Suchergebnisse

International audience ; The EDGAR (Emissions Database for Global Atmospheric Research) v4.3 global anthropogenic emissions inventory of several gaseous (SO2, NOx, CO, non-methane volatile organic compounds (NMVOCs) and NH3) and particulate (PM10, PM2.5, black and organic carbon (BC and OC)) air pollutants for the period 1970–2010 is used to develop retrospective air pollution emission scenarios to quantify the roles and contributions of changes in fuels consumption, technology, end-of-pipe emission reduction measures and their resulting impact on health and crop yields. This database presents changes in activity data, fuels and air pollution abatement technology for the past 4 decades, using international statistics and following guidelines for bottom-up emission inventory at the Tier 1 and Tier 2 levels with region-specific default values. With two further retrospective scenarios we assess (1) the impact of the technology and end-of-pipe (EOP) reduction measures in the European Union (EU) by considering a stagnation of technology with constant emission factors from 1970 and with no further abatement measures and improvement in European emissions standards, but fuel consumption occurring at historical pace, and (2) the impact of increased fuel consumption by considering unchanged energy use with constant fuel consumption since 1970, but technological development and end-of-pipe reductions. Our scenario analysis focuses on the three most important and most regulated sectors (power generation, the manufacturing industry and road transport), which are subject of multi-pollutant EU Air Quality regulations. If technology and European EOP reduction measures had stagnated at 1970 levels, EU air quality in 2010 would have suffered from 129 % higher SO2, 71 % higher NOx and 69 % higher PM2.5 emissions, demonstrating the large role of technology in reducing emissions in 2010. However, if fuel consumption had remained constant starting in 1970, the EU would have benefited from current technology and emission control standards, with reductions in NOx by even 13 % more. Such further savings are not observed for SO2 and PM2.5. If the EU consumed the same amount of fuels as in 1970 but with the current technology and emission control standards, then the emissions of SO2 and PM2.5 would be 42 % respectively 10 % higher. This scenario shows the importance for air quality of abandoning heavy residual fuel oil and shifting fuel types (from, e.g., coal to gas) in the EU. A reduced-form TM5-FASST (Fast Screening Scenario Tool based on the global chemical Transport Model 5) is applied to calculate regional and global levels of aerosol and ozone concentrations and to assess the impact of air quality improvements on human health and crop yield loss, showing substantial impacts of export of EU technologies and standards to other world regions.

International audience ; The EDGAR (Emissions Database for Global Atmospheric Research) v4.3 global anthropogenic emissions inventory of several gaseous (SO2, NOx, CO, non-methane volatile organic compounds (NMVOCs) and NH3) and particulate (PM10, PM2.5, black and organic carbon (BC and OC)) air pollutants for the period 1970–2010 is used to develop retrospective air pollution emission scenarios to quantify the roles and contributions of changes in fuels consumption, technology, end-of-pipe emission reduction measures and their resulting impact on health and crop yields. This database presents changes in activity data, fuels and air pollution abatement technology for the past 4 decades, using international statistics and following guidelines for bottom-up emission inventory at the Tier 1 and Tier 2 levels with region-specific default values. With two further retrospective scenarios we assess (1) the impact of the technology and end-of-pipe (EOP) reduction measures in the European Union (EU) by considering a stagnation of technology with constant emission factors from 1970 and with no further abatement measures and improvement in European emissions standards, but fuel consumption occurring at historical pace, and (2) the impact of increased fuel consumption by considering unchanged energy use with constant fuel consumption since 1970, but technological development and end-of-pipe reductions. Our scenario analysis focuses on the three most important and most regulated sectors (power generation, the manufacturing industry and road transport), which are subject of multi-pollutant EU Air Quality regulations. If technology and European EOP reduction measures had stagnated at 1970 levels, EU air quality in 2010 would have suffered from 129 % higher SO2, 71 % higher NOx and 69 % higher PM2.5 emissions, demonstrating the large role of technology in reducing emissions in 2010. However, if fuel consumption had remained constant starting in 1970, the EU would have benefited from current technology and emission control ...

