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Since 2018, the TROPOspheric Monitoring Instrument (TROPOMI) on board the Sentinel-5 Precursor (S5P) has provided unprecedented images of nitrogen dioxide (NO2) tropospheric columns at a relatively high spatial resolution with a daily revisit. This study aims at assessing the potential of TROPOMI–PAL data to estimate the national to urban NOx emissions in France from 2019 to 2021, using the variational mode of the recent Community Inversion Framework (CIF) coupled to the CHIMERE regional transport model at a spatial resolution of 10 km × 10 km. The seasonal to inter-annual variations in the French NOx emissions are analyzed. Special attention is paid to the current capability to quantify strong anomalies in the NOx emissions at intra-annual scales, such as the ones due to the COVID-19 pandemic, by using TROPOMI NO2 observations. At the annual scale, the inversions suggest a decrease in the average emissions over 2019–2021 of −3 % compared to the national budget from the Copernicus Atmosphere Monitoring Service regional inventory (CAMS-REG) for the year 2016, which is used as a prior estimate of the national-scale emissions for each year by the Bayesian inversion framework. This is lower than the decrease of −14 % from 2016 to the average over 2019–2021 in the estimates of the French Technical Reference Center for Air Pollution and Climate Change (CITEPA). The lower decrease in the inversion results may be linked in large part to the limited level of constraint brought by the TROPOMI data, due to the observation coverage and the ratio between the current level of errors in the observation and the chemistry-transport model, and to the NO2 signal from the French anthropogenic sources. Focusing on local analysis and selecting the days during which the TROPOMI coverage is good over a specific local source, we compute the reductions in the anthropogenic NOx emission estimates by the inversions from spring 2019 to spring 2020. These reductions are particularly pronounced for the largest French urban areas with high emission levels (e.g., −26 % from April 2019 to April 2020 in the Paris urban area), reflecting reductions in the intensity of vehicle traffic reported during the lockdown period. However, the system does not show large emission decreases for some of the largest cities in France (such as Bordeaux, Nice and Toulouse), even though they were also impacted by the lockdown measures. Despite the current limitations for the monitoring of emissions at the national scale, or for some of the largest cities in France, these results open positive perspectives regarding the ability to support the validation or improvement of inventories with satellite observations, at least at the local level. This leads to discussions on the need for a stepwise improvement of the inversion configuration for a better extraction and extrapolation in space and time of the information from the satellite observations.

​​​​​​​We have used the variational inversion drivers of the recent Community Inversion Framework (CIF), coupled to a European configuration of the CHIMERE regional chemistry transport model and its adjoint to derive carbon monoxide (CO) emissions from Measurement of Pollution in the Troposphere (MOPITT) TIR-NIR (thermal-infrared near-infrared) observations, for a period of over 10 years from 2011 to 2021. The analysis of the inversion results reveals the challenges associated with the inversion of CO emissions at the regional scale over Europe. Annual budgets of national emissions have decreased by about 1 %–11 % over the decade and across Europe. These decreases are mainly due to negative corrections during autumn and winter. The posterior CO emissions follow a decreasing trend over the European Union and United Kingdom area of about −2.2 % yr−1, slightly lower than in the prior emissions. The assimilation of the MOPITT observation in the inversions indeed attenuates the decreasing trend of the CO emissions in the TNO inventory over areas benefiting from the highest number of MOPITT super-observations (particularly over Italy and over the Balkans), and particularly in autumn and winter. The small corrections of the CO emissions at national scales by the inversion can be attributed, first, to the general consistency between the TNO-GHGco-v3 inventory and the satellite data. Analysis of specific patterns such as the impact of the Covid-19 crisis reveals that it can also be seen as a lack of observation constraints to adjust the prior estimate of the emissions. The large errors associated with the observations in our inversion framework and the lack of data over large parts of Europe are sources of limitation on the observational constraint. Emission hotspots generate a relatively strong local signal, which is much better caught and exploited by the inversions than the larger-scale signals, despite the moderate spatial resolution of the MOPITT data. This is why the corrections of these hotspot emissions are stronger and more convincing than the corrections of the national- and continental-scale emissions. Accurate monitoring of the CO national anthropogenic emissions may thus require modelling and inversion systems at spatial resolutions finer than those used here as well as satellite images at high spatial resolution. The CO data of the TROPOMI instrument on board the Sentinel-5P mission should be well suited for such a perspective.

