# CO, NOx and 13CO2 as tracers for fossil fuel CO2: results from a pilot study in Paris during winter 2010

Morgan Lopez, M. Schmidt, M. Delmotte, Aurélie Colomb, Valérie Gros, C. Janssen, S. J. Lehman, D. Mondelain, O. Perrussel, Michel Ramonet, et al.

► To cite this version:

Morgan Lopez, M. Schmidt, M. Delmotte, Aurélie Colomb, Valérie Gros, et al. CO, NOx and 13CO2 as tracers for fossil fuel CO2: results from a pilot study in Paris during winter 2010. Atmospheric Chemistry and Physics, 2013, 13, pp.7343-7358. 10.5194/ACP-13-7343-2013. hal-00997594

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# CO, NOₓ and ¹³CO₂ as tracers for fossil fuel CO₂: results from a pilot study in Paris during winter 2010

M. Lopez¹, M. Schmidt¹, M. Delmotte¹, A. Colomb²,*, V. Gros¹, C. Janssen³, S. J. Lehman⁴, D. Mondelain³,**, O. Perrussel⁵, M. Ramonet¹, I. Xueref-Remy¹, and P. Bousquet¹

¹Laboratoire des Sciences du Climat et de l'Environnement (LSCE), Unité mixte CEA-CNRS-UVSQ, UMR8212, 91191 Gif-sur-Yvette, France

²Laboratoire Interuniversitaire des Systèmes Atmosphériques (LISA), CNRS-IPSL, 94010 Creteil, France

³Laboratoire de Physique Moléculaire pour l'Atmosphère et l'Astrophysique (LPMAA), CNRS, Université Pierre et Marie Curie, 75005 Paris, France

⁴Institute of Arctic and Alpine Research (INSTAAR), University of Colorado, Boulder, USA

⁵AIRPARIF, Association de Surveillance de la Qualité de l'Air en Ile-de-France, Paris, France

*now at: Laboratoire de Métrologie Physique (LaMP), CNRS, 63171 Aubière, France

**now at: Laboratoire Interdisciplinaire de Physique (LiPhy), CNRS, Université Joseph Fourier, 38402 Saint Martin d'Hères, France

Correspondence to: M. Lopez (morgan.lopez@lsce.ipsl.fr)

Received: 19 December 2012 – Published in Atmos. Chem. Phys. Discuss.: 22 January 2013

Revised: 20 June 2013 – Accepted: 21 June 2013 – Published: 1 August 2013

**Abstract.** Measurements of the mole fraction of the CO₂ and its isotopes were performed in Paris during the MEGAPOLI winter campaign (January–February 2010). Radiocarbon (¹⁴CO₂) measurements were used to identify the relative con- tributions of 77 % CO₂ from fossil fuel consumption (CO₂ff from liquid and gas combustion) and 23 % from biospheric CO₂ (CO₂ from the use of biofuels and from human and plant respiration: CO₂bio). These percentages correspond to aver- age mole fractions of 26.4 ppm and 8.2 ppm for CO₂ff and CO₂bio, respectively. The ¹³CO₂ analysis indicated that gas and liquid fuel contributed 70 % and 30 %, respectively, of the CO₂ emission from fossil fuel use. Continuous measure- ments of CO and NOₓ and the ratios CO/CO₂ff and NOₓ/CO₂ff de- rived from radiocarbon measurements during four days make it possible to estimate the fossil fuel CO₂ contribution over the entire campaign. The ratios CO/CO₂ff and NOₓ/CO₂ff are func- tions of air mass origin and exhibited daily ranges of 7.9 to 14.5 ppb ppm⁻¹ and 1.1 to 4.3 ppb ppm⁻¹, respectively. These ratios are consistent with different emission invento- ries given the uncertainties of the different approaches. By using both tracers to derive the fossil fuel CO₂, we observed similar diurnal cycles with two maxima during rush hour traf- fic.

## 1 Introduction

Worldwide, approximately 20 “megacities” have a popula- tion of more than 10 million inhabitants. According to the United Nations, half of the world’s population now lives in cities, and in the near future, the number of megacities and their population density figures are expected to grow consid- erably. In the context of global warming and in the frame- work of the Kyoto Protocol, it is important to better char- acterise greenhouse gas (GHG) emissions from megacities, which constitute a significant emission source at the global scale. More than 70 % of global fossil fuel CO₂ emissions are concentrated in cities (Duren and Miller, 2012).

With 12 million inhabitants (approximately 18 % of the French population), Paris and its suburbs constitute the largest megacity in Europe. According to the regional French emission inventory provided by AirParif (http://www. airparif.asso.fr/), CO₂ emissions from Paris and its agglom- eration (the Ile-de-France region or IdF) were 50 Mt in 2005, or 13 % of the total French anthropogenic CO₂ emissions, although the IdF region, with a surface area of 12 011 km², composes only 1.8 % of the French territory. The annual CO₂ emission density within the IdF region increases from
approximately 5000 t CO₂ km⁻² limits of the suburbs to ap-
proximately 70 000 t CO₂ km⁻² at the centre of Paris, reflect-
ing the change in population density. Based on the Kyoto
Protocol, France is committed to reducing its greenhouse gas
emissions by 8 % with respect to its 1990 emissions by 2012.
A decrease of 6.0 % was observed in 2010 compared to the
reference year 1990, primarily due to reductions in N₂O and
CO₂ emissions (CITEPA, 2012). In addition, France adopted
the “climate and energy package”, which aims to reduce
greenhouse gas emissions by 20 % with respect to the emis-
sions of 2005 by 2020.

Currently, regional and local GHG emissions data are pri-
marily derived from statistical inventories that are gathered
using a bottom-up method that involves the compilation of
activity and process data. Economic statistics are gathered
from the local to the national level to produce gridded maps
of GHG emissions (EDGAR: Olivier et al., 2001; Olivier
and Berdowsky, 2001). Peylin et al. (2011) showed that
such emission inventories can vary up to 40 % on the na-
tional scale even for developed countries like the Nether-
lands, where we can expect the best datasets available for
use in compiling the inventory. Atmospheric measurements
can provide an alternative to develop methods of emission
verification, in association with bottom-up inventories. At-
mospheric methods (top-down methods) rely on a combi-
nation of high-precision measurements of atmospheric mole
fractions of GHGs such as CO₂ as well as on measurements
of atmospheric tracers and atmospheric transport models. At
global to regional scales, inverse models have been used suc-
cessfully to quantify GHG emissions for CO₂ (Rayner and
Law, 1999; Bousquet et al., 2000; Rödenbeck et al., 2003;
Peylin et al., 2005), CH₄ (Rödenbeck, 2005; Bousquet et al.,
2006) and N₂O (Hirsch et al., 2006; Thompson et al., 2011).
On the local and regional scales, continuous observations
of GHGs can be combined with observations of radon-222,
which is used as a tracer for atmospheric dilution (van der
Laan et al., 2009; Yver et al., 2009; Hammer and Levin,
2009) to estimate surface emissions.

