Estimation of the fossil fuel component in atmospheric CO 2 based on radiocarbon measurements at the Beromünster tall tower, Switzerland

. Fossil fuel CO 2 (CO 2ff ) is the major contributor of anthropogenic CO 2 in the atmosphere, and accurate quan-tiﬁcation is essential to better understand the carbon cycle. Since October 2012


Introduction
Fossil fuel CO 2 (CO 2ff ) is the fundamental contributor to the increase in atmospheric CO 2 ; hence its precise quantification is crucial to better understand the global carbon budget.One of the major uncertainties in the projections of climate change is the uncertainty in the future carbon budget due to feedbacks between terrestrial ecosystems and climate (Heimann and Reichstein, 2008).Information on the response of the biosphere to climate variations can be obtained from atmospheric CO 2 observations, but isolating the biospheric signal in the measured CO 2 mixing ratios requires an accurate quantification of the fossil fuel component.Several T. A. Berhanu et al.: Estimation of the fossil fuel component in atmospheric CO 2 methods have therefore been proposed for quantifying CO 2ff , which are based on observations or models.A widely employed approach is to determine CO 2ff with an atmospheric transport model that incorporates CO 2ff emissions from a bottom-up emission inventory.
Emission inventories are based on statistics of the energy use by different sectors and the quantification of CO 2ff emissions by accounting for the carbon content of each fuel and its corresponding oxidation ratios (Friedlingstein et al., 2010;Le Quéré et al., 2016).When compared to other greenhouse gases, national emission inventories for CO 2 are quite accurate, but the computation of these inventories is laborious, and the quality depends on the energy statistics and reporting methods that vary greatly between countries (Marland, 2008;Marland et al., 2009).A recent study evaluating different energy statistics and cement production data estimated an uncertainty of about 5 % for the global fossil fuel emissions of the past decade (2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015) (Le Quéré et al., 2016).At country level the uncertainties are usually below 5 % in developed countries but often exceed 10 % in developing countries (Ballantyne et al., 2015).
Additional uncertainties arise from the spatial and temporal disaggregation of national annual total emissions to the grid of the atmospheric transport model.At sub-country scales (less than 150 km), the uncertainty from bottom-up estimates can reach up to 50 % (Ciais et al., 2010).Finally, errors in the transport model and the inability to correctly represent point observations in the model may contribute substantially to the uncertainty of model-simulated CO 2ff mixing ratios (Tolk et al., 2008;Peylin et al., 2011).
Radiocarbon measurements can be used to directly quantify CO 2ff in atmospheric CO 2 observations.Radiocarbon is produced in the upper atmosphere during the reaction of neutrons with nitrogen induced by cosmic rays (Currie, 2004).In addition, nuclear bomb tests in the 1960s led to large radiocarbon input into the atmosphere, which thereafter decreased due to gradual uptake by the oceans and the terrestrial biosphere (Manning et al., 1990;Levin et al., 2010).Nowadays, the decline in atmospheric 14 CO 2 is mainly driven by input from 14 C-free fossil fuel CO 2 (Levin et al., 2010).This decline is well detectable at background sites such as Jungfraujoch, Switzerland, and Schauinsland, Germany (Levin et al., 2013).While all reservoirs exchanging carbon with the atmosphere are relatively rich in 14 C, fossil fuels (millions of years old) are devoid of 14 C due to its radioactive decay with a half-life of 5370 years.Hence, any fossil fuel CO 2 emitted to the atmosphere will dilute the background 14 C signal, the so-called Suess effect, which can then be used to unravel recently added fossil fuel CO 2 to the atmosphere (Zondervan and Meijer, 1996;Levin et al., 2003;Gamnitzer et al., 2006;Turnbull et al., 2006Turnbull et al., , 2009Turnbull et al., , 2011aTurnbull et al., , 2014Turnbull et al., , 2015;;Levin and Karstens, 2007;Lopez et al., 2013).However, this depletion can also partially be offset by CO 2 release from the biosphere which has enriched 14 C / 12 C ratios due to nuclear bomb tests in the 1960s. 14C produced by these tests was absorbed by the land biosphere and is now gradually being released back to the atmosphere (Naegler and Levin, 2009).Another contribution could be direct 14 C emissions from nuclear industries (Levin et al., 2010).This technique also enables separation between biospheric and fossil fuel CO 2 components in atmospheric CO 2 observations, and it thus better constrains the biospheric CO 2 fluxes when coupled with inversion models (Basu et al., 2016).The uncertainty in CO 2ff estimated by the radiocarbon method is mainly determined by the precision in the 14 C measurement, the choice of background, and the uncertainty in the contribution from other sources of 14 C such as nuclear power plants (NPPs) (Turnbull et al., 2009).
Despite its importance as a fossil fuel tracer, measurements of 14 C are still sparse.The measurements are expensive and laborious, which so far has prevented frequent sampling and has motivated researchers to combine 14 C measurements with additional tracers such as CO to enhance spatial and temporal coverage (Gamnitzer et al., 2006;Turnbull et al., 2006Turnbull et al., , 2011aTurnbull et al., , 2014Turnbull et al., , 2015;;Levin and Karstens, 2007;Vogel et al., 2010;Lopez et al., 2013).The CO method relies on using high frequency CO measurements and regular calibration of the temporally changing CO : CO 2ff ratios based on weekly or biweekly 14 C measurements.Despite its advantage of providing a proxy for continuous CO 2ff data, the method introduces additional uncertainties due to diurnal and seasonal variability in the CO sink, and the presence of multiple non-fossil CO sources such as oxidation of hydrocarbons or wood and biofuel combustion (Gamnitzer et al., 2006).Spatial variations in the CO : CO 2 ratio across Europe due to different source compositions and environmental regulations, which affect the measured ratios due to changes in air mass origin (Oney et al., 2017), are the main reason for the temporally changing CO : CO 2ff ratio for a given measurement site.Additionally, variability in the CO / CO 2 emission ratios of the sources can contribute to its spatial and temporal variability (Vogel et al., 2010;Turnbull et al., 2015).
In Switzerland, CO 2 contributes about 82 % of the total greenhouse gas emissions according to the Swiss national emission inventory for 2013, and fossil fuel combustion from the energy sector contributes more than 80 % of the total CO 2 emission (FOEN, 2015b).In order to validate such bottomup estimates, independent techniques based on atmospheric measurements are desirable.In addition, as mentioned above, the biospheric CO 2 signals can only be estimated with a good knowledge of CO 2ff .In this study, we present and discuss 14 CO 2 measurements conducted biweekly between 2013 and 2015 at the Beromünster tall tower in Switzerland.From these samples in combination with background CO, CO 2 , and 14 CO 2 measurements at the high-altitude remote location Jungfraujoch, Switzerland, / CO 2ff ratios (R CO ) are derived.These ratios are then combined with the in situ measured CO mixing ratios to estimate a high-resolution time series of atmospheric CO 2ff mixing ratios and, by difference, of the biospheric CO 2 component.The influence of 14 C emissions from nearby NPPs and correction strategies are also discussed.

