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Mercury (Hg) is a strong neurotoxin with substantial dangers to human health. Hg undergoes active global cycles, and the emission sources there of can also be geographically relocated through economic trade. Through investigation of a longer chain of the global biogeochemical Hg cycle from economic production to human health, international cooperation on Hg control strategies in Minamata Convention can be facilitated. In the present study, four global models are combined to investigate the effect of international trade on the relocation of Hg emissions, pollution, exposure, and related human health impacts across the world. The results show that 47% of global Hg emissions are related to commodities consumed outside of the countries where the emissions are produced, which has largely influenced the environmental Hg levels and human exposure thereto across the world. Consequently, international trade is found to enable the whole world to avoid 5.7 × 105 points for intelligence quotient (IQ) decline and 1,197 deaths from fatal heart attacks, saving a total of $12.5 billion (2020 USD) in economic loss. Regionally, international trade exacerbates Hg challenges in less developed countries, while resulting in an alleviation in developed countries. The change in economic loss therefore varies from the United States (−$4.0 billion) and Japan (−$2.4 billion) to China (+$2.7 billion). The present results reveal that international trade is a critical factor but might be largely overlooked in global Hg pollution mitigation.

Quantification of land surface-atmosphere fluxes of carbon dioxide (CO2) fluxes 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 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, 2021b). 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 ecosystems. The work integrates updated emission inventory data, process-based model results, data-driven sectoral 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 European National Greenhouse Gas Inventories (NGHGIs) 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 NGHGIs 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 3392 ± 49 Tg CO2 yr-1 (926 ± 13 Tg C yr-1), while eight other BU sources report a mean value of 3340 [3238,3401] [25th,75th percentile] Tg CO2 yr-1 (948 [937,961] Tg C yr-1). The sole top-down inversion of fossil emissions currently available accounts for 3800 Tg CO2 yr-1 (1038 Tg C yr-1), a value close to that of the NGHGI, but for which uncertainty estimates are not yet available. For the net CO2 land fluxes, during the most recent five-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 five-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 percentile of [-135,45] Tg C yr-1), and was calculated after removing land-atmosphere CO2 fluxes caused by lateral transport of carbon (crops, wood trade and inland waters) resulting in increased agreement with the the NGHGI and bottom-up approaches. Results at the sub-sector level (Forestland, Cropland, Grassland) show generally good agreement between the NGHGI and sub-sector-specific models, but results for a DGVM are mixed. Overall, for both CO2 fossil and net CO2 land fluxes, we find 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 large uncertainties on net uptake of CO2 by the land surface prevent trend identification. 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. The data used to plot the figures are available at https://doi.org/10.5281/zenodo.7365863.

This study, performed under the umbrella of the Task Force on Hemispheric Transport of Air Pollution (TF-HTAP), responds to the need of the global and regional atmospheric modelling community of having a mosaic emission inventory of air pollutants that conforms to specific requirements: global coverage, long time series, spatially distributed emissions with high time resolution, and a high sectoral resolution. The mosaic approach of integrating official regional emission inventories based on locally reported data, with a global inventory based on a globally consistent methodology, allows modellers to perform simulations of a high scientific quality while also ensuring that the results remain relevant to policymakers. HTAP_v3, an ad-hoc global mosaic of anthropogenic inventories, has been developed by integrating official inventories over specific areas (North America, Europe, Asia including Japan and Korea) with the independent Emissions Database for Global Atmospheric Research (EDGAR) inventory for the remaining world regions. The results are spatially and temporally distributed emissions of SO2, NOx, CO, NMVOC, NH3, PM10, PM2.5, Black Carbon (BC), and Organic Carbon (OC), with a spatial resolution of 0.1 x 0.1 degree and time intervals of months and years covering the period 2000–2018 (DOI 10.5281/zenodo.7516361, https://edgar.jrc.ec.europa.eu/dataset_htap_v3). The emissions are further disaggregated to 16 anthropogenic emitting sectors. This paper describes the methodology applied to develop such an emission mosaic, reports on source allocation, differences among existing inventories, and best practices for the mosaic compilation. One of the key strengths of the HTAP_v3 emission mosaic is its temporal coverage, enabling the analysis of emission trends over the past two decades. The development of a global emission mosaic over such long time series represents a unique product for global air quality modelling and for better-informed policy making, reflecting the community effort expended by the TF-HTAP to disentangle the complexity of transboundary transport of air pollution.

