and-forth process.
- Establishing a regular, predictable schedule for updated comparisons (e.g., annually). This builds
long-term relationships and avoids having to reassemble the relevant expertise and data on an adhoc basis.
- Bringing in additional expertise, e.g., from emitting industry.
 Insight into what is driving emissions has been gained by combining on-the-ground knowledge ofsources (from the inventory agency) with analysis of- temporal and spatial patterns in emissions (e.g., seasonality in emissions) and20

- emissions of different trace gases (including F-GHGs) that may be emitted separately or together incharacteristic ratios with the F-GHGs.
 Given that useful comparisons take time, successful programs have prioritized certain gases/sources
over others.
3. Assess the possibility that emerging datasets from atmospheric observations could be used to test
and verify particular IPCC default values (emission factors) and associated uncertainties
 It is difficult to use atmosphere-based estimates to gain insights into specific default factors because
current inverse systems generally provide total emissions from the sum of all emissive processes.
 In addition, emissions for many F-gas source categories depend on multiple parameters (in addition toactivity data), making it challenging to determine which of these parameters should be adjusted.
- Nevertheless, in some cases, country-specific parameters have been informed by atmospherederived emissions among other datasets. In the long term, these country-specific factors could
inform IPCC default values.
 Targeted pilot atmospheric measurement projects can provide insights into specific processes (e.g.,associated with fluorochemical production).
4. Discuss the use of gridding (spatial and temporal) of NGHGIs to allow comparison with atmosphericobservation data Geographically or temporally disaggregating National GHGI information can facilitate more accuratecomparisons with atmosphere-based emission estimates when the latter aren't representative of an
entire country or year.
 Furthermore, the disaggregated inventory can be used to extrapolate atmosphere-based results
representative of a limited portion of a country or time period to the entire country or year.
 Finally, disaggregated National GHGI information can help identify regions of a country where
atmospheric observations should be best situated in order to capture emissions from the most emissive
regions.
5. Discuss terminology and classifications of sources/sinks and associated natural andanthropogenic GHG fluxes to find a common understanding of consistency and differences inatmospheric observation data and GHG inventory estimates Important for both inventory compilers and atmospheric science community to use consistent GWPs in
aggregations across GHGs when comparisons are made. (Inventory compilers are likely to prefer thecurrent UNFCCC-adopted GWP values.) We propose including a glossary for the following terms:- Gas abundance measurements,- priors- uninformed (flat) vs. informed- weather prediction models,- transport models,- inverse systems,- “background concentrations” or concentrations upwind of the region of interest
6. Additional Observations
 Atmospheric measurements are currently informing refinements to existing industrial GHG reporting
programs (e.g., updated emission factors used by facilities for reporting).
 May be useful to establish a forum for the regular exchange of ideas among inventory compilers
regarding verification using atmosphere-based estimates.

21Annex 1: Materials for the Meeting
Guiding Note
(Prepared by Task Force Bureau to help participants have focused discussion
consistently with the decision by the IPCC at its 54th(bis) Session)
Focus
the use of atmospheric observation data and models in verification of national greenhouse gas (GHG)
inventories
National GHG Inventories scope and associated requirements
National GHG inventories provide information on the level and trend of GHG emissions and removals associatedwith human activities which is essential to the assessment of human impacts on the climate system. National GHG
inventories are important for policy makers to plan actions to curb those emissions as well as to quantify the resultsof implemented actions to reduce the atmospheric concentration of GHGs, so tracking progress by countries inachieving the goal of United Framework Convention on Climate Change (UNFCCC).
Under the UNFCCC, countries are required to develop and report national GHG inventories consistent with the
IPCC Guidelines, to ensure transparency, accuracy, completeness, consistency and comparability of their national
GHG inventories. For example, under the Paris Agreement, all Parties shall use the 2006 IPCC Guidelines for
National Greenhouse Gas Inventories (2006 IPCC Guidelines) in accordance with Decision 18/CMA.1 "Modalities,
procedures and guidelines for the transparency framework for action and support referred to in Article 13 of theParis Agreement”.
IPCC methods are generally based on bottom-up calculation of estimates through the quantification of processes
and activities that cause GHG emissions and removals (i.e., activity data) at the level of source category and theapplication of associated emission/removal factors. At higher tiers, for certain source categories, IPCC methods
may make use of country-specific and facility-specific data based on in-situ measurements and other information.
Use of remote (i.e., top-down) estimation methods using atmospheric concentration is in its early stages.
In the 2006 IPCC Guidelines, the benefit of use of atmospheric measurement data was referred to, but practicalguidance on how to use these data was not provided. Taking into account developments in GHG monitoring
networks and advances in technologies since 2006, guidance on the use of atmospheric measurements forassessment and improvement of national GHG inventories was updated and elaborated in the 2019 Refinement
to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories (2019 Refinement), Volume 1, Chapter 6.
Further, the development and improvement of source-specific emission factors are becoming increasingly
important to keep enhancing the quality of GHG estimates, especially for those sectors and categories wheredevelopment and application of new technologies impact the associated rate of emissions, and the use of
atmospheric observation data and models may support verification of EFs.
Nowadays, atmospheric observations are based on a large variety of platforms (e.g., ground-based (including
vehicle-based mobile laboratories), ship-borne, aircraft-borne, satellite-borne), sensors/instruments (e.g., infraredabsorption spectroscopy, UV-visible differential optical absorption spectroscopy, solid-state and electrochemicalsensors), and models applied to derive activity-dependant fluxes and/or time-dependant rates of change inatmospheric concentrations. Such large variability provides for an improved capacity to monitor emissions undera variety of circumstances.