Site description and continuous measurement of CO and CO 2
A detailed description of the Beromünster tall tower measurement system as well as a characterization of the site with respect to local meteorological conditions, seasonal and diurnal variations of greenhouse gases, and regional representativeness can be obtained from previous publications (Oney et al., 2015;Berhanu et al., 2016;Satar et al., 2016).In brief, the tower is located near the southern border of the Swiss Plateau, the comparatively flat part of Switzerland between the Alps in the south and the Jura Mountains in the northwest (47 • 11 23 N, 8 • 10 32 E, 797 m a.s.l.), which is characterized by intense agriculture and rather high population density (Fig. 1).The tower is 217.5 m tall with access to five sampling heights (12.5, 44.6, 71.5, 131.6, 212.5 m) for measuring CO, CO 2 , CH 4 , and H 2 O using cavity ring-down spectroscopy (CRDS) (Picarro Inc., G-2401).By sequentially switching from the highest to the lowest level, mixing ratios of these trace gases were recorded continuously for 3 min per height, but only the last 60 s was retained for data analysis.The calibration procedure for ambient air includes measurements of reference gases with high and low mixing ratios traceable to international standards (WMO-X2007 for CO 2 and WMO-X2004 for CO and CH 4 ), as well as target gas and more frequent working gas determinations to ensure the quality of the measurement system.From 2 years of data a long-term reproducibility of 2.79 ppb, 0.05 ppm, and 0.29 ppb for CO, CO 2 , and CH 4 , respectively, was determined for this system (Berhanu et al., 2016).

