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Abstract - We estimate methane emissions from North America with high spatial resolution by inversion of SCIAMACHY satellite observations using the GEOS-Chem chemical transport model and its adjoint. The inversion focuses on summer 2004 when data from the INTEX-A aircraft campaign over the eastern US are available to validate the SCIAMACHY retrievals and evaluate the inversion. From the INTEX-A data we identify and correct a water vapor-dependent bias in the SCIAMACHY data. We conduct an initial inversion of emissions on the horizontal grid of GEOS-Chem (1/2ox2/3o) to identify correction tendencies relative to the EDGAR v4.2 emission inventory used as a priori. We then cluster these grid cells with a hierarchical algorithm to extract the maximum information from the SCIAMACHY observations. A 1000-cluster ensemble can be adequately constrained, providing ~100 km resolution across North America. Analysis of results indicates that the Hudson Bay Lowland wetlands source is 2.1 Tg a-1, lower than the a priori but consistent with other recent estimates. Anthropogenic US emissions are 30.1 ± 1.3 Tg a-1, compared to 25.8 Tg a-1 and 28.3 Tg a-1 in the EDGAR v4.2 and EPA inventories respectively. We find that US livestock emissions are 40% greater than in these two inventories. No such discrepancy is apparent for overall US oil and gas emissions, although this may reflect some compensation between overestimate of emissions from storage/distribution and underestimate from production. We find that US livestock emissions are 70% greater than the oil and gas emissions, in contrast to the EDGAR v4.2 and EPA inventories where these two sources are of comparable magnitude.
Wecht, K. J., D. J. Jacob, C. Frankenberg, Z. Jiang, & D. R. Blake (2014) Mapping of North American methane emissions with high spatial resolution by inversion of SCIAMACHY satellite data, Journal of Geophysical Research: Atmospheres (Accepted Article).