CoCO2-MOSAIC 1.0: a global mosaic of regional, gridded, fossil, and biofuel CO2 emission inventories

  1. Urraca, Ruben
  2. Janssens-Maenhout, Greet
  3. Álamos, Nicolás
  4. Berna-Peña, Lucas
  5. Crippa, Monica
  6. Darras, Sabine
  7. Dellaert, Stijn
  8. Denier van der Gon, Hugo
  9. Dowell, Mark
  10. Gobron, Nadine
  11. Granier, Claire
  12. Grassi, Giacomo
  13. Guevara, Marc
  14. Guizzardi, Diego
  15. Gurney, Kevin
  16. Huneeus, Nicolás
  17. Keita, Sekou
  18. Kuenen, Jeroen
  19. Lopez-Noreña, Ana
  20. Puliafito, Enrique
  21. Roest, Geoffrey
  22. Rossi, Simone
  23. Soulie, Antonin
  24. Visschedijk, Antoon

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1000 Titel
  • CoCO2-MOSAIC 1.0: a global mosaic of regional, gridded, fossil, and biofuel CO2 emission inventories
1000 Autor/in
  1. Urraca, Ruben |
  2. Janssens-Maenhout, Greet |
  3. Álamos, Nicolás |
  4. Berna-Peña, Lucas |
  5. Crippa, Monica |
  6. Darras, Sabine |
  7. Dellaert, Stijn |
  8. Denier van der Gon, Hugo |
  9. Dowell, Mark |
  10. Gobron, Nadine |
  11. Granier, Claire |
  12. Grassi, Giacomo |
  13. Guevara, Marc |
  14. Guizzardi, Diego |
  15. Gurney, Kevin |
  16. Huneeus, Nicolás |
  17. Keita, Sekou |
  18. Kuenen, Jeroen |
  19. Lopez-Noreña, Ana |
  20. Puliafito, Enrique |
  21. Roest, Geoffrey |
  22. Rossi, Simone |
  23. Soulie, Antonin |
  24. Visschedijk, Antoon |
1000 Verlag
  • Copernicus Publications
1000 Erscheinungsjahr 2024
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2024-01-22
1000 Erschienen in
1000 Quellenangabe
  • 16(1):501-523
1000 Copyrightjahr
  • 2024
1000 Lizenz
1000 Verlagsversion
  • https://doi.org/10.5194/essd-16-501-2024 |
1000 Publikationsstatus
1000 Begutachtungsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • <jats:p>Abstract. Gridded bottom-up inventories of CO2 emissions are needed in global CO2 inversion schemes as priors to initialize transport models and as a complement to top-down estimates to identify the anthropogenic sources. Global inversions require gridded datasets almost in near-real time that are spatially and methodologically consistent at a global scale. This may result in a loss of more detailed information that can be assessed by using regional inventories because they are built with a greater level of detail including country-specific information and finer resolution data. With this aim, a global mosaic of regional, gridded CO2 emission inventories, hereafter referred to as CoCO2-MOSAIC 1.0, has been built in the framework of the CoCO2 project. CoCO2-MOSAIC 1.0 provides gridded (0.1∘ × 0.1∘) monthly emissions fluxes of CO2 fossil fuel (CO2ff, long cycle) and CO2 biofuel (CO2bf, short cycle) for the years 2015–2018 disaggregated in seven sectors. The regional inventories integrated are CAMS-REG-GHG 5.1 (Europe), DACCIWA 2.0 (Africa), GEAA-AEI 3.0 (Argentina), INEMA 1.0 (Chile), REAS 3.2.1 (East, Southeast, and South Asia), and VULCAN 3.0 (USA). EDGAR 6.0, CAMS-GLOB-SHIP 3.1 and CAMS-GLOB-TEMPO 3.1 are used for gap-filling. CoCO2-MOSAIC 1.0 can be recommended as a global baseline emission inventory for 2015 which is regionally accepted as a reference, and as such we use the mosaic to inter-compare the most widely used global emission inventories: CAMS-GLOB-ANT 5.3, EDGAR 6.0, ODIAC v2020b, and CEDS v2020_04_24. CoCO2-MOSAIC 1.0 has the highest CO2ff (36.7 Gt) and CO2bf (5.9 Gt) emissions globally, particularly in the USA and Africa. Regional emissions generally have a higher seasonality representing better the local monthly profiles and are generally distributed over a higher number of pixels, due to the more detailed information available. All super-emitting pixels from regional inventories contain a power station (CoCO2 database), whereas several super-emitters from global inventories are likely incorrectly geolocated, which is likely because regional inventories provide large energy emitters as point sources including regional information on power plant locations. CoCO2-MOSAIC 1.0 is freely available at zenodo (https://doi.org/10.5281/zenodo.7092358; Urraca et al., 2023) and at the JRC Data Catalogue (https://data.jrc.ec.europa.eu/dataset/6c8f9148-ce09-4dca-a4d5-422fb3682389, last access: 15 May 2023; Urraca Valle et al., 2023). </jats:p>
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