Satellite quantification of methane emissions from South American countries: A high-resolution inversion of TROPOMI and GOSAT observations

Abstract. We use 2021 TROPOMI and GOSAT satellite observations of atmospheric methane in an analytical inversion to quantify national methane emissions from South America at up to 25 km × 25 km resolution. From the inversion, we derive optimal posterior estimates of methane emissions correcting the national anthropogenic emission inventories reported by individual countries to the United Nations Framework Convention on Climate Change (UNFCCC) and taken here as prior estimates. We also evaluate two alternative wetland emission inventories (WetCHARTs and LPJ-wsl) as prior estimates. Our best posterior estimates for wetland emissions are consistent with previous inventories for the Amazon but lower for the Pantanal and higher for the Parana. Our best posterior estimate of South American anthropogenic emissions is 48 (41-56) Tg a-1, where numbers in parentheses are the range from our inversion ensemble. This is 55% higher than UNFCCC reports and is dominated by livestock (65% of anthropogenic total). We find that TROPOMI and GOSAT observations can effectively optimize and separate national emissions by sector for 10 of the 13 countries and territories in the region, 7 of which account for 93% of continental anthropogenic emissions: Brazil (19 (16-23) Tg a−1), Argentina (9.2 (7.9-11) Tg a−1 ), Venezuela (7.0 (5.5-9.9) Tg a−1), Colombia (5.0 (4.4-6.7) Tg a−1), Peru (2.4 (1.6-3.9) Tg a−1), Bolivia (0.96 (0.66-1.2) Tg a−1), and Paraguay (0.93 (0.88 – 1.0) Tg a−1). Our estimates align with UNFCCC reports for Brazil, Bolivia, and Paraguay, but are significantly higher for other countries. Emissions in all countries are dominated by livestock (mainly enteric fermentation) except for oil/gas in Venezuela and landfills in Peru. Methane intensities from the oil/gas industry are high in Venezuela (33%), Colombia (6.5%) and Argentina (5.9%). Country-average emission factors for enteric fermentation from cattle in UNFCCC reports are in the range 46-60 kg head-1 a-1, close to the IPCC Tier 1 estimate which is mostly based on data from Brazil. Our inversion yields cattle enteric fermentation emission factors consistent with the UNFCCC reports for Brazil and Bolivia but a factor of two higher for other countries. The discrepancy for Argentina can be corrected by using IPCC Tier 2 emission estimates accounting for high milk production. 1 Introduction Methane (CH4) is a potent greenhouse gas with a relatively short atmospheric lifetime of 9.1 ± 0.9 years (Szopa et al., 2021). Methane atmospheric concentrations have nearly tripled since pre-industrial times, resulting in an emission-based radiative forcing of 1.21 W m−2 compared to 2.16 W m−2 for CO2 (Naik et al., 2021). Here we use satellite observations to quantify and attribute methane emissions from South American countries, which have been estimated to contribute 14% of global anthropogenic methane emissions (Worden et al., 2022) and are thought to be a major contributor to the methane rise over the past decade (Y. Zhang et al., 2021). The 194 Parties to the Paris Agreement, including all 12 South American countries, must regularly submit Nationally Determined Contributions (NDCs) outlining their plans to reduce greenhouse gas emissions. These NDCs are based on national emission inventories constructed using bottom-up methods that combine activity data for individual sectors with emission factors, sometimes supplemented by direct measurements of individual sources. The inventories tend to have large uncertainties because emission factors (and sometimes the activity data) are poorly quantified (Saunois et al., 2020), and even direct emission measurements may not capture source variability. Top-down information from atmospheric observations of methane concentrations can reduce these uncertainties through inverse analyses with an atmospheric transport model and using the bottom-up inventories as prior estimates in the inversion. Anthropogenic emissions of methane come from many sectors, including oil/gas, coal, livestock, rice cultivation, landfills, and wastewater treatment. Natural emissions are from wetlands, fires, termites, and geological seeps. South American anthropogenic emissions are heavily dominated by livestock. Of particular importance is Brazil, which is estimated to be the 3rd highest anthropogenic methane-emitting country globally (Worden et al., 2022) and has been identified as a major contributor to the recent global rise in methane through livestock and wetland emissions (Y. Zhang et al., 2021, Qu et al., 2024). Venezuela, Colombia, and Argentina are also high emitters (Worden et al., 2022). Wetlands are a major natural methane source in South America but again with large uncertainty (B. Zhang et al., 2017). Satellite observations in the shortwave infrared (SWIR) are particularly attractive for top-down emission estimates due to their global coverage and sensitivity down to the surface. Inversions of data from the Greenhouse Gases Observing Satellite (GOSAT, 2009-present) (Parker et al., 2020a) have been used to infer the distribution of methane emissions globally (Maasakkers et al., 2019; Janardanan et al., 2020; Qu et al., 2021) and regionally for South America (Tunnicliffe et al., 2020, Wilson et al., 2021). Regional inversions have identified upward corrections in emissions inventories over Venezuela and the Eastern Amazon, and downward corrections over the Western Amazon. However, GOSAT observations are sparse, separated by about 250 km, which limits the spatial resolution that can be achieved, increasing uncertainties in attributing emissions to countries and sectors. The TROPOspheric Monitoring Instrument (TROPOMI) (2018-present) provides global continuous daily mapping of atmospheric methane at 7 km × 5.5 km nadir resolution (Lorente et al., 2023). This coverage in combination with high resolution provides TROPOMI with a unique capability for quantifying national emissions and attributing emissions to sectors. This has recently been demonstrated for the United States (Nesser et al., 2024), the Middle East and North Africa (Chen et al., 2023), China (Chen et al., 2022, Liang et al., 2023), and Venezuela (Nathan et al., 2023). Here we use TROPOMI observations in an inverse analysis of 2021 methane emissions over South America at up to 25 km resolution, using as prior estimates the national anthropogenic inventories reported to the United Nations Framework Convention on Climate Change (UNFCCC) under the Paris Agreement. We use two alternative bottom-up wetland emission inventories as prior estimates. We use a new TROPOMI satellite product that corrects surface, aerosol, and cloud artifacts with a machine learning algorithm trained by GOSAT data (Balasus et al., 2023). We also use GOSAT data, which though sparse provides unique information over wetlands. We quantify emissions by country and by sector and give recommendations for improving the bottom-up national inventories.