Journal cover Journal topic
Atmospheric Chemistry and Physics An interactive open-access journal of the European Geosciences Union
Atmos. Chem. Phys., 17, 10753-10766, 2017
https://doi.org/10.5194/acp-17-10753-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Research article
13 Sep 2017
Estimation of the fossil fuel component in atmospheric CO2 based on radiocarbon measurements at the Beromünster tall tower, Switzerland
Tesfaye A. Berhanu1, Sönke Szidat2, Dominik Brunner3, Ece Satar1, Rüdiger Schanda1, Peter Nyfeler1, Michael Battaglia2, Martin Steinbacher3, Samuel Hammer4, and Markus Leuenberger1 1Climate and Environmental Physics, Physics Institute and Oeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland
2Department of Chemistry and Biochemistry and Oeschger Center for Climate Change Research, University of Bern, Bern, Switzerland
3Empa, Laboratory for Air Pollution/Environmental Technology, Dübendorf, Switzerland
4Institut für Umweltphysik, Universität Heidelberg, Heidelberg, Germany
Abstract. Fossil fuel CO2 (CO2ff) is the major contributor of anthropogenic CO2 in the atmosphere, and accurate quantification is essential to better understand the carbon cycle. Since October 2012, we have been continuously measuring the mixing ratios of CO, CO2, CH4, and H2O at five different heights at the Beromünster tall tower, Switzerland. Air samples for radiocarbon (Δ14CO2) analysis have also been collected from the highest sampling inlet (212.5 m) of the tower on a biweekly basis. A correction was applied for 14CO2 emissions from nearby nuclear power plants (NPPs), which have been simulated with the Lagrangian transport model FLEXPART-COSMO. The 14CO2 emissions from NPPs offset the depletion in 14C by fossil fuel emissions, resulting in an underestimation of the fossil fuel component in atmospheric CO2 by about 16 %. An average observed ratio (RCO) of 13.4 ± 1.3 mmol mol−1 was calculated from the enhancements in CO mixing ratios relative to the clean-air reference site Jungfraujoch (ΔCO) and the radiocarbon-based fossil fuel CO2 mole fractions. The wintertime RCO estimate of 12.5 ± 3.3 is about 30 % higher than the wintertime ratio between in situ measured CO and CO2 enhancements at Beromünster over the Jungfraujoch background (8.7 mmol mol−1) corrected for non-fossil contributions due to strong biospheric contribution despite the strong correlation between ΔCO and ΔCO2 in winter. By combining the ratio derived using the radiocarbon measurements and the in situ measured CO mixing ratios, a high-resolution time series of CO2ff was calculated exhibiting a clear seasonality driven by seasonal variability in emissions and vertical mixing. By subtracting the fossil fuel component and the large-scale background, we have determined the regional biospheric CO2 component that is characterized by seasonal variations ranging between −15 and +30 ppm. A pronounced diurnal variation was observed during summer modulated by biospheric exchange and vertical mixing, while no consistent pattern was found during winter.

Citation: Berhanu, T. A., Szidat, S., Brunner, D., Satar, E., Schanda, R., Nyfeler, P., Battaglia, M., Steinbacher, M., Hammer, S., and Leuenberger, M.: Estimation of the fossil fuel component in atmospheric CO2 based on radiocarbon measurements at the Beromünster tall tower, Switzerland, Atmos. Chem. Phys., 17, 10753-10766, https://doi.org/10.5194/acp-17-10753-2017, 2017.
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Short summary
Fossil fuel CO2 is the major contributor of anthropogenic CO2 in the atmosphere, and accurate quantification is essential to better understand the carbon cycle. Such accurate quantification can be conducted based on radiocarbon measurements. In this study, we present radiocarbon measurements from a tall tower site in Switzerland. From these measurements, we have observed seasonally varying fossil fuel CO2 contributions and a biospheric CO2 component that varies diurnally and seasonally.
Fossil fuel CO2 is the major contributor of anthropogenic CO2 in the atmosphere, and accurate...
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