Continuation of long-term global SO2 pollution monitoring from OMI to OMPS

Other literature type English OPEN
Zhang, Yan ; Li, Can ; Krotkov, Nickolay A. ; Joiner, Joanna (2016)

Over the past 20 years, advances in satellite remote sensing of pollution-relevant species have made space-borne observations an increasingly important part of atmospheric chemistry research and air quality management. This progress has been facilitated by advanced UV-Vis spectrometers, such as the Ozone Monitoring Instrument (OMI) on board the NASA EOS Aura satellite, and continues with new instruments, such as the Ozone Mapping and Profiler Suite (OMPS) on board the NASA-NOAA Suomi National Polar-orbiting Partnership (SNPP) satellite. In this study, we demonstrate that it is possible, using our state-of-the-art principal component analysis (PCA) retrieval technique, to continue the long-term global SO<sub>2</sub> pollution monitoring started by OMI with the current and future OMPS instruments that will fly on the NOAA Joint Polar Satellite System (JPSS)&ndash;1, &ndash;2, &ndash;3, &ndash;4 satellites in addition to SNPP, with a very good consistency of retrievals from these instruments. Since OMI SO<sub>2</sub> data have been primarily used for 1) providing regional context on air pollution and long-range transport on a daily basis; and 2) providing information on point emission sources on an annual basis after data averaging, we focused on these two aspects in our OMI-OMPS comparison. Four years of retrievals during 2012&ndash;2015 have been compared for three regions: eastern China, Mexico, and South Africa. In general, the comparisons show high temporal correlations (r&thinsp;=&thinsp;0.79&ndash;0.96) of SO<sub>2</sub> mass between the two instruments and near unity regression slopes (0.76&ndash;0.97). The annual averaged SO<sub>2</sub> loading difference between OMI and OMPS is small (<&thinsp;0.03 Dobson Unit (DU)) over South Africa and up to 0.1&thinsp;DU over eastern China). We also found a very good correlation (r&thinsp;=&thinsp;0.92&ndash;0.97) in the spatial distribution of annual mean SO<sub>2</sub> between OMI and OMPS over the three regions during 2012&ndash;2015. For 82&thinsp;% of the days, the two instruments have a spatial correlation coefficient of 0.6 or better over the Mexico region. It is worth noting that such consistent retrievals were achieved without any explicit adjustment to OMI or OMPS radiance data, and that the retrieval agreement may be further improved by introducing a more comprehensive Jacobian lookup table than currently used.
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