Assumptions about prior fossil fuel inventories impact our ability to estimate posterior net CO2 fluxes that are needed for verifying national inventories

Abstract

Abstract Monitoring national and global greenhouse gas (GHG) emissions is a critical component of the Paris Agreement, necessary to verify collective activities to reduce GHG emissions. Top-down approaches to infer GHG emission estimates from atmospheric data are widely recognized as a useful tool to independently verify emission inventories reported by individual countries under the United Nation Framework Convention on Climate Change. Conventional top-down atmospheric inversion methods often prescribe fossil fuel CO2 emissions (FFCO2) and fit the resulting model values to atmospheric CO2 observations by adjusting natural terrestrial and ocean flux estimates. This approach implicitly assumes that we have perfect knowledge of FFCO2 and that any gap in our understanding of atmospheric CO2 data can be explained by natural fluxes; consequently, it also limits our ability to quantify non-FFCO2 emissions. Using two independent FFCO2 emission inventories, we show that differences in sub-annual emission distributions are aliased to the corresponding posterior natural flux estimates. Over China, for example, where the two inventories show significantly different seasonal variations in FFCO2, the resulting differences in national-scale flux estimates are small but are significant on the subnational scale. We compare natural CO2 flux estimates inferred from in-situ and satellite observations. We find that sparsely distributed in-situ observations are best suited for quantifying natural fluxes and large-scale carbon budgets and less suitable for quantifying FFCO2 errors. Satellite data provide us with the best opportunity to quantify FFCO2 emission errors; a similar result is achievable using dense, regional in-situ measurement networks. Enhancing the top-down flux estimation capability for inventory verification requires a coordinated activity to (a) improve GHG inventories; (b) extend methods that take full advantage of measurements of trace gases that are co-emitted during combustion; and (c) improve atmospheric transport models.