Knowledge of the spatial distribution of the fluxes of greenhouse gases and their temporal variability as well as flux attribution to natural and anthropogenic processes is essential to monitoring the progress in mitigating anthropogenic emissions under the Paris Agreement and to inform its Global Stocktake. This study provides a consolidated synthesis of CH4 and N2O emissions using bottom-up (BU) and top-down (TD) approaches for the European Union and UK (EU27+UK) and updates earlier syntheses (Petrescu et al., 2020, 2021). The work integrates updated emission inventory data, process-based model results, data-driven sector model results, inverse modelling estimates, and extends the previous period 1990–2017 to 2020. BU and TD products are compared with European National GHG Inventories (NGHGI) reported by Parties under the United Nations Framework Convention on Climate Change (UNFCCC) in 2021. The uncertainties of NGHGIs were evaluated using the standard deviation obtained by varying parameters of inventory calculations, 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), arise from diverse sources including within-model uncertainty related to parameterization as well as structural differences between models. By comparing NGHGIs with other approaches, the activities included are a key source of bias between estimates e.g. anthropogenic and natural fluxes, which, in atmospheric inversions are sensitive to the prior geospatial distribution of emissions. For CH4 emissions, over the updated 2015–2019 period, which covers a sufficiently robust number of overlapping estimates, and most importantly the NGHGIs, the anthropogenic BU approaches are directly comparable, accounting for mean emissions of 20.5 Tg CH4 yr−1 (EDGAR v5v6.0, last year 2018) and 18.4 Tg CH4 yr−1 (GAINS, 2015), close to the NGHGI estimates of 17.5 ± 2.1 Tg CH4 yr−1. TD inversions estimates give higher emission estimates, as they also detect natural emissions. Over the same period, high resolution regional TD inversions report a mean emission of 34 Tg CH4 yr−1. Coarser-resolution global-scale TD inversions result in emission estimates of 23 Tg CH4 yr−1 and 24 Tg CH4 yr−1 inferred from GOSAT and surface (SURF) network atmospheric measurements, respectively. The magnitude of natural peatland and mineral soils emissions from the JSBACH-HIMMELI model, natural rivers, lakes and reservoirs emissions, geological sources and biomass burning together could account for the gap between NGHGI and inversions and account for 8 Tg CH4 yr−1. For N2O emissions, over the 2015–2019 period, both BU products (EDGAR v5v6.0 and GAINS) report a mean value of anthropogenic emissions of 0.9 Tg N2O yr−1, close to the NGHGI data (0.8 ± 55 % Tg N2O yr−1). Over the same period, the mean of TD global and regional inversions was 1.4 Tg N2O yr−1 (excluding TOMCAT which reported no data). The TD and BU comparison method defined in this study can be "operationalized" for future annual updates for the calculation of CH4 and N2O budgets at the national and EU27+UK scales. Future comparability will be enhanced with further steps involving analysis at finer temporal resolutions and estimation of emissions over intra-annual timescales, of great importance for CH4 and N2O, which may help identify sector contributions to divergence between prior and posterior estimates at the annual/inter-annual scale. Even if currently comparison between CH4 and N2O inversions estimates and NGHGIs is highly uncertain because of the large spread in the inversion results, TD inversions inferred from atmospheric observations represent the most independent data against which inventory totals can be compared. With anticipated improvements in atmospheric modelling and observations, as well as modelling of natural fluxes, TD inversions may arguably emerge as the most powerful tool for verifying emissions inventories for CH4, N2O and other GHGs. The referenced datasets related to figures are visualized at https://doi.org/10.5281/zenodo.6992472 (Petrescu et al., 2022).