International audience ; The EDGAR (Emissions Database for Global Atmospheric Research) v4.3 global anthropogenic emissions inventory of several gaseous (SO2, NOx, CO, non-methane volatile organic compounds (NMVOCs) and NH3) and particulate (PM10, PM2.5, black and organic carbon (BC and OC)) air pollutants for the period 1970–2010 is used to develop retrospective air pollution emission scenarios to quantify the roles and contributions of changes in fuels consumption, technology, end-of-pipe emission reduction measures and their resulting impact on health and crop yields. This database presents changes in activity data, fuels and air pollution abatement technology for the past 4 decades, using international statistics and following guidelines for bottom-up emission inventory at the Tier 1 and Tier 2 levels with region-specific default values. With two further retrospective scenarios we assess (1) the impact of the technology and end-of-pipe (EOP) reduction measures in the European Union (EU) by considering a stagnation of technology with constant emission factors from 1970 and with no further abatement measures and improvement in European emissions standards, but fuel consumption occurring at historical pace, and (2) the impact of increased fuel consumption by considering unchanged energy use with constant fuel consumption since 1970, but technological development and end-of-pipe reductions. Our scenario analysis focuses on the three most important and most regulated sectors (power generation, the manufacturing industry and road transport), which are subject of multi-pollutant EU Air Quality regulations. If technology and European EOP reduction measures had stagnated at 1970 levels, EU air quality in 2010 would have suffered from 129 % higher SO2, 71 % higher NOx and 69 % higher PM2.5 emissions, demonstrating the large role of technology in reducing emissions in 2010. However, if fuel consumption had remained constant starting in 1970, the EU would have benefited from current technology and emission control standards, with reductions in NOx by even 13 % more. Such further savings are not observed for SO2 and PM2.5. If the EU consumed the same amount of fuels as in 1970 but with the current technology and emission control standards, then the emissions of SO2 and PM2.5 would be 42 % respectively 10 % higher. This scenario shows the importance for air quality of abandoning heavy residual fuel oil and shifting fuel types (from, e.g., coal to gas) in the EU. A reduced-form TM5-FASST (Fast Screening Scenario Tool based on the global chemical Transport Model 5) is applied to calculate regional and global levels of aerosol and ozone concentrations and to assess the impact of air quality improvements on human health and crop yield loss, showing substantial impacts of export of EU technologies and standards to other world regions.

International audience The EDGAR (Emissions Database for Global Atmospheric Research) v4.3 global anthropogenic emissions inventory of several gaseous (SO2, NOx, CO, non-methane volatile organic compounds (NMVOCs) and NH3) and particulate (PM10, PM2.5, black and organic carbon (BC and OC)) air pollutants for the period 1970–2010 is used to develop retrospective air pollution emission scenarios to quantify the roles and contributions of changes in fuels consumption, technology, end-of-pipe emission reduction measures and their resulting impact on health and crop yields. This database presents changes in activity data, fuels and air pollution abatement technology for the past 4 decades, using international statistics and following guidelines for bottom-up emission inventory at the Tier 1 and Tier 2 levels with region-specific default values. With two further retrospective scenarios we assess (1) the impact of the technology and end-of-pipe (EOP) reduction measures in the European Union (EU) by considering a stagnation of technology with constant emission factors from 1970 and with no further abatement measures and improvement in European emissions standards, but fuel consumption occurring at historical pace, and (2) the impact of increased fuel consumption by considering unchanged energy use with constant fuel consumption since 1970, but technological development and end-of-pipe reductions. Our scenario analysis focuses on the three most important and most regulated sectors (power generation, the manufacturing industry and road transport), which are subject of multi-pollutant EU Air Quality regulations. If technology and European EOP reduction measures had stagnated at 1970 levels, EU air quality in 2010 would have suffered from 129 % higher SO2, 71 % higher NOx and 69 % higher PM2.5 emissions, demonstrating the large role of technology in reducing emissions in 2010. However, if fuel consumption had remained constant starting in 1970, the EU would have benefited from current technology and emission control ...