Sampling and CO 2 extraction for isotope analysis
Air samples for 14 CO 2 analysis were collected from the highest inlet usually between 09:00 to 13:00 UTC.At the beginning we collected one sample per month, which was eventually changed to sampling every second week from November 2013 onwards.During each sampling event, three samples were collected over a 15 min interval in 100 L PE-AL-PE bags (TESSERAUX, Germany) from the flush pump exhaust line of the 212.5 m sampling inlet, which has a flow rate of about 9 L min −1 at ambient conditions.The sampling interval was chosen to ensure radiocarbon sample collection in parallel with the continuous CO and CO 2 measurements by the CRDS analyzer at the highest level.Each bag was filled at ambient air pressure for 6 to 8 min, and a total air volume of 50 to 70 L (at STP) was collected.CO 2 extraction was conducted cryogenically in the laboratory at the University of Bern usually the day after the sample collection.During the extraction step, the air sample was first pumped through a stainless-steel water trap (−75 • C), which was filled with glass beads (Raschig rings, 5 mm, Germany).A flow controller (Analyt-MTC, Aalborg, USA) with a flow totalizer tool was attached to this trap to maintain a constant flow of air (1.2 L min −1 ) towards the second trap (trap 2), a spiral-shaped stainless-steel tube (1/4 in.) filled with glass beads (∼ 2 mm) and immersed in liquid nitrogen to freeze out CO 2 .When the flow ceased, trap 2 was isolated from the line and evacuated to remove gases which are non-condensable at this temperature.Then, trap 2 was warmed to room temperature and eventually immersed in slush at −75 • C to freeze out any remaining water.Finally, the extracted CO 2 was expanded and collected in a 50 mL glass flask immersed in liquid nitrogen.
Sample extraction efficiency was calculated by comparing the amount of the cryogenically extracted CO 2 with the CO 2 measured in situ by the CRDS analyzer during the time of sampling.The amount of CO 2 extracted is determined first by transferring the extracted CO 2 cryogenically to a vacuum line of predetermined volume.Then, based on the pressure reading of the expanded gas, and the total volume of air collected determined by the mass flow controller with a totalizer function attached to trap 1, CO 2 mixing ratios were calculated.
At the end of 2014 we noticed that there was a leakage from the sampling line exhaust pumps, which resulted in unrealistically high CO 2 mixing ratios (usually more than 500 ppm).Therefore, we replaced all the exhaust pumps.To further ensure that the leakage problem during sampling is solved, we regularly check for leaks before sampling by closing the needle valves leading to the pumps and monitoring in case there is any flow with the flow meter attached after the pump.Since the replacement we have not observed any indication of leakage.Seven samples which were suspected to be contaminated due to this issue were consequently excluded.The sample extraction efficiency since then has usually been better than 99 %.We also conducted a blank test to check the presence of any leaks or contamination during sample processing but did not observe any of these issues.Five more samples were excluded in 2014 due to a strong mismatch among triplicates in the measured CO 2 after the sample extraction which indicated contamination.
2.3 Measurement of δ 13 C, δ 18 O, and 14 C Prior to radiocarbon measurement, the extracted CO 2 was analyzed for the stable isotopes δ 13 C and δ 18 O using an isotope ratio mass spectrometer (IRMS, Finnigan MAT 250) at the Climate and Environmental Physics Division of the University of Bern, which has an accuracy and precision of better than 0.1 ‰ for both δ 13 C and δ 18 O (Leuenberger et al., 2003). 14C analysis of the extracted CO 2 was performed with an accelerator mass spectrometer (AMS), MICADAS (MIni CArbon DAting System), at the Laboratory for the Analysis of Radiocarbon (LARA) at the Department of Chemistry and Biochemistry of the University of Bern (Szidat et al., 2014).The Automated Graphitization Equipment (AGE) was used to prepare solid target gas (Nemec et al., 2010) from the extracted CO 2 stored in 50 mL glass flasks.A measurement series consisted of up to 15 air samples converted to 30 solid graphite targets (duplicates), together with four and three targets from CO 2 produced by combustion of the NIST standard oxalic acid II (SRM 4990C) and fossil CO 2 (Carbagas, Gümligen), respectively, which were used for the blank subtraction, standard normalization, and correction for isotopic fractionations.For the fractionation correction, δ 13 C values of the AMS were used, which show a long-term standard uncertainty of ±1.2 ‰ (Szidat et al., 2014).The AMS δ 13 C values agree well on average with the corresponding IRMS results, revealing a statistically insignificant difference of −0.2 ± 1.2 ‰ with slightly more depleted AMS results.
During calculation of weighted averages of the duplicates, the uncertainty of the mean is determined with the contributions of the counting statistics and the normalization, whereas the uncertainty of the unaccounted-for long-term variability is considered fully afterwards, as this contribution cannot be reduced by averaging of two measurements performed on the same day.This uncertainty of the weighted average typically amounts to ∼ 1.9 ‰; it is compared with the standard deviation of the duplicates, and the larger of these values is used as the final uncertainty of the duplicates.The mean of the three individual samples from the same day, which is used below in Sect.2.4.1 as 14 C meas , is then determined and associated with the average uncertainty of the three duplicates, as the variability of the three samples is comparable to this average uncertainty for all cases.
As the 14 C / 12 C from Beromünster was measured at the LARA laboratory in Bern, whereas the corresponding background samples from Jungfraujoch were analyzed at the lowlevel counting (LLC) facility of the Institute of Environmental Physics, Heidelberg University, the data sets needed to be adjusted to each other.A recent interlaboratory compatibility test between the LARA lab (code no. 2) and Heidelberg (LLC) estimated a small bias (Hammer et al., 2016).The measurement bias (i.e., the mean difference of the measured 14 C minus the consensus value of the participating laboratories for all investigated CO 2 samples) is +1.8 ± 0.1 and −0.3 ± 0.5 ‰ for Bern and Heidelberg, respectively, from which the bias between both labs of 2.1 ± 0.5 ‰ is determined with a larger measured 14 C for Bern.Consequently, 2.1 ± 0.5 ‰ was subtracted from the 14 C measurements of the Beromünster samples.

The 14 C technique
For the determination of the CO 2ff component we followed approaches similar to those in in previous studies (Zondervan and Meijer, 1996;Levin et al., 2003;Levin and Karstens, 2007;Turnbull et al., 2009).The measured CO 2 is assumed to be composed of three major components: the free troposphere background (CO 2bg ), the regional biospheric component (CO 2bio ) comprising photosynthesis and respiration components, and the fossil fuel component (CO 2ff ): Each of these components has a specific 14 C value (i.e., the deviation in per mill of the 14 C / 12 C ratio from its primary standard, and corrected for fractionation and decay using 13 C measurements) described as 14 C meas , 14 C bg , 14 C bio , and 14 C ff .In analogy to Eq. ( 1), a mass balance approximation equation can also be formulated for 14 C as CO 2meas 14 C meas + 1000 ‰ = CO 2bg 14 C bg Note that non-fossil-fuel components such as biofuels are incorporated into the biospheric component in Eq. ( 1).The fossil fuel term in Eq. ( 2) is zero as fossil fuels are devoid of radiocarbon ( 14 C ff = −1000 ‰).By replacing the biospheric CO 2 component in Eq. ( 1) by a formulation derived from Eq. ( 2), the fossil fuel CO 2 component is derived as Equation ( 3) can be further simplified by assuming that 14 C bio is equal to 14 C bg (Levin et al., 2003) as Hence, the fossil fuel CO 2 component can be determined using the CO 2meas and 14 C meas values measured at the site as well as 14 C bg obtained from the Jungfraujoch mountain background site in the Swiss Alps.However, the CO 2ff determined using Eq. ( 4) incorporates a small bias due to the non-negligible disequilibrium contribution of heterotrophic respiration as well as due to contributions from NPPs.To correct for the bias from these other contributions, an additional term (CO 2other and 14 C other ) can be included in Eq. (4) as suggested by Turnbull et al. (2009): where CO 2other and 14 C other represent the additional CO 2 and radiocarbon contributions from other sources such as NPPS and biospheric fluxes, respectively.
The contributions from heterotrophic respiration will lead to an underestimation of CO 2ff on average by 0.2 ppm in winter and 0.5 ppm in summer, estimated for the Northern Hemisphere using a mean terrestrial carbon residence time of 10 years (Turnbull et al., 2006).
To account for the bias from heterotrophic respiration, a harmonic function varying seasonally between these values was added to the derived CO 2ff values.However, variation of respiration fluxes on shorter timescales cannot be accounted for by this simple correction.The correction strategy for the contribution from NPPs is described in Sect.2.4.2 below.

