Search

The Emissions Database for Global Atmospheric Research (EDGAR) estimates the human-induced emission rates on Earth. EDGAR collaborates with atmospheric modelling activities and aids policy in the design of mitigation strategies and in evaluating their effectiveness. In these applications, the uncertainty estimate is an essential component, as it quantifies the accuracy and qualifies the level of confidence in the emission. This study complements the EDGAR emissions inventory by providing an estimation of the structural uncertainty stemming from its base components (activity data, AD, statistics and emission factors, EFs) by (i) associating uncertainty to each AD and EF characterizing the emissions of the three main greenhouse gases (GHGs), namely carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O); (ii) combining them; and (iii) making assumptions regarding the cross-country uncertainty aggregation of source categories. It was deemed a natural choice to obtain the uncertainties in EFs and AD statistics from the Intergovernmental Panel on Climate Change (IPCC) guidelines issued in 2006 (with a few exceptions), as the EF and AD sources and methodological aspects used by EDGAR have been built over the years based on the IPCC recommendations, which assured consistency in time and comparability across countries. On the one hand, the homogeneity of the method is one of the key strengths of EDGAR, on the other hand, it facilitates the propagation of uncertainties when similar emission sources are aggregated. For this reason, this study aims primarily at addressing the aggregation of uncertainties' sectorial emissions across GHGs and countries. Globally, we find that the anthropogenic emissions covered by EDGAR for the combined three main GHGs for the year 2015 are accurate within an interval of −15 % to +20 % (defining the 95 % confidence of a log-normal distribution). The most uncertain emissions are those related to N2O from waste and agriculture, while CO2 emissions, although responsible for 74 % of the total GHG emissions, account for approximately 11 % of global uncertainty share. The sensitivity to methodological choices is also discussed.

The Emissions Database for Global Atmospheric Research (EDGAR) estimates the human-induced emission rates on Earth collaborating with atmospheric modelling activities as well as aiding policy in the design of mitigation strategies and in evaluating their effectiveness. In these applications, the uncertainty estimate is an essential component as it quantifies the accuracy and qualifies the level of confidence in the emission. This study complements the EDGAR's emissions inventory with estimation of the structural uncertainty stemming from its base components (activity data statistics (AD) and emission factors (EF)) by i) associating uncertainty to each AD and EF characterizing the emissions of the three main greenhouse gases (GHG) CO2, CH4 and N2O; ii) combining them, and iii) making assumptions for the cross-country uncertainty aggregation of source categories. It was deemed a natural choice to obtain the uncertainties in EFs and AD from the Intergovernmental Panel on Climate Change (IPCC) guidelines issued in 2006 (with a few exceptions), since the EF and AD sources and methodological aspects used by EDGAR have been built over the years based on the IPCC recommendations, which assured consistency in time and comparability across countries. While on one side the homogeneity of the method is one of the key strengths of EDGAR, on the other side it facilitates the propagation of uncertainties when similar emission sources are aggregated. For this reason, this study aims primarily at addressing the aggregation of uncertainties sectorial emissions across GHGs and countries. On global average we find that the anthropogenic emissions of the combined three main GHGs for the year 2015 are accurate within an interval of −15 % to +20 % (defining the 95 % confidence of a log-normal distribution). The most uncertain emissions are those related to N2O from agriculture, while CO2 emissions, although responsible for 74 % of total GHG emissions, accounts for and for approximately 11 % of global uncertainty share. Sensitivity to methodological choices is also discussed.

