Articles | Volume 16, issue 6
https://doi.org/10.5194/essd-16-2811-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-16-2811-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
14 Jun 2024
Data description paper |
| 14 Jun 2024
| 14 Jun 2024
Insights into the spatial distribution of global, national, and subnational greenhouse gas emissions in the Emissions Database for Global Atmospheric Research (EDGAR v8.0)
Monica Crippa
Unisystems S.A., Milan, Italy
Diego Guizzardi
European Commission, Joint Research Centre (JRC), Ispra, Italy
Federico Pagani
Unisystems S.A., Milan, Italy
Marcello Schiavina
NTT DATA, Rue de Spa 8, 1000 Brussels, Belgium
Michele Melchiorri
European Commission, Joint Research Centre (JRC), Ispra, Italy
Enrico Pisoni
CORRESPONDING AUTHOR
European Commission, Joint Research Centre (JRC), Ispra, Italy
Francesco Graziosi
European Commission, Joint Research Centre (JRC), Ispra, Italy
Marilena Muntean
European Commission, Joint Research Centre (JRC), Ispra, Italy
Joachim Maes
European Commission, Directorate-General for Regional and Urban Policy, Brussels, Belgium
Lewis Dijkstra
European Commission, Joint Research Centre (JRC), Ispra, Italy
European Commission, Directorate-General for Regional and Urban Policy, Brussels, Belgium
Martin Van Damme
Université libre de Bruxelles (ULB), Spectroscopy, Quantum Chemistry and Atmospheric Remote Sensing (SQUARES), Brussels, Belgium
Royal Belgian Institute for Space Aeronomy (BIRA-IASB), Brussels, Belgium
Lieven Clarisse
Université libre de Bruxelles (ULB), Spectroscopy, Quantum Chemistry and Atmospheric Remote Sensing (SQUARES), Brussels, Belgium
Pierre Coheur
Université libre de Bruxelles (ULB), Spectroscopy, Quantum Chemistry and Atmospheric Remote Sensing (SQUARES), Brussels, Belgium
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11 citations as recorded by crossref.
- Lifetime exposure to health-related air pollutants in the United Kingdom: A spatiotemporal evaluation (1930–2010) through WRF-CMAQ modeling G. Chen et al. 10.1016/j.atmosenv.2025.121093
- Assessment of thermal power plant CO2 emissions quantification performance and uncertainty of measurements by ground-based remote sensing C. Li et al. 10.1016/j.envpol.2024.124886
- Emerging carbon dioxide hotspots in East Asia identified by a top-down inventory L. Xia et al. 10.1038/s43247-024-01991-7
- Enhancing Space-Based Tracking of Fossil Fuel CO2 Emissions via Synergistic Integration of OCO-2, OCO-3, and TROPOMI Measurements T. Li et al. 10.1021/acs.est.4c05896
- Mapping the Global Carbon Emissions of Marine Sectors C. Feng et al. 10.1021/acs.est.4c09209
- Learn from Simulations, Adapt to Observations: Super-Resolution of Isoprene Emissions via Unpaired Domain Adaptation A. Giganti et al. 10.3390/rs16213963
- Quantifying the impact of air pollution from coal-fired electricity generation on crop productivity in India K. Singh et al. 10.1073/pnas.2421679122
- Changes in global NO2 pollution by shipping during the COVID-19 lockdown: Implication for sustainable marine operations S. Athul et al. 10.1016/j.jhazmat.2024.136482
- Temporal-spatial characteristics and driver pattern of methane emission in heterogeneous Chinese cities C. Xu et al. 10.1016/j.jclepro.2025.144748
- Satellite quantification of methane emissions from South American countries: a high-resolution inversion of TROPOMI and GOSAT observations S. Hancock et al. 10.5194/acp-25-797-2025
- SO2 emissions derived from TROPOMI observations over India using a flux-divergence method with variable lifetimes Y. Chen et al. 10.5194/acp-25-1851-2025
1 citations as recorded by crossref.
Latest update: 22 Feb 2025
Short summary
Knowing where emissions occur is essential for planning effective emission reduction measures and atmospheric modelling. Disaggregating national emissions over high-resolution grids requires spatial proxies that contain information on the location of different emission sources. This work incorporates state-of-the-art spatial information to improve the spatial representation of global emissions with the Emissions Database for Global Atmospheric Research (EDGAR).
Knowing where emissions occur is essential for planning effective emission reduction measures...
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