Quantification of land surface–atmosphere fluxes of carbon dioxide (CO2) and their trends and uncertainties is essential for monitoring progress of the EU27+UK bloc as it strives to meet ambitious targets determined by both international agreements and internal regulation. This study provides a consolidated synthesis of fossil sources (CO2 fossil) and natural (including formally managed ecosystems) sources and sinks over land (CO2 land) using bottom-up (BU) and top-down (TD) approaches for the European Union and United Kingdom (EU27+UK), updating earlier syntheses (Petrescu et al., 2020, 2021). Given the wide scope of the work and the variety of approaches involved, this study aims to answer essential questions identified in the previous syntheses and understand the differences between datasets, particularly for poorly characterized fluxes from managed and unmanaged ecosystems. The work integrates updated emission inventory data, process-based model results, data-driven categorical model results, and inverse modeling estimates, extending the previous period 1990–2018 to the year 2020 to the extent possible. BU and TD products are compared with the European national greenhouse gas inventory (NGHGI) reported by parties including the year 2019 under the United Nations Framework Convention on Climate Change (UNFCCC). The uncertainties of the EU27+UK NGHGI were evaluated using the standard deviation reported by the EU member states following the guidelines of the Intergovernmental Panel on Climate Change (IPCC) and harmonized by gap-filling procedures. Variation in estimates produced with other methods, such as atmospheric inversion models (TD) or spatially disaggregated inventory datasets (BU), originate from within-model uncertainty related to parameterization as well as structural differences between models. By comparing the NGHGI with other approaches, key sources of differences between estimates arise primarily in activities. System boundaries and emission categories create differences in CO2 fossil datasets, while different land use definitions for reporting emissions from land use, land use change, and forestry (LULUCF) activities result in differences for CO2 land. The latter has important consequences for atmospheric inversions, leading to inversions reporting stronger sinks in vegetation and soils than are reported by the NGHGI. For CO2 fossil emissions, after harmonizing estimates based on common activities and selecting the most recent year available for all datasets, the UNFCCC NGHGI for the EU27+UK accounts for 926 ± 13 Tg C yr−1, while eight other BU sources report a mean value of 948 [937,961] Tg C yr−1 (25th, 75th percentiles). The sole top-down inversion of fossil emissions currently available accounts for 875 Tg C in this same year, a value outside the uncertainty of both the NGHGI and bottom-up ensemble estimates and for which uncertainty estimates are not currently available. For the net CO2 land fluxes, during the most recent 5-year period including the NGHGI estimates, the NGHGI accounted for −91 ± 32 Tg C yr−1, while six other BU approaches reported a mean sink of −62 [-117,-49] Tg C yr−1, and a 15-member ensemble of dynamic global vegetation models (DGVMs) reported −69 [-152,-5] Tg C yr−1. The 5-year mean of three TD regional ensembles combined with one non-ensemble inversion of −73 Tg C yr−1 has a slightly smaller spread (0th–100th percentiles of [-135,+45] Tg C yr−1), and it was calculated after removing net land–atmosphere CO2 fluxes caused by lateral transport of carbon (crop trade, wood trade, river transport, and net uptake from inland water bodies), resulting in increased agreement with the NGHGI and bottom-up approaches. Results at the category level (Forest Land, Cropland, Grassland) generally show good agreement between the NGHGI and category-specific models, but results for DGVMs are mixed. Overall, for both CO2 fossil and net CO2 land fluxes, we find that current independent approaches are consistent with the NGHGI at the scale of the EU27+UK. We conclude that CO2 emissions from fossil sources have decreased over the past 30 years in the EU27+UK, while land fluxes are relatively stable: positive or negative trends larger (smaller) than 0.07 (−0.61) Tg C yr−2 can be ruled out for the NGHGI. In addition, a gap on the order of 1000 Tg C yr−1 between CO2 fossil emissions and net CO2 uptake by the land exists regardless of the type of approach (NGHGI, TD, BU), falling well outside all available estimates of uncertainties. However, uncertainties in top-down approaches to estimate CO2 fossil emissions remain uncharacterized and are likely substantial, in addition to known uncertainties in top-down estimates of the land fluxes. The data used to plot the figures are available at https://doi.org/10.5281/zenodo.8148461 (McGrath et al., 2023).

Atmospheric inversion approaches are expected to play a critical role in future observation-based monitoring systems for surface fluxes of greenhouse gases (GHGs), pollutants and other trace gases. In the past decade, the research community has developed various inversion software, mainly using variational or ensemble Bayesian optimization methods, with various assumptions on uncertainty structures and prior information and with various atmospheric chemistry–transport models. Each of them can assimilate some or all of the available observation streams for its domain area of interest: flask samples, in situ measurements or satellite observations. Although referenced in peer-reviewed publications and usually accessible across the research community, most systems are not at the level of transparency, flexibility and accessibility needed to provide the scientific community and policy makers with a comprehensive and robust view of the uncertainties associated with the inverse estimation of GHG and reactive species fluxes. Furthermore, their development, usually carried out by individual research institutes, may in the future not keep pace with the increasing scientific needs and technical possibilities. We present here the Community Inversion Framework (CIF) to help rationalize development efforts and leverage the strengths of individual inversion systems into a comprehensive framework. The CIF is primarily a programming protocol to allow various inversion bricks to be exchanged among researchers. In practice, the ensemble of bricks makes a flexible, transparent and open-source Python-based tool to estimate the fluxes of various GHGs and reactive species both at the global and regional scales. It will allow for running different atmospheric transport models, different observation streams and different data assimilation approaches. This adaptability will allow for a comprehensive assessment of uncertainty in a fully consistent framework. We present here the main structure and functionalities of the system, and we demonstrate how it operates in a simple academic case.

Up-to-date and accurate emission inventories for air pollutants are essential for understanding their role in the formation of tropospheric ozone and particulate matter at various temporal scales, for anticipating pollution peaks and for identifying the key drivers that could help mitigate their concentrations. This paper describes the Bayesian variational inverse system PYVAR-CHIMERE, which is now adapted to the inversion of reactive species. Complementarily with bottom-up inventories, this system aims at updating and improving the knowledge on the high spatiotemporal variability of emissions of air pollutants and their precursors. The system is designed to use any type of observations, such as satellite observations or surface station measurements. The potential of PYVAR-CHIMERE is illustrated with inversions of both carbon monoxide (CO) and nitrogen oxides (NOx) emissions in Europe, using the MOPITT and OMI satellite observations, respectively. In these cases, local increments on CO emissions can reach more than +50 %, with increases located mainly over central and eastern Europe, except in the south of Poland, and decreases located over Spain and Portugal. The illustrative cases for NOx emissions also lead to large local increments (> 50 %), for example over industrial areas (e.g., over the Po Valley) and over the Netherlands. The good behavior of the inversion is shown through statistics on the concentrations: the mean bias, RMSE, standard deviation, and correlation between the simulated and observed concentrations. For CO, the mean bias is reduced by about 27 % when using the posterior emissions, the RMSE and the standard deviation are reduced by about 50 %, and the correlation is strongly improved (0.74 when using the posterior emissions against 0.02); for NOx, the mean bias is reduced by about 24 % and the RMSE and the standard deviation are reduced by about 7 %, but the correlation is not improved. We reported strong non-linear relationships between NOx emissions and satellite NO2 columns, now requiring a fully comprehensive scientific study.