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

Emission inventories of greenhouse gases built up from international statistics of human-related activities and emission factors (often referred to as ‘bottom-up’ inventories) are at the core of emission trend analysis to inform policy actions and scientific applications, to support climate negotiation and pledges for mitigation options.Increasingly gaining importance is the quantification of the inherent uncertainty of these inventories that could allow moving towards a verification system in support of the enhanced transparency framework of the Paris Agreement, in particular the global stocktakes. Recently, two H2020 projects – CHE (CO2 Human Emissions) and VERIFY – are focusing on this sensible aspect. This paper produces an unprecedented propagation of uncertainty applied to emissions of CO2, CH4 and N2O, impinging in both projects. Starting from the human emission estimates of the Emission Database for Global Atmospheric Research (EDGAR), which encompasses historic and sectoral emissions from all world countries and using the error propagation method, uncertainties of the CO2, CH4 and N2O emissions were computed per sector and country.The devised methodology applies uncertainty stemming from statistics of human activity and emission factors using the guidelines of Intergovernmental Panel on Climate Change (IPCC 2006). The analysis takes into consideration the accuracy of emission estimates for developed versus developing countries, correlation arising from sector aggregation, and includes an ad-hoc treatment for specific sources and country specific emission factors. The results of emissions and their uncertainties are available for all world countries and all IPCC/EDGAR sectors, and for each country, the share of the total uncertainty each sector is responsible for, is identified.Our results show that world-wide CO2, CH4 and N2O emissions lies in a confidence range of 5%, 33% and in excess of 100%, respectively. The sectors most responsible for such uncertainty depend strongly on the statistical infrastructure of the country but we observe in general that few sectors with smaller emission total are contributing to a large proportion of the total uncertainty.This global uncertainty assessment aims at contributing to the European initiative of the CO2 Monitoring Task Force, building up an operational greenhouse gas monitoring and verification support capacity.

During the last 30 years, the global energy sector has undergone through significant transformation, delivering a considerably larger electricity output whilst attempting to reduce air pollutant and greenhouse gas emissions. The international community has tackled this challenging dilemma by implementing different kind of policies and by encouraging several types of technological changes; including the partial replacement of coal and liquid fossil fuels by low carbon energy vectors (natural gas and renewable sources), the incorporation of more efficient power trains (natural gas fired combined cycles and supercritical coal fired plants) and the deployment of primary and secondary treatment processes for limiting air pollutant concentration in flue gases.EDGAR is a unique global emission database due to its high sectorial, technological and geographical coverage; reporting greenhouse and air pollutant emission time series (1970-nowadays) in a very detailed way. Research is currently being conducted, aimed at updating the energy conversion and end of pipe processes so that the quantified emissions can better reflect the latest global and regional changes. By using EDGAR new data, it is possible to evaluate the impact of technology and regulatory frameworks on air pollutant emissions as well as to identify possible co-benefits and trade off associated with climate change mitigation policies for the energy industries.This work is intended to study the drivers for greenhouse and air pollutant emission trends within this sector - both in large emitting developed and developing economies; by focusing on the role of demand increase, on the penetration of non-fossil sources and specially on the incorporation of more efficient power islands, combustion and air pollutant abatement units.

Over the last three decades, socio-economic, demographic and technological transitions have been witnessed throughout the world, modifying both sectorial and geographical distributions of greenhouse gas (GHG) emissions. Understanding these trends is central to the design of current and future climate change mitigation policies, requiring up-to-date methodologically robust emission inventories such as the Emissions Database for Global Atmospheric Research (EDGAR), the European Commission’s in-house, independent global emission inventory. EDGAR is a key tool to track the evolution of GHG emissions and contributes to quantifying the global carbon budget, providing independent and systematically calculated emissions for all countries. According to the results of the EDGAR v.5.0 release, total anthropogenic global greenhouse gas emissions (excluding land use, land use change and forestry) were estimated at 49.1 Gt CO2eq in 2015, 50 % higher than in 1990, despite a monotonic decrease in GHG emissions per unit of economic output. Between 1990 and 2015, emissions from developed countries fell by 9%, while emissions from low to medium income countries increased by 130%, predominantly from 2000 onwards. The 27 Member States of the European Union and the United Kingdom led the pathway for emission reductions in industrialised economies whilst, in developing countries, the rise in emissions was driven by higher emissions in China, India, Brazil and nations in the South-East Asian region. This diversity of patterns shows how different patterns for GHG emissions are and the need for identifying regionally tailored emission reduction measures.

