The ability of a Bayesian atmospheric inversion to quantify the Paris region's fossil fuel CO₂ emissions on a monthly basis, based on a network of three surface stations operated for 1 year as part of the CO₂-MEGAPARIS experiment (August 2010–July 2011), is analysed. Differences in hourly CO₂ atmospheric mole fractions between the near-ground monitoring sites (CO₂ gradients), located at the north-eastern and south-western edges of the urban area, are used to estimate the 6 h mean fossil fuel CO₂ emission. The inversion relies on the CHIMERE transport model run at 2 km × 2 km horizontal resolution, on the spatial distribution of fossil fuel CO₂ emissions in 2008 from a local inventory established at 1 km × 1 km horizontal resolution by the AIRPARIF air quality agency, and on the spatial distribution of the biogenic CO₂ fluxes from the C-TESSEL land surface model. It corrects a prior estimate of the 6 h mean budgets of the fossil fuel CO₂ emissions given by the AIRPARIF 2008 inventory. We found that a stringent selection of CO₂ gradients is necessary for reliable inversion results, due to large modelling uncertainties. In particular, the most robust data selection analysed in this study uses only mid-afternoon gradients if wind speeds are larger than 3 m s⁻¹ and if the modelled wind at the upwind site is within ±15° of the transect between downwind and upwind sites. This stringent data selection removes 92 % of the hourly observations. Even though this leaves few remaining data to constrain the emissions, the inversion system diagnoses that their assimilation significantly reduces the uncertainty in monthly emissions: by 9 % in November 2010 to 50 % in October 2010. The inverted monthly mean emissions correlate well with independent monthly mean air temperature. Furthermore, the inverted annual mean emission is consistent with the independent revision of the AIRPARIF inventory for the year 2010, which better corresponds to the measurement period than the 2008 inventory. Several tests of the inversion's sensitivity to prior emission estimates, to the assumed spatial distribution of the emissions, and to the atmospheric transport modelling demonstrate the robustness of the measurement constraint on inverted fossil fuel CO₂ emissions. The results, however, show significant sensitivity to the description of the emissions' spatial distribution in the inversion system, demonstrating the need to rely on high-resolution local inventories such as that from AIRPARIF. Although the inversion constrains emissions through the assimilation of CO₂ gradients, the results are hampered by the improperly modelled influence of remote CO₂ fluxes when air masses originate from urbanised and industrialised areas north-east of Paris. The drastic data selection used in this study limits the ability to continuously monitor Paris fossil fuel CO₂ emissions: the inversion results for specific months such as September or November 2010 are poorly constrained by too few CO₂ measurements. The high sensitivity of the inverted emissions to the prior emissions' diurnal variations highlights the limitations induced by assimilating data only during the afternoon. Furthermore, even though the inversion improves the seasonal variation and the annual budget of the city's emissions, the assimilation of data during a limited number of suitable days does not necessarily yield robust estimates for individual months. These limitations could be overcome through a refinement of the data processing for a wider data selection, and through the expansion of the observation network.

To develop an accurate measurement network of greenhouse gases, instruments in the field need to be stable and precise and thus require infrequent calibrations and a low consumption of consumables. For about 10 years, cavity ring-down spectroscopy (CRDS) analyzers have been available that meet these stringent requirements for precision and stability. Here, we present the results of tests of CRDS instruments in the laboratory (47 instruments) and in the field (15 instruments). The precision and stability of the measurements are studied. We demonstrate that, thanks to rigorous testing, newer models generally perform better than older models, especially in terms of reproducibility between instruments. In the field, we see the importance of individual diagnostics during the installation phase, and we show the value of calibration and target gases that assess the quality of the data. Finally, we formulate recommendations for use of these analyzers in the field.

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 contributions 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 average 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 measurements of CO and NO_x and the ratios CO/CO₂ff and NO_x/CO₂ff derived 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 NO_x/CO₂ff are functions 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 inventories 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 traffic.