International audience ; The EDGAR (Emissions Database for Global Atmospheric Research) v4.3 global anthropogenic emissions inventory of several gaseous (SO2, NOx, CO, non-methane volatile organic compounds (NMVOCs) and NH3) and particulate (PM10, PM2.5, black and organic carbon (BC and OC)) air pollutants for the period 1970–2010 is used to develop retrospective air pollution emission scenarios to quantify the roles and contributions of changes in fuels consumption, technology, end-of-pipe emission reduction measures and their resulting impact on health and crop yields. This database presents changes in activity data, fuels and air pollution abatement technology for the past 4 decades, using international statistics and following guidelines for bottom-up emission inventory at the Tier 1 and Tier 2 levels with region-specific default values. With two further retrospective scenarios we assess (1) the impact of the technology and end-of-pipe (EOP) reduction measures in the European Union (EU) by considering a stagnation of technology with constant emission factors from 1970 and with no further abatement measures and improvement in European emissions standards, but fuel consumption occurring at historical pace, and (2) the impact of increased fuel consumption by considering unchanged energy use with constant fuel consumption since 1970, but technological development and end-of-pipe reductions. Our scenario analysis focuses on the three most important and most regulated sectors (power generation, the manufacturing industry and road transport), which are subject of multi-pollutant EU Air Quality regulations. If technology and European EOP reduction measures had stagnated at 1970 levels, EU air quality in 2010 would have suffered from 129 % higher SO2, 71 % higher NOx and 69 % higher PM2.5 emissions, demonstrating the large role of technology in reducing emissions in 2010. However, if fuel consumption had remained constant starting in 1970, the EU would have benefited from current technology and emission control standards, with reductions in NOx by even 13 % more. Such further savings are not observed for SO2 and PM2.5. If the EU consumed the same amount of fuels as in 1970 but with the current technology and emission control standards, then the emissions of SO2 and PM2.5 would be 42 % respectively 10 % higher. This scenario shows the importance for air quality of abandoning heavy residual fuel oil and shifting fuel types (from, e.g., coal to gas) in the EU. A reduced-form TM5-FASST (Fast Screening Scenario Tool based on the global chemical Transport Model 5) is applied to calculate regional and global levels of aerosol and ozone concentrations and to assess the impact of air quality improvements on human health and crop yield loss, showing substantial impacts of export of EU technologies and standards to other world regions.

For the investigation of megacity emission development and the impact outside the source region, mobile aerosol and trace gas measurements were carried out in the Paris metropolitan area between 1 July and 31 July 2009 (summer conditions) and 15 January and 15 February 2010 (winter conditions) in the framework of the European Union FP7 MEGAPOLI project. Two mobile laboratories, MoLa and MOSQUITA, were deployed, and here an overview of these measurements and an investigation of the applicability of such measurements for the analysis of megacity emissions are presented. Both laboratories measured physical and chemical properties of fine and ultrafine aerosol particles as well as gas phase constituents of relevance for urban pollution scenarios. The applied measurement strategies include cross-section measurements for the investigation of plume structure and quasi-Lagrangian measurements axially along the flow of the city's pollution plume to study plume aging processes. Results of intercomparison measurements between the two mobile laboratories represent the adopted data quality assurance procedures. Most of the compared measurement devices show sufficient agreement for combined data analysis. For the removal of data contaminated by local pollution emissions a video tape analysis method was applied. Analysis tools like positive matrix factorization and peak integration by key analysis applied to high-resolution time-of-flight aerosol mass spectrometer data are used for in-depth data analysis of the organic particulate matter. Several examples, including a combination of MoLa and MOSQUITA measurements on a cross section through the Paris emission plume, are provided to demonstrate how such mobile measurements can be used to investigate the emissions of a megacity. A critical discussion of advantages and limitations of mobile measurements for the investigation of megacity emissions completes this work. ; ISSN:1867-1381 ; ISSN:1867-8548

