BOG Report
BOG 4 – F-gases

IPCC TFI Expert Meeting on Use of Atmospheric
Observation Data in Emission Inventories
5-7 September 2022
WMO HQ, Geneva - Switzerland

IPCC TFI TSUDiscussion Question #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 the guidance provided in the 2019
Refinement

Discussion Question #1
o Both atmospheric scientists and inventory compilers should be awareof the uncertainties in the emissions derived from atmosphericobservations.
o For the most commonly used inverse modeling approach, these
uncertainties may result from any of the components of the modellingsystem, including gas abundance measurements, priors, weather
prediction models, transport models, inverse systems, andconcentrations upwind of the region of interest.
o One way to better understand these uncertainties is to calculate results
based on multiple versions of these components.

Discussion Question #1
o Priors are supplied as inputs to inversions, and priors with a range ofdetail (from uninformed to extensively informed) supply different but
useful emissions estimates (an entirely independent estimate vs. arefinement of the inventory estimate) to the inventory community forthe purpose of verification (as defined in the 2019 Refinement) of
national emission estimates.
o Recognize that inverse analysis systems are not yet standardized;
therefore, there is room for additional progress and refinement ofemission estimates and uncertainties. As a result, 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 ofmultiple configurations of models and observations.

Discussion Question #2
 Assess and evaluate successful examples of:• comparisons between atmospheric observations and national
inventories that are consistent with good practice provided in
the 2019 Refinement that have led to implemented or planned
improvements in national inventories;• available examples where emission factors derived fromatmospheric observations have been incorporated into abottom-up inventory framework

Discussion Question #2
o Atmosphere-derived emission estimates for F-gases are included in NIRs
for four different countries.
o These successful examples all include ongoing respectful communication
between both atmospheric and inventory-focused communities to better
understand emission estimates, trends, and their uncertainties. The best
examples include those where there was a dedication to continuous andlong-term engagement in this collaborative process.

Discussion Question #2
o 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 onan ad-hoc basis.
– Bringing in additional expertise, e.g., from emitting industry.

Discussion Question #2
o Insight into what is driving emissions has been gained by combining
on-the-ground knowledge of sources (from the inventory agency) withanalysis of– temporal and spatial patterns in emissions (e.g., seasonality inemissions) and– emissions of different F-GHGs that may be emitted separately or
together in characteristic ratios.
o Given that useful comparisons take time, successful programs haveprioritized gases/sources.

Discussion Question #3
 Assess the possibility that emerging datasets from atmosphericobservations could be used to test and verify particular IPCC
default values (emission factors) and associated uncertainties

Discussion Question #3•

It is difficult to use atmosphere-based estimates to gain insights into
specific default factors because current inverse systems provide total
emissions from the sum of all emissive processes.

Discussion Question #3
o In addition, emissions for many F-gas source categories depend on
multiple parameters (in addition to activity data), making it challenging
to determine which of these parameters should be adjusted.
– Nevertheless, in some cases, country-specific parameters havebeen informed by atmosphere-derived emissions among otherdatasets. In the long term, these country-specific factors could
inform IPCC default values.
o Targeted pilot atmospheric measurement projects can provide insights
into specific processes (e.g., associated with fluorochemicalproduction).

Discussion Question #4
 Discuss the use of gridding (spatial and temporal) of NGHGIs toallow comparison with atmospheric observation data

Discussion Question #4
o Geographically or temporally disaggregating National GHGI information
can facilitate more accurate comparisons with atmosphere-based
emission estimates when the latter aren't representative of the entire
country or year.
o Furthermore, the disaggregated inventory can be used to extrapolate
atmosphere-based results representative of a limited portion of acountry or time period to the entire country or year.
o 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.

Discussion Question #5
 Discuss terminology and classifications of sources/sinks andassociated natural and anthropogenic GHG fluxes to find acommon understanding of consistency and differences inatmospheric observation data and GHG inventory estimates

Discussion Question #5
o 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
the current UNFCCC-adopted GWP values.)

Discussion Question #5
o 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 theregion of interest

Additional Observationso Atmospheric measurements are currently informing refinements toexisting industrial GHG reporting programs (e.g., updated emission
factors used by facilities for reporting).
o May be useful to establish a forum for the regular exchange of ideas
among inventory compilers regarding verification using atmospherebased estimates.

Thank you