Abstract
Abstract. Radiocarbon dioxide (14CO2, reported in Δ14CO2) can be used to determine the fossil fuel CO2 addition to the atmosphere, since fossil fuel CO2 no longer contains any 14C. After the release of CO2 at the source, atmospheric transport causes dilution of strong local signals into the background and detectable gradients of Δ14CO2 only remain in areas with high fossil fuel emissions. This fossil fuel signal can moreover be partially masked by the enriching effect that anthropogenic emissions of 14CO2 from the nuclear industry have on the atmospheric Δ14CO2 signature. In this paper, we investigate the regional gradients in 14CO2 over the European continent and quantify the effect of the emissions from nuclear industry. We simulate the emissions and transport of fossil fuel CO2 and nuclear 14CO2 for Western Europe using the Weather Research and Forecast model (WRF-Chem) for a period covering 6 summer months in 2008. We evaluate the expected CO2 gradients and the resulting Δ14CO2 in simulated integrated air samples over this period, as well as in simulated plant samples. We find that the average gradients of fossil fuel CO2 in the lower 1200 m of the atmosphere are close to 15 ppm at a 12 km × 12 km horizontal resolution. The nuclear influence on Δ14CO2 signatures varies considerably over the domain and for large areas in France and the UK it can range from 20 to more than 500% of the influence of fossil fuel emissions. Our simulations suggest that the resulting gradients in Δ14CO2 are well captured in plant samples, but due to their time-varying uptake of CO2, their signature can be different with over 3‰ from the atmospheric samples in some regions. We conclude that the framework presented will be well-suited for the interpretation of actual air and plant 14CO2 samples.
Highlights
The magnitude of anthropogenic fossil fuel CO2 emissions is relatively well known on the global scale (Raupach et al, 2007; Friedlingstein et al, 2010) as bottom-up inventories constrain the sum of all emissions to within 6–10 % uncertainty (Marland and Rotty, 1984; Turnbull et al, 2006; Marland, 2008)
In a recent publication (Bozhinova et al, 2013), we showed that the interpretation of growing season integrated plant samples requires simulation of location and weather dependent photosynthetic uptake and plant development patterns
The simulated net CO2 flux (NEE) compares well to observations with a rootmean squared deviation (RMSD) of 0.26 mg CO2 m−1 s−1 and correlation coefficient (r) for the entire period of 0.70, which is even higher in clear days
Summary
The magnitude of anthropogenic fossil fuel CO2 emissions is relatively well known on the global scale (Raupach et al, 2007; Friedlingstein et al, 2010) as bottom-up inventories constrain the sum of all emissions to within 6–10 % uncertainty (Marland and Rotty, 1984; Turnbull et al, 2006; Marland, 2008). There is a challenge to aggregate available bottom-up information on the level of individual roads, or power plants, or industrial complexes to a larger scale consistently In between these two lies an important opportunity for atmospheric monitoring, as it can independently verify the reported emission magnitudes at the intermediate scales, uniquely constrained by the integrating capacity of atmospheric transport. 10 % of all emissions in our domain come from only 30 grid cells and more than half of these are located in densely populated cities or urban conglomerations This might provide an opportunity for a better fossil fuel estimate of the highest emitting regions in Europe even when only selected locations are visited in a plant sampling campaign.
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