Emissions into the atmosphere from human activities show marked temporal variations, from inter-annual to hourly levels. The consolidated practice of calculating yearly emissions follows the same temporal allocation of the underlying annual statistics. However, yearly emissions might not reflect heavy pollution episodes, seasonal trends, or any time-dependant atmospheric process. This study develops high-time resolution profiles for air pollutants and greenhouse gases co- emitted by anthropogenic sources in support of atmospheric modelling, Earth observation communities and decision makers. The key novelties of the Emissions Database for Global Atmospheric Research (EDGAR) temporal profiles are the development of (i) country/region- and sector- specific yearly profiles for all sources, (ii) time dependent yearly profiles for sources with inter-annual variability of their seasonal pattern, (iii) country- specific weekly and daily profiles to represent hourly emissions, (iv) a flexible system to compute hourly emissions including input from different users. This work creates a harmonized emission temporal distribution to be applied to any emission database as input for atmospheric models, thus promoting homogeneity in inter-comparison exercises., Measurement(s)air pollution • greenhouse gas • temporal measurementTechnology Type(s)computational modeling techniqueFactor Type(s)sector • geographic locationSample Characteristic - Environmentclimate systemSample Characteristic - LocationEarth (planet) Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.12052887

Non-methane volatile organic compounds (NMVOCs) include a large number of chemical species which differ significantly in their chemical characteristics and thus in their impacts on ozone and secondary organic aerosol formation. It is important that chemical transport models (CTMs) simulate the chemical transformation of the different NMVOC species in the troposphere consistently. In most emission inventories, however, only total NMVOC emissions are reported, which need to be decomposed into classes to fit the requirements of CTMs. For instance, the Emissions Database for Global Atmospheric Research (EDGAR) provides spatially resolved global anthropogenic emissions of total NMVOCs. In this study the EDGAR NMVOC inventory was revised and extended in time and in sectors. Moreover the new version of NMVOC emission data in the EDGAR database were disaggregated on a detailed sector resolution to individual species or species groups, thus enhancing the usability of the NMVOC emission data by the modelling community. Region- and source-specific speciation profiles of NMVOC species or species groups are compiled and mapped to EDGAR processes (detailed resolution of sectors), with corresponding quality codes specifying the quality of the mapping. Individual NMVOC species in different profiles are aggregated to 25 species groups, in line with the common classification of the Global Emissions Initiative (GEIA). Global annual grid maps with a resolution of 0.1° × 0.1° for the period 1970–2012 are produced by sector and species. Furthermore, trends in NMVOC composition are analysed, taking road transport and residential sources in Germany and the United Kingdom (UK) as examples.

The EDGARv4.3.1 (Emissions Database for Global Atmospheric Research) global anthropogenic emissions inventory of gaseous (SO2, NOx, CO, non-methane volatile organic compounds and NH3) and particulate (PM10, PM2.5, black and organic carbon) air pollutants for the period 1970–2010 is used to develop retrospective air pollution emissions scenarios to quantify the roles and contributions of changes in energy consumption and efficiency, technology progress and end-of-pipe emission reduction measures and their resulting impact on health and crop yields at European and global scale. The reference EDGARv4.3.1 emissions include observed and reported changes in activity data, fuel consumption and air pollution abatement technologies over the past 4 decades, combined with Tier 1 and region-specific Tier 2 emission factors. Two further retrospective scenarios assess the interplay of policy and industry. The highest emission STAG_TECH scenario assesses the impact of the technology and end-of-pipe reduction measures in the European Union, by considering historical fuel consumption, along with a stagnation of technology with constant emission factors since 1970, and assuming no further abatement measures and improvement imposed by European emission standards. The lowest emission STAG_ENERGY scenario evaluates the impact of increased fuel consumption by considering unchanged energy consumption since the year 1970, but assuming the technological development, end-of-pipe reductions, fuel mix and energy efficiency of 2010. Our scenario analysis focuses on the three most important and most regulated sectors (power generation, manufacturing industry and road transport), which are subject to multi-pollutant European Union Air Quality regulations. Stagnation of technology and air pollution reduction measures at 1970 levels would have led to 129 % (or factor 2.3) higher SO2, 71 % higher NOx and 69 % higher PM2.5 emissions in Europe (EU27), demonstrating the large role that technology has played in reducing emissions in 2010. However, stagnation of energy consumption at 1970 levels, but with 2010 fuel mix and energy efficiency, and assuming current (year 2010) technology and emission control standards, would have lowered today's NOx emissions by ca. 38 %, SO2 by 50 % and PM2.5 by 12 % in Europe. A reduced-form chemical transport model is applied to calculate regional and global levels of aerosol and ozone concentrations and to assess the associated impact of air quality improvements on human health and crop yield loss, showing substantial impacts of EU technologies and standards inside as well as outside Europe. We assess that the interplay of policy and technological advance in Europe had substantial benefits in Europe, but also led to an important improvement of particulate matter air quality in other parts of the world.