Agriculture is the main source of ammonia (NH3) in France, an important gaseous precursor of atmospheric particulate matter (PM). National and global emission inventories are known to have difficulty representing the large spatial and temporal variability inherent to atmospheric NH3. In this study, we compare NH3 emissions in France during spring 2011 from one reference inventory, the TNO inventory, and two alternative inventories that account in different manners for both the spatial and temporal variabilities of the emissions: (i) the NH3SAT satellite-derived inventory based on IASI NH3 columns and (ii) the CADASTRE-CIT inventory that combines NH3 emissions due to nitrogen fertilization calculated with the mechanistic model VOLT'AIR on the database of the CADASTRE_NH3 framework and other source emissions from the CITEPA. The total spring budgets, from March to May 2011, at the national level are higher when calculated with both alternative inventories than with the reference, the difference being more marked with CADASTRE-CIT. NH3SAT and CADASTRE-CIT inventories both yield to large NH3 spring emissions due to fertilization on soils with high pH in the northeastern part of France (65 and 135 kt NH3, respectively, vs. 48 kt NH3 for TNO-GEN), while soil properties are not accounted for by the TNO-GEN methodology. For the other parts of France, the differences are smaller. The timing of fertilization and associated ammonia emissions is closely related to the nitrogen requirements and hence the phenological stage of the crops, and therefore to the crop year's specific weather conditions. Maximum emissions are observed in March for 2011 for some regions for both alternative inventories, while April is the period with maximum emissions for the reference inventory regardless of the region or the year. Comparing the inventories at finer temporal resolutions, typically at daily scale, large differences are found. The convergence of alternative, independent and complementary methods on the spatiotemporal representation of the spring NH3 emissions, particularly over areas where the contribution of mineral fertilizer spreading to the spring budget is strong, encourages further developments in both prospective complementary directions, as this will help improve national NH3 emission inventories.

In this paper, we present the first multiyear time series of atmospheric ammonia (NH3) ground-based measurements in the Paris region (Créteil, 48.79∘ N, 2.44∘ E, France) retrieved with the midresolution “Observations of the Atmosphere by Solar absorption Infrared Spectroscopy” (OASIS) ground-based Fourier transform infrared solar observatory. Located in an urban region, OASIS has previously been used for monitoring air quality (tropospheric ozone and carbon monoxide) thanks to its specific column sensitivity across the whole troposphere down to the atmospheric boundary layer. A total of 4920 measurements of atmospheric total columns of ammonia have been obtained from 2009 to 2017, with uncertainties ranging from 20 % to 35 %, and have been compared with NH3 concentrations derived from the Infrared Atmospheric Sounding Interferometer (IASI). OASIS ground-based measurements show significant interannual and seasonal variabilities of atmospheric ammonia. NH3 total columns over the Paris megacity (12 million people) vary seasonally by 2 orders of magnitude from approximately 0.1×1016 molec. cm−2 in winter to 10×1016 molec. cm−2 for spring peaks, probably due to springtime spreading of fertilizers on surrounding croplands.

Atmospheric carbon monoxide (CO) concentrations have been decreasing since 2000, as observed by both satellite- and ground-based instruments, but global bottom-up emission inventories estimate increasing anthropogenic CO emissions concurrently. In this study, we use a multi-species atmospheric Bayesian inversion approach to attribute satellite-observed atmospheric CO variations to its sources and sinks in order to achieve a full closure of the global CO budget during 2000–2017. Our observation constraints include satellite retrievals of the total column mole fraction of CO, formaldehyde (HCHO), and methane (CH4) that are all major components of the atmospheric CO cycle. Three inversions (i.e., 2000–2017, 2005–2017, and 2010–2017) are performed to use the observation data to the maximum extent possible as they become available and assess the consistency of inversion results to the assimilation of more trace gas species. We identify a declining trend in the global CO budget since 2000 (three inversions are broadly consistent during overlapping periods), driven by reduced anthropogenic emissions in the US and Europe (both likely from the transport sector), and in China (likely from industry and residential sectors), as well as by reduced biomass burning emissions globally, especially in equatorial Africa (associated with reduced burned areas). We show that the trends and drivers of the inversion-based CO budget are not affected by the inter-annual variation assumed for prior CO fluxes. All three inversions contradict the global bottom-up inventories in the world's top two emitters: for the sign of anthropogenic emission trends in China (e.g., here -0.8±0.5 % yr−1 since 2000, while the prior gives 1.3±0.4 % yr−1) and for the rate of anthropogenic emission increase in South Asia (e.g., here 1.0±0.6 % yr−1 since 2000, smaller than 3.5±0.4 % yr−1 in the prior inventory). The posterior model CO concentrations and trends agree well with independent ground-based observations and correct the prior model bias. The comparison of the three inversions with different observation constraints further suggests that the most complete constrained inversion that assimilates CO, HCHO, and CH4 has a good representation of the global CO budget, and therefore matches best with independent observations, while the inversion only assimilating CO tends to underestimate both the decrease in anthropogenic CO emissions and the increase in the CO chemical production. The global CO budget data from all three inversions in this study can be accessed from https://doi.org/10.6084/m9.figshare.c.4454453.v1 (Zheng et al., 2019).

