Atmospheric concentration measurements are used to adjust the daily to monthly budget of fossil fuel CO₂ emissions of the Paris urban area from the prior estimates established by the Airparif local air quality agency. Five atmospheric monitoring sites are available, including one at the top of the Eiffel Tower. The atmospheric inversion is based on a Bayesian approach, and relies on an atmospheric transport model with a spatial resolution of 2 km with boundary conditions from a global coarse grid transport model. The inversion adjusts prior knowledge about the anthropogenic and biogenic CO₂ fluxes from the Airparif inventory and an ecosystem model, respectively, with corrections at a temporal resolution of 6 h, while keeping the spatial distribution from the emission inventory. These corrections are based on assumptions regarding the temporal autocorrelation of prior emissions uncertainties within the daily cycle, and from day to day. The comparison of the measurements against the atmospheric transport simulation driven by the a priori CO₂ surface fluxes shows significant differences upwind of the Paris urban area, which suggests a large and uncertain contribution from distant sources and sinks to the CO₂ concentration variability. This contribution advocates that the inversion should aim at minimising model–data misfits in upwind–downwind gradients rather than misfits in mole fractions at individual sites. Another conclusion of the direct model–measurement comparison is that the CO₂ variability at the top of the Eiffel Tower is large and poorly represented by the model for most wind speeds and directions. The model's inability to reproduce the CO₂ variability at the heart of the city makes such measurements ill-suited for the inversion. This and the need to constrain the budgets for the whole city suggests the assimilation of upwind–downwind mole fraction gradients between sites at the edge of the urban area only. The inversion significantly improves the agreement between measured and modelled concentration gradients. Realistic emissions are retrieved for two 30-day periods and suggest a significant overestimate by the AirParif inventory. Similar inversions over longer periods are necessary for a proper evaluation of the optimised CO₂ emissions against independent data.

We present inverse modelling (top down) estimates of European methane (CH₄) emissions for 2006–2012 based on a new quality-controlled and harmonised in situ data set from 18 European atmospheric monitoring stations. We applied an ensemble of seven inverse models and performed four inversion experiments, investigating the impact of different sets of stations and the use of a priori information on emissions. The inverse models infer total CH₄ emissions of 26.8 (20.2–29.7) Tg CH₄ yr⁻¹ (mean, 10th and 90th percentiles from all inversions) for the EU-28 for 2006–2012 from the four inversion experiments. For comparison, total anthropogenic CH₄ emissions reported to UNFCCC (bottom up, based on statistical data and emissions factors) amount to only 21.3 Tg CH₄ yr⁻¹ (2006) to 18.8 Tg CH₄ yr⁻¹ (2012). A potential explanation for the higher range of top-down estimates compared to bottom-up inventories could be the contribution from natural sources, such as peatlands, wetlands, and wet soils. Based on seven different wetland inventories from the Wetland and Wetland CH₄ Inter-comparison of Models Project (WETCHIMP), total wetland emissions of 4.3 (2.3–8.2) Tg CH₄ yr⁻¹ from the EU-28 are estimated. The hypothesis of significant natural emissions is supported by the finding that several inverse models yield significant seasonal cycles of derived CH₄ emissions with maxima in summer, while anthropogenic CH₄ emissions are assumed to have much lower seasonal variability. Taking into account the wetland emissions from the WETCHIMP ensemble, the top-down estimates are broadly consistent with the sum of anthropogenic and natural bottom-up inventories. However, the contribution of natural sources and their regional distribution remain rather uncertain. Furthermore, we investigate potential biases in the inverse models by comparison with regular aircraft profiles at four European sites and with vertical profiles obtained during the Infrastructure for Measurement of the European Carbon Cycle (IMECC) aircraft campaign. We present a novel approach to estimate the biases in the derived emissions, based on the comparison of simulated and measured enhancements of CH₄ compared to the background, integrated over the entire boundary layer and over the lower troposphere. The estimated average regional biases range between −40 and 20 % at the aircraft profile sites in France, Hungary and Poland.

Measurements of gaseous and particulate organic carbon were performed during the MEGAPOLI experiments, in July 2009 and January–February 2010, at the SIRTA observatory in suburban Paris. Measurements comprise primary and secondary volatile organic compounds (VOCs), of both anthropogenic and biogenic origins, including C₁₂–C₁₆ n-alkanes of intermediate volatility (IVOCs), suspected to be efficient precursors of secondary organic aerosol (SOA). The time series of gaseous carbon are generally consistent with times series of particulate organic carbon at regional scale, and are clearly affected by meteorology and air mass origin. Concentration levels of anthropogenic VOCs in urban and suburban Paris were surprisingly low (2–963 ppt) compared to other megacities worldwide and to rural continental sites. Urban enhancement ratios of anthropogenic VOC pairs agree well between the urban and suburban Paris sites, showing the regional extent of anthropogenic sources of similar composition. Contrary to other primary anthropogenic VOCs (aromatics and alkanes), IVOCs showed lower concentrations in winter (< 5 ppt) compared to summer (13–27 ppt), which cannot be explained by the gas-particle partitioning theory. Higher concentrations of most oxygenated VOCs in winter (18–5984 ppt) suggest their dominant primary anthropogenic origin. The respective role of primary anthropogenic gaseous compounds in regional SOA formation was investigated by estimating the SOA mass concentration expected from the anthropogenic VOCs and IVOCs (I / VOCs) measured at SIRTA. From an integrated approach based on emission ratios and SOA yields, 38 % of the SOA measured at SIRTA is explained by the measured concentrations of I / VOCs, with a 2% contribution by C₁₂–C₁₆ n-alkane IVOCs. From the results of an alternative time-resolved approach, the average IVOC contribution to SOA formation is estimated to be 7%, which is half of the average contribution of the traditional aromatic compounds (15%). Both approaches, which are based on in situ observations of particular I / VOCs, emphasize the importance of the intermediate volatility compounds in the SOA formation, and support previous results from chamber experiments and modeling studies. They also support the need to make systematic the IVOCs' speciated measurement during field campaigns.

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.

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.