Simulation of 14 CO 2 from nuclear power plants
Radiocarbon is produced by nuclear reactions in NPPs and primarily emitted in the form of 14 CO 2 (Yim and Caron, 2006), except for pressurized water reactors (PWRs), which release 14 C mainly in the form of 14 CH 4 .Previous studies have shown that such emissions can lead to large-scale gradients in atmospheric 14 C activity and offset the depletion from fossil fuel emissions (Graven and Gruber, 2011).In Heidelberg, Germany, an offset of 25 and 10 % of the fossil fuel signal was observed during summer and winter, respectively, due to emissions from a nearby plant (Levin et al., 2003).Similarly, Vogel et al. (2013) determined the influence of NPPs for a measurement site in Canada and estimated that about 56 % of the total CO 2ff component was masked by the contribution from NPPs, though this large number was obtained for a site in close vicinity of the CANadian Deutrium Uranium-type reactor (CANDU), known for producing particularly high 14 C emissions.In Switzerland, there are five NPPs, and the closest plant is located about 30 km to the northwest of Beromünster (Fig. 1).Furthermore, air masses arriving at Beromünster are frequently advected from France, which is the largest producer of nuclear power in Europe.
To estimate the influence of Swiss and other European NPPs on 14 C at Beromünster, we used FLEXPART-COSMO backward Lagrangian particle dispersion simulations (Henne et al., 2016).FLEXPART-COSMO was driven by hourly operational analyses of the non-hydrostatic numerical weather prediction model COSMO provided by the Swiss weather service MeteoSwiss at approximately 7 × 7 km 2 resolution for a domain covering large parts of western Europe from the southern tip of Spain to the northern tip of Denmark and from the west coast of Ireland to eastern Poland.For each 3 h measurement interval during the 3-year period, a source sensitivity map (footprint) was calculated by tracing the paths of 50 000 particles released from Beromünster at 212 m above ground over 4 days backward in time.The source sensitivities were then multiplied with the 14 CO 2 emissions of all NPPs within the model domain.Thereby, the emission of a given NPP was distributed over the area of the model grid cell containing the NPP.Source sensitivities were calculated for three different vertical layers (0-50, 50-200, 200-500 m).Since the height of ventilation chimneys of the T. A. Berhanu et al.: Estimation of the fossil fuel component in atmospheric CO 2 Swiss NPPs is between 99 and 120 m, only the sensitivity of the middle layer was selected here as it corresponds best to the effective release height.
The release of 14 C both in inorganic (CO 2 ) and organic form (CH 4 ) is routinely measured at all Swiss NPPs.Annual totals of 14 C emissions are published in the annual reports of the Swiss Federal Nuclear Safety Inspectorate ENSI (https://www.ensi.ch/de/dokumente/document-category/strahlenschutzberichte/).The corresponding data have been kindly provided by the Swiss Federal Nuclear Safety Inspectorate ENSI and the Berner Kraftwerke (BKW), operating the NPP Mühleberg at temporal resolutions ranging from annual (Benznau 1 & 2) to monthly (Leibstadt, Gösgen) and biweekly (Mühleberg), and we assumed constant emissions over the corresponding periods.For Beznau 1, the emissions of 2015 were distributed over the first 3 months of the year due to the shutdown of the plant in March 2015.The largest sources of 14 CO 2 in Switzerland are the two boiling water reactors Mühleberg and Leibstadt (Loosli and Oeschger, 1989).Beznau 1 and 2 and Gösgen are PWRs emitting about 1 order of magnitude less 14 CO 2 .For NPPs outside Switzerland, the emissions were estimated from energy production data reported to the International Atomic Energy Agency (IAEA) and NPP type-specific emission factors following Graven and Gruber (2011).The difference δ 14 C nucBRM in 14 C between the nuclear emission signals at Beromünster ( 14 C nucBRM ) and at Jungfraujcoh ( 14 C nucJFJ ) was then computed following Eq.( 4) in Levin et al. (2010) and assuming that the mole fraction (n 14 ) of 14 C due to NPPs at Jungfraujoch is negligible compared to Beromünster.We then obtain 14 with the dimensionless factor f = 8.19 × 10 14 and n 14 npp /n CO 2 meas being the number of 14 C atoms due to NPPs simulated with FLEXPART-COSMO relative to the total number of C atoms ( 12 C + 13 C + 14 C) (which is equal to the total number of CO 2 molecules) measured at Beromünster.