22

Discussion at the expert meeting can be articulated in the following items:
I.

Take stock of efforts by inventory compilers to implement the 2019 Refinement guidance on use of
atmospheric measurements to improve national GHG inventories, through examples that are consistent
with good practice provided in the 2019 Refinement (e.g., following the steps provided in Tables 6.3 andBox 6.5 of Volume 1). Examples and case studies should include both efforts to incorporate
observations data directly into GHG inventories, and efforts to use observations to provide independent
assessments of GHG inventory results that have led to identification of areas for improvement for GHG
Inventories.

II.

Assess and critique advances in datasets as well as new and operational systems, platforms,
instruments/sensors and methods/models since 2019, and their relevance to improving national GHG
inventories consistent with the IPCC Guidelines.

III.

Assess the strengths and limitations of this experience with the 2019 Refinement and develop
recommendations for how implementation can be improved in the future, including through improved
technical, human and financial resources.

Potential BOGs
A.

 Assess and critique recent estimation techniques that utilise atmospheric observations as well as other new
and operational systems, platforms, instruments/sensors and methods/models for their potential to be used
for the verification of national inventory sectoral emission estimates, consistent with the guidance provided
in the 2019 Refinement; Assess the possibility that emerging datasets from atmospheric observations could be used to test andverify particular IPCC default values and associated uncertainties.
 The assessment should consider the use of gridding of NGHGIs to allow comparison with atmosphericobservation data.

Focus on combustion CO2
Discuss items for both approaches: 1. satellite-based measurements; 2. - close-range atmosphericmeasurements
B.

 Assess and critique recent estimation techniques that utilise atmospheric observations as well as other new
and operational systems, platforms, instruments/sensors and methods/models for their potential to be used
for the verification of national inventory sectoral emission estimates, consistent with the guidance provided
in the 2019 Refinement; Assess the possibility that emerging datasets from atmospheric observations could be used to test andverify particular IPCC default values and associated uncertainties.
 The assessment should consider the use of gridding of NGHGIs to allow comparison with atmosphericobservation data.

Focus on fugitive CH4
Discuss items for both approaches: 1. satellite-based measurements; 2. close-range atmospheric measurements
C.

 Assess and critique recent estimation techniques that utilise atmospheric observations as well as other new
and operational systems, platforms, instruments/sensors and methods/models for their potential to be used
for the verification of national inventory sectoral emission estimates, consistent with the guidance provided
in the 2019 Refinement; Assess the possibility that emerging datasets from atmospheric observations could be used to test andverify particular IPCC default values and associated uncertainties.
23 The assessment should consider the use of gridding of NGHGIs to allow comparison with atmosphericobservation data.
Focus on AFOLU N2O, CH4, CO2
Discuss items for both approaches: 1. satellite-based measurements; 2. close-range atmospheric measurements
D.

 Assess and critique recent estimation techniques that utilise atmospheric observations as well as other new
and operational systems, platforms, instruments/sensors and methods/models for their potential to be used
for the verification of national inventory sectoral emission estimates, consistent with the guidance provided
in the 2019 Refinement; Assess the possibility that emerging datasets from atmospheric observations could be used to test andverify particular IPCC default values and associated uncertainties.
 The assessment should consider the use of gridding of NGHGIs to allow comparison with atmosphericobservation data.

