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.

Abstract In this paper, we present ten scenarios developed using the IMAGE2.4 framework (Integrated Model to Assess the Global Environment) to explore how different assumptions on future climate and air pollution policies influence emissions of greenhouse gases and air pollutants. These scenarios describe emission developments in 26 world regions for the 21st century, using a matrix of climate and air pollution policies. For climate policy, the study uses a baseline resulting in forcing levels slightly above RCP6.0 and an ambitious climate policy scenario similar to RCP2.6. For air pollution, the study explores increasingly tight emission standards, ranging from no improvement, current legislation and three variants assuming further improvements. For all pollutants, the results show that more stringent control policies are needed after 2030 to prevent a rise in emissions due to increased activities and further reduce emissions. The results also show that climate mitigation policies have the highest impact on SO2 and NOX emissions, while their impact on BC and OC emissions is relatively low, determined by the overlap between greenhouse gas and air pollutant emission sources. Climate policy can have important co-benefits; a 10% decrease in global CO2 emissions by 2100 leads to a decrease of SO2 and NOX emissions by about 10% and 5%, respectively compared to 2005 levels. In most regions, low levels of air pollutant emissions can also be achieved by solely implementing stringent air pollution policies. The largest differences across the scenarios are found in Asia and other developing regions, where a combination of climate and air pollution policy is needed to bring air pollution levels below those of today.

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.

Successful regulation of greenhouse gas emissions requires knowledge of current methane emission sources. Existing state regulations in California and Massachusetts require ∼15% greenhouse gas emissions reductions from current levels by 2020. However, government estimates for total US methane emissions may be biased by 50%, and estimates of individual source sectors are even more uncertain. This study uses atmospheric methane observations to reduce this level of uncertainty. We find greenhouse gas emissions from agriculture and fossil fuel extraction and processing (i.e., oil and/or natural gas) are likely a factor of two or greater than cited in existing studies. Effective national and state greenhouse gas reduction strategies may be difficult to develop without appropriate estimates of methane emissions from these source sectors.

International audience ; Emission of greenhouse gases (GHGs) and removals from land, including both anthropogenic and natural fluxes, require reliable quantification, including estimates of uncertainties, to support credible mitigation action under the Paris Agreement. This study provides a state-of-the-art scientific overview of bottom-up anthro-pogenic emissions data from agriculture, forestry and other land use (AFOLU) in the European Union (EU28 1). The data integrate recent AFOLU emission inventories with ecosystem data and land carbon models and summarize GHG emissions and removals over the period 1990-2016. This compilation of bottom-up estimates of the AFOLU GHG emissions of European national greenhouse gas inventories (NGHGIs), with those of land carbon models and observation-based estimates of large-scale GHG fluxes, aims at improving the overall estimates of the GHG balance in Europe with respect to land GHG emissions and removals. Whenever available, we present uncertainties, its propagation and role in the comparison of different estimates. While NGHGI data for the EU28 provide consistent quantification of uncertainty following the established IPCC Guidelines, uncertainty in the estimates produced with other methods needs to account for both within model uncertainty and the spread from different model results. The largest inconsistencies between EU28 estimates are mainly due to different sources of data related to human activity, referred to here as activity data (AD) and methodologies (tiers) used for calculating emissions and removals from AFOLU sectors. The referenced datasets related to figures are visualized at https://doi.org/10.

International audience ; Emission of greenhouse gases (GHGs) and removals from land, including both anthropogenic and natural fluxes, require reliable quantification, including estimates of uncertainties, to support credible mitigation action under the Paris Agreement. This study provides a state-of-the-art scientific overview of bottom-up anthro-pogenic emissions data from agriculture, forestry and other land use (AFOLU) in the European Union (EU28 1). The data integrate recent AFOLU emission inventories with ecosystem data and land carbon models and summarize GHG emissions and removals over the period 1990-2016. This compilation of bottom-up estimates of the AFOLU GHG emissions of European national greenhouse gas inventories (NGHGIs), with those of land carbon models and observation-based estimates of large-scale GHG fluxes, aims at improving the overall estimates of the GHG balance in Europe with respect to land GHG emissions and removals. Whenever available, we present uncertainties, its propagation and role in the comparison of different estimates. While NGHGI data for the EU28 provide consistent quantification of uncertainty following the established IPCC Guidelines, uncertainty in the estimates produced with other methods needs to account for both within model uncertainty and the spread from different model results. The largest inconsistencies between EU28 estimates are mainly due to different sources of data related to human activity, referred to here as activity data (AD) and methodologies (tiers) used for calculating emissions and removals from AFOLU sectors. The referenced datasets related to figures are visualized at https://doi.org/10.

International audience ; Emission of greenhouse gases (GHGs) and removals from land, including both anthropogenic and natural fluxes, require reliable quantification, including estimates of uncertainties, to support credible mitigation action under the Paris Agreement. This study provides a state-of-the-art scientific overview of bottom-up anthro-pogenic emissions data from agriculture, forestry and other land use (AFOLU) in the European Union (EU28 1). The data integrate recent AFOLU emission inventories with ecosystem data and land carbon models and summarize GHG emissions and removals over the period 1990-2016. This compilation of bottom-up estimates of the AFOLU GHG emissions of European national greenhouse gas inventories (NGHGIs), with those of land carbon models and observation-based estimates of large-scale GHG fluxes, aims at improving the overall estimates of the GHG balance in Europe with respect to land GHG emissions and removals. Whenever available, we present uncertainties, its propagation and role in the comparison of different estimates. While NGHGI data for the EU28 provide consistent quantification of uncertainty following the established IPCC Guidelines, uncertainty in the estimates produced with other methods needs to account for both within model uncertainty and the spread from different model results. The largest inconsistencies between EU28 estimates are mainly due to different sources of data related to human activity, referred to here as activity data (AD) and methodologies (tiers) used for calculating emissions and removals from AFOLU sectors. The referenced datasets related to figures are visualized at https://doi.org/10.