Cities currently covering only a very small portion ( < 3 %) of the world's land surface directly release to the atmosphere about 44 % of global energy-related CO₂, but they are associated with 71–76 % of CO₂ emissions from global final energy use. Although many cities have set voluntary climate plans, their CO₂ emissions are not evaluated by the monitoring, reporting, and verification (MRV) procedures that play a key role for market- or policy-based mitigation actions. Here we analyze the potential of a monitoring tool that could support the development of such procedures at the city scale. It is based on an atmospheric inversion method that exploits inventory data and continuous atmospheric CO₂ concentration measurements from a network of stations within and around cities to estimate city CO₂ emissions. This monitoring tool is configured for the quantification of the total and sectoral CO₂ emissions in the Paris metropolitan area (∼ 12 million inhabitants and 11.4 TgC emitted in 2010) during the month of January 2011. Its performances are evaluated in terms of uncertainty reduction based on observing system simulation experiments (OSSEs). They are analyzed as a function of the number of sampling sites (measuring at 25 m a.g.l.) and as a function of the network design. The instruments presently used to measure CO₂ concentrations at research stations are expensive (typically ∼ EUR 50 k per sensor), which has limited the few current pilot city networks to around 10 sites. Larger theoretical networks are studied here to assess the potential benefit of hypothetical operational lower-cost sensors. The setup of our inversion system is based on a number of diagnostics and assumptions from previous city-scale inversion experiences with real data. We find that, given our assumptions underlying the configuration of the OSSEs, with 10 stations only the uncertainty for the total city CO₂ emission during 1 month is significantly reduced by the inversion by ∼ 42 %. It can be further reduced by extending the network, e.g., from 10 to 70 stations, which is promising for MRV applications in the Paris metropolitan area. With 70 stations, the uncertainties in the inverted emissions are reduced significantly over those obtained using 10 stations: by 32 % for commercial and residential buildings, by 33 % for road transport, by 18 % for the production of energy by power plants, and by 31 % for total emissions. These results indicate that such a high number of stations would be likely required for the monitoring of sectoral emissions in Paris using this observation–model framework. They demonstrate some high potential that atmospheric inversions can contribute to the monitoring and/or the verification of city CO₂ emissions (baseline) and CO₂ emission reductions (commitments) and the advantage that could be brought by the current developments of lower-cost medium precision (LCMP) sensors.

Measurements of CO2, CO, NOx and selected Volatile Organic Compounds (VOCs) mole fractions were performed continuously during a 10-day period in the Guy Môquet tunnel in Thiais, a peri-urban area about 15 km south of the centre of Paris, between 28 September and 8 October 2012. This data set is used here to identify the characteristics of traffic-emitted CO2 by evaluating its ratios to co-emitted species for the first time in the Paris region. High coefficients of determination (r2 > 0.7) are observed between CO2 and certain compounds that are characteristic of the traffic source (CO, NOx, benzene, xylenes and acetylene). Weak correlations (r2 < 0.2) are found with species such as propane, n-butane and i-butane that are associated with fuel evaporation, an insignificant source for CO2. To better characterise the traffic signal we focus only on species that are well-correlated with CO2 and on rush-hour periods characterised by the highest traffic-related mole fractions. From those mole fractions we remove the nighttime-average weekday mole fraction obtained for each species that we infer to be the most appropriate background signal for our study. Then we calculate observed Δspecies / ΔCO2 ratios, which we compare with the ones provided by the 2010 bottom–up high-resolved regional emission inventory from Airparif (the association in charge of monitoring the air quality in Île-de-France), focusing on local emission data for the specific road of the tunnel. We find an excellent agreement (2%) between the local inventory emission CO / CO2 ratio and our observed ΔCO / ΔCO2 ratio. Former tunnel experiments carried out elsewhere in the world provided observed ΔCO / ΔCO2 ratios that differ from 49 to 592% to ours. This variability can be related to technological improvement of vehicles, differences in driving conditions, and fleet composition. We also find a satisfactory agreement with the Airparif inventory for n-propylbenzene, n-pentane and xylenes to CO2 ratios. For most of the other species, the ratios obtained from the local emission inventory overestimate the observed ratios to CO2 by 34 to more than 300%. However, the emission ratios of NOx, o-xylene and i-pentane are underestimated by 30 to 79%. One main cause of such high differences between the inventory and our observations is likely the obsolete feature of the VOCs speciation matrix of the inventory that has not been updated since 1998, although law regulations on some VOCs have occurred since that time. Our study bears important consequences, discussed in the conclusion, for the characterisation of the urban CO2 plume and for atmospheric inverse modelling of urban CO2 emissions.