Air pollution reaching hazardous levels in many Chinese cities has been a major concern in China over the past decades. New policies have been applied to regulate anthropogenic pollutant emissions, leading to changes in atmospheric composition and in particulate matter (PM) production. Increasing levels of atmospheric ammonia columns have been observed by satellite during recent years. In particular, observations from the Infrared Atmospheric Sounding Interferometer (IASI) reveal an increase of these columns by 15 % and 65 % from 2011 to 2013 and 2015, respectively, over eastern China. In this paper we performed model simulations for 2011, 2013 and 2015 in order to understand the origin of this increase and to quantify the link between ammonia and the inorganic components of particles: NH4(p)+/SO4(p)2-/NO3(p)-. Interannual change of meteorology can be excluded as a reason: year 2015 meteorology leads to enhanced sulfate production over eastern China, which increases the ammonium and decreases the ammonia content, which is contrary to satellite observations. Reductions in SO2 and NOx emissions from 2011 to 2015 of 37.5 % and 21 % respectively, as constrained from satellite data, lead to decreased inorganic matter (by 14 % for NH4(p)++SO4(p)2-+NO3(p)-). This in turn leads to increased gaseous NH3(g) tropospheric columns by as much as 24 % and 49 % (sampled corresponding to IASI data availability) from 2011 to 2013 and 2015 respectively and thus can explain most of the observed increase.

China is a highly polluted region, particularly the North China Plain (NCP). However, emission reductions have been occurring in China for about the last 10 years; these reduction measures have been in effect since 2006 for SO2 emissions and since 2010 for NOx emissions. Recent studies have shown a decrease in the NO2 tropospheric column since 2013 that has been attributed to the reduction in NOx emissions. Quantifying how these emission reductions translate regarding ozone concentrations remains unclear due to apparent inconsistencies between surface and satellite observations. In this study, we use the lower tropospheric (LT) columns (surface – 6 km a.s.l. – above sea level) derived from the IASI-A satellite instrument to describe the variability and trend in LT ozone over the NCP for the 2008–2016 period. First, we investigate the IASI retrieval stability and robustness based on the influence of atmospheric conditions (thermal conditions and aerosol loading) and retrieval sensitivity changes. We compare IASI-A observations with the independent IASI-B instrument aboard the Metop-B satellite as well as comparing them with surface and ozonesonde measurements. The conclusion from this evaluation is that the LT ozone columns retrieved from IASI-A are reliable for deriving a trend representative of the lower/free troposphere (3–5 km). Deseasonalized monthly time series of LT ozone show two distinct periods: the first period (2008–2012) with no significant trend (< − 0.1 % yr−1) and a second period (2013–2016) with a highly significant negative trend of −1.2 % yr−1, which leads to an overall significant trend of −0.77 % yr−1 for the 2008–2016 period. We explore the dynamical and chemical factors that could explain these negative trends using a multivariate linear regression model and chemistry transport model simulations to evaluate the sensitivity of ozone to the reduction in NOx emissions. The results show that the negative trend observed from IASI for the 2013–2016 period is almost equally attributed to large-scale dynamical processes and emissions reduction, with the large El Niño event in 2015–2016 and the reduction of NOx emissions being the main contributors. For the entire 2008–2016 period, large-scale dynamical processes explain more than half of the observed trend, with a possible reduction of the stratosphere–troposphere exchanges being the main contributor. Large-scale transport and advection, evaluated using CO as a proxy, only contributes to a small part of the trends ( ∼ 10 %). However, a residual significant negative trend remains; this shows the limitation of linear regression models regarding their ability to account for nonlinear processes such as ozone chemistry and stresses the need for a detailed evaluation of changes in chemical regimes with the altitude.

Current national pledges to reduce greenhouse gas emissions track to a temperature rise of about 3 °C. Here the authors use future projections to show that 3 °C warming under a business as usual scenario would result in large increases in ozone concentrations, off-setting any benefits from mitigation policies.

A Bayesian inversion system is used to evaluate the capability of the current global surface network and of the space-borne GOSAT/TANSO-FTS and IASI instruments to quantify surface flux anomalies of methane at various spatial (global, semi-hemispheric and regional) and time (seasonal, yearly, 3-yearly) scales. The evaluation is based on a signal-to-noise ratio analysis, the signal being the methane fluxes inferred from the surface-based inversion from 2000 to 2011 and the noise (i.e., precision) of each of the three observing systems being computed from the Bayesian equation. At the global and semi-hemispheric scales, all observing systems detect flux anomalies at most of the tested timescales. At the regional scale, some seasonal flux anomalies are detected by the three observing systems, but year-to-year anomalies and longer-term trends are only poorly detected. Moreover, reliably detected regions depend on the reference surface-based inversion used as the signal. Indeed, tropical flux inter-annual variability, for instance, can be attributed mostly to Africa in the reference inversion or spread between tropical regions in Africa and America. Our results show that inter-annual analyses of methane emissions inferred by atmospheric inversions should always include an uncertainty assessment and that the attribution of current trends in atmospheric methane to particular regions' needs increased effort, for instance, gathering more observations (in the future) and improving transport models. At all scales, GOSAT generally shows the best performance of the three observing systems.

Negative trends of carbon monoxide (CO) concentrations are observed in the recent decade by both surface measurements and satellite retrievals over many regions of the globe, but they are not well explained by current emission inventories. Here, we analyse the observed CO concentration decline with an atmospheric inversion that simultaneously optimizes the two main CO sources (surface emissions and atmospheric hydrocarbon oxidations) and the main CO sink (atmospheric hydroxyl radical OH oxidation). Satellite CO column retrievals from Measurements of Pollution in the Troposphere (MOPITT), version 6, and surface observations of methane and methyl chloroform mole fractions are assimilated jointly for the period covering 2002–2011. Compared to the model simulation prescribed with prior emission inventories, trends in the optimized CO concentrations show better agreement with that of independent surface in situ measurements. At the global scale, the atmospheric inversion primarily interprets the CO concentration decline as a decrease in the CO emissions (−2.3 % yr−1), more than twice the negative trend estimated by the prior emission inventories (−1.0 % yr−1). The spatial distribution of the inferred decrease in CO emissions indicates contributions from western Europe (−4.0 % yr−1), the United States (−4.6 % yr−1) and East Asia (−1.2 % yr−1), where anthropogenic fuel combustion generally dominates the overall CO emissions, and also from Australia (−5.3 % yr−1), the Indo-China Peninsula (−5.6 % yr−1), Indonesia (−6.7 % y−1), and South America (−3 % yr−1), where CO emissions are mostly due to biomass burning. In contradiction with the bottom-up inventories that report an increase of 2 % yr−1 over China during the study period, a significant emission decrease of 1.1 % yr−1 is inferred by the inversion. A large decrease in CO emission factors due to technology improvements would outweigh the increase in carbon fuel combustions and may explain this decrease. Independent satellite formaldehyde (CH2O) column retrievals confirm the absence of large-scale trends in the atmospheric source of CO. However, it should be noted that the CH2O retrievals are not assimilated and OH concentrations are optimized at a very large scale in this study.