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.

The Emissions Database for Global Atmospheric Research (EDGAR) compiles anthropogenic global emissions and trends based on international statistics and best-available emission factors, for the use in atmospheric models and in policy evaluation. The new version v4.3.2 of the EDGAR emission inventory provides global emission estimates, disaggregated at source-sector level, for the historic period from 1970 (the year of EU's first Air Quality Directive) until 2012 (the end year of the first commitment period of the Kyoto Protocol). The global geo-coverage and continuous time-series are strengths of the EDGAR database, which applies the same methodology and mainly default emission factors to all world countries, in order to achieve comparability and full transparency. Region-specific emission factors are selected, when these are recommended by IPCC (2006) guidelines or when these are justified by robust information on significant differences in economic activities, in customs or in geographical ambient conditions and proven to be more representative than the global average. This database is not only unique in its space-time coverage, but also in the completeness and consistency of the estimated emissions of multiple pollutants: the greenhouse gases (GHG), air pollutants and aerosols. This publication documents the first part of the EDGAR v4.3.2 emissions database focusing on emissions of the three major greenhouse gases of CO2, CH4 and N2O, from human activities apart from the land-use, land-use change and forestry (LULUCF) sector (including forest and savannah burning). Unlike the activities of the LULUCF sector, which are typically estimated top-down from less certain land-use observations, all these activities are estimated bottom-up from standard annual statistics of fuel, products, waste, crops or livestock. We present country-specific emission totals and analyse the trends and variations in emissions of the largest emitting countries together with the EU in more detail, to uncover the effect of changes in human activities with time on each of the gases. The GWP-100 weighted global total GHG emission trend is predominantly determined by the global CO2 trend and in particular, by fuel markets trends, geopolitical changes and financial crises rather than population changes. We also evaluate the uncertainty in emissions for different sectors and three groups of countries (the OECD countries of 1990, the countries with economies in transition in 1990 and the remaining non-Annex I countries). Even though large progress has been made on emission inventory compilation, the uncertainty in global total GHG emissions has not decreased, because of the increasing share of emissions from countries with less developed statistical infrastructure and secondly the decreasing share of emissions from the activities (e.g. coal power plants) for which relatively accurate information is available. Finally, we discuss changes in geospatial distribution with a focus on hot spots and megacities using gridded information. Data is presented online for each source category with annual and monthly global emissions grid-maps of 0.1° × 0.1° resolution and can be freely accessed from the EDGAR website http://edgar.jrc.ec.europa.eu/overview.php?v=432&SECURE=123 (DOI: https://data.europa.eu/doi/10.2904/JRC_DATASET_EDGAR).

Pollutant emissions need to be accurately estimated to ensure that air quality plans are designed and implemented appropriately. Emission factors (EFs) are empirical functional relations between pollutant emissions and the activity that causes them. In this review article, the techniques used to measure road vehicle emissions are examined in relation to the development of EFs found in emission models used to produce emission inventories. The emission measurement techniques covered include those most widely used for road vehicle emissions data collection, namely chassis and engine dynamometer measurements, remote sensing, road tunnel studies and portable emission measurements systems (PEMS). The main advantages and disadvantages of each method with regards to emissions modelling are presented. A review of the ways in which EFs may be derived from test data is also performed, with a clear distinction between data obtained under controlled conditions (engine and chassis dynamometer measurements using standard driving cycles) and measurements under real-world operation.