Calculation of R CO , CO / CO 2 , and high-resolution CO 2ff
A CO / CO 2ff ratio (R CO ) was calculated as the slope of the geometric mean regression (model II), with CO being the CO enhancement over a background measured at Jungfraujoch, and the CO 2ff values as determined above.The CO measurements at Jungfraujoch were conducted using a CRDS analyzer (Picarro Inc., G-2401) with a measurement precision of ±2.5 ppb for 1 min aggregates (Zellweger et al., 2012).
As CO is usually co-emitted with CO 2 during incomplete combustion of fossil and other fuels, we have also computed a tracer ratio designated as CO / CO 2 from the enhancements in the in situ measured CO and CO 2 mixing ratios over the Jungfraujoch background (Oney et al., 2017).CO 2bg and CO bg values were obtained by applying the robust extraction of baseline signal (REBS) statistical method (Ruckstuhl et al., 2012) to the continuous CO 2 and CO measurements at the high-altitude site Jungfraujoch (Schibig et al., 2016) with a bandwidth of 60 days.Note that, while R CO strictly refers to the ratio of CO to fossil fuel CO 2 emissions, the CO / CO 2 ratio can be influenced by biospheric contribution as well as CO 2 emissions from non-fossil sources such as biofuels and biomass burning.
In order to construct the high-resolution CO 2ff time series, we combined the in situ measured CO enhancements at the Beromünster tower with the radiocarbon-derived ratios R CO and estimated CO CO 2ff for the 3-year data set as where CO obs is the hourly averaged CO measurements at the tower.
3 Results and discussions 3.1 14 CO 2 and CO 2ff Figure 2a shows the in situ measured hourly mean CO 2 dryair mole fractions at Beromünster (black) from the 212.5 m sample inlet matching at hours when air samples were collected for radiocarbon analysis and the corresponding background CO 2 at Jungfraujoch (blue).During the measurement period, we recorded CO 2 mixing ratios between 389 and 417 ppm.Spikes of CO 2 were observed mainly during winter, associated with weak vertical mixing and enhanced anthropogenic emissions, while lower CO 2 mixing ratios were recorded during summer due to strong vertical mixing and photosynthetic uptake.Isotopic analysis of the air samples yielded 14 C meas between −12.3 and +22.8 ‰, with no clear seasonal trend, after correction for the model-simulated contribution from NPPs (Fig. 2b).Based on the simulations described in Sect.2.4.2, we have calculated a mean enhancement in 14 C of +1.6 ‰ and a maximum of +8.4 ‰ due to NPPs.This agrees qualitatively with the coarse-resolution simulations of Graven and Gruber (2011), which suggest a mean enhancement of +1.4 to +2.8 ‰ over this region (Graven and Gruber, 2011).While about 70 % of this contribution is due to Swiss NPPs, the remaining contribution is of foreign origin.About 75 % of the contribution from the Swiss NPPs is due to Mühleberg, which is located west of Beromünster and hence frequently upstream of the site, due to the prevailing westerly winds (Oney et al., 2015).Note that each data point represents a mean value of the triplicate samples collected consecutively with a standard error of 2 ‰ among triplicates.During this period, the background 14 C values measured at Jungfraujoch varied between 15 and 28 ‰.Regional depletions in 14 C due to fossil fuel emissions, i.e., Figure 2. CO 2 mixing ratios (hourly averages) at Beromünster (black) from the sample inlet at 212.5 m and from background measurements at Jungfraujoch (blue) filtered using the REBS function for periods when 14 C sampling was conducted (a), 14 C determined from the biweekly point samplings at the site before (green) and after (red) correction for the intercomparison offset (see Sect. 2.3) and the 14 C contribution from NPPs (see Eq. 5) and from 14-day integrated samplings at Jungfraujoch (blue) (b), CO 2ff determined during this period applying Eq. ( 4) with a mean CO 2ff value of 4.3 ppm (dashed line) (c), the biospheric CO 2 determined by simple subtraction of CO 2bg and CO 2ff from the CO 2meas (d), and the temperature record during this period at the 212.differences between Beromünster and the clean-air reference site Jungfraujoch, were in the range of −0.7 to −29.9 ‰ with a mean value of −9.9 ‰.
Figure 2c shows the corresponding CO 2ff determined after correcting for radiocarbon emissions from NPPs.The typical uncertainty in CO 2ff is 1.2 ppm calculated by quadratically combining a mean 14 C measurement uncertainty of 2.0 ‰ in both the sample and the background values, 0.3 ‰ from biospheric correction, 0.5 ‰ from interlaboratory offset, and a mean uncertainty of 1.2 ‰ in the estimation of 14 C contribution from NPPs.A mean fossil fuel CO 2 contribution of 4.3 ppm was calculated from these samples.Few cases, notably the sample from 27 March 2014, showed a higher CO 2ff and a strong depletion in 14 C meas , consistent with the high CO 2 mixing ratio shown in the top panel.This could be due to a strong local fossil fuel contribution or a polluted air mass transported from other regions of Europe coinciding with the grab samplings.As this event occurred during a period with moderate temperatures (mean tempera-ture of 6.8 • C measured at the highest level of the Beromünster tower between March and May), strong fossil fuel CO 2 emissions due to heating are not expected.The FLEXPART-COSMO transport simulations for this event suggest an air mass origin from southeastern Europe (see Supplement).Periods with winds from the east, colloquially known as Bise, are well known to be associated with very stable boundary layers and correspondingly strong accumulation of air pollutants during the cold months of the year between autumn and spring.Air masses reaching Beromünster from eastern Europe have recently been reported to contain unusually high levels of CO during late winter and early spring periods, coinciding with this sampling period (Oney et al., 2017).
By subtracting the background and fossil fuel CO 2 contributions from the measured mixing ratios, CO 2bio values were also determined, ranging between +11.2 and −12.4 ppm (Fig. 2d).Even if there is no clear seasonal trend, the lowest CO 2bio values were recorded during summer, implying net photosynthetic CO 2 uptake, while most of the values in Table 1.Ratios (R CO ) determined using radiocarbon measurements after correcting for influence from NPPs and applying model II regression, and ratios derived from continuous CO and CO 2 measurements by the CRDS analyzer as enhancements ( CO : CO 2 ) using Jungfraujoch background measurements.R CO values are given in mmol mol −1 with standard uncertainties of the slope and r 2 values in brackets, and n represents the number of samples for the radiocarbon method.Note that, according to the Swiss emission inventory report for greenhouse gas emissions in 2013, the annual anthropogenic CO / CO 2 emission ratio for the national estimate is 7.8 mmol mol −1 .
Winter (Dec-Feb) 12.5 ± 3.3 (0.6) 8 (0.9) Summer (Jun-Aug) 14.1 ± 4.0 (0.3) 14 13.4 (0.02)All data 13.4 ± 1.3 (0.6) 45 8.3 (0.5) winter are positive or close to zero due to respiration.During summer 2015, we observed strong variability in both CO 2 and CO 2bio (Fig. 2a and d).However, this period was one of the hottest and driest summers in central Europe (Orth et al., 2016).In Switzerland, it was the second-hottest summer since the beginning of measurements in 1864 with most of the extreme dates in July (MeteoSuisse, 2015).Such climate extremes can lead to enhanced respiration and reduced photosynthesis and, in turn, higher CO 2 and CO 2bio in the atmosphere.Looking specifically at the two data points in June and July 2015, the daily average temperatures recorded at Beromünster were 24.6 and 26 • C at the highest inlet of 212.5 m (Fig. 2e).Based on measurements at Beromünster and other cities of the CarboCount CH network in 2013, Oney et al. (2017) reported that for a daily mean temperature of greater than 20 • C the biosphere over the Swiss plateau tends to become a net CO 2 source.The observed positive spikes in CO 2 (Fig. 2a) and CO 2bio (Fig. 2d) likely resulted from such extremes.