Satellite retrievals of methane weighted atmospheric columns are assimilated within a Bayesian inversion system to infer the global and regional methane emissions and sinks for the period August 2009 to July 2010. Inversions are independently computed from three different space-borne observing systems and one surface observing system under several hypotheses for prior-flux and observation errors. Posterior methane emissions are compared and evaluated against surface mole fraction observations via a chemistry-transport model. Apart from SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CartograpHY), the simulations agree fairly well with the surface mole fractions. The most consistent configurations of this study using TANSO-FTS (Thermal And Near infrared Sensor for carbon Observation – Fourier Transform Spectrometer), IASI (Infrared Atmospheric Sounding Interferometer) or surface measurements induce posterior methane global emissions of, respectively, 565 ± 21 Tg yr−1, 549 ± 36 Tg yr−1 and 538 ± 15 Tg yr−1 over the one-year period August 2009–July 2010. This consistency between the satellite retrievals (apart from SCIAMACHY) and independent surface measurements is promising for future improvement of CH4 emission estimates by atmospheric inversions.

A modified cumulus convection parametrisation scheme is presented. This scheme computes the mass of air transported upward in a cumulus cell using conservation of moisture and a detailed distribution of convective precipitation provided by a reanalysis dataset. The representation of vertical transport within the scheme includes entrainment and detrainment processes in convective updrafts and downdrafts. Output from the proposed parametrisation scheme is employed in the National Institute for Environmental Studies (NIES) global chemical transport model driven by JRA-25/JCDAS reanalysis. The simulated convective precipitation rate and mass fluxes are compared with observations and reanalysis data. A simulation of the short-lived tracer 222Rn is used to further evaluate the performance of the cumulus convection scheme. Simulated distributions of 222Rn are evaluated against observations at the surface and in the free troposphere, and compared with output from models that participated in the TransCom-CH4 Transport Model Intercomparison. From this comparison, we demonstrate that the proposed convective scheme in general is consistent with observed and modeled results.

For the first time, carbon monoxide (CO) and formaldehyde (HCHO) satellite retrievals are used together with methane (CH4) and methyl choloroform (CH3CCl3 or MCF) surface measurements in an advanced inversion system. The CO and HCHO are respectively from the MOPITT and OMI instruments. The multi-species and multi-satellite dataset inversion is done for the 2005–2010 period. The robustness of our results is evaluated by comparing our posterior-modeled concentrations with several sets of independent measurements of atmospheric mixing ratios. The inversion leads to significant changes from the prior to the posterior, in terms of magnitude and seasonality of the CO and CH4 surface fluxes and of the HCHO production by non-methane volatile organic compounds (NMVOC). The latter is significantly decreased, indicating an overestimation of the biogenic NMVOC emissions, such as isoprene, in the GEIA inventory. CO and CH4 surface emissions are increased by the inversion, from 1037 to 1394 TgCO and from 489 to 529 TgCH4 on average for the 2005–2010 period. CH4 emissions present significant interannual variability and a joint CO-CH4 fluxes analysis reveals that tropical biomass burning probably played a role in the recent increase of atmospheric methane.

Globally, terrestrial ecosystems have absorbed about 30% of anthropogenic greenhouse gas emissions over the period 2000–2007 and inter-hemispheric gradients indicate that a significant fraction of terrestrial carbon sequestration must be north of the Equator. We present a compilation of the CO2, CO, CH4 and N2O balances of Europe following a dual constraint approach in which (1) a land-based balance derived mainly from ecosystem carbon inventories and (2) a land-based balance derived from flux measurements are compared to (3) the atmospheric data-based balance derived from inversions constrained by measurements of atmospheric GHG (greenhouse gas) concentrations. Good agreement between the GHG balances based on fluxes (1294 ± 545 Tg C in CO2-eq yr−1), inventories (1299 ± 200 Tg C in CO2-eq yr−1) and inversions (1210 ± 405 Tg C in CO2-eq yr−1) increases our confidence that the processes underlying the European GHG budget are well understood and reasonably sampled. However, the uncertainty remains large and largely lacks formal estimates. Given that European net land to atmosphere exchanges are determined by a few dominant fluxes, the uncertainty of these key components needs to be formally estimated before efforts could be made to reduce the overall uncertainty. The net land-to-atmosphere flux is a net source for CO2, CO, CH4 and N2O, because the anthropogenic emissions by far exceed the biogenic sink strength. The dual-constraint approach confirmed that the European biogenic sink removes as much as 205 ± 72 Tg C yr−1 from fossil fuel burning from the atmosphere. However, This C is being sequestered in both terrestrial and inland aquatic ecosystems. If the C-cost for ecosystem management is taken into account, the net uptake of ecosystems is estimated to decrease by 45% but still indicates substantial C-sequestration. However, when the balance is extended from CO2 towards the main GHGs, C-uptake by terrestrial and aquatic ecosystems is offset by emissions of non-CO2 GHGs. As such, the European ecosystems are unlikely to contribute to mitigating the effects of climate change.

