The impact of day-to-day variability in input assumptions on regional satellite retrievals of NO2

In the retrieval of satellite measurements of NO2, the conversion of the observed slant column densities (SCDs) to the desired vertical column densities (VCDs) requires a priori knowledge of information such as NO2 profiles to calculate the air mass factor (AMF) necessary for the conversion. Day to day changes in this information introduce uncertainty in retrievals. As an example, biomass burning events substantially enhance the NO2 concentration in usually clean regions, causing an underestimation of the NO2 columns due to an incorrect NO2 profile. Similarly, AMFs for pixels surrounding a city will vary day to day as the winds shift, leading to potential underestimation of the plume downwind of the city, with consequences for estimates of NO2 lifetime calculated from these plumes. Building upon the existing BErkeley High Resolution (BEHR) NO2 retrieval, we have implemented daily a priori NO2 profiles to the retrieval algorithm for several test cases and will demonstrate the quantitative effect of these daily profiles on the retrieved NO2 columns.