Country-Scale Analysis of Methane Emissions with a High-Resolution Inverse Model Using GOSAT and Surface Observations

Abstract

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.

Large and increasing methane emissions from Eastern Amazonia derived from satellite data, 2010–2018

“…CC BY 4.0 License. mean flux is within the range found by, and agrees well with the findings ofJanardanan et al (2020).…”

Meteorological Drivers of Permian Basin Methane Anomalies Derived from TROPOMI

“…This study provides an example of the potential future value of utilizing satellitederived CH 4 for atmospheric photochemical transport studies (assuming emission locations and rates are known). CH 4 from satellite has been used in previous atmospheric inversion modeling and transport studies to estimate CH 4 emissions [74][75][76]. The advent of high-resolution satellite data now provides new opportunities for observing from space the impacts of atmospheric flow patterns on the regional distribution of pollutants.…”

A Structured Approach for the Mitigation of Natural Methane Emissions—Lessons Learned from Anthropogenic Emissions

“…The smaller the flux is, the lower is in general the concentration of methane in air near the source and the harder it is to capture the methane after the release (not accounting for factors such as wind speed, seasonality or size of the area and thus edge effects). To understand the order of magnitude of natural fluxes, Table 2 shows total, anthropogenic and natural methane fluxes for selected countries [47]. It becomes evident that methane fluxes for specific natural areal sources are in a similar range as the annual fluxes of the countries accounting for all sources in that country.…”

“…Measured and globally averaged fluxes of selected methane sources. Annual methane fluxes from different countries, calculated using country-specific emission data from[47].…”