Continuing global monitoring of anthropogenic and volcanic SO2 sources from Aura/OMI to SNPP/OMPS

Sulfur dioxide (SO2) is an important trace gas that has significant impacts on air quality, the climate, and stratospheric ozone. It is predominantly emitted from anthropogenic sources such as coal-fired power plants and smelters, but also has sizable sources from volcanic activity. The Ozone Monitoring Instrument (OMI) aboard NASA's Earth Observing System (EOS) Aura spacecraft has been providing global observations of both anthropogenic and volcanic SO2 since its launch in 2004. The Ozone Mapping and Profiler Suite (OMPS) nadir mapper, launched aboard the NASA/NOAA Suomi National Polar-orbiting Partnership (SNPP) satellite in 2011, will continue the 13+ year OMI SO2 time series. However, it is a significant challenge to build a coherent data record between OMI and OMPS, as the SO2 signal is relatively weak and its retrieval is subject to a number of interferences such as ozone absorption. Additionally, the two instruments also have different spectral and spatial resolutions that result in different sensitivities to SO2. Even a relatively small error in retrievals, due to either algorithmic or instrumental factors, may lead to a large inter-instrument bias in SO2. In this presentation, we report on our latest effort and progress in developing EOS continuity SNPP/OMPS SO2 products. We have applied a consistent retrieval technique based on principal component analysis (PCA) of measured radiance data to both OMI and OMPS. We show that the PCA retrieval technique, which extracts principal components (PCs) from measured radiances and applies these PCs in spectral fitting to minimize the effects of various interfering processes, is capable of producing highly consistent OMI and OMPS SO2 data for both anthropogenic sources and large volcanic eruptions. To gain a quantitative understanding of the two instruments' capabilities of monitoring SO2 sources, we have also applied a new emission estimation technique that combines satellite SO2 and wind information to both of them. This method allows SO2 emissions from 500 sources worldwide to be detected and quantified from OMI data. The OMPS-based emission estimates using the same method agree well with OMI-based ones, although OMPS detects fewer of the smaller sources seen by OMI, owing to its coarser spatial resolution.