Uploaded files can be used to generate all figures of the results form our publication. The publication deals with long-term ambient aerosol mass spectrometric data that was analyzed with a statistical model (PMF) to obtain source contributions & fingerprints. The new aspects of this manuscript involve time-dependent source fingerprints by a rolling technique and the replacement of the full visual inspection of each run, by a user-defined set of criteria to monitor the quality of each of these runs more efficiently. More reliable sources will finally provide better instruments for political mitigation strategies.

The growth in anthropogenic carbon dioxide ( CO 2 ) emissions acts as a major climate change driver, which has widespread implications across society, influencing the scientific, political, and public sectors. For an increased understanding of the CO 2 emission sources, patterns, and trends, a link between the emission inventories and observed CO 2 concentrations is best established via Earth system modelling and data assimilation. Bringing together the different pieces of the puzzle of a very different nature (measurements, reported statistics, and models), it is of utmost importance to know their level of confidence and boundaries well. Inversions disaggregate the variation in observed atmospheric CO 2 concentration to variability in CO 2 emissions by constraining the regional distribution of CO 2 fluxes, derived either bottom-up from statistics or top-down from observations. The level of confidence and boundaries for each of these CO 2 fluxes is as important as their intensity, though often not available for bottom-up anthropogenic CO 2 emissions. This study provides a postprocessing tool CHE_UNC_APP for anthropogenic CO 2 emissions to help assess and manage the uncertainty in the different emitting sectors. The postprocessor is available under https://doi.org/10.5281/zenodo.5196190 (Choulga et al., 2021). Recommendations are given for regrouping the sectoral emissions, taking into account their uncertainty instead of their statistical origin; for addressing local hot spots; for the treatment of sectors with small budget but uncertainties larger than 100 %; and for the assumptions around the classification of countries based on the quality of their statistical infrastructure. This tool has been applied to the EDGARv4.3.2_FT2015 dataset, resulting in seven input grid maps with upper- and lower-half ranges of uncertainty for the European Centre for Medium-Range Weather Forecasts Integrated Forecasting System. The dataset is documented and available under https://doi.org/10.5281/zenodo.3967439 (Choulga et al., 2020). While the uncertainty in most emission groups remains relatively small (5 %–20 %), the largest contribution (usually over 40 %) to the total uncertainty is determined by the OTHER group (of fuel exploitation and transformation but also agricultural soils and solvents) at the global scale. The uncertainties have been compared for selected countries to those reported in the inventories submitted to the United Nations Framework Convention on Climate Change and to those assessed for the European emission grid maps of the Netherlands Organisation for Applied Scientific Research. Several sensitivity experiments are performed to check (1) the country dependence (by analysing the impact of assuming either a well- or less well-developed statistical infrastructure), (2) the fuel type dependence (by adding explicit information for each fuel type used per activity from the Intergovernmental Panel on Climate Change), and (3) the spatial source distribution dependence (by aggregating all emission sources and comparing the effect against an even redistribution over the country). The first experiment shows that the SETTLEMENTS group (of energy for buildings) uncertainty changes the most when development level is changed. The second experiment shows that fuel-specific information reduces uncertainty in emissions only when a country uses several different fuels in the same amount; when a country mainly uses the most globally typical fuel for an activity, uncertainty values computed with and without detailed fuel information are the same. The third experiment highlights the importance of spatial mapping.