A chemistry-transport model (CTM) intercomparison experiment (TransCom-CH4) has been designed to investigate the roles of surface emissions, transport and chemical loss in simulating the global methane distribution. Model simulations were conducted using twelve models and four model variants and results were archived for the period of 1990–2007. All but one model transports were driven by reanalysis products from 3 different meteorological agencies. The transport and removal of CH4 in six different emission scenarios were simulated, with net global emissions of 513 ± 9 and 514 ± 14 Tg CH4 yr−1 for the 1990s and 2000s, respectively. Additionally, sulfur hexafluoride (SF6) was simulated to check the interhemispheric transport, radon (222Rn) to check the subgrid scale transport, and methyl chloroform (CH3CCl3) to check the chemical removal by the tropospheric hydroxyl radical (OH). The results are compared to monthly or annual mean time series of CH4, SF6 and CH3CCl3 measurements from 8 selected background sites, and to satellite observations of CH4 in the upper troposphere and stratosphere. Most models adequately capture the vertical gradients in the stratosphere, the average long-term trends, seasonal cycles, interannual variations (IAVs) and interhemispheric (IH) gradients at the surface sites for SF6, CH3CCl3 and CH4. The vertical gradients of all tracers between the surface and the upper troposphere are consistent within the models, revealing vertical transport differences between models. An average IH exchange time of 1.39 ± 0.18 yr is derived from SF6 time series. Sensitivity simulations suggest that the estimated trends in exchange time, over the period of 1996–2007, are caused by a change of SF6 emissions towards the tropics. Using six sets of emission scenarios, we show that the decadal average CH4 growth rate likely reached equilibrium in the early 2000s due to the flattening of anthropogenic emission growth since the late 1990s. Up to 60% of the IAVs in the observed CH4 concentrations can be explained by accounting for the IAVs in emissions, from biomass burning and wetlands, as well as meteorology in the forward models. The modeled CH4 budget is shown to depend strongly on the troposphere-stratosphere exchange rate and thus on the model's vertical grid structure and circulation in the lower stratosphere. The 15-model median CH4 and CH3CCl3 atmospheric lifetimes are estimated to be 9.99 ± 0.08 and 4.61 ± 0.13 yr, respectively, with little IAV due to transport and temperature.

This paper presents an analysis of the recent tropospheric molecular hydrogen (H2) budget with a particular focus on soil uptake and European surface emissions. A variational inversion scheme is combined with observations from the RAMCES and EUROHYDROS atmospheric networks, which include continuous measurements performed between mid-2006 and mid-2009. Net H2 surface flux, then deposition velocity and surface emissions and finally, deposition velocity, biomass burning, anthropogenic and N2 fixation-related emissions were simultaneously inverted in several scenarios. These scenarios have focused on the sensibility of the soil uptake value to different spatio-temporal distributions. The range of variations of these diverse inversion sets generate an estimate of the uncertainty for each term of the H2 budget. The net H2 flux per region (High Northern Hemisphere, Tropics and High Southern Hemisphere) varies between −8 and +8 Tg yr−1. The best inversion in terms of fit to the observations combines updated prior surface emissions and a soil deposition velocity map that is based on bottom-up and top-down estimations. Our estimate of global H2 soil uptake is −59±9 Tg yr−1. Forty per cent of this uptake is located in the High Northern Hemisphere and 55% is located in the Tropics. In terms of surface emissions, seasonality is mainly driven by biomass burning emissions. The inferred European anthropogenic emissions are consistent with independent H2 emissions estimated using a H2/CO mass ratio of 0.034 and CO emissions within the range of their respective uncertainties. Additional constraints, such as isotopic measurements would be needed to infer a more robust partition of H2 sources and sinks.

The recent increase of atmospheric methane is investigated by using two atmospheric inversions to quantify the distribution of sources and sinks for the 2006–2008 period, and a process-based model of methane emissions by natural wetland ecosystems. Methane emissions derived from the two inversions are consistent at a global scale: emissions are decreased in 2006 (−7 Tg) and increased in 2007 (+21 Tg) and 2008 (+18 Tg), as compared to the 1999–2006 period. The agreement on the latitudinal partition of the flux anomalies for the two inversions is fair in 2006, good in 2007, and not good in 2008. In 2007, a positive anomaly of tropical emissions is found to be the main contributor to the global emission anomalies (~60–80%) for both inversions, with a dominant share attributed to natural wetlands (~2/3), and a significant contribution from high latitudes (~25%). The wetland ecosystem model produces smaller and more balanced positive emission anomalies between the tropics and the high latitudes for 2006, 2007 and 2008, mainly due to precipitation changes during these years. At a global scale, the agreement between the ecosystem model and the inversions is good in 2008 but not satisfying in 2006 and 2007. Tropical South America and Boreal Eurasia appear to be major contributors to variations in methane emissions consistently in the inversions and the ecosystem model. Finally, changes in OH radicals during 2006–2008 are found to be less than 1% in inversions, with only a small impact on the inferred methane emissions.

Between July and November 2008, simultaneous observations were conducted by several orbiting instruments that monitor carbon monoxide in the atmosphere, among them the Infrared Atmospheric Sounding Instrument (IASI) and Measurements Of Pollution In The Troposphere (MOPITT). In this paper, the concentration retrievals at about 700 hPa from these two instruments are successively used in a variational Bayesian system to infer the global distribution of CO emissions. Starting from a global emission budget of 479 Tg for the considered period, the posterior estimate of CO emissions using IASI retrievals gives a total of 643 Tg, which is in close agreement with the budget calculated with version 3 of the MOPITT data (649 Tg). The regional totals are also broadly consistent between the two inversions. Even though our theoretical error budget indicates that IASI constrains the emissions slightly less than MOPITT, because of lesser sensitivity in the lower troposphere, these first results indicate that IASI may play a major role in the quantification of the emissions of CO.

No abstract available.

