Estimation of anthropogenic and volcanic SO2 emissions from satellite data in the presence of snow/ice on the ground

Early versions of satellite nadir-viewing UV SO2 data products assumed snow-free surface conditions. Snow covered terrain, with its high reflectance in the UV, typically enhances satellite sensitivity to boundary layer pollution. However, a significant fraction of high-quality cloud-free measurements over snow is currently excluded from analyses. This leads to increasing the uncertainties of the satellite emissions estimates and introducing potential seasonal biases due to the lack of data in winter months for some high-latitudinal sources. In this study, we investigated how OMI and TROPOMI satellite SO2 measurements over snow-covered surfaces could be used to improve the annual emissions reported in our SO2 emissions catalogue (version 2, Fioletov et al., 2023). Although only 100 out of 759 sources listed in the catalogue have 10% or more of the observations over snow, for 40 high-latitude sources more than 30% of measurements suitable for emission calculations were made over snow-covered surfaces. For example, in the case of Norilsk, the world’s largest SO2 emissions point source, annual emissions estimates in the SO2 catalogue were based only on 3-4 summer months, while addition of data for snow conditions extends that period to 7 months. Emissions in the SO2 catalogue were based on satellite measurements of SO2 slant column densities (SCDs) that were converted to vertical column densities (VCDs) using site-specific clear-sky air mass factors (AMFs), calculated for snow-free conditions. The same approach was applied to measurements with snow on the ground whereby a new set of constant, site-specific, clear-sky with snow AMFs was created, and these were applied to the measured SCDs. Annual emissions were then estimated for each source considering (i) only snow-free days, (ii) only clear-sky with snow days and (iii) a merged dataset (snow and no snow conditions). For individual sources, the difference between emissions estimated for snow and snow-free conditions is within ±20% for three quarters of smelters and oil and gas sources, and with practically no systematic bias. This is excellent consistency given that there is typically a 3-5 times difference between AMFs for snow and snow-free conditions. For coal-fired power plants, however, emissions estimated for snow conditions are on average 25% higher than for no snow conditions; this difference is likely real and due to larger production (consumption of coal) and emissions in wintertime. Reference:Fioletov, V. E., McLinden, C. A., Griffin, D., Abboud, I., Krotkov, N., Leonard, P. J. T., Li, C., Joiner, J., Theys, N., and Carn, S.: Version 2 of the global catalogue of large anthropogenic and volcanic SO2 sources and emissions derived from satellite measurements, Earth Syst. Sci. Data, 15, 75–93, https://doi.org/10.5194/essd-15-75-2023, 2023.

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