The growth in anthropogenic carbon dioxide (CO2) emissions acts as a major climate change driver, which has widespread implications across society, influencing the scientific, political, and public sectors. For an increased understanding of the CO2 emission sources, patterns, and trends, a link between the emission inventories and observed CO2 concentrations is best established via Earth system modelling and data assimilation. Bringing together the different pieces of the puzzle of a very different nature (measurements, reported statistics, and models), it is of utmost importance to know their level of confidence and boundaries well. Inversions disaggregate the variation in observed atmospheric CO2 concentration to variability in CO2 emissions by constraining the regional distribution of CO2 fluxes, derived either bottom-up from statistics or top-down from observations. The level of confidence and boundaries for each of these CO2 fluxes is as important as their intensity, though often not available for bottom-up anthropogenic CO2 emissions. This study provides a postprocessing tool CHE_UNC_APP for anthropogenic CO2 emissions to help assess and manage the uncertainty in the different emitting sectors. The postprocessor is available under https://doi.org/10.5281/zenodo.5196190 (Choulga et al., 2021). Recommendations are given for regrouping the sectoral emissions, taking into account their uncertainty instead of their statistical origin; for addressing local hot spots; for the treatment of sectors with small budget but uncertainties larger than 100 %; and for the assumptions around the classification of countries based on the quality of their statistical infrastructure. This tool has been applied to the EDGARv4.3.2_FT2015 dataset, resulting in seven input grid maps with upper- and lower-half ranges of uncertainty for the European Centre for Medium-Range Weather Forecasts Integrated Forecasting System. The dataset is documented and available under https://doi.org/10.5281/zenodo.3967439 (Choulga et al., 2020). While the uncertainty in most emission groups remains relatively small (5 %–20 %), the largest contribution (usually over 40 %) to the total uncertainty is determined by the OTHER group (of fuel exploitation and transformation but also agricultural soils and solvents) at the global scale. The uncertainties have been compared for selected countries to those reported in the inventories submitted to the United Nations Framework Convention on Climate Change and to those assessed for the European emission grid maps of the Netherlands Organisation for Applied Scientific Research. Several sensitivity experiments are performed to check (1) the country dependence (by analysing the impact of assuming either a well- or less well-developed statistical infrastructure), (2) the fuel type dependence (by adding explicit information for each fuel type used per activity from the Intergovernmental Panel on Climate Change), and (3) the spatial source distribution dependence (by aggregating all emission sources and comparing the effect against an even redistribution over the country). The first experiment shows that the SETTLEMENTS group (of energy for buildings) uncertainty changes the most when development level is changed. The second experiment shows that fuel-specific information reduces uncertainty in emissions only when a country uses several different fuels in the same amount; when a country mainly uses the most globally typical fuel for an activity, uncertainty values computed with and without detailed fuel information are the same. The third experiment highlights the importance of spatial mapping.

Anthropogenic carbon dioxide (CO 2 ) emissions and their observed growing trends raise awareness in scientific, political and public sectors of the society as the major driver of climate-change. For an increased understanding of the CO 2 emission sources, patterns and trends, a link between the emission inventories and observed CO 2 concentrations is best established via Earth system modelling and data assimilation. In this study anthropogenic CO 2 emission inventories are processed into gridded maps to provide an estimate of prior CO 2 emissions for 7 main emissions groups: 1) power generation super-emitters and 2) energy production average-emitters, 3) manufacturing, 4) settlements, 5) aviation, 6) transport and 7) others, with estimation of their uncertainty and covariance to be included in the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS). The emission inventories are sourced from the Intergovernmental Panel on Climate Change (IPCC) 2006 Guidelines for National Greenhouse Gas Inventories and revised information from its 2019 Refinements, and the global grid-maps of Emissions Database for Global Atmospheric Research (EDGAR) inventory. The anthropogenic CO 2 emissions for 2012 and 2015, (EDGAR versions 4.3.2 and 4.3.2_FT2015 respectively) are considered, updated with improved apportionment of the energy sector, energy usage for manufacturing and diffusive CO 2 emissions from coal mines. These emissions aggregated into 7 ECMWF groups with their emission uncertainties are calculated per country considering its statistical infrastructure development level and sector considering the most typical fuel type and use the IPCC recommended error propagation method assuming fully uncorrelated emissions to generate covariance matrices of parsimonious dimension (7×7). While the uncertainty of most groups remains relatively small, the largest contribution to the total uncertainty is determined by the group with usually the smallest budget, consisting of oil refineries and transformation industry, fuel exploitation, coal production, agricultural soils and solvents and products use emissions. Several sensitivity studies are performed: for country type (with well-/less well-developed statistical infrastructure), for fuel type specification, and for national emission source distribution (highlights the importance of 30 accurate point source mapping). Uncertainties are compared with United Nations Framework Convention on Climate Change (UNFCCC) and the Netherlands Organisation for Applied Scientific Research (TNO) data. Upgraded anthropogenic CO 2 emission maps with their yearly and monthly uncertainties are combined into the CHE_EDGAR-ECMWF_2015 dataset (Choulga et al., 2020) available from https://doi.org/10.5281/zenodo.3712339 .