R CO values from radiocarbon measurements
From the simultaneous CO and radiocarbon measurements, we calculated an R CO of 13.4 ± 1.3 mmol CO/mol CO 2 with a correlation coefficient (r 2 ) of 0.7 and a median value of 11.2 mmol CO/mol CO 2 (note that change in R CO is insignificant when we use smoothed 14 C background from Jungfraujoch).When we split the data seasonally, R CO values of 12.5 ± 3.3 and 14.1 ± 4.0 mmol CO/mol CO 2 were obtained during winter and summer, respectively (Table 1).Even if the two values are not significantly different considering the uncertainties, the very low correlation coefficient during summer (r 2 = 0.3) implies a larger uncertainty in the derived R CO .Our wintertime estimate is well within the range of values from previous studies (10-15 mmol mol −1 ) observed at other sites in Europe and North America (Gamnitzer et al., 2006;Vogel et al., 2010;Turnbull et al., 2011a).To test the sensitivity of this ratio to the selection of background site, we additionally calculated R CO using background values estimated with the REBS method from the in situ CO measurements at Beromünster instead of Jungfraujoch.The value obtained in this way (12.7 ± 1.2, r 2 = 0.6) is not sig-nificantly different from the value obtained using Jungfraujoch as the background site.Considering the persistent decrease in CO emissions (Zellweger et al., 2009) in response to the European emission legislation, our estimated R CO is surprisingly high.A recent study investigating the CO / CO 2 ratio from road traffic in Islisberg tunnel, Switzerland, also observed a significant decrease in this ratio compared to previous estimates, pointing to a substantial reduction in CO emissions from road traffic, with a CO / CO 2 ratio of 4.15 ± 0.34 ppb ppm −1 (Popa et al., 2014).This may indicate a significant contribution from non-road traffic emissions, which account for more than 70 % of the total CO 2 emissions leading to the high apparent R CO .
The R CO value derived in this study is significantly higher than the anthropogenic CO / CO 2 emission ratio of 7.8 mmol mol −1 calculated from Switzerland's greenhouse gas inventory report for 2013 (FOEN, 2015b, a).However, this can be due to enhanced CO emissions transported from other European cities towards Beromünster.Oney et al. (2017) observed particularly large CO / CO 2 ratios at Beromünster during several pollution events in late winter and early spring 2013 which were associated with air mass transport from eastern Europe, where poorly controlled combustion of biofuels and coal likely results in high ratios.

