A Bayesian inversion of TROPOMI methane observations over South Africa: Implications for bottom-up inventories

We present the first inverse analysis of 2019 annual mean methane (CH₄) emissions in South Africa, focusing on a rectilinear region between the latitudes of 24°- 28° South and the longitudes of 26° - 30° East, containing large commercial agricultural fields, the biggest industries and urbanised environments. Using TROPOMI satellite observations and the cloud-based Integrated Methane Inversion v2 tool, we estimate CH₄ emissions at a spatial resolution of 25 × 25 km². Our analysis employs the EDGAR v8 greenhouse gas inventory as the prior and produces a posterior estimate of 0.65 Tg CH₄ yr^-1 - 62% lower than the original bottom-up inventory estimate. This substantial discrepancy is discussed in the context of potential uncertainties in emission factors and activity data, particularly for livestock-dominated regions, where relative prediction errors in cattle energy intake calculations can exceed 20%. The exclusion of biogenic sources in bottom-up inventories may also contribute to these differences, though such sources would likely increase, not decrease, anthropogenic emissions. These findings underscore the limitations of bottom-up approaches for accurate CH₄ emissions quantification. Our study contributes to global CH₄ research by providing the first satellite-based inverse analysis of CH₄ observations for South Africa and the first observational evaluation of the country's 2019 gridded CH₄ inventory from the Department of Forestry, Fisheries, and the Environment.