The Emissions Database for Global Atmospheric Research (EDGAR) compiles anthropogenic emissions data for greenhouse gases (GHGs), and for multiple air pollutants, based on international statistics and emission factors. EDGAR data provide quantitative support for atmospheric modelling and for mitigation scenario and impact assessment analyses as well as for policy evaluation. The new version (v4.3.2) of the EDGAR emission inventory provides global estimates, broken down to IPCC-relevant source-sector levels, from 1970 (the year of the European Union's first Air Quality Directive) to 2012 (the end year of the first commitment period of the Kyoto Protocol, KP). Strengths of EDGAR v4.3.2 include global geo-coverage (226 countries), continuity in time, and comprehensiveness in activities. Emissions of multiple chemical compounds, GHGs as well as air pollutants, from relevant sources (fossil fuel activities but also, for example, fermentation processes in agricultural activities) are compiled following a bottom-up (BU), transparent and IPCC-compliant methodology. This paper describes EDGAR v4.3.2 developments with respect to three major long-lived GHGs (HYDRO, CH 4 , and HYDRO) derived from a wide range of human activities apart from the land-use, land-use change and forestry (LULUCF) sector and apart from savannah burning; a companion paper quantifies and discusses emissions of air pollutants. Detailed information is included for each of the IPCC-relevant source sectors, leading to global totals for 2010 (in the middle of the first KP commitment period) (with a 95% confidence interval in parentheses): HYDRO PgCO HYDRO yr HYDRO, HYDRO PgCH HYDRO yr HYDRO, and HYDRO TgN HYDRO Oyr HYDRO. We provide uncertainty factors in emissions data for the different GHGs and for three different groups of countries: OECD countries of 1990, countries with economies in transition in 1990, and the remaining countries in development (the UNFCCC non-Annex I parties). We document trends for the major emitting countries together with the European Union in more for each source sector.

International audience ; Reliable quantification of the sources and sinks of atmospheric carbon dioxide (CO2), including that of their trends and uncertainties, is essential to monitoring the progress in mitigating anthropogenic emissions under the Kyoto Protocol and the Paris Agreement. This study provides a consolidated synthesis of estimates for all anthropogenic and natural sources and sinks of CO2 for the European Union and UK (EU27 + UK), derived from a combination of state-of-the-art bottom-up (BU) and top-down (TD) data sources and models. Given the wide scope of the work and the variety of datasets involved, this study focuses on identifying essential questions which need to be answered to properly understand the differences between various datasets, in particular with regards to the less-well-characterized fluxes from managed ecosystems. The work integrates recent emission inventory data, process-based ecosystem model results, data-driven sector model results and inverse modeling estimates over the period 1990–2018. BU and TD products are compared with European national greenhouse gas inventories (NGHGIs) reported under the UNFCCC in 2019, aiming to assess and understand the differences between approaches. For the uncertainties in NGHGIs, we used the standard deviation obtained by varying parameters of inventory calculations, reported by the member states following the IPCC Guidelines. Variation in estimates produced with other methods, like atmospheric inversion models (TD) or spatially disaggregated inventory datasets (BU), arises from diverse sources including within-model uncertainty related to parameterization as well as structural differences between models. In comparing NGHGIs with other approaches, a key source of uncertainty is that related to different system boundaries and emission categories (CO2 fossil) and the use of different land use definitions for reporting emissions from land use, land use change and forestry (LULUCF) activities (CO2 land). At the EU27 + UK level, the NGHGI (2019) ...