Focus on F-gases
Discuss items for both approaches: 1. satellite-based measurements; 2. close-range atmospheric measurements
Discussion points
a. Consider covering all/most significant sources of emissions of the relevant GHG(s)b. GHG Inventory compiler data/QAQC needs relevant to observations
c. Discussion how to clarify terminology and classifications to find a common understanding of consistency anddifferences in atmospheric observation data and GHG inventory estimates24Annex 2: Agenda
IPCC Expert Meeting on Use of Atmospheric Observation Data in
Emission Inventories
5 – 7 September 2022

WMO HQ, Geneva - Switzerland

AgendaDay 1 – Monday, 5 September 2022
Part I – Opening Plenary
8:30 – 9:00

 Registration of participants Welcome• IPCC Secretary (Abdalah Mokssit) – 5 min• IPCC TFI Co-Chairs Eduardo Calvo Buendia and Kiyoto Tanabe – 5 min
9.00 - 10.00  Adoption of Agenda• IPCC TFI Co-Chairs Eduardo Calvo Buendia and Kiyoto Tanabe – 5 min
 Introductory presentation on Scope, Context, BOGs (+Q&A)• IPCC TFI TSU – 45 min Presentations & Q&A (30 min each)• Comparing national greenhouse gas budgets reported in UNFCCC
inventories against atmospheric inversions - Philippe Ciais
Day 1• Pilot national-scale estimates of CO2 and CH4 emissions and removals
from space-based measurements - Masataka Watanabe
10.00 - 12.25• CarbonWatch NZ: combining measurements of GHGs in the air above
New Zealand in a bird's eye view of New Zealand’s carbon balance –8:30-17.00
Sara Mikaloff-Fletcher•
Emissions, Methods, Uncertainty, and Evaluation - Steven J. Smith(CEST)+ coffee break (25 minutes) [at 10:30]
GenevaTime(UTC+2)

12.25 - 13.55

Lunch Presentations & Q&A (30 min each)• Gridding CH4 estimates from national GHG inventories for comparison
with atmospheric observation data and discriminating among
anthropogenic and natural fluxes – Bram Maasakkers• Monitoring and validating CH4 point sources with remote observations –Matthew Johnson• The role of the International Methane Emissions Observatory in
13.55 - 17.20
Strengthening National Greenhouse Gas Inventories – Steven Hamburg• Airborne Amazon Carbon budget and CH4 emissions – Luciana Vanni
Gatti• Use of remote observation to verify N2O emissions from Land – Stephen
Ogle• F-gas inventories and comparisons with atmospheric observations –Deborah Ottinger+ coffee break (25 minutes) [at 15:30]
25

Day 2 – Tuesday, 6 September 2022
Part II – Break-out groups (BOG) presentations and discussion
BOG

Item

Facilitator

Rapporteur

TSU staff

1

CO2 emissions
from fuelcombustion

Dario Gomez

Ole-Kenneth
NielsenTakeshi Enoki

2

Fugitive CH4
emissions

Melissa Weitz

Anna
Romanovskaya

3

AFOLU GHG
emissions

Maria Jose’ Sanz
Sanchez

Stephen Ogle

4

F-gases

Jongikhaya Witi

Deborah Ottinger

GenevaTime(UTC+2)9.00 - 12.30

Pavel Shermanau

BOG 1

BOG 2

 Presentations & Q&A (30 min each)• Estimating fugitive CH4 emissions from thedetection of CH4 plumes using aeroplane flyovers Bryce Kelly Discussion (all day)

BOG 3

 Presentations & Q&A (30 min each)• Using satellite observations to model net carbon
dioxide emissions from AFOLU (REgional Carbon
Cycle Assessment and Processes (RECCAP)
under the Global Carbon Project - Yohanna
Villalobos Cortes
 Discussion (all day)

BOG 4

 Presentations & Q&A (30 min each)• High precision F-gas measurement instruments
and application in estimate Chinese F-gas
emission - Bo Yao• F-gas emissions monitoring through atmosphericobservation - Alistair James Manning
 Discussion (all day)12.30 - 14.00 Lunch

14.00 – 17.20

Sandro Federici

 Presentations & Q&A (30 min each)• Estimates of CO2 emissions from airborne sensors- Hiroshi Suto Discussion (all day)Day 2
9:0017.00(CEST)

