PlainEmissions · Guide
Why EDGAR and UNFCCC Disagree on the Same Country
Last updated · PlainEmissions
Answer first
According to the European Commission's Joint Research Centre, EDGAR is a globally consistent bottom-up model; UNFCCC inventories are country-specific legal records, so disagreement is expected, especially in LULUCF, methane, and agriculture.
According to JRC, PlainEmissions renders EDGAR figures; UNFCCC remains the Paris Agreement legal record. Use both, and treat a 30% gap as a methodology signal.
- Site source
- EDGAR
- Legal record
- UNFCCC
- EDGAR #1 2023
- China
- Top-2 share
- 47%
Bottom-up JRC model
Paris inventory track
15,970 Mt
Of tracked EDGAR total
These are EDGAR bottom-up totals only, the same countries' UNFCCC inventories can differ by 5–30%+, especially once LULUCF and methane enter the frame. Top-two share of the tracked 2023 total: about 47%.
Top-two concentration
Share of 2023 tracked EDGAR total
Two different ways to count the same thing
Open any country page and you'll see two emissions totals that don't match. EDGAR, the EU's Joint Research Centre database, typically reports a different number than that country's official UNFCCC inventory submission, sometimes by 5%, sometimes by 30%, occasionally by more. This isn't a mistake. It's a feature of how these two systems are designed.
EDGAR is a globally-consistent bottom-up model. The European Commission's Joint Research Centre takes activity data (energy consumption from IEA, agricultural statistics from FAO, industrial production from UN Industrial Statistics) and applies its own emission factors to estimate emissions for every country using the same methodology. The strength is comparability, every country is measured the same way. The weakness is that EDGAR doesn't have local knowledge of country-specific practices, fuel quality, or regulatory measures.
UNFCCC inventories are self-reported. Each country compiles its own inventory using IPCC reporting guidelines, with country-specific emission factors, country-specific activity data, and country-specific quality-assurance processes. The strength is local accuracy, a Norwegian inventory team knows Norwegian conditions better than a Brussels modeller does. The weakness is heterogeneous methodology and (in some cases) political pressure to present favorable numbers.
Where the gap is small
For well-resourced developed countries with mature inventory systems (EU member states, the United States, Canada, Australia, Japan), EDGAR and UNFCCC typically agree within 5-10% on the national CO2 total from energy. Energy CO2 is the easiest sector to estimate, fuel consumption data is well-recorded, emission factors are well-characterized, and the chemistry is straightforward (carbon in fuel → carbon dioxide in atmosphere).
For these countries, when EDGAR and UNFCCC agree closely, you can be confident the headline national energy-CO2 number is reliable to within roughly 5%. That's tighter than most economic indicators.
Where the gap is large
Three sectors regularly produce disagreement greater than 20%:
- LULUCF (land use, land-use change, and forestry). Forest growth, deforestation, and soil carbon stocks are notoriously hard to measure. Country-specific inventory methods often produce dramatically different LULUCF figures than EDGAR's globally-consistent approach. For some countries (Brazil, Indonesia, Russia, Canada) LULUCF disagreement can flip the country between being a net sink and a net source.
- Methane from fossil-fuel extraction. Methane leaks from oil and gas systems are difficult to measure and easy to undercount. Top-down satellite observations (Climate TRACE, GHGSat) routinely find more methane in the atmosphere over major producing regions than bottom-up inventories report.
- Agriculture (especially livestock methane and fertilizer N2O). Emission factors per unit of livestock or per kilogram of fertilizer vary by climate, soil, feed composition, and management practice. A globally-consistent factor (EDGAR's approach) cannot capture this variation; a country-specific factor (UNFCCC approach) can, but the choice of factor materially affects the total.