The use of atmospheric measurements of CO₂ to estimate
surface emissions in urban areas is of growing interest. Dur-
ing the last several years, a few projects focusing on quantify-
ing CO₂ fluxes from cities using top-down approaches have
emerged in the USA and in France, including the InFLUX
project in Indianapolis, USA (http://influx.psu.edu/), the Los
Angeles Megacity project (Duren and Miller, 2012) and the
CO₂-Megaparis project in Paris (https://co2-megaparis.isce.
ipsl.fr). One challenging issue associated with the atmo-
spheric top-down approach is the attribution of emissions
to specific processes. The first step in this process is to dis-
tinguish between CO₂ emitted from anthropogenic activities
and CO₂ emitted from biospheric activities. Even in urban
areas, variations in the atmospheric CO₂ mole fraction con-
tain signatures from both fossil fuel combustion and bio-
genic sources. These signatures can be decrypted by addi-
tional information that is provided by specific tracers. Only

¹⁴CO₂ measurements allow for the direct quantification of the contribution of fossil fuel CO₂ to observed CO₂ mole fractions (Levin et al., 2003; Turnbull et al., 2006; Vogel et al., 2010) because CO₂ from fossil fuels does not contain ¹⁴C. Levin and Karstens (2007) showed that fossil fuel emissions and biospheric fluxes are of similar orders of magnitude in Europe. Because precise ¹⁴CO₂ measurements are difficult to perform, carbon monoxide is often used as a tracer for fossil fuel CO₂ emissions (CO₂ff) in order to separate the biospheric and the fossil fuel components from the total measured CO₂ mole fraction. The CO/CO₂ff ratio depends on the condition of combustion and on the fuel type, and can range from 17.5 ppb CO ppm⁻¹ CO₂ for industrial sources and 14.5 ppb CO ppm⁻¹ CO₂ for residential heating to 5.3 ppb CO ppm⁻¹ CO₂ for traffic according to the national emission inventories by the Centre Interprofessionnel Technique d'Etude de la Pollution Atmospherique (CITEPA, http://www.citepa.org/) for the year 2010 in France. From 2000 to 2010, improvements in combustion efficiency due to regulations that are intended to improve air quality led to a significant reduction in CO emissions and also to changes in CO/CO₂ff fossil fuel ratios, which decreased from 20 to 13 ppb CO ppm⁻¹ CO₂ in France. This reduction was primarily caused by the introduction of catalytic converters for cars, which decreased the road traffic CO/CO₂ff ratio from 21 to 5 ppb CO ppm⁻¹ CO₂.

The European project MEGAPOLI (Megacities: Emis-
sions, urban, regional and Global Atmospheric POLlution
and climate effects, and Integrated tools for assessment and
mitigation, http://www.megapoli.info) aims to assess the im-
pact of megacities on air pollution, to quantify the feed-
back regarding megacity air quality and to develop inte-
grated tools for predicting air pollution in megacities. To ad-
dress these three objectives, the MEGAPOLI project organ-
ised two intensive measurement campaigns in Paris: one in
July 2009 and one in January–February 2010. During the
campaigns, numerous atmospheric pollutants and parame-
ters were monitored by different groups (Royer et al., 2011;
Healy et al., 2012; Dolgorouky et al., 2012). The French
Atmospheric Network for Greenhouse Gases Monitoring
(RAMCES), which is part of the Laboratory for Climate and
Environmental Sciences (LSCE), participated in the frame of
the CO₂-Megaparis project to the measurement campaign in
the winter of 2010, which extended from 15 January to 19
February. During this campaign, we focused on continuous
CO₂ and CO measurement in Paris and the Plateau of Saclay
(20 km south-west of Paris, Sect. 2). In addition, air was sam-
pled in flasks for ¹⁴CO₂ analysis (Sects. 2.2.2 and 3.1). Ra-
diocarbon and stable CO₂ isotope measurements were used
to compute the respective contributions of fossil fuels and
biospheric CO₂ to the overall CO₂ mole fraction in Paris
(Sects. 3.2 and 3.3). These direct estimations of CO₂ff were
used to evaluate the potential of alternative proxies to radio-
carbon such as CO and NOₓ (Sect. 3.4).
## 2 Methods

### 2.1 Description of measurement stations

#### 2.1.1 Paris

Paris is the largest city in France; it has 2.2 million inhabitants (source: INSEE, January 2009) and a population density of 21 196 inhabitants per square kilometre, which is one of the highest densities in Europe. Paris and its suburbs include several industrial and transportation hot spots, although numerous industrial activities were removed from the Paris agglomeration in the 1960s. Two sites were instrumented for atmospheric measurements within the city centre during the MEGAPOLI campaign (see Fig. 1). The Laboratoire de l'Hygiène de la Ville de Paris (LHVP), located at 48°50' N, 2°21' E and at 62 m above sea level (a.s.l.), lies within the southern part of Paris (13th district). This laboratory is located on the edge of the Parc de Choisy, approximately 100 m from a main road. A large number of instruments were deployed at the LHVP station to monitor atmospheric compounds such as aerosols, volatile organic compounds (VOCs), ozone, nitrogen oxides ($NO_x = NO + NO_2$) and meteorological parameters. A cavity ring-down spectrometer (CRDS) was installed for continuous atmospheric carbon dioxide ($CO_2$) and carbon monoxide (CO) measurement, and a flask sampling unit was also installed. All inlet lines were positioned on the roof of the LHVP, 15 m above the ground level (a.g.l.).

A second site was equipped for atmospheric measurements at the QualAir station in Jussieu (http://qualair.aero.jussieu.fr/), a campus of University Pierre et Marie Curie, 48°51' N, 2°21' E and 38 m a.s.l., which is located in the city centre of Paris. This station is approximately 2 km from the LHVP. This site was already equipped with several atmospheric monitoring instruments (including those for CO measurement) and was adapted to use larger instruments than those at the LHVP. An automatic flask sampler (Neubert et al., 2004) and a tunable diode laser (TDL) spectrometer, developed and operated by the Laboratory of Molecular Physics for Atmosphere and Astrophysics (LPMAA, Croizé et al., 2010), were installed for continuous $CO_2$ and $\delta^{13}CO_2$ measurements. The two inlet lines were located on the roof of the building, 22 m a.g.l.

We used the meteorological parameters of the QualAir station (wind speed and wind direction) as these figures are higher for this station because wind shielding is less important and measurements at this site are more representative than at the LHVP station. During the campaign, wind directions with approximately equal frequency from all four directions and a mean wind speed of 2.7 m s⁻¹ have been observed.

<figure><img src="image_3.png" /><figcaption>Fig. 1. Location of the different sampling sites.</figcaption></figure>

#### 2.1.2 The Plateau of Saclay

The Plateau of Saclay is a semi-urban flat area that is located approximately 20 km south-west of Paris. The plateau contains atmospheric measurement stations at Gif-sur-Yvette and SIRTA, which are 5 km apart (see Fig. 1). The sites are mainly surrounded by agricultural fields, forests and villages and can be described as suburban.

Gif-sur-Yvette station (Gif station), 48°42' N, 02°09' E and 160 m a.s.l., is part of the LSCE and belongs to the RAMCES team. The closest villages and small towns are Saint-Aubin (673 inhabitants) and Gif-sur-Yvette (21 352 inhabitants), which are located 500 m north-west and 1 km south of the station, respectively (Yver et al., 2009). The station is equipped with a gas chromatograph (GC) system that performs continuous measurements of $CO_2$, $CH_4$, $N_2O$, $SF_6$, CO and $H_2$ (Pépin et al., 2001; Yver et al., 2009; Lopez et al., 2012). The analytical laboratory is also equipped with an isotope ratio mass spectrometer (IRMS) that is dedicated to the atmospheric measurement of $CO_2$ isotopes: $\delta^{13}C$ and $\delta^{18}O$ (WMO-GAW, 2005). The inlet lines are located on the roof of the laboratory building, 7 m a.g.l.

The Instrumental Site of Research by Atmospheric Remote Sensing observatory (SIRTA, Haeffelin et al., 2005), located at 48°43' N, 02°12' E and 156 m a.s.l., in Palaiseau, is approximately 5 km east of Gif-sur-Yvette station. During the winter campaign, $NO_x$ were monitored by the Interuniversity Laboratory of Atmospheric Systems (LISA).

During the 2010 winter campaign, two primary wind regimes were observed: winds from the north (0–45°) that blew 22 % of the time and transported polluted air masses from Paris, and winds from the west (225–270° wind sector) that also blew 22 % of the time. The mean wind speed in both cases was 5.4 m s⁻¹. During the rest of time, the wind regimes were well distributed among the remaining sectors except for the eastern one (45–90°), which was underrepresented (with winds blowing from that direction less than 3 % of time).
### 2.1.3 Trainou station

Trainou station (47°57′N, 02°06′E, 131 m a.s.l.) is a site located 100 km south of Paris (see Fig. 1) that is mainly surrounded by agricultural fields and forests. The nearest city is Orléans, which is 15 km south-west of the site and has 116 000 inhabitants. Trainou can thus be considered a rural site, especially in comparison to the Paris area. Air inlet lines are located at 5, 50, 100 and 180 m a.g.l. on a television tower (TeleDiffusion de France). Continuous GC analysis for CO₂, CH₄, N₂O, SF₆, CO and H₂ mole fractions have been conducted since 2007 (Messager, 2007; Yver et al., 2010; Lopez et al., 2012). The analysed meteorological variables from the data assimilation system of the European Centre for Medium-Range Weather Forecasts (ECMWF) were used for Trainou station. During the campaign, the station experienced approximately the same wind regimes as Gif-sur-Yvette station, with 24 % of the wind coming from the north-north-east (0–45°) and 25 % of the wind from the west-south-west (225–270°). The mean wind speeds were 4.6 m s⁻¹ and 4.3 m s⁻¹ for the two sectors, respectively.

