We employed a global high-resolution inverse model to optimize the CH₄ emission using Greenhouse gas Observing Satellite (GOSAT) and surface observation data for a period from 2011–2017 for the two main source categories of anthropogenic and natural emissions. We used the Emission Database for Global Atmospheric Research (EDGAR v4.3.2) for anthropogenic methane emission and scaled them by country to match the national inventories reported to the United Nations Framework Convention on Climate Change (UNFCCC). Wetland and soil sink prior fluxes were simulated using the Vegetation Integrative Simulator of Trace gases (VISIT) model. Biomass burning prior fluxes were provided by the Global Fire Assimilation System (GFAS). We estimated a global total anthropogenic and natural methane emissions of 340.9 Tg CH₄ yr⁻¹ and 232.5 Tg CH₄ yr⁻¹, respectively. Country-scale analysis of the estimated anthropogenic emissions showed that all the top-emitting countries showed differences with their respective inventories to be within the uncertainty range of the inventories, confirming that the posterior anthropogenic emissions did not deviate from nationally reported values. Large countries, such as China, Russia, and the United States, had the mean estimated emission of 45.7 ± 8.6, 31.9 ± 7.8, and 29.8 ± 7.8 Tg CH₄ yr⁻¹, respectively. For natural wetland emissions, we estimated large emissions for Brazil (39.8 ± 12.4 Tg CH₄ yr⁻¹), the United States (25.9 ± 8.3 Tg CH₄ yr⁻¹), Russia (13.2 ± 9.3 Tg CH₄ yr⁻¹), India (12.3 ± 6.4 Tg CH₄ yr⁻¹), and Canada (12.2 ± 5.1 Tg CH₄ yr⁻¹). In both emission categories, the major emitting countries all had the model corrections to emissions within the uncertainty range of inventories. The advantages of the approach used in this study were: (1) use of high-resolution transport, useful for simulations near emission hotspots, (2) prior anthropogenic emissions adjusted to the UNFCCC reports, (3) combining surface and satellite observations, which improves the estimation of both natural and anthropogenic methane emissions over spatial scale of countries.

We present a global 0.1° × 0.1° high-resolution inverse model, NIES-TM-FLEXPART-VAR (NTFVAR), and a methane emission evaluation using the Greenhouse Gas Observing Satellite (GOSAT) satellite and ground-based observations from 2010–2012. Prior fluxes contained two variants of anthropogenic emissions, Emissions Database for Global Atmospheric Research (EDGAR) v4.3.2 and adjusted EDGAR v4.3.2 which were scaled to match the country totals by national reports to the United Nations Framework Convention on Climate Change (UNFCCC), augmented by biomass burning emissions from Global Fire Assimilation System (GFASv1.2) and wetlands Vegetation Integrative Simulator for Trace Gases (VISIT). The ratio of the UNFCCC-adjusted global anthropogenic emissions to EDGAR is 98%. This varies by region: 200% in Russia, 84% in China, and 62% in India. By changing prior emissions from EDGAR to UNFCCC-adjusted values, the optimized total emissions increased from 36.2 to 46 Tg CH₄ yr⁻¹ for Russia, 12.8 to 14.3 Tg CH₄ yr⁻¹ for temperate South America, and 43.2 to 44.9 Tg CH₄ yr⁻¹ for contiguous USA, and the values decrease from 54 to 51.3 Tg CH₄ yr⁻¹ for China, 26.2 to 25.5 Tg CH₄ yr⁻¹ for Europe, and by 12.4 Tg CH₄ yr⁻¹ for India. The use of the national report to scale EDGAR emissions allows more detailed statistical data and country-specific emission factors to be gathered in place compared to those available for EDGAR inventory. This serves policy needs by evaluating the national or regional emission totals reported to the UNFCCC.

Considering the significant role of global methane emissions in the Earth’s radiative budget, global or regionally persistent increasing trends in its emission are of great concern. Understanding the regional contributions of various emissions sectors to the growth rate thus has policy relevance. We used a high-resolution global methane inverse model to independently optimize sectoral emissions using GOSAT and ground-based observations for 2009–2020. Annual emission trends were calculated for top-emitting countries, and the sectoral contributions to the total anthropogenic trend were studied. Global total posterior emissions show a growth rate of 2.6 Tg yr⁻² (p < 0.05), with significant contributions from waste (1.1 Tg yr⁻²) and agriculture (0.9 Tg yr⁻²). Country-level aggregated sectoral emissions showed statistically significant (p < 0.1) trends in total posterior emissions for China (0.56 Tg yr⁻²), India (0.22 Tg yr⁻²), United States (0.65 Tg yr⁻²), Pakistan (0.22 Tg yr⁻²) and Indonesia (0.28 Tg yr⁻²) among the top methane emitters. Emission sectors contributing to the above country-level emission trend are, China (waste 0.35; oil and gas 0.07 Tg yr⁻²), India (agriculture 0.09; waste 0.11 Tg yr⁻²), United States (oil and gas 1.0; agriculture 0.07; coal −0.15 Tg yr⁻²), Brazil (waste 0.09; agriculture 0.08 Tg yr⁻²), Russia (waste 0.04; biomass burning 0.15; coal 0.11; oil and gas −0.42 Tg yr⁻²), Indonesia (coal 0.28 Tg yr⁻²), Canada (oil and gas 0.08 Tg yr⁻²), Pakistan (agriculture 0.15; waste 0.03 Tg yr⁻²) and Mexico (waste 0.04 Tg yr⁻²). Additionally, our analysis showed that methane emissions from wetlands in Russia (0.24 Tg yr⁻²) and central African countries such as Congo (0.09 Tg yr⁻²), etc. have a positive trend with a considerably large increase after 2017, whereas Bolivia (−0.09 Tg yr⁻²) have a declining trend. Our results reveal some key emission sectors to be targeted on a national level for designing methane emission mitigation efforts.

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