Where the gap is enormous
For some developing countries the gap can exceed 50% on the national total. Common reasons: incomplete UNFCCC reporting (some countries submit inventories only every 4-8 years, and the most recent submission may use 5-year-old activity data); large LULUCF uncertainty; methane from extensive livestock with no country-specific factor work; and, more rarely, political incentives to under-report. The reverse can also happen: country-specific inventories sometimes report more emissions than EDGAR because the country has better data on coal-mining methane or specific industrial-process emissions than the global model.
How to read the disagreement
For policy debates, the legal record is the UNFCCC inventory, that's what countries are accountable for under the Paris Agreement. For cross-country comparison and historical trend analysis, EDGAR is more useful because the methodology is consistent. For independent verification, Climate TRACE's satellite-derived estimates are increasingly the third leg of the stool.
PlainEmissions currently ingests and renders EDGAR's figures only; UNFCCC and Climate TRACE are documented here for methodological context rather than displayed side by side on our country pages today. When published EDGAR and UNFCCC figures for a country are within 5% of each other, that agreement is reassuring; when they're 30% apart, our methodology page documents which sectors tend to drive that kind of gap.
A worked example: Russia's emissions
Russia's UNFCCC inventory has historically reported substantially lower national totals than EDGAR's bottom-up model. The gap is driven by two factors documented in the methodological literature on this dataset pair. First, LULUCF: Russia's inventory reports very large forest-sink credits that bring the national net total down, while EDGAR's land-use model is more conservative, a known source of divergence for forest-rich countries generally (see the LULUCF note above). Second, methane from oil and gas extraction is one of the sectors where satellite-based estimates (Climate TRACE, GHGSat) most often diverge from bottom-up inventories across major producing regions worldwide, Russia included. The result is a national-total disagreement of roughly 15-25% depending on year and sector. Our Russia country page shows EDGAR's figures; the UNFCCC and Climate TRACE comparisons above are drawn from the published record for context, not from a live side-by-side feature on this site.
The takeaway
Pick one number and you're picking a methodology. EDGAR is the number PlainEmissions presents; this guide exists to make the wider methodology disagreement visible rather than let a single figure read as the only truth.
Further reading on PlainEmissions
- Understanding CO2-equivalent and GWP100 - the unit-conversion explainer.
- EDGAR vs UNFCCC - why two sources disagree.
- LULUCF: most-disputed sector - where source disagreement is largest.
- Climate TRACE explained - independent satellite verification.
- Reading emissions time series - six framing choices to watch.
- IPCC sector taxonomy - the canonical 8-sector hierarchy.
- Methodology page - full data-source provenance and harmonization steps.
Definitions used on this site
- CO2-equivalent (CO2e): any greenhouse gas expressed as the mass of CO2 that would produce equivalent warming over a chosen time horizon, typically 100 years.
- GWP100 / GWP20: global-warming potential over 100 (or 20) years; the multiplier used to convert from native gas units to CO2-equivalent.
- LULUCF: Land Use, Land-Use Change, and Forestry, the IPCC sector covering carbon stocks in vegetation and soils.
- Production-based emissions: emissions attributed to the country where they physically occur.
- Consumption-based emissions: emissions attributed to the country where the final goods or services are consumed.
- Annex I: the group of historically-developed countries under the UNFCCC with deeper reporting obligations.
Source: European Commission Joint Research Centre EDGAR v8.0 greenhouse-gas inventories · 2026 Educational guide; live charts query the same EDGAR fact table as country pages.
According to the European Commission's Joint Research Centre, the EDGAR v8.0 dataset publishes country- and sector-level greenhouse-gas inventories on a common bottom-up model. Every figure on PlainEmissions is rebuilt from that release; no number is typed in by an editor. Educational EDGAR methodology; figures on linked country/ranking pages come from the live EDGAR fact table. See our editorial standards & corrections policy, the methodology behind these numbers, or report a data error. Data current as of 2026-05-20. EDGAR figures are production-based inventory totals for a published reference year (AR6 GWP100, LULUCF excluded on ranked surfaces) - not climate policy advice, real-time emissions, or a substitute for UNFCCC legal inventories.