Exploring the utility of global high-resolution NO2 columns from TROPOMI for investigating the diurnal variability and downscaling historical measurements

Satellite remote sensing techniques can provide detailed information on the spatial and temporal distribution of nitrogen dioxide (NO₂) in the troposphere, which enables us to monitor changes in NO₂ levels over time and assess the effectiveness of emissions reduction measures. The TROPOspheric Monitoring Instrument (TROPOMI/Sentinel-5P) is particularly useful for identifying pollution sources within individual urban areas, as it has a higher spatial resolution with daily global coverage. In this study, we first compared the S5P-PAL reprocessing data with offline products (processor versions are earlier than v2.3.1) and used ground-based Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) observations in Xuzhou (a city in eastern China) to evaluate the performance. It was found that the size of the footprint can impact the validation results, and the smaller pixels (<29 km²) have a higher correlation with MAX-DOAS (R=0.91). Then we explored its serendipitous capability with the advantages of orbital characteristics and the high spatial resolution of the sensor. Using the overlapping orbits of TROPOMI at high latitudes, we applied a model-free inversion approach to derive diurnal NOx emissions. The orbits of Sentinel-5P allow for a greater than 20% probability of being observed twice within a 100-minute interval on the same day within a range from 35° to high latitudes.  Besides that, we proposed a downscaling method to generate high-resolution (0.05°) NO₂ columns from the Ozone Monitoring Instrument (OMI/Aura) retrievals, which has provided continuous measurements since 2004 while having the limitation of relatively low spatial resolution. This model used data from the common observation period of TROPOMI and OMI after 2018 to derive the relationship between high- and low-resolution NO₂ concentrations and applied to the historical dataset. Overall, this study demonstrates the utility of overlapping NO₂ columns for investigating diurnal variability and highlights the importance of the spatial scale when analyzing and interpreting NO₂ data.