Baasansuren
Jamsranjav

BOG 1

 Discussion (all day)

BOG 2

 Discussion (all day)

BOG 3

 Discussion (all day)

BOG 4

 Discussion (all day)

Coffee Breaks: 20 minutes each at 10:30 and 15:30
26

Day 3 – Wednesday, 7 September 2022
Part II – Break-out groups (BOG) presentations and discussion

9.00 - 12.30
Day 3
9:0017.00

12.30 - 14.00

 Discussion (all morning)

BOG 2

 Discussion (all morning)

BOG 3

 Discussion (all morning)

BOG 4



Discussion (all morning)

Lunch

Part III – Closing Plenary(CEST)
GenevaTime(UTC+2)

BOG 1

14.00 –
16:35

 BOGs’ Presentations + QA (35 min each)• BOG 1 – Ole-Kenneth Nielsen• BOG 2 – Anna Romanovskaya• BOG 3 – Stephen Ogle
• BOG 4 – Deborah Ottinger+ coffee break (15 minutes)

16:35-17:20  Discussion and conclusions (45 min)17:20-17:30

 Closing remarks
IPCC TFI Co-Chairs Eduardo Calvo Buendia and Kiyoto Tanabe – 10 min

Coffee Breaks: 20 minutes at 10:30 and 15 minutes at 16:20

27

Annex 3: List of Participants
Dominique Blain
Environment and Climate Change Canada
CanadaAnita Ganesan
University of Bristol - School of Geographical Sciences- Atmospheric Chemistry
Cabot Institute for the Environment
United Kingdom

Antonio Bombelli
GCOS Global Climate Observing System, WMO
Switzerland

Savitri Garivait
The Joint Graduate School of Energy andEnvironment (JGSEE), King Mongkut's University ofTechnology Thonburi (KMUTT)
ThailandPeter Brown
Ricardo Energy & Environment
United Kingdom

Eduardo Calvo Buendia (TFI Co-Chair)Rebecca Garland
Universidad Nacional Mayor de San Marcos (UNMSM) University of Pretoria
PeruSouth Africa
Pep Canadell
CSIRO Climate Science Centre
Australia

Veronika Ginzburg
Yu.A. Izrael Institute of Global Climate and Ecology
Russian Federation

Philippe Ciais
Laboratoire des Sciences du Climat et del'Environnement / IPSL, CEA-CNRS-UVSQ, Université
Paris-Saclay
FranceDario Gómez
Comisión Nacional de Energía Atómica(Atomic Energy Commission of Argentina)
Argentina

Philip L. DeCola
University of Maryland, Department of Atmosphericand Oceanic Sciences
USA
Fatma Betül Demirok
Turkish Statistical Institute (TurkStat)
Turkiye

Giacomo Grassi
Directorate Sustainable Resources
Institute for Environment and Sustainability - Joint
Research Centre of the European Commissions
Italy
Michel Alexandre Grutter de la Mora
Directorate Sustainable Resources
Universidad Nacional Autonoma de Mexico – UNAM
Centre of Atmospheric Sciences
MexicoFrank J. DentenerInstitute for Environment and Sustainability - Joint
Chia Ha
Research Centre of the European Commissions
The Netherlands
Environment and Climate Change Canada
CanadaRichard Engelen
Copernicus Atmosphere Monitoring Service
Steven Hamburg
Project Coordinator of CoCO2
Environmental Defense Fund/ International Methane
Copernicus Department
Emissions Observatory- UNEP
European Centre for Medium-Range Weather United States
Forecasts
United Kingdom

28

Mark Hunstone
Sara Mikaloff-Fletcher
Department of Industry, Science, Energy and National Institute for Atmospheric and Oceanic
Resources, Australian Government
Research (NIWA)
Australia
New Zealand
Matthew Johnson
Mechanical & Aerospace Engineering
Carleton University
CanadaStephen Montzka
NOAA Global Monitoring Laboratory
United States