We used chemical transport modelling to better understand the extent to which policy-related anthropogenic mercury emissions changes (a policy signal) can be statistically detected in wet deposition measurements in the Great Lakes region on the subdecadal scale, given sources of noise. In our modelling experiment, we consider hypothetical regional (North American) and global (rest of the world) policy changes, consistent with existing policy efforts (Δglobal = −18%; Δregional = −30%) that divide an eight-year period. The magnitude of statistically significant (p < 0.1) pre- and post-policy period wet deposition differences, holding all else constant except for the policy change, ranges from −0.3 to −2.0% for the regional policy and −0.8 to −2.7% for the global policy. We then introduce sources of noise—trends and variability in factors that are exogenous to the policy action—and evaluate the extent to which the policy signals can still be detected. For instance, technology-related variability in emissions magnitude and speciation can shift the magnitude of differences between periods, in some cases dampening the policy effect. We have found that the interannual variability in meteorology has the largest effect of the sources of noise considered, driving deposition differences between periods to ±20%, exceeding the magnitude of the policy signal. However, our simulations suggest that gaseous elemental mercury concentration may be more robust to this meteorological variability in this region, and a stronger indicator of local/regional emissions changes. These results highlight the potential challenges of detecting statistically significant policy-related changes in Great Lakes wet deposition within the subdecadal scale.

The new version of the Emissions Database for Global Atmospheric Research (EDGAR v4.3.2) compiles gaseous and particulate air pollutant emissions, making use of the same anthropogenic sectors, time period (1970–2012), and international activity data that is used for estimating GHG emissions, as described in a companion paper (Janssens-Maenhout et al., 2017). All human activities, except large scale biomass burning and land use, land-use change, and forestry are included in the emissions calculation. The bottom-up compilation methodology of sector-specific emissions was applied consistently for all world countries, providing methodological transparency and comparability between countries. In addition to the activity data used to estimate GHG emissions, air pollutant emissions are determined by the process technology and end-of-pipe emission reduction abatements. Region-specific emission factors and abatement measures were selected from recent available scientific literature and reports. Compared to previous versions of EDGAR, the EDGAR v4.3.2 dataset covers all gaseous and particulate air pollutants, has extended time series (1970–2012), and has been evaluated with quality control and quality assurance (QC and QA) procedures both for the emission time series (e.g. particulate matter – PM – mass balance, gap-filling for missing data, the split-up of countries over time, few updates in the emission factors, etc.) and grid maps (full coverage of the world, complete mapping of EDGAR emissions with sector-specific proxies, etc.). This publication focuses on the gaseous air pollutants of CO, NOx, SO2, total non-methane volatile organic compounds (NMVOCs), NH3, and the aerosols PM10, PM2.5, black carbon (BC), and organic carbon (OC). Considering the 1970–2012 time period, global emissions of SO2 increased from 99 to 103 Mt, CO from 441 to 562 Mt, NOx from 68 to 122 Mt, NMVOC from 119 to 170 Mt, NH3 from 25 to 59 Mt, PM10 from 37 to 65 Mt, PM2.5 from 24 to 41 Mt, BC from 2.7 to 4.5 Mt, and OC from 9 to 11 Mt. We present the country-specific emission totals and analyze the larger emitting countries (including the European Union) to provide insights on major sector contributions. In addition, per capita and per GDP emissions and implied emission factors – the apparent emissions per unit of production or energy consumption – are presented. We find that the implied emission factors (EFs) are higher for low-income countries compared to high-income countries, but in both cases decrease from 1970 to 2012. The comparison with other global inventories, such as the Hemispheric Transport of Air Pollution Inventory (HTAP v2.2) and the Community Emission Data System (CEDS), reveals insights on the uncertainties as well as the impact of data revisions (e.g. activity data, emission factors, etc.). As an additional metric, we analyze the emission ratios of some pollutants to CO2 (e.g. CO∕CO2, NOx∕CO2, NOx∕CO, and SO2∕CO2) by sector, region, and time to identify any decoupling of air pollutant emissions from energy production activities and to demonstrate the potential of such ratios to compare to satellite-derived emission data. Gridded emissions are also made available for the 1970–2012 historic time series, disaggregated for 26 anthropogenic sectors using updated spatial proxies. The analysis of the evolution of hot spots over time allowed us to identify areas with growing emissions and where emissions should be constrained to improve global air quality (e.g. China, India, the Middle East, and some South American countries are often characterized by high emitting areas that are changing rapidly compared to Europe or the USA, where stable or decreasing emissions are evaluated). Sector- and component-specific contributions to grid-cell emissions may help the modelling and satellite communities to disaggregate atmospheric column amounts and concentrations into main emitting sectors. This work addresses not only the emission inventory and modelling communities, but also aims to broaden the usefulness of information available in a global emission inventory such as EDGAR to also include the measurement community. Data are publicly available online through the EDGAR website http://edgar.jrc.ec.europa.eu/overview.php?v=432_AP and registered under https://doi.org/10.2904/JRC_DATASET_EDGAR.

