4.7 Article

Global distribution of methane emissions: a comparative inverse analysis of observations from the TROPOMI and GOSAT satellite instruments

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ATMOSPHERIC CHEMISTRY AND PHYSICS
卷 21, 期 18, 页码 14159-14175

出版社

COPERNICUS GESELLSCHAFT MBH
DOI: 10.5194/acp-21-14159-2021

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  1. NASA [80NSSC18K0178]
  2. NSFC [42007198]
  3. UK National Centre for Earth Observation [NE/N018079/1]

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In this study, we assess global atmospheric methane column retrievals from the new TROPOMI satellite instrument and use them to conduct a global inversion of methane sources for 2019. Comparisons with GOSAT retrievals and a joint inversion using both TROPOMI and GOSAT reveal discrepancies in global and regional biases, with TROPOMI having higher observation density but less utility for quantifying emissions at larger scales compared to GOSAT. Nevertheless, both TROPOMI and GOSAT show potential for improving the quantification and attribution of methane emissions on a global scale through future advancements in retrieval techniques and finer-scale inversions.
We evaluate the global atmospheric methane column retrievals from the new TROPOMI satellite instrument and apply them to a global inversion of methane sources for 2019 at 2 degrees x2.5 degrees horizontal resolution. We compare the results to an inversion using the sparser but more mature GOSAT satellite retrievals and to a joint inversion using both TROPOMI and GOSAT. Validation of TROPOMI and GOSAT with TCCON ground-based measurements of methane columns, after correcting for retrieval differences in prior vertical profiles and averaging kernels using the GEOS-Chem chemical transport model, shows global biases of -2.7ppbv for TROPOMI and -1.0ppbv for GOSAT and regional biases of 6.7ppbv for TROPOMI and 2.9ppbv for GOSAT. Intercomparison of TROPOMI and GOSAT shows larger regional discrepancies exceeding 20ppbv, mostly over regions with low surface albedo in the shortwave infrared where the TROPOMI retrieval may be biased. Our inversion uses an analytical solution to the Bayesian inference of methane sources, thus providing an explicit characterization of error statistics and information content together with the solution. TROPOMI has similar to 100 times more observations than GOSAT, but error correlation on the 2 degrees x2.5 degrees scale of the inversion and large spatial inhomogeneity in the number of observations make it less useful than GOSAT for quantifying emissions at that scale. Finer-scale regional inversions would take better advantage of the TROPOMI data density. The TROPOMI and GOSAT inversions show consistent downward adjustments of global oil-gas emissions relative to a prior estimate based on national inventory reports to the United Nations Framework Convention on Climate Change but consistent increases in the south-central US and in Venezuela. Global emissions from livestock (the largest anthropogenic source) are adjusted upward by TROPOMI and GOSAT relative to the EDGAR v4.3.2 prior estimate. We find large artifacts in the TROPOMI inversion over southeast China, where seasonal rice emissions are particularly high but in phase with extensive cloudiness and where coal emissions may be misallocated. Future advances in the TROPOMI retrieval together with finer-scale inversions and improved accounting of error correlations should enable improved exploitation of TROPOMI observations to quantify and attribute methane emissions on the global scale.

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