CO / CO 2 from continuous measurements
Figure 3 shows the seasonally resolved correlations of CO with CO 2 derived from in situ measured CO and CO 2 enhancements over the background observed at Jungfraujoch, for which we estimated a tracer ratio of 8.3 ± 0.1 mmol mol −1 (r 2 = 0.5) for the entire measurement period.Considering the seasonally resolved CO / CO 2 ratios, barely any correlation is observed in summer, and weak correlations (r 2 < 0.4) are observed during spring and autumn.This can be due to the dominance of biogenic fluxes over fossil fuel fluxes during these periods of the year.From measurements during winter, when the two species are most strongly correlated, a CO / CO 2 ratio of 7.3 ± 0.1 mmol mol −1 (r 2 = 0.9) is obtained.Recently, Oney et al. ( 2017) reported a higher wintertime ratio of 8.3 mmol mol −1 for the same combination of measurements at Beromünster and Jungfraujoch but for a different time period.If we consider only winter 2013 as in their data, we obtain essentially the same value, while much lower ratios of 6.5 and 6.4 mmol mol −1 were calculated for 2014 and 2015, respectively.The higher ratios in winter 2013 are likely related to the unusually cold conditions and extended periods of air mass transport from eastern Europe.Note that, in contrast to R CO , these enhancement ratios also include emissions from non-fossil sources such as biofuels and biomass burning as well as the influence of biogenic fluxes.The Swiss national inventory attributes about 15 % of total CO 2 emissions in 2014 to non-fossil-fuel sources (FOEN, 2015b).If we correct for these sources assuming a constant contribution throughout the year, the wintertime CO / CO 2 ratio for the 3-year data becomes 8.7 mmol mol −1 .
This ratio of 8.7 mmol mol −1 is still about 30 % lower than the R CO estimate for the same period of 12.5 mmol mol −1 , shown as a black line in Fig. 3.This suggests that despite the strong correlation between CO and CO 2 in winter the regional CO 2 enhancements are not only caused by anthropogenic emissions but include a significant contribution from biospheric respiration.Miller et al. (2012) showed that such strong correlations between CO 2 and CO during winter may arise from respiratory fluxes co-located with fossil fuel fluxes trapped under the wintertime shallow and stable boundary layer but with strongly biased ratios when compared to R CO .Turnbull et al. (2011b) also observed a substantial contribution of biospheric CO 2 fluxes even during winter (20-30 % from non-fossil-fuel sources including photosynthesis and respiration) from samples collected at two sites in East Asia.The magnitude of these fluxes was roughly similar to the CO 2ff flux when continental background was used (Turnbull et al., 2015).Hence, the observed correlation between CO and CO 2 in this study is not only due to spatially and temporally correlated sources but is caused to a large extent by meteorological variability associated with more or less accumulation of trace gases in the boundary layer irrespective of their sources.This interpretation is also supported by the fact that a strong correlation (r 2 > 0.7) was also observed between CO and CH 4 during winter at the same tower site (Satar et al., 2016) despite their sources being vastly distinct.In Switzerland about 80 % of CH 4 emissions are from agriculture (mainly from ruminants), while more than 85 % of CO emissions are from the transport sector and residential heating (FOEN, 2015a).

High-resolution time series of CO 2ff and CO 2bio
Figure 4 shows the hourly mean CO mixing ratios at Jungfraujoch and Beromünster between 2013 and 2015.CO mixing ratios as high as 480 ppb were recorded at Beromünster, while generally lower CO values were recorded at the more remote site Jungfraujoch.A pronounced seasonality in CO can be observed at Beromünster with higher values in winter and lower values during summer due to stronger vertical mixing and chemical depletion of CO by OH (Satar et al., 2016).The hourly mean CO 2ff time series calculated using these continuous CO measurements and the seasonally resolved R CO values derived using the radiocarbon measurements are displayed in Fig. 4c.A seasonal trend in the calculated CO 2ff is observed with frequent spikes of CO 2ff during winter, while summer values show less variability.We calculated a monthly mean amplitude (peak to trough) of 6.3 ppm with a maximum in February and a minimum in July.During the measurement period, we observed CO 2ff mixing ratios ranging up to 27 ppm coinciding with cold periods and likely from enhanced anthropogenic emissions due to heating.Instances of slightly negative CO 2ff contributions, which occurred during less than 5 % of the time, were associated with negative enhancements in CO (i.e., CO < 0).This could be simply due to an overestimation of background values by the REBS function during these periods.
Figure 5a shows the hourly averaged residual CO 2bio values, which exhibit not only a clear seasonal cycle but also a considerable scatter in all seasons, ranging from −13 to +30 ppm.During winter, most values were close to zero or positive, implying a dominance of respiration fluxes.In summer, conversely, pronounced negative and positive excursions were observed mostly due to the diurnal cycle in net CO 2 fluxes, which are dominated by photosynthetic uptake during daytime and respiration at night.Another factor contributing to such variations may be the application of a constant emission ratio neglecting any diurnal variability (Vogel et al., 2010).
It should also be noted that any non-fossil-fuel CO 2 sources such as emissions from biofuels would be incorporated into the CO 2bio term since CO 2ff in Eq. (1) represents the fossil fuel sources only, adding more variability to the data set.In order to reduce the influence of these diurnal factors, we have looked into afternoon CO 2bio values (12:00-15:00 UTC), when the CO 2 mixing ratios along the tower are uniform (Satar et al., 2016) and R CO variability is minimal.Similar to the seasonal pattern in Fig. 5a, a clear seasonal cycle in biospheric CO 2 can be observed (Fig. 5b) in agreement with biospheric exchange, but both positive and negative extremes are less frequently observed (−12 to +22 ppm).
The variation in CO 2bio during afternoon (12:00-15:00 UTC) was recently estimated at this site at a range of −20 to +20 ppm by combining observations and model simulations for the year 2013 (Oney et al., 2017).Our estimates are more positive than those in their study, due to the higher R CO which results in lower CO 2ff and correspondingly higher CO 2bio values.
Biospheric CO 2 shows a seasonally dependent diurnal variation as shown in Fig. 6.During winter (December-February), the biospheric CO 2 component remains consistently positive (+2 to +5 ppm) throughout the day, implying net respiration fluxes.In summer, a clear feature with increasing CO 2bio values during the night peaking between 07:00 and 08:00 UTC (i.e., between 08:00 and 09:00 local time) can be observed.This buildup during the night can be explained by CO 2 from respiration fluxes accumulating in the stable and shallow nocturnal boundary layer.Then, after sunrise, the early morning CO 2bio peak starts to gradually decrease due to a combination of onset of photosynthesis and enhanced vertical mixing due to the growth of the boundary layer.At Beromünster, a decrease in CO 2 mixing ratios from both processes is visible more or less at the same time at the 212.5 m height level.As reported by Satar et al. (2016), this decrease in early morning CO 2 concentrations at the 212 m inlet lags behind the decrease at the lowest sampling level of 12.5 m by approximately 1 h.Between 12:00 and 15:00 UTC, when the daytime convective bound-  ary layer is fully established, the biospheric CO 2 continues to become more negative, implying net photosynthetic uptake, which eventually stabilizes for 3-5 h until nighttime CO 2bio accumulation starts.

