Published September 11, 2017
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Comparison of four inverse modelling systems applied to the estimation of HFC-125, HFC-134a, and SF<sub>6</sub> emissions over Europe
Authors/Creators
- 1. Laboratory for Air Pollution/Environmental Technology, Empa, Swiss Federal Laboratories for Materials Science and Technology, 8600 Dübendorf, Switzerland
- 2. Met Office, Exeter, EX1 3PB, UK
- 3. National Physical Laboratory, Teddington, Middlesex, TW11 0LW, UK
- 4. School of GeoSciences, University of Edinburgh, Edinburgh, EH9 3FF, UK
- 5. NILU – Norwegian Institute for Air Research, 2007 Kjeller, Norway
- 6. Dipartimento di Scienze Pure e Applicate (DiSPeA), University of Urbino "Carlo Bo", 61029 Urbino, Italy
- 7. School of Chemistry, University of Bristol, Bristol, BS8 1TS, UK
Description
Hydrofluorocarbons (HFCs) are used in a range of industrial applications and
have largely replaced previously used gases (CFCs and HCFCs). HFCs are not
ozone-depleting but have large global warming potentials and are, therefore,
reported to the United Nations Framework Convention on Climate
Change (UNFCCC). Here, we use four independent inverse models to estimate
European emissions of the two HFCs contributing the most to global warming
(HFC-134a and HFC-125) and of SF6 for the year 2011. Using an ensemble
of inverse models offers the possibility to better understand systematic
uncertainties in inversions. All systems relied on the same measurement time
series from Jungfraujoch (Switzerland), Mace Head (Ireland), and Monte Cimone
(Italy) and the same a priori estimates of the emissions, but differed in
terms of the Lagrangian transport model (FLEXPART, NAME), inversion method
(Bayesian, extended Kalman filter), treatment of baseline mole fractions,
spatial gridding, and a priori uncertainties. The model systems were compared
with respect to the ability to reproduce the measurement time series, the
spatial distribution of the posterior emissions, uncertainty reductions, and
total emissions estimated for selected countries. All systems were able to
reproduce the measurement time series very well, with prior correlations
between 0.5 and 0.9 and posterior correlations being higher by 0.05 to 0.1.
For HFC-125, all models estimated higher emissions from Spain + Portugal
than reported to UNFCCC (median higher by 390 %) though with a large
scatter between individual estimates. Estimates for Germany (+140 %) and
Ireland (+850 %) were also considerably higher than UNFCCC, whereas the
estimates for France and the UK were consistent with the national reports. In
contrast to HFC-125, HFC-134a emissions from Spain + Portugal were
broadly consistent with UNFCCC, and emissions from Germany were only 30 %
higher. The data suggest that the UK over-reports its HFC-134a emissions to
UNFCCC, as the model median emission was significantly lower, by 50 %. An
overestimation of both HFC-125 and HFC-134a emissions by about a factor of 2
was also found for a group of eastern European countries (Czech
Republic + Poland + Slovakia), though with less confidence since the
measurement network has a low sensitivity to these countries. Consistent with
UNFCCC, the models identified Germany as the highest national emitter of
SF6 in Europe, and the model median emission was only 1 % lower than
the UNFCCC numbers. In contrast, the model median emissions were 2–3 times
higher than UNFCCC numbers for Italy, France, and Spain + Portugal. The
country-aggregated emissions from the different models often did not overlap
within the range of the analytical uncertainties formally given by the
inversion systems, suggesting that parametric and structural uncertainties
are often dominant in the overall a posteriori uncertainty. The current
European network of three routine monitoring sites for synthetic greenhouse
gases has the potential to identify significant shortcomings in nationally
reported emissions, but a denser network would be needed for more reliable
monitoring of country-wide emissions of these important greenhouse gases
across Europe.
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