Speciated mercury gridded emissions inventories together with chemical transport models and concentration measurements are essential when investigating both the effectiveness of mitigation measures and the mercury cycle in the environment. Since different mercury species have contrasting behaviour in the atmosphere, their proportion in anthropogenic emissions could determine the spatial impacts. In this study, the time series from 1970 to 2012 of the EDGARv4.tox2 global mercury emissions inventory are described; the total global mercury emission in 2010 is 1772 tonnes. Global grid-maps with geospatial distribution of mercury emissions at a 0.1° × 0.1° resolution are provided for each year. Compared to the previous tox1 version, tox2 provides updates for more recent years and improved emissions in particular for agricultural waste burning, power generation and artisanal and small-scale gold mining (ASGM) sectors. We have also developed three retrospective emissions scenarios based on different hypotheses related to the proportion of mercury species in the total mercury emissions for each activity sector; improvements in emissions speciation are seen when using information primarily from field measurements. We evaluated them using the GEOS-Chem 3-D mercury model in order to explore the influence of speciation shifts, to reactive mercury forms in particular, on regional wet deposition patterns. The reference scenario S1 (EDGARv4.tox2_S1) uses speciation factors from the Arctic Monitoring and Assessment Programme (AMAP); scenario S2 (“EPA_power”) uses factors from EPA's Information Collection Request (ICR); and scenario S3 (“Asia_filedM”) factors from recent scientific publications. In the reference scenario, the sum of reactive mercury emissions (Hg-P and Hg2+) accounted for 25.3% of the total global emissions; the regions/countries that have shares of reactive mercury emissions higher than 6% in total global reactive mercury are China+ (30.9%), India+ (12.5%) and the United States (9.9%). In 2010, the variations of reactive mercury emissions amongst the different scenarios are in the range of −19.3 t/yr (China+) to 4.4 t/yr (OECD_Europe). However, at the sector level, the variation could be different, e.g., for the iron and steel industry in China reaches 15.4 t/yr. Model evaluation at the global level shows a variation of approximately ±10% in wet deposition for the three emissions scenarios. An evaluation of the impact of mercury speciation within nested grid sensitivity simulations is performed for the United States and modelled wet deposition fluxes are compared with measurements. These studies show that using the S2 and S3 emissions of reactive mercury, can improve wet deposition estimates near sources.