In the framework of the RECCAP2 initiative, we present the greenhouse gas (GHG) and carbon (C) budget of Europe. For the decade of the 2010s, we present a bottom‐up (BU) estimate of GHG net‐emissions of 3.9 Pg CO2‐eq. yr−1 (using a global warming potential on a 100 years horizon), which are largely dominated by fossil fuel emissions. In this decade, terrestrial ecosystems acted as a net GHG sink of 0.9 Pg CO2‐eq. yr−1, dominated by a CO2 sink that was partially counterbalanced by net emissions of CH4 and N2O. For CH4 and N2O, we find good agreement between BU and top‐down (TD) estimates from atmospheric inversions. However, our BU land CO2 sink is significantly higher than the TD estimates. We further show that decadal averages of GHG net‐emissions have declined by 1.2 Pg CO2‐eq. yr−1 since the 1990s, mainly due to a reduction in fossil fuel emissions. In addition, based on both data driven BU and TD estimates, we also find that the land CO2 sink has weakened over the past two decades. A large part of the European CO2 and C sinks is located in Northern Europe. At the same time, we find a decreasing trend in sink strength in Scandinavia, which can be attributed to an increase in forest management intensity. These are partly offset by increasing CO2 sinks in parts of Eastern Europe and Northern Spain, attributed in part to land use change. Extensive regions of high CH4 and N2O emissions are mainly attributed to agricultural activities and are found in Belgium, the Netherlands and the southern UK. We further analyzed interannual variability in the GHG budgets. The drought year of 2003 shows the highest net‐emissions of CO2 and of all GHGs combined. Plain Language Summary: We have synthesized the European budgets of carbon and the greenhouse gases (GHG) carbon dioxide, methane and nitrous oxide. This synthesis includes estimates of direct emissions from fossil fuel burning, industrial production, waste management and agriculture, as well as of sources and sinks in the terrestrial biosphere. Summing up the sources and sinks of the three GHGs, we estimate for the decade of the 2010s an average annual net‐emission of 3.9 billion tons of carbon dioxide equivalents. These net‐emissions are dominated by carbon dioxide from fossil fuel emissions (4.1 billion tons of carbon dioxide). In contrast, the terrestrial biosphere acts as a net sink of carbon dioxide, the effect of which is only partly counterbalanced by net emissions of methane and nitrous oxide. The net‐effect of the terrestrial biosphere's GHG budget is a sink of 0.9 billion tons of carbon dioxide equivalents per year. Over the last three decades, European GHG emissions have declined by 1.2 billion tons carbon dioxide equivalents per year, mainly due to reductions in fossil fuel emissions. However, the sink capacity of the terrestrial biosphere has diminished since the 2000s. Key Points: We provide a bottom‐up estimate of CO2, CH4, N2O emissions of 3.9 Pg CO2‐eq. yr−1 over Europe, 2010–2019Terrestrial ecosystems acted as a greenhouse gas net sink of 0.9 Pg CO2‐eq. yr−1, dominated by CO2 sinkNet‐greenhouse gas emissions decreased by ∼1/4 since the 1990s, but land carbon sink is weakening since the 2000s [ABSTRACT FROM AUTHOR]

Since 2018, the TROPOspheric Monitoring Instrument (TROPOMI) on board the Sentinel-5 Precursor (S5P) has provided unprecedented images of nitrogen dioxide (NO2) tropospheric columns at a relatively high spatial resolution with a daily revisit. This study aims at assessing the potential of TROPOMI–PAL data to estimate the national to urban NOx emissions in France from 2019 to 2021, using the variational mode of the recent Community Inversion Framework (CIF) coupled to the CHIMERE regional transport model at a spatial resolution of 10 km × 10 km. The seasonal to inter-annual variations in the French NOx emissions are analyzed. Special attention is paid to the current capability to quantify strong anomalies in the NOx emissions at intra-annual scales, such as the ones due to the COVID-19 pandemic, by using TROPOMI NO2 observations. At the annual scale, the inversions suggest a decrease in the average emissions over 2019–2021 of - 3 % compared to the national budget from the Copernicus Atmosphere Monitoring Service regional inventory (CAMS-REG) for the year 2016, which is used as a prior estimate of the national-scale emissions for each year by the Bayesian inversion framework. This is lower than the decrease of - 14 % from 2016 to the average over 2019–2021 in the estimates of the French Technical Reference Center for Air Pollution and Climate Change (CITEPA). The lower decrease in the inversion results may be linked in large part to the limited level of constraint brought by the TROPOMI data, due to the observation coverage and the ratio between the current level of errors in the observation and the chemistry-transport model, and to the NO2 signal from the French anthropogenic sources. Focusing on local analysis and selecting the days during which the TROPOMI coverage is good over a specific local source, we compute the reductions in the anthropogenic NOx emission estimates by the inversions from spring 2019 to spring 2020. These reductions are particularly pronounced for the largest French urban areas with high emission levels (e.g., - 26 % from April 2019 to April 2020 in the Paris urban area), reflecting reductions in the intensity of vehicle traffic reported during the lockdown period. However, the system does not show large emission decreases for some of the largest cities in France (such as Bordeaux, Nice and Toulouse), even though they were also impacted by the lockdown measures. Despite the current limitations for the monitoring of emissions at the national scale, or for some of the largest cities in France, these results open positive perspectives regarding the ability to support the validation or improvement of inventories with satellite observations, at least at the local level. This leads to discussions on the need for a stepwise improvement of the inversion configuration for a better extraction and extrapolation in space and time of the information from the satellite observations. [ABSTRACT FROM AUTHOR]

The 1,1,1,2-tetrafluoroethane (HFC-134a), an important alternative to CFC-12 in accordance with the Montreal Protocol on Substances that Deplete the Ozone Layer, is a high global warming potential greenhouse gas. Here we evaluate variations in global and regional HFC-134a emissions and emission trends, from 1995 to 2010, at a relatively high spatial and temporal (3.75° in longitude × 2.5° in latitude and 8 day) resolution, using surface HFC-134a measurements. Our results show a progressive increase of global HFC-134a emissions from 19 ± 2 Gg/yr in 1995 to 167 ± 5 Gg/yr in 2010, with both a slowdown in developed countries and a 20%/yr increase in China since 2005. A seasonal cycle is also seen since 2002, which becomes enhanced over time, with larger values during the boreal summer.

