Abstract
Abstract. 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.
Highlights
Air pollutant emissions represent a major concern for air quality (Monks et al, 2009), climate impacts (Anenmber et al, 2012; IPCC, 2013), health (WHO, 2016), environmental effects (Van Dingenen et al, 2009), and visibility (Wang et al, 2012)
In the recent years several global emission inventories have been developed, such as the one of Lamarque et al (2010), the MACCity by Granier et al (2011), the one documented by Klimont et al (2013) for SO2, the Hemispheric Transport of Air Pollution Inventory (HTAP v2.2) by JanssensMaenhout et al (2015), the Community Emission Data System (CEDS) by Hoesly et al (2018), and the inventory based on Greenhouse Gas and Air Pollution Interactions and Synergies (GAINS), and ECLIPSEV5a by Klimont et al (2017) for particulate matter
The definition of the anthropogenic emission sectors was kept identical to the ones used for the EDGAR v4.3.2 GHG dataset (Janssens-Maenhout et al, 2017) that were based on the Intergovernmental Panel on Climate Change (IPCC,1996) guidelines for which the conversion to the Selected Nomenclature for Air Pollution (SNAP) categories used by TFEIP (Task Force on Emission Inventories and Projections) and the parties of the Convention on Long-range Transboundary Air Pollution (CLRTAP)
Summary
Air pollutant emissions represent a major concern for air quality (Monks et al, 2009), climate impacts (Anenmber et al, 2012; IPCC, 2013), health (WHO, 2016), environmental effects (Van Dingenen et al, 2009), and visibility (Wang et al, 2012). Atmospheric pollutants can be emitted as gaseous compounds, e.g. SO2 (sulfur dioxide), NOx (nitrogen oxides), CO (carbon monoxide), NMVOCs (nonmethane volatile organic compounds), NH3 (ammonia), etc., or as particles with different sizes and composition, e.g. particulate matter with a diameter of less than 10, 2.5, and 1 μm (PM10, PM2.5, and PM1, respectively), black carbon (BC), and organic carbon (OC) These pollutants can be directly injected into the atmosphere by anthropogenic or natural sources (primary emissions), or they can form through secondary chemical–physical processes (secondary components). Despite regional variations, air pollution is a ubiquitous problem with, to a large extent, common solutions between regions To tackle these regional and global aspects, global emission inventories coupled with chemical transport models (CTMs) are useful tools, complementing air pollution measurements that provide information on local and regional air quality impacts.
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