## 2.2 Instrumentation and air sampling strategies

### 2.2.1 In situ analysers

The cavity ring-down spectrometer (G1302 Picarro, Wastine et al., 2009) that was installed at the LHVP analyses CO₂, CO and water vapour (H₂O) mole fractions with a sampling frequency of 1 Hz. This instrument was calibrated for CO₂ and CO before and after the campaign with four calibration tanks based on the WMO-X2007 scale. During the campaign, two high-pressure cylinders were analysed for 30 min every 10 h. One cylinder was used as a working standard to correct for potential temporal drift by the analyser, and the second cylinder was used as a target gas to evaluate repeatability. During the measurement period, a systematic drift in the CO₂ raw data of 0.08 ppm per month was observed, whereas no significant variation in the CO measurements was detected. After drift corrections for the entire campaign, the target gas showed a repeatability level (1 sigma) of 0.03 ppm for the CO₂ measurements and 10.1 ppb for the CO measurements when 1 min averages were used. Because the ambient air was not dried prior to the CRDS analysis, a water vapour correction for CO₂ was used together with a constant correction (−15 ppb) for CO measurements, which was empirically determined during several weeks of testing in our laboratory in Gif-sur-Yvette (Kaiser et al., 2010).

At Jussieu, a tunable diode laser spectrometer has been installed and is operated by the LPMAA to continuously monitor the atmospheric total CO₂ mole fraction and δ¹³C for four consecutive days in February (Croizé et al., 2010). The analysis technique is based on the absorbance correlations between a sealed reference cell and the sample cell. More details regarding the instrumental set-up and calibra-

tion strategy used are provided in Croizé et al. (2010). All of the reference and calibration cylinders used in this instrument were calibrated at the central laboratory of LSCE by GC and IRMS.

The two gas chromatographs (Agilent HP-6890 and HP-6890N) located at Gif-sur-Yvette (suburban site) and Trainou (rural site) were optimised for semi-continuous atmospheric measurements. The GC are equipped with two detectors to simultaneously analyse CO₂ and CH₄ with a flame ionisation detector (FID, Messager, 2007) and N₂O and SF₆ with an electron capture detector (ECD, Lopez et al., 2012). In 2006 at Gif-sur-Yvette and in 2009 at Trainou, two Peak Performers (PP1) were coupled to the GC for additional analysis of CO and H₂ using a reduction gas detector (RGD, Yver et al., 2009). In addition to continuous measurements, the GC at Gif-sur-Yvette has been optimised for flask analysis and tank calibration. All of the GC measurements (continuous, flasks and tanks) were calibrated on the WMO-X2007 scale.

The isotope ratio mass spectrometer (Finnigan MAT 252) located at Gif-sur-Yvette measures the isotopic composition of atmospheric CO₂ (δ¹³C and δ¹⁸O in CO₂) from flasks (Schmidt et al., 2005). An automated sampling line was set-up according to the “BGC-Airtrap” design as described in Werner et al. (2001) to cryogenically separate CO₂ (along with N₂O) from the other air constituents. The “airtrap” is coupled to the IRMS inlet system and used to analyse the air sampled in the flasks. During the campaign, the IRMS was used for semi-continuous analysis of the atmospheric CO₂ isotopes at Gif-sur-Yvette during a 3 day period. Each analysis sequence consisted of injections of an ambient air standard followed by a target gas and up to 10 flasks, with another ambient air standard injected at the end. The carbon dioxide isotopic data are reported in the δ notation (Eq. 1); R is the ratio of the heavy isotope to the light one. The δ¹³C values are referenced to the VPDB scale.

$$ \delta = \left( \frac{R_{\text{sample}}}{R_{\text{standards}}} - 1 \right) \times 1000 \quad (1) $$

In addition to CO₂ and CO, NOₓ have been monitored at the LHVP and SIRTA stations. NOₓ were measured continuously using two chemiluminescent analysers (AC31M, Environment SA) that were operated by the LSCE at the LHVP and by the LISA at SIRTA. A summary of the instrumentation used for this study during the MEGAPOLI campaign is given in Table 1.

### 2.2.2 Flask sampling strategy and radiocarbon measurements

In addition to continuous measurements, flask sampling was carried out at the LHVP and Jussieu stations. At the LHVP, a manual sampler was used to fill 43 pairs of 1 and 2 L glass flasks. Ambient air was dried using a magnesium perchlorate cartridge. We flushed the flasks for 10 min before pressurisation. The flasks were filled in the morning during the traffic
<table><caption>**Table 1.** Technologies, models, locations and accuracy of instruments for the analysed species with the respective measurement dates.</caption><thead><tr><th>Technology</th><th>Model</th><th>Location</th><th>Date</th><th>Species and accuracy</th></tr></thead><tbody><tr><td>CRDS</td><td>Picarro G1302</td><td>LHVP</td><td>15 Jan 2010–19 Feb 2010</td><td>CO₂: 0.03 ppm; CO: 10.0 ppb</td></tr><tr><td>TDL</td><td>SIMCO</td><td>Jussieu</td><td>8 Feb2010–12 Feb 2010</td><td>CO₂: 0.05 ppm; δ<sup>13</sup>C: 0.15‰</td></tr><tr><td>GC (FID/ECD)</td><td>HP-6890</td><td>LSCE Trainou</td><td>15 Jan 2010–19 Feb 2010</td><td>CO₂: 0.05 ppm; CH₄: 1.0 ppb<br>N₂O: 0.3 ppb; SF₆: 0.05 ppt</td></tr><tr><td>GC (RGD)</td><td>Peak Performer</td><td>LSCE Trainou</td><td>15 Jan 2010–19 Feb 2010</td><td>CO: 1.0 ppb; H₂: 2.0 ppb</td></tr><tr><td>Chemiluminescence</td><td>Environment SA AC31M</td><td>LHVP SIRTA</td><td>15 Jan 2010–15 Feb 2010</td><td>NOₓ: 10%</td></tr><tr><td>MS</td><td>Finnigan MAT 252</td><td>LSCE</td><td>flasks</td><td>δ<sup>13</sup>C: 0.02‰; δ<sup>18</sup>O: 0.06‰</td></tr><tr><td>AMS</td><td></td><td>Boulder (USA)</td><td>flasks</td><td>Δ<sup>14</sup>C: 1.4–2.0‰</td></tr></tbody></table>

rush hour on six days in February. At Jussieu, we filled 35 flasks of 2.5 L volume every 2 h for two complete days (9–10 and 14–15 February) and during one night (11–12 February). The samples were dried by passing through a water trap maintained in an ethanol bath at –60 °C as described by Neubert et al. (2004). The flasks are automatically flushed for 2 h before pressurisation. All flasks were analysed using a GC and IRMS to provide additional trace gas information and to independently determine the quality of the continuous CRD (CO₂ and CO) and TDL (CO₂, ¹³C) spectrometer measurements.

We selected 23 flasks (17 from LHVP and 6 sampled at Jussieu) for high-precision ¹⁴CO₂ analysis. Flasks were chosen based on the atmospheric CO₂ mole fraction, and days with large temporal CO₂ gradients were favoured in order to maximise the ¹⁴CO₂ signal with respect to measurement uncertainties (corresponding to ~±1 ppm CO₂ff). Compared to the whole campaign, the selected flasks represent well the typical diurnal gradients. The ¹⁴CO₂ samples were prepared at the University of Colorado, Boulder, and measurements were performed via accelerator mass spectrometry (AMS) at the University of California, Irvine, following Turnbull et al. (2007). The radiocarbon values are expressed in Δ notation (Stuiver and Polach, 1977).