Ole-Kenneth Nielsen
Bryce Kelly
Aarhus University
School of Biological, Earth and Environmental Denmark
Sciences,University of New South Wales
Australia
Sini Niinistö
Statistics Finland, FI GHG inventory teamMiao Lang
FinlandMeteorological Observation Center of China
Meteorological Administration (MOC/CMA)
Wolfgang Alexander Obermeier
China
Ludwig Maximilian University of Munich
Germany
Bundit Limmeechokchai
Sirindhorn International Insitute of Technology, Steven Ogle
Thammasat University
Colorado State University, Natural Resource Ecology
ThailandLaboratory and Department of Ecosystem Scienceand Sustainability
Werner Leo Kutsch
United States
director general of ICOS ERIC
Germany
Deborah Ottinger
U.S. Environmental Protection Agency
Toshihiro Kuwayama
United States
California Air Resources Board
United States
Prabir Kumar Patra
Japan Agency for Marine-Earth Science and
Zhu Liu
Technology (JAMSTEC)
Associate Professor at Tsinghua University
India/Japan
Department of Earth System Science
China
Lucia Perugini
CMCC
Bram Maasakkers
Italy
SRON Netherlands Institute for Space Research
The Netherlands
Ana Maria Roxana Petrescu
Research Associate, Faculty of Science, Earth andDouglas MacDonald
Climate - Vrij University
Environment and Climate Change Canada
The Netherlands
CanadaRiitta Kristiina Pipatti
Alistair James Manning
FinlandUK Met Office
United Kingdom
Cynthia A. Randles
United Nations Environment Program, International
Greg Marland
Methane Emissions Observatory
Appalachian State University
United States
United States29

Lars Peter Riishojgaard
WMO Director, WIGOS Branch
Switzerland

Kiyoto Tanabe (IPCC TFI Co-Chair)
Institute for Global Environmental Strategies (IGES)Japan

Yasna Rojas
Instituto Forestal de Chile (INFOR)
Chile

Oksana Tarasova
World Meteorological Organization
RussiaAnna Romanovskaya
Yu. A. Izrael Institute of Global Climate and Ecology
Russian Federation

Rona Louise Thompson
Norwegian Institute for Air Research - Atmosphere
and Climate Department
New Zealand

Kokou Sabi
Université de Lomé (UL) - Faculté Des Science (FDS) Yogesh K. Tiwari- Laboratoire de Chimie Atmosphérique (LCA)
Indian Institute of Tropical Meteorology,
Togo
India

Batouli Said Abdallah
Jocelyn Turnbull
National Center of Documentation and Scientific GNS Science
Research (CNDRS)New Zealand
Comoros
Luciana Vanni Gatti
Maria Jose Sanz Sanchez
INPE
Basque Centre for Climate Change (BC3)
BrazilSpain
Daniel Varon
Marko Scholze
Harvard University
Dept of Physical Geography and Ecosystem Science - United States
Lund University
SwedenSara VenturiniGroup on Earth Observation Secretariat (GEO)
Steven J. Smith
Switzerland
Joint Global Change Research InstituteYohanna Villalobos Cortes
United States
CSIRO
Steve Smyth
Australia
Environment and Climate Change Canada
CanadaFelix Vogel
Environment and Climate Change Canada
Rob Sturgiss
CanadaBailleul Climate Consulting
Australia
Masataka Watanabe
Research and Development Initiative, Chuo University
Wanqi Sun
Japan
China Meteorological Administration MeteorologicalObservation Centre
Melissa Weitz(CMAMOC)U.S. Environmental Protection Agency
China
United States
Hiroshi Suto
Japan Aerospace Exploration Agency
Japan

Tom Charles Wirth
US Environmental Protection Agency
United States

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Jongikhaya Witi
Department of forestry, fisheries and the Environment
South Africa

IPCC TFI TSU℅ Institute for Global Environmental Strategies (IGES)
Japan

Jung-Hun Woo
Konkuk University
South Korea

Sandro Federici
Baasansuren Jamsranjav

Pavel Shermanau
Yousuke Yamashita
Earth System Division, Satellite Observation Center,
National Institute for Environmental Studies (NIES), Toru Matsumoto
Japan
Eriko Nakamura
Bo YaoDepartment of Atmospheric and Oceanic Sciences & Takeshi Enoki (IGES Fellow/TSU scientific advisor)
Institute of Atmospheric Sciences, Fudan University,
ChinaChina
Irina Yesserkepova
Joint Stock Company(JSC) "Zhasyl Damu", theMinistry of Ecology, Geology and Natural Resources of
the Republic of Kazakhstan, Almaty office
Kazakhstan
Lingxi Zhou
Chinese Academy of Meteorological Sciences (CAMS)
China

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