A better understanding of the discrepancies in multi-scale inventories could give an insight on their approaches and limitations, and provide indications for further improvements; international, national and plant-by-plant data sources are primarily obtained to compile those inventories. In this study we develop a high-resolution inventory of Hg emissions at 0.05° × 0.05° for Jiangsu China using a bottom-up approach and then compare the results with available global/national inventories. With detailed information on individual sources and the updated emission factors from field measurements incorporated, the annual Hg emissions of anthropogenic origin in Jiangsu 2010 are estimated at 39 105 kg, of which 51 %, 47 % and 2 % were released as Hg0, Hg2+, and HgP, respectively. This provincial inventory is thoroughly compared to the downscaled results from three national inventories (NJU, THU and BNU) and two global inventories (AMAP/UNEP and EDGARv4.tox2). Attributed to varied methods and data sources, clear information gaps exist in multi-scale inventories, leading to differences in the emission levels, speciation and spatial distributions of atmospheric Hg. The total emissions in the provincial inventory are the largest, i.e., 28 %, 7 %, 19 %, 22 %, and 70 % higher than NJU, THU, BNU, AMAP/UNEP, and EDGARv4.tox2, respectively. For major sectors including power generation, cement, iron & steel and other coal combustion, the Hg contents (HgC) in coals/raw materials, abatement rates of air pollution control devices (APCD) and activity levels are identified as the crucial parameters responsible for the differences in estimated emissions between inventories. Regarding speciated emissions, larger fraction of Hg2+ is found in the provincial inventory than national and global inventories, resulting mainly from the results by the most recent domestic studies in which enhanced Hg2+ were measured for cement and iron & steel plants. Inconsistent information of big power and industrial plants is the main source of differences in spatial distribution of emissions between the provincial and other inventories, particularly in southern and northwestern Jiangsu where intensive coal combustion and industry are located. Quantified with Monte-Carlo simulation, uncertainties of provincial Hg emissions are smaller than those of NJU national inventory, resulting mainly from the more accurate activity data of individual plants and the reduced uncertainties of HgC in coals/raw materials.

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.

The Emission Database for Global Atmospheric Research (EDGAR) provides a time-series of man-made emissions of greenhouse gases and short-lived atmospheric pollutants from 1970 to 2008. Mercury is included in EDGARv4.tox1, thereby enriching the spectrum of multi-pollutant sources in the database. With an average annual growth rate of 1.3% since 1970, EDGARv4 estimates that the global mercury emissions reached 1287 tonnes in 2008. Specifically, gaseous elemental mercury (GEM) (Hg[superscript 0]) accounted for 72% of the global total emissions, while gaseous oxidised mercury (GOM) (Hg[superscript 2 +]) and particle bound mercury (PBM) (Hg-P) accounted for only 22% and 6%, respectively. The less reactive form, i.e., Hg[superscript 0], has a long atmospheric residence time and can be transported long distances from the emission sources. The artisanal and small-scale gold production, accounted for approximately half of the global Hg[superscript 0] emissions in 2008 followed by combustion (29%), cement production (12%) and other metal industry (10%). Given the local-scale impacts of mercury, special attention was given to the spatial distribution showing the emission hot-spots on gridded 0.1° × 0.1° resolution maps using detailed proxy data. The comprehensive ex-post analysis of the mitigation of mercury emissions by end-of-pipe abatement measures in the power generation sector and technology changes in the chlor-alkali industry over four decades indicates reductions of 46% and 93%, respectively. Combined, the improved technologies and mitigation measures in these sectors accounted for 401.7 tonnes of avoided mercury emissions in 2008. A comparison shows that EDGARv4 anthropogenic emissions are nearly equivalent to the lower estimates of the United Nations Environment Programme (UNEP)'s mercury emissions inventory for 2005 for most sectors. An evaluation of the EDGARv4 global mercury emission inventory, including mercury speciation, was performed using the GEOS-Chem global 3-D mercury model. The model can generally reproduce both spatial variations and long-term trends in total gaseous mercury concentrations and wet deposition fluxes., National Science Foundation (U.S.) (Atmospheric Chemistry Program Grant 1053648)