As shown in several studies (Levin et al., 2003; Gamnitzer et al., 2006), the amount of ¹⁴CO₂ in atmospheric samples can be used to derive the contribution of fossil fuel CO₂ to the measured atmospheric CO₂ mole fraction. The measured CO₂ mole fraction (CO₂meas) is assumed to consist of a background CO₂ (CO₂bg), a biospheric component (CO₂bio) and a fossil fuel (CO₂ff) component:

$$CO_2\text{meas} = CO_2\text{bg} + CO_2\text{ff} + CO_2\text{bio}. \quad (2)$$

Each component has a characteristic Δ¹⁴C value. Δ¹⁴Cff is equal to –1000‰ (free of ¹⁴C), while Δ¹⁴Cbg can be measured remotely (or assumed). Δ¹⁴Cbio is equivalent to Δ¹⁴Cbg as Δ¹⁴Cbio includes a correction for mass-dependent fractionation. Equation (3) is then derived as follows:

$$CO_2\text{ff} = CO_2\text{meas} \times \frac{\Delta^{14}\text{Cbg} - \Delta^{14}\text{Cmeas}}{\Delta^{14}\text{Cbg} + 1000}. \quad (3)$$

In Eq. (3), other contributions to the ¹⁴CO₂ budget such as the terrestrial disequilibrium isoflux due to heterotrophic respiration and ¹⁴CO₂ production from nuclear power plants or the reprocessing sector have been neglected. Turnbull et al. (2006) showed that in winter, isoflux corresponds to ~0.2 ppm CO₂ff, which is negligible in comparison with the large CO₂ff signal we observe in Paris (see Sect. 3.2). In France, the main production of ¹⁴CO₂ by the nuclear sector is from La Hague (a nuclear waste treatment plant, located approximately 300 km west of Paris), which emits an amount of ¹⁴C about 100 times higher than the French nuclear power plants. Using a diffusion model, no influence of air masses from La Hague during the four days of flasks sampling have been observed at Paris.

### 2.2.3 Comparison of continuous measurements with flasks sampling

The flask results were compared with the corresponding 2 min averages from the continuous analysers. At LHVP, the
mean difference between 36 pairs of flasks and the CRDS analyser data was −0.03 ± 3.33 ppm for CO₂ and −1.9 ± 31.1 ppb for CO, indicating good agreement in both cases. The comparison between the flasks and the TDL spectrometer for the CO₂ mole fraction and δ¹³C also indicates good agreement, with mean differences between the flasks and in situ measurements of 0.07 ± 2.33 ppm (N = 15) for CO₂ and 0.29 ± 0.20‰ (N = 16) for δ¹³C. The substantial standard deviation is likely related to the strong temporal variability in Paris, which often reaches several ppm for CO₂ and 10 ppb for CO in just a few minutes. The 0.29‰ mean difference observed in the δ¹³C analysis may have been caused by an underestimated correction of the TDL spectrometer measurements. The correction aims to account for the small temperature difference between the atmospheric air and the calibration gas after the atmospheric air has been passed through a cold trap to remove water vapour (Croizé et al., 2010).

The mean mole fraction differences for the CO₂ and CO measurements derived from continuous measurement versus flask sampling are consistent with the WMO-GAW recommendation for background measurements (WMO-GAW, 2009). The objective is to maintain a network intercompatibility level of ±0.1 ppm and ±2 ppb for CO₂ and CO, respectively. The δ¹³C figures do not meet the WMO-GAW recommended maximum difference of ±0.01‰. The substantial difference is due to instrumental accuracy. However, this difference is not likely to impact the conclusions of this study, which shows that large signals are associated with sampling close to sources in a polluted area.

# 3 Results and discussion

## 3.1 The observation of CO₂, CO and NOₓ in Paris, at the Plateau of Saclay and at Trainou station

In the Paris region, CO₂ is mainly emitted by anthropogenic sources through the combustion of fossil fuel and biomass (biofuel and wood), although natural sources such as soil respiration also contribute to a degree that remains highly uncertain. Carbon monoxide is often considered as a reliable combustion tracer. It results from fossil fuel and biomass burning and has an atmospheric lifetime of approximately 2 months (assuming an OH value of 10⁶ molecules cm⁻³, Atkinson et al., 2006). Nitrogen oxides are typical markers of traffic exhaust emissions and have a lifetime of approximately 9 h (Atkinson et al., 2006). However, due to its short lifetime, NOₓ cannot be transported over long distances and consequently can only be used as tracers for local emissions.

Figure 2 presents the hourly mean CO₂, CO and NOₓ mole fractions observed at the LHVP (Paris), at the Plateau of Saclay and at Trainou tower (TR3, 180 m a.g.l. air inlet) from 15 January 2010 to 19 February 2010. The LHVP yielded the highest CO₂, CO and NOₓ values, and the data exhibit the largest synoptic variability because the station is close to an-

<figure><img src="image_4.png" /><figcaption>**Fig. 2.** The CO₂, CO and NOₓ mole fractions at the LHVP, Plateau of Saclay (poS) and Trainou 180 m a.g.l. (TR3). Periods during which the air masses originate from the west are highlighted in blue, and periods during which the air masses originate from the east are highlighted in green. No colour is used for the days without a clear air mass origin.</figcaption></figure>

thropogenic sources. Trainou yielded the lowest values and synoptic variability, which was expected given that we sampled at 180 m a.g.l. and the rural site likely has weaker local CO₂ and CO sources.

The wind regimes were classified based on back trajectories obtained using the Lagrangian particle dispersion model, FLEXPART (version 8.2), which is described by Stohl et al. (2007). In Fig. 2, the blue areas correspond to times when the air masses that influenced the sites originated from the western sector (180 to 360°). We refer to this as the “oceanic regime” using the MEGAPOLI project nomenclature. The green areas correspond to times when air masses came from eastern Europe (0 to 180°) and crossed Germany or Benelux before arriving at the LHVP, the Plateau of Saclay and Trainou station. We refer to this as the “continental regime”. The data collected on days for which air mass back trajectories could not be clearly classified (uncoloured ones) are not considered in the analysis that follows. Figure 3 presents the CO source contributions at LHVP for typical continental (Fig. 3a) and oceanic (Fig. 3b) air masses. Figure 3a and Fig. 3b indicate which grid cells contribute most to our signals. They are also obtained with the FLEXPART model (version 8.2, Stohl et al., 2007) coupled with the EMEP emission inventory (European Monitoring and Evaluation Programme, http://www.emep.int/) for the reference year 2005.

Table 2 summarises the average mole fractions of CO₂, CO and NOₓ for the two different regimes. On average, the three sites show higher CO₂ and CO mole fractions during the continental regime. According to a Student's t test, the average mole fractions for the continental and oceanic regimes are statistically distinct at all three sites. Carbon
<table><caption>**Table 2.** Average of the CO₂, CO and NOₓ mole fractions, with their respective standard deviation, as a function of the air mass origin at the LHVP, Plateau of Saclay and Trainou sites from 15 January to 19 February 2010.</caption><thead><tr><th rowspan="2">Species<br>Regime</th><th colspan="2">CO₂ (ppm)</th><th colspan="2">CO (ppb)</th><th colspan="2">NOₓ (ppb)</th></tr><tr><th>Ocean.</th><th>Cont.</th><th>Ocean.</th><th>Cont.</th><th>Ocean.</th><th>Cont.</th></tr></thead><tbody><tr><td>LHVP</td><td>414.8 ± 13.4</td><td>425.0 ± 14.6</td><td>288 ± 98</td><td>362 ± 116</td><td>39 ± 28</td><td>41 ± 24</td></tr><tr><td>Plateau of Saclay</td><td>401.5 ± 6.9</td><td>417.5 ± 14.3</td><td>201 ± 62</td><td>331 ± 120</td><td>12 ± 13</td><td>13 ± 11</td></tr><tr><td>Trainou</td><td>396.8 ± 4.4</td><td>405.9 ± 6.7</td><td>163 ± 42</td><td>249 ± 64</td><td></td><td></td></tr></tbody></table>

<figure><img src="image_5.png" /><figcaption>**Fig. 3.** Maps showing the typical CO source contributions observed for the continental (a) and oceanic (b) wind regime during the measurement campaign at LHVP.</figcaption></figure>

dioxide and carbon monoxide, with lifetimes of 100 yr and 2 months, respectively, can be transported over longer distances than NOₓ can. Thus, higher CO₂ and CO mole fractions are associated with the continental regime because the air masses are progressively charged with pollutants on their trajectory to Paris. When the main wind direction shifts from east (continental) to west (oceanic), a decrease in CO₂ and CO mole fractions is observed. Nitrogen oxides cannot be transported over long distances; thus, at the LHVP and the Plateau of Saclay, NOₓ mole fractions are similar for the oceanic and continental regimes.

