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

• Published in: Atmospheric Measurement Techniques
• Main Authors: Fioletov, Vitali E., McLinden, Chris A., Griffin, Debora, Krotkov, Nickolay A., Li, Can, Joiner, Joanna, Theys, Nicolas, Carn, Simon
• Format: Text
• Language: English
• Published: 2023
• Subjects: Norilsk; norilsk
• Online Access: https://doi.org/10.5194/amt-16-5575-2023; https://amt.copernicus.org/articles/16/5575/2023/

Early versions of satellite nadir-viewing UV SO 2 data products did not explicitly account for the effects of snow/ice on retrievals. 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 increased uncertainties of satellite emission estimates and potential seasonal biases due to the lack of data in winter months for some high-latitudinal sources. In this study, we investigated how Ozone Monitoring Instrument (OMI) and TROPOspheric Monitoring Instrument (TROPOMI) satellite SO 2 measurements over snow-covered surfaces can be used to improve the annual emissions reported in our SO 2 emissions catalogue (version 2; Fioletov et al., 2023). Only 100 out of 759 sources listed in the catalogue have 10 % or more of the observations over snow. However, 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 SO 2 point-source, annual emission estimates in the SO 2 catalogue were based only on 3–4 summer months, while the addition of data for snow conditions extends that period to 7 months. Emissions in the SO 2 catalogue were based on satellite measurements of SO 2 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 clear-sky and snow-free days, (ii) only clear-sky with snow days, and (iii) a merged dataset (snow and snow-free conditions). For individual sources, the difference between ...