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Title page 1

Contents 7

Abstract 4

Résumé 5

Acknowledgements 6

Executive summary 9

1. Introduction 11

2. National GHG emission inventoryd atasets 14

2.1. The PRIMAP-hist national historical emission time series (PRIMAP) 16

2.2. Emission Database for Global Atmospheric Research (EDGAR) 17

2.3. Climate Watch GHG Emission database (CLIMWATCH) 18

3. Comparison of datasets 19

3.1. Availability of disaggregated data on emission categories 19

3.2. Alignment of emissions data 20

3.3. Discussion 26

4. Compiling a global dataset of GHG inventories 27

5. Next steps 29

References 31

Annex A. Additional comparisons 33

Annex B. Preliminary results 48

Tables 8

Table 1. Three selected unofficial datasets that provide global coverage and high timeliness 15

Table 2. The breakdown by emission categories varies substantially across datasets 20

Figures 7

Figure 1. There are important data gaps in GHG emission inventories for selected UNFCCC non-Annex-I countries 12

Figure 2. PRIMAP emission levels align best with UNFCCC data among unofficial inventories 22

Figure 3. Emission levels of PRIMAP align best for big emitters 23

Figure 4. PRIMAP emission trends align best with UNFCCC data 24

Figure 5. PRIMAP shows the best alignment to official data at the first IPCC category level 25

Boxes 14

Box 1. Compilation principles and classifications of GHG emission data 14

Annex Figures 8

Figure A.1. PRIMAP also aligns with linearly interpolated official data 33

Figure A.2. PRIMAP emission levels align best with official data for each CO₂, CH₄ and N₂O gas 34

Figure A.3. Availability of granular data for Annex-I countries 35

Figure A.4. Availability of granular data for non-Annex-I countries 36

Figure A.5. Differences in emission levels are higher for the first level of IPCC categories 37

Figure A.6. Discrepancies in CO₂ emission levels are lowest for energy 38

Figure A.7. Discrepancies in CH₄ emission levels are lowest for agriculture 39

Figure A.8. Discrepancies for N₂O are lowest for agriculture and waste 40

Figure A.9. Unofficial data on emissions from energy align best with official data for countries with a higher relative size of the category 41

Figure A.10. Unofficial data on emissions from industrial processes and product use align best with official data for countries with a higher relative size of the category 42

Figure A.11. PRIMAP data on emissions from agriculture align best with official data for countries with a higher relative size of the category 43

Figure A.12. PRIMAP emission trends align best with UNFCCC across all first level IPCC categories 44

Figure A.13. Energy subcategories show discrepancies across all datasets for Non-Annex I countries 45

Figure A.14. Chile's GHG emission inventories 46

Figure A.15. Germany's GHG emission inventories 46

Figure A.16. China's GHG emission inventories 47

Figure A.17. India's GHG emission inventories 47

Figure B.1. The strategy allows to fill important gaps in official data for OECD partner countries 48

Figure B.2. The strategy allows to fill gaps for OECD countries 48

Figure B.3. Compiled GHG emission estimates by country groups 49

Figure B.4. Trends in compiled GHG emission estimates by country groups 49

Figure B.5. CO₂, CH₄ and N₂O emissions by country groups 50

Figure B.6. GHG emissions by IPCC categories and country groups 51

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