Figure 4 shows the mean diurnal cycles of CO₂, CO and NOₓ at the three stations for both weekdays (in red) and weekends (in black) for the entire measurement period. The mole fractions of trace gases and the mean amplitudes of the diurnal cycles are both smaller at weekends than on weekdays. The mean CO₂, CO and NOₓ diurnal cycles show two peaks at LHVP, in the morning (07:00 to 09:00 UTC) and at the end of the afternoon (18:00 to 20:00 UTC). At the Plateau of Saclay, the afternoon peak is weak and is only visible for CO and NOₓ. The mean diurnal cycle of the traffic flow in the IdF region during weekdays for the year 2010 is presented along with the NOₓ diurnal cycles at the LHVP (Fig. 4). This cycle exhibits the same pattern as the NOₓ, CO₂ and CO diurnal cycle, with maxima in the morning and at the end of the afternoon, which suggests the influence of traffic emissions on NOₓ measurements. Traffic counts, provided by the Directorate of Ile-de-France roads (DiRIF), are recorded for the main roads of the IdF region. The diurnal cycles of CO₂ and CO at Trainou (180 m a.g.l.) present a single peak at noon on weekend and weekdays primarily reflecting the diurnal dynamics in the planetary boundary layer (PBL) as shown by Lopez et al. (2012) for radon-222 and nitrous oxide.

In Fig. 5, the diurnal cycles of CO₂, CO and NOₓ that are recorded at the LHVP are plotted as functions of the air mass origin. The vertical lines are the standard deviation for each hour. As previously explained, the mean concentrations are generally higher when the air masses originate from the east, but the amplitudes of the morning peaks for the three species are similar for the two wind regimes. In contrast, the afternoon peaks in the oceanic wind regimes are more marked for CO₂, CO and NOₓ than are those of the continental regime. In the oceanic wind regime, the LHVP is more
<figure><img src="image_6.png" /></figure>

**Fig. 4.** Mean diurnal cycles of CO₂, CO and NOₓ at the LHVP, Plateau of Saclay and Trainou sites for weekend and weekdays with the associated standard deviations. In the NOₓ plot for the LHVP, the mean diurnal cycle of vehicle flow during the weekdays for the year 2010 in Ile-de-France is added in orange (DiRIF).

sensitive to local pollution, which increases between 16:00 and 18:00 UTC due to the traffic rush hour and the decrease in the PBL height. The signals decrease at the end of traffic rush hour as the atmosphere is refreshed by relatively clean air masses from the west. This second peak is less marked during the continental regime because the atmosphere is subsequently refreshed by the polluted air masses coming from east of Paris.

At the LHVP, non-methane hydrocarbons including benzene and toluene were monitored during the whole campaign using gas chromatography equipped with an ionisation flame detector (see Gros et al., 2011, for more details). Benzene and toluene have lifetimes of approximately 11 and 2 days, respectively (assuming an OH value of $10^6$ molecules cm⁻³, Atkinson et al., 2006), and are typically emitted by the same sources. The toluene to benzene ratio is therefore often used to determine the photochemical age of an air mass: the lower the ratio, the older the air mass (Roberts et al., 1984; Warneke et al., 2007). This ratio may therefore be used to specify whether the observed pollution originated from a local source or was subject to long-range transport. On 4 and 5 February (oceanic regime), the ratio of toluene to benzene was recorded as approximately 5, whereas on 9 and 10 February (continental regime), the ratio decreased to 2. This result indicates that during the oceanic regime, air masses arriving in Paris were primarily affected by local pollution, whereas during the continental regime, long-range pollution sources were an additional factor.

<figure><img src="image_7.png" /></figure>

**Fig. 5.** The CO₂, CO and NOₓ diurnal cycles at the LHVP as a function of the air mass regime. The green curves correspond to the continental regime, whereas the blue curves correspond to the oceanic regime. The error bars represent the standard deviation of the mean.

## 3.2 Calculating the fossil fuel CO₂ contribution using radiocarbon measurements

In this study, Eq. (3) (see Sect. 2.2.2) is applied to the flasks sampled at the LHVP and Jussieu station to quantify the contribution of fossil fuel CO₂ to the ambient air in Paris. The background value of $\Delta^{14}$Cbg is derived from $^{14}$CO₂ measurement at Mace Head (Ireland, 53°19′N, 9°54′W, 25 m a.s.l.), which is considered a background site for Europe. In February 2010, the monthly mean $^{14}$CO₂ and CO₂ values at Mace Head (wind selected for the oceanic sector, Bousquet et al., 1996) were 43.7‰ (I. Levin, personal communication, 2011) and 393.5 ppm, respectively. The analysis of the flasks yielded $\Delta^{14}$Cmeas between -54.04 and +15.59‰ and a resulting CO₂ff contribution of 10.9 to 41.9 ppm relative to the background air at Mace Head.

Figure 6 presents an example of a typical measurement day, 4 February 2010, at the LHVP. The 1 min averaged CO₂ mole fractions obtained via continuous measurement are plotted in orange, and the CO₂ mole fractions obtained from the flask measurements are indicated with red crosses. The background CO₂ mole fraction at Mace Head during the maritime background conditions (Bousquet et al., 1996) for February 2010 is plotted in blue.

Combining the CO₂ and $\Delta^{14}$CO₂ measurements from the individual flask samples permits us to determine the contribution of CO₂ff and CO₂bio to the observed CO₂ mole fraction following Eq. (2): see Fig. 6. Fossil fuel CO₂ increases by 22.7 ppm from 07:15 to 08:15 UTC to reach a maximum of 41.9 ppm. Subsequently, we observe a small decrease until 12:00 UTC followed by a strong decrease (17.0 ppm) to 17.2 ppm at 13:00 UTC. The NOₓ cycle (not shown) follows the same pattern, suggesting that local traffic contributes to
<figure><img src="image_8.png" /><figcaption>**Fig. 6.** A comparison between the continuous measurements for CO₂ (in orange) and the data obtained using flask sampling (red crosses) at the LHVP site are presented for 4 February 2010 on the left axis. We added the background level of CO₂ as measured at Mace Head (Ireland), which is represented by the blue horizontal dashed line. The figures for CO₂ff and CO₂bio, as derived from flask sampling, are represented on the right axis by the black and green curves, respectively. The left and right axes have the same CO₂ amplitude.</figcaption></figure>

the CO₂ff signal in the centre of Paris. The morning CO₂ff increase is due to the morning rush hour, and the subsequent decrease indicates the reduction in traffic as well as the PBL development. The figures for CO₂bio are lower (0–10 ppm) and exhibit less variation than those of CO₂ff. The same diurnal cycles are observed for CO₂ff and CO₂bio for the four sampling days at the LHVP and the single sampling day at Jussieu. Table 3 summarises the daily averages for CO₂ff and CO₂bio for each sampling day. The fossil fuel CO₂ enhancement with respect to the background varies from 16.2 to 32.8 ppm, and the biospheric CO₂ contribution varies from 4.5 to 10.2 ppm. The differences in the CO₂ff and CO₂bio mole fractions at the LHVP and Jussieu sites as they were observed on 10 February are related to the sampling period and location.

The contributions of the two CO₂ sources (fossil fuel and biogenic) to the CO₂meas variability show that the majority of this variability is due to the injection of CO₂ff into the atmosphere. On average, 77 % of the observed signal is caused by CO₂ff (Table 3), mainly from road traffic, heating and the residential sectors. However, despite Paris being a megacity, the biospheric contribution of CO₂ fluxes was significant (23 % on average), even in winter.