​​​​​​​We have used the variational inversion drivers of the recent Community Inversion Framework (CIF), coupled to a European configuration of the CHIMERE regional chemistry transport model and its adjoint to derive carbon monoxide (CO) emissions from Measurement of Pollution in the Troposphere (MOPITT) TIR-NIR (thermal-infrared near-infrared) observations, for a period of over 10 years from 2011 to 2021. The analysis of the inversion results reveals the challenges associated with the inversion of CO emissions at the regional scale over Europe. Annual budgets of national emissions have decreased by about 1 %–11 % over the decade and across Europe. These decreases are mainly due to negative corrections during autumn and winter. The posterior CO emissions follow a decreasing trend over the European Union and United Kingdom area of about - 2.2 % yr -1 , slightly lower than in the prior emissions. The assimilation of the MOPITT observation in the inversions indeed attenuates the decreasing trend of the CO emissions in the TNO inventory over areas benefiting from the highest number of MOPITT super-observations (particularly over Italy and over the Balkans), and particularly in autumn and winter. The small corrections of the CO emissions at national scales by the inversion can be attributed, first, to the general consistency between the TNO-GHGco-v3 inventory and the satellite data. Analysis of specific patterns such as the impact of the Covid-19 crisis reveals that it can also be seen as a lack of observation constraints to adjust the prior estimate of the emissions. The large errors associated with the observations in our inversion framework and the lack of data over large parts of Europe are sources of limitation on the observational constraint. Emission hotspots generate a relatively strong local signal, which is much better caught and exploited by the inversions than the larger-scale signals, despite the moderate spatial resolution of the MOPITT data. This is why the corrections of these hotspot emissions are stronger and more convincing than the corrections of the national- and continental-scale emissions. Accurate monitoring of the CO national anthropogenic emissions may thus require modelling and inversion systems at spatial resolutions finer than those used here as well as satellite images at high spatial resolution. The CO data of the TROPOMI instrument on board the Sentinel-5P mission should be well suited for such a perspective. [ABSTRACT FROM AUTHOR]

Since 2018, TROPOMI on-board Sentinel-5P provides unprecedented images of NO2 tropospheric columns at a relatively high spatial resolution with a daily revisit. This study aims at assessing the potential of the TROPOMI-PAL data to estimate the national to urban NO x emissions in France from 2019 to 2021, using the variational mode of the recent Community Inversion Framework coupled to the CHIMERE regional transport model at a spatial resolution of 10×10 km2. The seasonal to inter-annual variations of the NO x French emissions are analyzed. A specific attention is paid to the current capability to quantify strong anomalies in the NO x emissions at intra-annual scales such as the ones due to the COVID-19 pandemic, by using TROPOMI NO2 observations. The inversions lead to a decrease of the average emissions over 2019–2021 compared to 2016 of -3 % at national scale, which is lower than the decrease of -14 % between these years in the estimates of the French Technical Center for Air Pollution and Climate Change (CITEPA). This may be linked especially to the limited level of constraint brought by the TROPOMI data, due to the observation coverage and the ratio between the current level of errors in the observation and the chemistry-transport model, and the NO2 signal from the French anthropogenic sources. Focusing on local analysis and selecting the days during which the TROPOMI coverage is good over a specific local source, we compute the reductions in the NO x anthropogenic emission estimates by the inversions from spring 2019 to spring 2020. These reductions are particularly pronounced for the largest French urban areas (e.g., -26 % from April 2019 to April 2020 in the Paris urban area) and along major roadways, consistently with the reduction in the intensity of vehicle traffic reported during the lockdown period. [ABSTRACT FROM AUTHOR]

We have used the variational inversion drivers of the recent Community Inversion Framework (CIF), coupled to a European configuration of the CHIMERE regional chemistry transport model and its adjoint to derive carbon monixide (CO) emissions from the MOPITT TIR-NIR observations, for a period of over 10 years from 2011 to 2021. The analysis of the inversion results reveals the challenges associated with the inversion of CO emissions at the regional scale over Europe. Annual budgets of the national emissions are decreased by about 1–11 % over the decade and across Europe. These decreases are mainly due to negative corrections during autumn and winter. The posterior CO emissions follow a decreasing trend over the European Union + United Kingdom area with a trend of about -2.2 %/year, slightly lower than in the prior emissions. The assimilation of the MOPITT observation in the inversions indeed attenuates the decreasing trend of the CO emissions in the TNO inventory over areas benefiting from the highest number of MOPITT super-observations (particularly over Italy and over the Balkans), and particularly in autumn and winter. The small corrections of the CO emissions at national scales by the inversion can be attributed, first, to the general consistency between the TNO-GHGco-v3 inventory and the satellite data. Analysis of specific patterns such as the impact of the covid-19 crisis reveal that it can also be seen as a lack of observation constraint to adjust the prior estimate of the emissions. The large errors in the observations, and the lack of data over large parts of Europe are sources of limitation on the observational constraint. Emission hot spots generate a relatively strong local signal, which is much better caught and exploited by the inversions than the larger scale signals, despite the moderate spatial resolution of the MOPITT data. This is why the corrections of these hot spot emissions are stronger and more convincing than the corrections of the national and continental scale emissions. Accurate monitoring of the CO national anthropogenic emissions may thus require modeling and inversion systems at spatial resolution finer than those used here, as well satellite images at high spatial resolution. The CO data of the TROPOMI instrument onboard the Sentinel-5P mission should be well suited for such a perspective. [ABSTRACT FROM AUTHOR]