Conclusions
From continuous measurements of CO and CO 2 and biweekly radiocarbon samples at the Beromünster tall tower, we have estimated a CO / CO 2ff ratio (R CO ) which was subsequently used to construct a 2.3-year-long highresolution CO 2ff time series.We have corrected the ratio for an offset of about 16 % caused by 14 C emissions from nearby NPPs.This bias was calculated by comparing the simulated mean enhancement in 14 C (1.6 ‰) due to NPPs with the measured mean depletion in 14 C due to fossil fuel CO 2 (9.9 ‰).The radiocarbon-based R CO derived in this study during winter is about 30 % higher than the CO:CO 2 enhancement ratios estimated from continuous CO and CO 2 measurements during the same period, suggesting a significant biospheric contribution to regional CO 2 enhancements during this period.This is in agreement with previous studies that observed 20-30 % biospheric contribution during winter (Turnbull et al., 2011b).
The obtained CO 2ff time series shows a clear seasonality with frequent spikes during winter associated with enhanced anthropogenic emissions and weak vertical mixing, while summer values are mostly stable.
By subtracting the estimated CO 2ff and CO 2bg from CO 2meas , we have also calculated the biospheric CO 2 component, which ranges between −15 and +30 ppm.Considering only afternoon data (12:00-15:00 UTC), when the convective boundary layer is fully established, CO 2bio showed its minimum in summer coinciding with net photosynthetic uptake but still with frequent positive excursions, especially during summer 2015, possibly driven by the record hot and dry summer during this period.During winter, CO 2bio becomes nearly zero or positive, implying respiration fluxes.
A pronounced diurnal variation in CO 2bio was observed during summer modulated by vertical mixing and biospheric exchange, while this variation disappears during winter.However, the variation in CO 2bio may also be influenced by the uncertainty of the CO 2ff estimate, especially due to applying a constant emission ratio while calculating CO 2ff .Hence, it will be important in the future to include seasonally and diurnally resolved R CO values from high-frequency radiocarbon measurements to better estimate CO 2ff .Detailed analysis of the planetary boundary layer height may also provide useful information to better clarify such variations, and it will be the focus of future studies.Additionally, including independent tracers such as atmospheric potential oxygen estimates based on concurrent CO 2 and O 2 measurements will be very useful to validate fossil fuel emission estimates from the radiocarbon method.This technique is also advantageous as the fossil fuel CO 2 estimate is unaltered by contribution from NPPs, and it accounts for the contribution from biofuels.The Supplement related to this article is available online at https://doi.org/10.5194/acp-17-10753-2017supplement.

Figure 1 .
Figure 1.The geographical map of Beromünster and Jungfraujoch measurement sites (blue) as well as the five NPPs in Switzerland (red).
Figure2.CO 2 mixing ratios (hourly averages) at Beromünster (black) from the sample inlet at 212.5 m and from background measurements at Jungfraujoch (blue) filtered using the REBS function for periods when 14 C sampling was conducted (a), 14 C determined from the biweekly point samplings at the site before (green) and after (red) correction for the intercomparison offset (see Sect. 2.3) and the 14 C contribution from NPPs (see Eq. 5) and from 14-day integrated samplings at Jungfraujoch (blue) (b), CO 2ff determined during this period applying Eq. (4) with a mean CO 2ff value of 4.3 ppm (dashed line) (c), the biospheric CO 2 determined by simple subtraction of CO 2bg and CO 2ff from the CO 2meas (d), and the temperature record during this period at the 212.5 m height level (e).Error bars in panels (b) and (c) indicate the mean uncertainty in 14 C measurement (±2.0 ‰) and calculated CO 2ff (±1.2 ppm), averaged for the triplicate samples, while error bars in panel (d) are obtained from error propagation of the components in panels (a), (b), and (c).CO 2 mixing ratios in the top panel are only shown from times matching the radiocarbon sampling at Beromünster tower.

Figure 3 .
Figure 3.The correlation between enhancements in CO and CO 2 at Beromünster over Jungfraujoch background for the different seasons.The black dots and the black solid line correspond to the individual wintertime R CO values and the linear fit to these points, respectively.

Figure 4 .
Figure 4. Time series of hourly mean CO mixing ratios measured at Jungfraujoch (a) and Beromünster (b) sites, with the red curve showing the estimated background values using the REBS method with 60-day window.Panel (c) shows the hourly mean CO 2ff time series calculated using the emission ratios determined from radiocarbon measurements, and the CO enhancements at Beromünster over the Jungfraujoch background based on Eq. (7).The blue dots in panel (c) shows the CO 2ff values determined using the radiocarbon measurements.

Figure 5 .
Figure5.Time series (hourly resolution) of the biospheric CO 2 derived as a residual of the difference between the total CO 2 , CO 2bg , and CO 2ff for all data (a), and only afternoon data from 12:00-15:00 UTC (b).The green lines show negative CO 2bio , implying uptake, while red ones represent positive CO 2bio .The average uncertainty of CO 2bio amounts ±1.3 ppm calculated from error propagation.

Figure 6 .
Figure 6.Hourly variations of monthly averaged biospheric CO 2 during summer (June-August) and winter (December-February).While winter values dominated by respiration are constant throughout a day, summer values show a significant diurnal variation induced by photosynthesis and vertical mixing.The error bars are the standard deviations of the hourly averaged CO 2bio values for each month.