Most of the global fossil fuel CO₂ emissions arise from urbanized and industrialized areas. Bottom-up inventories quantify them but with large uncertainties. In 2010–2011, the first atmospheric in situ CO₂ measurement network for Paris, the capital of France, began operating with the aim of monitoring the regional atmospheric impact of the emissions coming from this megacity. Five stations sampled air along a northeast–southwest axis that corresponds to the direction of the dominant winds. Two stations are classified as rural (Traînou – TRN; Montgé-en-Goële – MON), two are peri-urban (Gonesse – GON; Gif-sur-Yvette – GIF) and one is urban (EIF, located on top of the Eiffel Tower). In this study, we analyze the diurnal, synoptic and seasonal variability of the in situ CO₂ measurements over nearly 1 year (8 August 2010–13 July 2011). We compare these datasets with remote CO₂ measurements made at Mace Head (MHD) on the Atlantic coast of Ireland and support our analysis with atmospheric boundary layer height (ABLH) observations made in the center of Paris and with both modeled and observed meteorological fields. The average hourly CO₂ diurnal cycles observed at the regional stations are mostly driven by the CO₂ biospheric cycle, the ABLH cycle and the proximity to urban CO₂ emissions. Differences of several µmol mol⁻¹ (ppm) can be observed from one regional site to the other. The more the site is surrounded by urban sources (mostly residential and commercial heating, and traffic), the more the CO₂ concentration is elevated, as is the associated variability which reflects the variability of the urban sources. Furthermore, two sites with inlets high above ground level (EIF and TRN) show a phase shift of the CO₂ diurnal cycle of a few hours compared to lower sites due to a strong coupling with the boundary layer diurnal cycle. As a consequence, the existence of a CO₂ vertical gradient above Paris can be inferred, whose amplitude depends on the time of the day and on the season, ranging from a few tenths of ppm during daytime to several ppm during nighttime. The CO₂ seasonal cycle inferred from monthly means at our regional sites is driven by the biospheric and anthropogenic CO₂ flux seasonal cycles, the ABLH seasonal cycle and also synoptic variations. Enhancements of several ppm are observed at peri-urban stations compared to rural ones, mostly from the influence of urban emissions that are in the footprint of the peri-urban station. The seasonal cycle observed at the urban station (EIF) is specific and very sensitive to the ABLH cycle. At both the diurnal and the seasonal scales, noticeable differences of several ppm are observed between the measurements made at regional rural stations and the remote measurements made at MHD, that are shown not to define background concentrations appropriately for quantifying the regional ( ∼ 100 km) atmospheric impact of urban CO₂ emissions. For wind speeds less than 3 m s⁻¹, the accumulation of local CO₂ emissions in the urban atmosphere forms a dome of several tens of ppm at the peri-urban stations, mostly under the influence of relatively local emissions including those from the Charles de Gaulle (CDG) Airport facility and from aircraft in flight. When wind speed increases, ventilation transforms the CO₂ dome into a plume. Higher CO₂ background concentrations of several ppm are advected from the remote Benelux–Ruhr and London regions, impacting concentrations at the five stations of the network even at wind speeds higher than 9 m s⁻¹. For wind speeds ranging between 3 and 8 m s⁻¹, the impact of Paris emissions can be detected in the peri-urban stations when they are downwind of the city, while the rural stations often seem disconnected from the city emission plume. As a conclusion, our study highlights a high sensitivity of the stations to wind speed and direction, to their distance from the city, but also to the ABLH cycle depending on their elevation. We learn some lessons regarding the design of an urban CO₂ network: (1) careful attention should be paid to properly setting regional (∼ 100 km) background sites that will be representative of the different wind sectors; (2) the downwind stations should be positioned as symmetrically as possible in relation to the city center, at the peri-urban/rural border; (3) the stations should be installed at ventilated sites (away from strong local sources) and the air inlet set up above the building or biospheric canopy layer, whichever is the highest; and (4) high-resolution wind information should be available with the CO₂ measurements.