Inverse modeling of SO2 and NOx emissions over China using multisensor satellite data - Part 1: Formulation and sensitivity analysis

Wang, Y., J. Wang, X. Xu, D.K. Henze, Z. Qu, and K. Yang (2020), Inverse modeling of SO2 and NOx emissions over China using multisensor satellite data - Part 1: Formulation and sensitivity analysis, Atmos. Chem. Phys., 20, 6631-6650, doi:10.5194/acp-20-6631-2020.
Abstract

SO2 and NO2 observations from the Ozone Mapping and Profiler Suite (OMPS) sensor are used for the first time in conjunction with GEOS-Chem adjoint model to optimize both SO2 and NOx emission estimates over China for October 2013. Separate and joint (simultaneous) optimizations of SO2 and NO2 emissions are both conducted and compared. Posterior emissions, compared to the prior, yield improvements in simulating columnar

20 SO2 and NO2, in comparison to measurements from OMI and OMPS. The posterior SO2 and NOx emissions from separate inversions are 748 Gg S and 672 Gg N, which are 36% and 6% smaller than prior MIX emissions (valid for 2010), respectively. In spite of the large reduction of SO2 emissions over the North China Plain, the simulated sulfate-nitrate-ammonium Aerosol Optical Depth (AOD) only decrease slightly, which can be attributed to (a) nitrate rather than sulfate as the dominant contributor to AOD and (b) replacement of ammonium sulfate with

25 ammonium nitrate as SO2 emissions are reduced. For joint inversions, both data quality control and the weight given to SO2 relative to NO2 observations can affect the spatial distributions of the posterior emissions. When the latter is properly balanced, the posterior emissions from assimilating OMPS SO2 and NO2 jointly yield a difference of -3% to 15% with respect to the separate assimilations for total anthropogenic SO2 emissions and ±2% for total anthropogenic NOx emissions; but the differences can be up to 100% for SO2 and 40% for NO2 in some grid cells.

30 Improvements on SO2 and NO2 simulations from the joint inversions are overall consistent with those from separate inversions. Moreover, the joint assimilations save ~50% of the computational time than assimilating SO2 and NO2 separately in a sequential manner of computation. The sensitivity analysis shows that a perturbation of

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Research Program
Atmospheric Composition
Atmospheric Composition Modeling and Analysis Program (ACMAP)
Tropospheric Composition Program (TCP)