This biospheric contribution of approximately 23 % can be attributed not only to net plant and soil respiration but also to the use of biofuel and to human respiration, which cannot be identified using ¹⁴CO₂ measurements because these sources have been fixed or metabolised recently and have isotopic

signatures that are similar to that of the ambient atmosphere. In this paragraph we attribute a percentage to the different biospheric sources in Paris using emission inventories and literature values. According to an AirParif emission inventory, CO₂ emissions from wood burning used for residential heating contribute less than 1 % of the total emissions in Paris and likely do not contribute significantly to the observed CO₂bio enhancement. By 2010, the biofuel ratios in gasoline and diesel increases to approximately 7 % in France, which suggests that road traffic sources contribute significantly to the CO₂bio results. In France, most of the biofuel is produced from rape, wheat and sugar beats (C3 plants), having a δ¹³C signature of approximately –28‰. AirParif estimates that the contribution of CO₂ from traffic is 17 % of the total fossil fuel CO₂ emissions for January 2008 after the emissions associated with biofuel in gasoline and diesel have been removed. According to our mean results for CO₂ff and CO₂bio as presented in Table 3, this contribution corresponds to an average CO₂ff of 5 ppm from traffic. Because gasoline and diesel contain up to 7 % biofuel, the CO₂bio enhancement due to traffic sources is 0.4 ppm, or approximately 12 % of the CO₂bio in Paris during the winter. A study by Turnbull et al. (2011) determined that the use of biofuels contributed up to 1 ppm of the positive CO₂bio signal when gasoline contained approximately 8 % ethanol in California.

A study by Ciais et al. (2007) shows that CO₂ emissions from human respiration in densely populated cities can reach 20 % of fossil fuel CO₂ emissions. Koerner and Klopatek (2002) show that human respiration is 500 kg CO₂ per year per person on average. With a population of 2.2 million in the centre of Paris, human respiration in the centre may be responsible for CO₂ emissions of approximately 1100 kt yr⁻¹. By comparing this value to the reported fossil fuel CO₂ emissions of 7218 kt for the year 2005 in Paris reported by AirParif, human respiration contributes 15 % of the CO₂ff emissions; this percentage is similar to the value reported in Ciais et al. (2007). Human respiration should be responsible for approximately 4 ppm of the CO₂ enhancement, and may therefore account for approximately 50 % of the CO₂bio calculated.

Here we can conclude that the biogenic sources can be attributed to 38 % of the net plant and soil respiration, 50 % to human respiration and 12 % to the use of biofuel. These values are only representative for our sampling sites at the LHVP and Jussieu in February 2010.

## 3.3 Separation of fossil fuel CO₂ sources using δ¹³C measurements

Several studies (Zondervan and Meijer, 1996; Meijer et al., 1996; Djuricin et al., 2010) have used ¹³C/¹²C ratios in combination with ¹⁴C measurements to quantify the fractions of emissions by different fossil fuel sources. Tans (1981) estimated that the release of CO₂ via anthropogenic combustion implies average worldwide δ¹³C emissions for natural
<table><caption>**Table 3.** CO₂ff and CO₂bio emissions with their respective contributions derived at the LHVP and at Jussieu.</caption><thead><tr><th rowspan="2">Site</th><th rowspan="2">No. of flasks</th><th rowspan="2">Date</th><th colspan="2">CO₂ enhancement (ppm)</th><th colspan="2">Respective distribution (%)</th></tr><tr><th>CO₂ff</th><th>CO₂bio</th><th>CO₂ff</th><th>CO₂bio</th></tr></thead><tbody><tr><td>LHVP</td><td>8</td><td>4 Feb 2010</td><td>30.2</td><td>9.7</td><td>76</td><td>24</td></tr><tr><td>LHVP</td><td>3</td><td>5 Feb 2010</td><td>16.2</td><td>4.5</td><td>78</td><td>22</td></tr><tr><td>LHVP</td><td>3</td><td>9 Feb 2010</td><td>26.6</td><td>10.2</td><td>72</td><td>28</td></tr><tr><td>LHVP</td><td>3</td><td>10 Feb 2010</td><td>32.8</td><td>8.6</td><td>79</td><td>21</td></tr><tr><td>Jussieu</td><td>6</td><td>10 Feb 2010</td><td>25.1</td><td>6.9</td><td>78</td><td>22</td></tr></tbody></table>

gas (δ¹³Cgas), liquid (δ¹³Cliq) and solid (δ¹³Csol) fuel of -41.0, -26.5 and -24.1‰, respectively. More recently, Andres et al. (2000) shown that δ¹³C signatures depend on the geographic origin of fossil fuels and can range from -19 to -35‰ for liquids and from -20 to -100‰ for natural gas. A study by Widory and Javoy (2003) determined δ¹³C from the main pollution source in Paris by directly measuring exhaust gases. The authors determined that the mean δ¹³C source ratio for natural gas, liquid fuel and coal is -39.1 ± 1.1, -28.9 ± 0.4 and -24.8 ± 0.4‰, respectively. Based on the atmospheric δ¹³C and CO₂ measurements, we estimate the signatures of the main δ¹³C sources, using a Keeling plot (Keeling, 1958, 1961; Pataki et al., 2003) for the daily observations. Assuming mass conservation and following Eq. (2) (see Sect. 2.2.2), we derive Eq. (4), where CO₂s represents the sum of the CO₂ sources (i.e. CO₂s = CO₂ff + CO₂bio). Combining Eqs. (2) and (4), we obtain Eq. (5). We compute the relationship between δ¹³Cmeas and the inverse mole fraction of the corresponding CO₂ using a least-squares method following Pataki et al. (2003). The intercept corresponds to the mean signature of the source: δ¹³Cs (i.e. the last term of Eq. 5). These values have been corrected for biospheric δ¹³C emission, assuming that δ¹³Cbio = -24.7‰ (Bakwin et al., 1998), resulting in δ¹³Cff.

$$ \delta^{13}\text{Cmeas} \times \text{CO}_2\text{meas} = \delta^{13}\text{Cbg} \times \text{CO}_2\text{bg} + \delta^{13}\text{Cs} \times \text{CO}_2\text{s} \quad (4) $$

$$ \delta^{13}\text{Cmeas} = \frac{\text{CO}_2\text{bg} \times (\delta^{13}\text{Cbg} - \delta^{13}\text{Cs})}{\text{CO}_2\text{meas}} + \delta^{13}\text{Cs} \quad (5) $$

Based on the data from the flasks sampled during the entire measurement period, δ¹³Cff at LHVP and Jussieu was equal to -36.1 ± 2.7‰ and -36.2 ± 1.1‰, respectively, where the errors are given by the uncertainty in the intercept from Eq. (5). According to AirParif, the use of coal in the Paris region accounts for less than 1% of the total anthropogenic CO₂ emission; thus, we will neglect this source. Using the δ¹³Cgas and δ¹³Cliq values measured by Widory and Javoy (2003) and the δ¹³Cff source values from the Keeling plots yielded percentages of 70 ± 6% for natural gas and 30 ± 3% for liquid fuel. The emission inventory for Paris for 2008 that was provided by AirParif (described in Sect. 3.5) estimates

the contribution of natural gas to be 37% of the total CO₂ emissions.

We surmise that the higher ratio of gas consumption derived using the atmospheric method (70 ± 6%) compared to the AirParif emission inventory (37%) likely arose from the spatial separation of automotive and residential sources and the lack of complete mixing prior to the sampling at our sampling location. We conducted our sampling during only a few days in winter, whereas the fraction provided by AirParif takes into account data from the entire year. We expected a higher fraction of gas consumption during the winter due to enhanced heating use.

Pataki et al. (2006) conducted δ¹³CO₂ continuous measurements over Salt Lake City (Utah, USA) during the early winter of 2004–2005. Using the same approach as presented in this section, they found a natural gas contribution between 30 and 40% during morning rush hour and 60 and 70% at pre-dawn. Newman et al. (2008) analysed δ¹³CO₂ in flasks for the years 2002–2003 in Pasadena (Los Angeles Basin, California, USA). They found a Keeling intercept of -29.9 ± 0.2‰, which is less depleted than our value (-36.1 ± 2.7‰). This shows a stronger annual influence of liquid fuel use in the total CO₂ emission in Pasadena, compared with the winter in Paris. Administration of the US Department of Energy indicates that 62% of the state of California’s energy from fossil fuel is from petroleum products and 37% from natural gas.