International audience ; Reliable quantification of the sources and sinks of atmospheric carbon dioxide (CO2), including that of their trends and uncertainties, is essential to monitoring the progress in mitigating anthropogenic emissions under the Kyoto Protocol and the Paris Agreement. This study provides a consolidated synthesis of estimates for all anthropogenic and natural sources and sinks of CO2 for the European Union and UK (EU27 + UK), derived from a combination of state-of-the-art bottom-up (BU) and top-down (TD) data sources and models. Given the wide scope of the work and the variety of datasets involved, this study focuses on identifying essential questions which need to be answered to properly understand the differences between various datasets, in particular with regards to the less-well-characterized fluxes from managed ecosystems. The work integrates recent emission inventory data, process-based ecosystem model results, data-driven sector model results and inverse modeling estimates over the period 1990–2018. BU and TD products are compared with European national greenhouse gas inventories (NGHGIs) reported under the UNFCCC in 2019, aiming to assess and understand the differences between approaches. For the uncertainties in NGHGIs, we used the standard deviation obtained by varying parameters of inventory calculations, reported by the member states following the IPCC Guidelines. Variation in estimates produced with other methods, like atmospheric inversion models (TD) or spatially disaggregated inventory datasets (BU), arises from diverse sources including within-model uncertainty related to parameterization as well as structural differences between models. In comparing NGHGIs with other approaches, a key source of uncertainty is that related to different system boundaries and emission categories (CO2 fossil) and the use of different land use definitions for reporting emissions from land use, land use change and forestry (LULUCF) activities (CO2 land). At the EU27 + UK level, the NGHGI (2019) ...

International audience ; Reliable quantification of the sources and sinks of greenhouse gases, together with trends and uncertainties, is essential to monitoring the progress in mitigating anthropogenic emissions under the Paris Agreement. This study provides a consolidated synthesis of CH4 and N2O emissions with consistently derived state-of-the-art bottom-up (BU) and top-down (TD) data sources for the European Union and UK (EU27 + UK). We integrate recent emission inventory data, ecosystem process-based model results and inverse modeling estimates over the period 1990–2017. BU and TD products are compared with European national greenhouse gas inventories (NGHGIs) reported to the UN climate convention UNFCCC secretariat in 2019. For uncertainties, we used for NGHGIs the standard deviation obtained by varying parameters of inventory calculations, reported by the member states (MSs) following the recommendations of the IPCC Guidelines. For atmospheric inversion models (TD) or other inventory datasets (BU), we defined uncertainties from the spread between different model estimates or model-specific uncertainties when reported. In comparing NGHGIs with other approaches, a key source of bias is the activities included, e.g., anthropogenic versus anthropogenic plus natural fluxes. In inversions, the separation between anthropogenic and natural emissions is sensitive to the geospatial prior distribution of emissions. Over the 2011–2015 period, which is the common denominator of data availability between all sources, the anthropogenic BU approaches are directly comparable, reporting mean emissions of 20.8 Tg CH4 yr−1 (EDGAR v5.0) and 19.0 Tg CH4 yr−1 (GAINS), consistent with the NGHGI estimates of 18.9 ± 1.7 Tg CH4 yr−1. The estimates of TD total inversions give higher emission estimates, as they also include natural emissions. Over the same period regional TD inversions with higher-resolution atmospheric transport models give a mean emission of 28.8 Tg CH4 yr−1. Coarser-resolution global TD inversions are consistent ...