the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Using new geospatial data and 2020 fossil fuel methane emissions for the Global Fuel Exploitation Inventory (GFEI) v3
Abstract. The Global Fuel Exploitation Inventory (GFEI) is a global 0.1° x 0.1° resolution gridded inventory of methane emissions from oil, gas, and coal exploitation. Here, we present GFEI v3 with updated national emissions to 2020 using reports submitted to the United Nations Framework Convention on Climate Change (UNFCCC), leading to new global emissions of 23, 20, and 31 Tg a-1 for oil, gas, and coal, respectively. We also use new geospatial information from the Oil and Gas Infrastructure Mapping database (OGIM v1) for spatial distribution of global oil-gas methane emissions. We use coal mine locations from the Global Energy Monitor’s Global Coal Mine Tracker (GCMT), combined with our own estimates for mine-level methane emissions, to distribute national emissions between coal mine locations. Our mine-level methane emission estimates use country specific emission factors for top producing countries supplemented with modeled emission factors based on coal mine depth and grade. We see the greatest change in the spatial distribution of emissions in GFEI v3 compared to v2 in China due to the use of GCMT for coal mine locations. Large point source plumes (super-emitters) observed by the NASA EMIT instrument are co-located with infrastructure identified in GFEI v3, but the magnitude of the measured emissions is poorly correlated with the gridded emissions in GFEI. This may reflect missing or misrepresented sources in GFEI v3 but also the sporadic nature of the super-emitter measurements used here. By aligning GFEI v3 with national UNFCCC reports and using state-of-the-science geospatial information, the inventory can be confronted with satellite observations of atmospheric methane through inverse modeling to evaluate and improve the UNFCCC reports. We plan to continue updating GFEI to align with reported national emissions and new geospatial information, including assessment of GFEI spatial accuracy through comparison to super-emitter detections. GFEI v3 emission grids by sector and subsector are available at https://doi.org/10.7910/DVN/HH4EUM (Scarpelli et al., 2024).
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RC1: 'Comment on essd-2024-552', Anonymous Referee #1, 19 Mar 2025
Overall a very useful paper.
It would be useful to compare your GFEI v3 results to other global methane estimates, e.g., EC EDGAR, IEA Global Methane Tracker, both of which you cite. Since GFEI relies substantially on country-level emission reports, please respond to or put in context GMT's statement that ""Methane emissions from the energy sector are about 70% higher than reported in official data." It seems (though I am not a methane measurement expert) that the US EPA continually revises upward methane emission estimates. This is likely the case in other national assessments, e.g., South Africa, and others that you cite.
Does the Rocky Mountain Institute GHG mapper (https://ociplus.rmi.org) or the Stanford's OPGEE models offer a useful comparison/ (RMI adopts GFEIv2 data).
You use US EPA emission data for abandoned coal mines. Can you make any useful extensions from the US mines to estimate abandoned mine CH4 rates elsewhere?
Certain anomalous results in GFEIv3 suggests further discussion, such as Mexico's 2x oil emissions., and Venezuela and Libya (the latter two are explained). Line 191. South Africa's large decrease in GFEIv3 warrants a mention.
Your highly detailed data is very useful. It is likely beyond your scope, but it would be interesting to see a table of leading countries' emission rates per commodity.
Minor correction: 99.8% vs 99.7% in lines 177 and 204.
Excellent work.
Citation: https://doi.org/10.5194/essd-2024-552-RC1 -
RC2: 'Comment on essd-2024-552', Anonymous Referee #2, 30 Apr 2025
The authors present an update version of the Global Fuel Exploitation Inventory (GFEI v3), integrating 2020 national emissions data and improved spatial allocation datasets. The resulting product (GFEI v3) enhances the fidelity of fossil fuel-related methane emissions at high spatial resolution. The work is timely, methodologically sound, and generally well written. That said, several key clarifications and improvements are recommended as follows.
1. Table detailing year and source of emissions for each country:
It would be helpful to provide a supplementary table that outlines, for each country (or at least the top 20 emitters), the year of the emission data used, whether it is directly from UNFCCC reporting or derived via IPCC Tier 1 methods, and any national communications or specific reports consulted. This would make the inventory’s provenance more transparent and facilitate comparisons with other datasets.
In line 107, the paper states that "Some countries do not submit reports to the UNFCCC, including Iraq and Libya." Please clarify: are Iraq and Libya the only two countries that do not submit any reports? If others also fall into this category (e.g., due to outdated or incomplete submissions), please include in the supplementary table.
2. Comparison with regional top-down inversions:
The paper would benefit from discussing whether the revisions from GFEI v2 to v3 are consistent with findings from regional inversions that previously used GFEI v2 as the prior. Examples include inversions using TROPOMI or GOSAT. Have those inversions shown discrepancies in regions where GFEI v3 now reports major changes? If yes, does GFEI v3 help reconcile any known discrepancies?
3. Nature of differences between GFEI v2 and v3 (Bias correction vs. infrastructure updates):
The paper describes both changes in national emissions and changes in spatial allocation. Please clarify: to what extent are the observed differences in emissions between GFEI v2 and v3 attributable to corrections of biases in GFEI v2 (e.g., underreporting in national inventories) versus actual changes in infrastructure (e.g., new coal mines or pipeline expansions)? A brief quantitative or regional breakdown would be useful here.
4. Figures 4 and 5 – Visual clarity and explanation:
The red triangles representing super-emitter detections are very small and hard to see. Please enlarge these markers to enhance readability.
The color of the red triangles overlaps with the color bar used for well density in the background. Consider changing the triangle color or altering the background color scale.
Figure 4 lacks an explanation for the green dots shown in the bottom panels. What do these represent? Please clarify in the figure caption.
Citation: https://doi.org/10.5194/essd-2024-552-RC2
Data sets
Global Fuel Exploitation Inventory (GFEI) v3 Tia R. Scarpelli, Daniel J. Jacob, and Elfie Roy https://doi.org/10.7910/DVN/HH4EUM
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