## 3.4 Constructing a continuous time series of fossil fuel CO₂

Precise ¹⁴CO₂ measurements are difficult to perform and are only possible on discrete samples. Therefore, there are no direct methods of obtaining a continuous record of fossil fuel CO₂. To derive such a record for the entire campaign (defined here as FFCO₂), we used two potential proxies: CO (see Gamnitzer et al., 2006; Levin and Karstens, 2007) and NOₓ. To our knowledge, this is the first time that NOₓ are used as proxy to derive the CO₂ fossil fuel contribution. Both tracers are known to be typical proxies for fossil fuel combustion, but the emission ratios with respect to CO₂ff vary as a function of the combustion source. The daily ratios of each selected proxy of CO₂ff for the four days when we took ¹⁴C
<table><caption>**Table 4.** $\frac{\text{CO}}{\text{CO}_2\text{ff}}(R_{\text{CO}})$ and $\frac{\text{NO}_x}{\text{CO}_2\text{ff}}(R_{\text{NO}_x})$ ratios with their respective coefficients of determination ($r^2$) and the number of points used for each sampled day and the corresponding values used for each regime (3 last lines).</caption><thead><tr><th>Date</th><th>Wind regime</th><th>R<sub>CO</sub></th><th>R<sub>NOx</sub></th><th>No. of points used</th></tr></thead><tbody><tr><td>4 Feb 2010</td><td>oceanic</td><td>11.5 (r<sup>2</sup> = 0.75)</td><td>3.7 (r<sup>2</sup> = 0.89)</td><td>8</td></tr><tr><td>5 Feb 2010</td><td>oceanic</td><td>14.5 (r<sup>2</sup> = 0.90)</td><td>4.3 (r<sup>2</sup> = 0.96)</td><td>3</td></tr><tr><td>9 Feb 2010</td><td>continental</td><td>9.2 (r<sup>2</sup> = 0.97)</td><td>1.1 (r<sup>2</sup> = 0.92)</td><td>3</td></tr><tr><td>10 Feb 2010</td><td>continental</td><td>7.9 (r<sup>2</sup> = 1)</td><td>2.1 (r<sup>2</sup> = 0.91)</td><td>3</td></tr><tr><td></td><td>oceanic regime</td><td>13.0</td><td>4.0</td><td>11</td></tr><tr><td></td><td>continental regime</td><td>8.5</td><td>1.6</td><td>6</td></tr><tr><td></td><td>not clearly defined regime</td><td>10.8</td><td>2.8</td><td></td></tr></tbody></table>

measurements at the LHVP site were used to construct the FFCO₂ curve. To compute the ratios R<sub>CO</sub> and R<sub>NOx</sub>, defined here as $\frac{\text{CO}}{\text{CO}_2\text{ff}} \times 1000$ and $\frac{\text{NO}_x}{\text{CO}_2\text{ff}} \times 1000$, we subtracted the background mole fraction from the ambient measurements. To ensure consistency, we chose to use the background CO mole fraction from the winter 2010 at Mace Head, which was equal to 121 ppb (Derwent et al., 2001, http://agage.eas.gatech.edu/Stations/macehead.htm). For NOx background, we used a value of zero because of its short lifetime (close to 9 h). The CO₂ff terms do not take into account the contribution of CO₂ from biofuel use. To determine the FFCO₂ values, Eqs. (6) and (7) were used.

$$ \text{FFCO}_2(\text{CO}) = \frac{\text{CO}-\text{CObg}}{R_{\text{CO}}} \qquad (6) $$

$$ \text{FFCO}_2(\text{NO}_x) = \frac{\text{NO}_x}{R_{\text{NO}_x}} \qquad (7) $$

The emissions ratios for each of the four days of measurements at the LHVP are presented in Table 4 along with their respective coefficients of determination ($r^2$). We observe that the ratios are functions of the wind regime (Table 4), with higher values on 4 and 5 February (oceanic regime) than on 9 and 10 February (continental regime). An average ratio for each air mass regime is applied to the appropriate segments of the continuous measurements to compute the FFCO₂ for each regime. For the few days without clearly identified air mass origin, we use the mean value from the two synoptic situations (Table 4).

In the upper panel of Fig. 7, we present the two curves inferred from R<sub>CO</sub> and R<sub>NOx</sub>: FFCO₂(CO) and FFCO₂(NOx), respectively. The estimated FFCO₂ is greater during the continental wind regime: up to 80 ppm at three different times. In contrast, during the oceanic regime, the FFCO₂ mole fractions never exceed 40 ppm. At the bottom of Fig. 7, the FFCO₂(CO) and FFCO₂(NOx) mean diurnal cycles are plotted. These plots show the same pattern: a peak during the morning in the rush hour and a second peak at the end of afternoon. The FFCO₂(CO) and FFCO₂(NOx) mean mole fractions are 20.6 and 18.7 ppm, respectively. Differences are

<figure><img src="image_9.png" /><figcaption>**Fig. 7.** Top: time series for FFCO₂ during the MEGAPOLI campaign calibrated using CO and NOx as proxies. The purple rhombuses correspond to the CO₂ff from the flasks sampling. Periods during which the air masses originate from the west are highlighted in blue, and periods during which the air masses originate from the east are highlighted in green. No colour is attributed on the days without a clear air mass origin (see Fig. 2). Bottom: mean diurnal cycles of FFCO₂(CO) in black and FFCO₂(NOx) in red at the LHVP station from 15 January 2010 to 19 February 2010.</figcaption></figure>

observed during the evening and over night (from 17:00 until 06:00 UTC) because of the short lifetime of NOx relative to the lifetime of CO.

A study by Vogel et al. (2010) shows that R<sub>CO</sub> has a diurnal cycle because anthropogenic CO₂ (and CO) fluxes are subject to strong diurnal variation. During the winter, the authors found a peak-to-peak amplitude of 8 ppb ppm⁻¹, with the lowest ratio at 08:00 UTC and the highest at 18:00 UTC. We assume a constant ratio during the day in this study.
<table><caption>**Table 5.** CO₂ contribution estimates by different inventories for the three main emission sectors. From the emission values, we computed the total ratios R<sub>CO</sub> and R<sub>NOx</sub> and also the ratios by sectors.</caption><thead><tr><th rowspan="2"></th><th colspan="3">Emission (%)</th><th colspan="4">R<sub>CO</sub></th><th colspan="4">R<sub>NOx</sub></th></tr><tr><th>Road</th><th>Resid.</th><th>Ind.</th><th>Total</th><th>Road</th><th>Resid.</th><th>Ind.</th><th>Total</th><th>Road</th><th>Resid.</th><th>Ind.</th></tr></thead><tbody><tr><td>CITEPA</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>2005</td><td>31</td><td>24</td><td>24</td><td>16.0</td><td>11.1</td><td>16.5</td><td>18.1</td><td>3.5</td><td>5.9</td><td>1.1</td><td>2.0</td></tr><tr><td>2008</td><td>31</td><td>24</td><td>24</td><td>14.7</td><td>7.4</td><td>15.8</td><td>17.6</td><td>3.1</td><td>5.4</td><td>1.1</td><td>1.8</td></tr><tr><td>2010</td><td>31</td><td>25</td><td>23</td><td>13.4</td><td>5.3</td><td>14.5</td><td>17.5</td><td>2.9</td><td>4.8</td><td>1.1</td><td>1.7</td></tr><tr><td>EDGAR 4.2<br>France (2008)</td><td>32</td><td>24</td><td>27</td><td>8.1</td><td>4.4</td><td>15.1</td><td>0.8</td><td>2.7</td><td>3.5</td><td>1.4</td><td>2.2</td></tr><tr><td>EDGAR 4.2<br>Paris (2008)</td><td>73</td><td>12</td><td>9</td><td>4.3</td><td>5.4</td><td>1.0</td><td>0.9</td><td>3.9</td><td>4.3</td><td>2.0</td><td>4.0</td></tr><tr><td>IER<br>Paris (2005)</td><td>36</td><td>45</td><td>15</td><td>14.6</td><td>12.8</td><td>19.8</td><td>0.4</td><td>3.0</td><td>4.3</td><td>1.2</td><td>3.6</td></tr><tr><td>AirParif<br>Paris (Jan. 2008)</td><td>30</td><td>63</td><td>7</td><td></td><td></td><td></td><td></td><td>2.1</td><td>4.1</td><td>1.2</td><td>1.5</td></tr></tbody></table>

