Analyzing nitrogen dioxide to nitrogen oxide scaling factors for data-driven satellite-based emission estimation methods: A case study of Matimba/Medupi power stations in South Africa

In this paper, we propose improved nitrogen dioxide (NO₂) to nitrogen oxide (NO_x) scaling factors for several data-driven methods that are used for the estimation of NO_x power plant emissions from satellite observations of NO₂. The scaling factors are deduced from high-resolution simulations of power plant plumes with the MicroHH large-eddy simulation model with a simplified chemistry and then applied to Sentinel-5 Precursor (S5P) TROPOspheric Monitoring Instrument (TROPOMI) NO₂ satellite observations over the Matimba/Medupi power stations in South Africa. We show that due to the non-linear chemistry the optimal NO₂ to NO_x scaling factors depend on both the method employed and the specific segments of the plume from which emission estimate is derived. The scaling factors derived from the MicroHH simulations in this study are substantially (more than 50%) higher than the typical values used in the literature with actual NO₂ observations. The results highlight the challenge in appropriately accounting for the conversion from NO₂ to NO_x when estimating point source emissions from satellite NO₂ observations.