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| Titel |
Modeling The Anthropogenic CO2 Footprint in Europe Using a High Resolution Atmospheric Model |
| VerfasserIn |
Yu Liu, Nicolas Gruber, Dominik Brunner |
| Konferenz |
EGU General Assembly 2015
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 17 (2015) |
| Datensatznummer |
250110218
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| Publikation (Nr.) |
 EGU/EGU2015-10195.pdf |
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| Zusammenfassung |
| The localized nature of most fossil fuel emission sources leaves a distinct footprint on
atmospheric CO2 concentrations, yet to date, most studies have used relatively coarse
atmospheric transport models to simulate this footprint, causing an excess amount of spatial
smoothing. In addition, most studies have considered only monthly variations in
emissions, neglecting their substantial diurnal and weekly fluctuations. With the
fossil fuel emission fluxes dominating the carbon balance in Europe and many
other industrialized countries, it is paramount to simulate the fossil fuel footprint in
atmospheric CO2 accurately in time and space in order to discern the footprint
of the terrestrial biosphere. Furthermore, a good understanding of the fossil fuel
footprint also provides the opportunity to monitor and verify any change in fossil fuel
emission.
We use here a high resolution (7 km) atmospheric model setup for central Europe based
on the operational weather forecast model COSMO and simulate the atmospheric CO2
concentrations separately for 5 fossil fuel emission sectors (i.e., power generation, heating,
transport, industrial processes, and rest), and for 10 different country-based regions. The
emissions were based on high-resolution emission inventory data (EDGAR(10km) and
MeteoTest(500m)), to which we have added detailed time functions for each process and
country. The total anthropogenic CO2 footprint compares well with observational
estimates based on radiocarbon (C14) and CO for a number of sites across Europe,
providing confidence in the emission inventory and atmospheric transport. Despite
relatively rapid atmospheric mixing, the fossil fuel footprint shows strong annual mean
structures reflecting the point-source nature of most emissions. Among all the processes,
the emissions from power plants dominates the fossil fuel footprint, followed by
industry, while traffic emissions are less distinct, largely owing to their spatially more
distributed nature. However, on shorter time-scales, atmospheric transport leads to strong
plume-like patterns, causing a high degree of variability on the mesoscale and up to
synoptic scales. This variability is enhanced through the temporal variability of the
emissions. The time-variations in the emissions also cause an annual mean reduction
in the near surface atmospheric CO2 concentration of several ppm relative to a
simulation with time-invariant emissions, owing to a diurnal "rectification" effect with
atmospheric transport and mixing. Finally, we also conducted a few ensitivity analyses to
check how well regional reductions of fossil fuel emissions can be detected by
various atmospheric CO2 observing systems, including satellites. Our results suggest
that the fine-scale spatiotemporal pattern of the fossil fuel footprint offer specific
opportunities for detection beyond the changes in annual mean atmospheric CO2. |
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