### 3.5 Comparison of R<sub>CO</sub> and R<sub>NOx</sub> ratios with emission inventories

In this section, we compare the R<sub>CO</sub> and R<sub>NOx</sub> emission ratios measured in Paris with those derived from emission inventories. Four different emission inventories are presented with different spatial and temporal resolutions. The reference years for the inventories vary from 2005 to 2010, which makes it difficult to compare the ratios directly. For France as a whole, CITEPA has calculated the GHG emissions on a yearly basis since 1960. In addition, AirParif provides a regional inventory for the IdF with a spatial resolution of 1 km × 1 km. AirParif assessed the CO₂ and NOx emissions with a 1 h time resolution for three typical days (weekdays, Saturdays and Sundays) in January 2008. The Institute for Energy Economics and the Rational Use of Energy (IER, 2005) has provided a European inventory with a resolution of 1 min × 1 min for France for the year 2005. EDGAR 4.2 is a global inventory of GHG emissions and has reported annual values for France since 1970. EDGAR 4.2 also provides a gridded version with a resolution of 0.1° × 0.1° for the reference year 2008 (Olivier et al., 2001; Olivier and Berdowsky, 2001). The spatial resolution of IER and AirParif allowed for us to extract the exact grid cells that corresponded to Paris, whereas for EDGAR 4.2, we chose the grid cell that included most of the Paris area.

The total ratios for each inventory are presented in Table 5 for different reference years and spatial and time resolutions. For France as a whole, CITEPA estimates a higher total R<sub>CO</sub> ratio than does EDGAR 4.2, whereas the total ratios are similar for R<sub>NOx</sub>. For Paris, EDGAR 4.2 shows much lower total R<sub>CO</sub> ratios (4.3) than does the IER inventory (14.6). The R<sub>NOx</sub> ratios vary substantially across the different emission

inventories; they are 3.9 (EDGAR 4.2), 3.0 (IER) and 2.1 (AirParif). These differences are due to discrepancies in the spatial source distribution for Paris and to the different ratios used for the same source sectors in different inventories. These large differences between inventories suggest that more work needs to be done to provide more consistent estimates.

In Table 5, we also summarised the percentage contributions of the three main source sectors (road transport, residential and industry) as well as the R<sub>CO</sub> and R<sub>NOx</sub> ratios for the different sectors for the different inventories. For France as a whole, the R<sub>CO</sub> and R<sub>NOx</sub> ratios stayed fairly constant between 2005 and 2010 except for the road transport ratio. The R<sub>CO</sub> ratio for road transport decreased by a factor of 2 in five years. This decrease is primarily a function of the environmental policy applied to road vehicles since 1970 and is also an effect of the adoption and improvement of catalytic converters for vehicles since 1993, which has reduced NOx and particularly CO emissions.

We compared the ratios determined using our top-down atmospheric approach (Table 4) with the available inventories (Table 5). We focus first on the R<sub>CO</sub> ratio and then on the R<sub>NOx</sub> ratio. During oceanic regimes, our mean R<sub>CO</sub> ratio of 13 is similar to the ratios from IER and CITEPA (Table 5). These high ratios are representative of the residential sector. This result is consistent with the ratio of benzene to toluene that we found in Sect. 3.1, which indicates that our samples are sensitive to local emissions during the oceanic regime. Our R<sub>CO</sub> ratio for the continental regime is 8.5 and lies between the IER and CITEPA estimates and those of EDGAR 4.2. According to the AirParif inventory, the north and north-eastern areas of Paris have relatively significant CO₂ emissions from industrial sources
(approximately 20% of anthropogenic CO₂) compared with southern Paris (less than 5% of anthropogenic CO₂). This result is in agreement with the ratio that we found for the continental regime, which indicates that the contribution of the road transport and industry sectors, which have low R<sub>CO</sub> ratios, are stronger. Moreover, the ratio of benzene to toluene during this regime indicated that long-range transport had occurred, which would have permitted the emissions from Benelux and Germany to have a greater influence. These are industrialised areas that are characterised by relatively low R<sub>CO</sub> ratios relative to those of France (Gamnitzer et al., 2006). We noticed that EDGAR 4.2 found a much lower R<sub>CO</sub> in Paris than did other inventories and that this figure was also much lower than our estimate. This difference is most likely due to the low R<sub>CO</sub> ratio of 1.0 for the residential sector for the Paris grid cell relative to the high value of 15.1 for France.

Because of its short lifetime, the R<sub>NOx</sub> ratio is less sensitive to contributions from different sources. Nevertheless, the ratios we found are within the range of the inventory estimates. During the continental regime, NOx were destroyed during transport over the continent, which leads to lower R<sub>NOx</sub> values. In the oceanic regime, the high ratios reflect the contribution of the road transport sector near the station. The ratios derived with our atmospheric approach for the different regimes agree well with the emission inventories given the uncertainties of the different approaches.

## 4 Conclusions

This pilot study has demonstrated that measurement of CO₂, CO and NOx mole fractions together with isotopic CO₂ measurements can help to better quantify the fossil fuels component in cities. Radiocarbon measurements using flask sampling allowed for us to directly derive the fossil fuel CO₂ mole fraction in Paris, which was approximately 20 ppm (on average), in February 2010. Of the total CO₂ enhancement in Paris during this period, 77% can be attributed to anthropogenic sources (CO₂ff) and 23% to biospheric sources (CO₂bio). Using values from the literature, we estimated that half of these biospheric emissions are due to human respiration and that the other half are due to soil respiration (38%) and the use of biofuel in gasoline and diesel (12%).

Making use of ¹³C measurements, we were able to determine the contributions of natural gas and liquid fuel to anthropogenic CO₂ emissions, which amounted to 70% and 30%, respectively. This estimation was possible in Paris because there are only two sources of fossil fuel emissions; the use of coal can be neglected because it produces less than 1% of the total CO₂ emission. This calculation would be even more powerful if we could reduce the errors generated by the isotopic source signature of natural gas, which varies according to the supply of natural gas (i.e. whether it originates in Siberia or the North Sea). During future campaigns,

it would be helpful to measure the source signature of natural gas from the gas supply network on a regular basis.

Carbon monoxide and nitrogen oxides, which were monitored continuously, were successfully used as proxies to determine the anthropogenic CO₂ emissions over the entire campaign. These proxies have been calibrated against the CO/CO₂ff and NOx/CO₂ff ratios. We determined that the ratios change as a function of the air mass origin. Therefore, it was possible to use different ratios for the proxies depending on the air mass regime. The data for the CO/CO₂ff and NOx/CO₂ff ratios are consistent with the information from the inventories although there are sizeable variations across the inventories themselves. According to these inventories, during the oceanic regime, we are more sensitive to the emissions from the residential sector, where the CO/CO₂ff ratio is high. During the continental regime, that ratio decreases, showing increasing influence of the road transport and industrial sectors.

*Acknowledgements.* We thank the MEGAPOLI project (funded by the European Union's Seventh Framework Programme FP/2007-2011) that allowed us to place our instruments at LHVP during the winter campaign 2010. We used NOx and VOCs data from the MEGAPOLI Database. We thank François Truong, Cyrille Vuillemin and Vincent Bazantay from LSCE/RAMCES for maintaining the instrumentation during the campaign and performing the flask analysis. We thank Ingeborg Levin for providing ¹⁴C measurement at Mace Head as well as Yao Té and Pascal Jeseck for the meteorological data for the Jussieu site. We want to thank Claude Camy-Peyret for his occasional help during the campaign with TDL spectrometer and Laurence Croizé for the instrumental development. We also thank Balendra Thiruchittampalam for the helpful discussions about IER inventory. This work was supported partly by the ANR-CO₂-MegaParis project, GHG-Europe, CNRS and CEA.

Edited by: C. Reeves

<figure><img src="image_10.png" /></figure>

The publication of this article is financed by CNRS-INSU.

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