Abstract

Abstract. SO2 and NO2 observations from the Ozone Mapping and Profiler Suite (OMPS) sensor are used for the first time in conjunction with the 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 SO2 and NO2, in comparison to measurements from the Ozone Monitoring Instrument (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 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. 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 compared to assimilating SO2 and NO2 separately in a sequential manner of computation. The sensitivity analysis shows that a perturbation of NH3 to 50 % (20 %) of the prior emission inventory can (a) have a negligible impact on the separate SO2 inversion but can lead to a decrease in posterior SO2 emissions over China by −2.4 % (−7.0 %) in total and up to −9.0 % (−27.7 %) in some grid cells in the joint inversion with NO2 and (b) yield posterior NOx emission decreases over China by −0.7 % (−2.8 %) for the separate NO2 inversion and by −2.7 % (−5.3 %) in total and up to −15.2 % (−29.4 %) in some grid cells for the joint inversion. The large reduction of SO2 between 2010 and 2013, however, only leads to ∼ 10 % decrease in AOD regionally; reducing surface aerosol concentration requires the reduction of emissions of NH3 as well.

Highlights

  • Both SO2 and NO2 in the atmosphere have adverse impacts on human health and can affect radiative forcing that leads to climate change

  • normalized mean bias (NMB) (106.5 %) between GOES-Chem prior simulation and Ozone Mapping and Profiler Suite (OMPS) is much larger than the NMB (−6.8 %, Fig. S1) caused by the difference in SO2 vertical profiles between the OMPS SO2 retrieval algorithm and current prior simulation; the averaging kernel is not considered in the OMPS SO2 observation operator

  • We developed 4D-Var observation operators for assimilating OMPS SO2 and NO2 vertical column densities (VCDs) to constrain SO2 and NOx emissions through GEOS-Chem adjoint model

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Summary

Introduction

Both SO2 and NO2 in the atmosphere have adverse impacts on human health and can affect radiative forcing that leads to climate change. Do they cause inflammation and irritation of humans’ respiratory system, but they react with other species to form sulfate and nitrate aerosols (Seinfeld and Pandis, 2016), which subsequently can lead to or exacerbate respiratory and cardiovascular diseases (Lim et al, 2012). Of particular interest for this study is China, which has large SO2 and NOx emissions from anthropogenic sources (coal-fired power plants, industry, transportation, and residential activity). The uncertainty is large and can be compounded by possible discrepancies caused by the temporal lag of bottomup emission inventories and the rapid changes in emissions over time

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