Potential of European 14CO2 observation network to estimate the fossil fuel CO2 emissions via atmospheric inversions
Authors: Wang Yilong , Broquet Grégoire , Ciais Philippe , Chevallier Frédéric , Vogel Felix , Wu Lin , Yin Yi , Wang Rong , Tao Shu 
Published: March 2018

Abstract. Combining measurements of atmospheric CO2 and its
radiocarbon (14CO2) fraction and transport modeling in atmospheric
inversions offers a way to derive improved estimates of CO2 emitted from
fossil fuel (FFCO2). In this study, we solve for the monthly FFCO2
emission budgets at regional scale (i.e., the size of a medium-sized country
in Europe) and investigate the performance of different observation networks
and sampling strategies across Europe. The inversion system is built on the
LMDZv4 global transport model at 3.75∘ × 2.5∘
resolution. We conduct Observing System Simulation Experiments (OSSEs) and use
two types of diagnostics to assess the potential of the observation and
inverse modeling frameworks. The first one relies on the theoretical
computation of the uncertainty in the estimate of emissions from the
inversion, known as “posterior uncertainty”, and on the uncertainty
reduction compared to the uncertainty in the inventories of these emissions,
which are used as a prior knowledge by the inversion (called “prior
uncertainty”). The second one is based on comparisons of prior and posterior
estimates of the emission to synthetic “true” emissions when these true
emissions are used beforehand to generate the synthetic fossil fuel CO2
mixing ratio measurements that are assimilated in the inversion. With
17 stations currently measuring 14CO2 across Europe using 2-week
integrated sampling, the uncertainty reduction for monthly FFCO2
emissions in a country where the network is rather dense like Germany, is
larger than 30 %. With the 43 14CO2 measurement stations
planned in Europe, the uncertainty reduction for monthly FFCO2 emissions
is increased for the UK, France, Italy, eastern Europe and the Balkans, depending
on the configuration of prior uncertainty. Further increasing the number of
stations or the sampling frequency improves the uncertainty reduction (up to
40 to 70 %) in high emitting regions, but the performance of the
inversion remains limited over low-emitting regions, even assuming a dense
observation network covering the whole of Europe. This study also shows that
both the theoretical uncertainty reduction (and resulting posterior
uncertainty) from the inversion and the posterior estimate of emissions
itself, for a given prior and “true” estimate of the emissions, are highly
sensitive to the choice between two configurations of the prior uncertainty
derived from the general estimate by inventory compilers or computations on
existing inventories. In particular, when the configuration of the prior
uncertainty statistics in the inversion system does not match the difference
between these prior and true estimates, the posterior estimate of emissions
deviates significantly from the truth. This highlights the difficulty of
filtering the targeted signal in the model–data misfit for this specific
inversion framework, the need to strongly rely on the prior uncertainty
characterization for this and, consequently, the need for improved estimates
of the uncertainties in current emission inventories for real applications
with actual data. We apply the posterior uncertainty in annual emissions to
the problem of detecting a trend of FFCO2, showing that increasing the
monitoring period (e.g., more than 20 years) is more efficient than reducing
uncertainty in annual emissions by adding stations. The coarse spatial
resolution of the atmospheric transport model used in this OSSE (typical of
models used for global inversions of natural CO2 fluxes) leads to large
representation errors (related to the inability of the transport model to
capture the spatial variability of the actual fluxes and mixing ratios at
subgrid scales), which is a key limitation of our OSSE setup to improve the
accuracy of the monitoring of FFCO2 emissions in European regions. Using
a high-resolution transport model should improve the potential to retrieve
FFCO2 emissions, and this needs to be investigated.