TROPOMI NO₂ Tropospheric Column Data: Regridding to 1 km Grid-Resolution and Assessment of their Consistency with In Situ Surface Observations

Abstract

This work presents a regridding procedure applied to the nitrogen dioxide (NO2) tropospheric column data, derived from the Copernicus Sentinel 5 Precursor Tropospheric Monitoring Instrument (S5P/TROPOMI). The regridding has been performed to provide a better comparison with punctual surface observations. It will be demonstrated that TROPOMI NO2 tropospheric column data show improved consistency with in situ surface measurements once the satellite retrievals are scaled to 1 km spatial sampling. A geostatistical technique, i.e., the ordinary kriging, has been applied to improve the spatial distribution of Level 2 TROPOMI NO2 data, which is originally sparse and uneven because of gaps introduced by clouds, to a final spatial, regular, sampling of 1 km × 1 km. The analysis has been performed for two study areas, one in the North and the other in the South of Italy, and for May 2018-April 2020, which also covers the period January 2020-April 2020 of COVID-19 diffusion over the Po Valley. The higher spatial sampling NO2 dataset indicated as Level 3 data, allowed us to explore spatial and seasonal data variability, obtaining better information on NO2 sources. In this respect, it will be shown that NO2 concentrations in March 2020 have likely decreased as a consequence of the lockdown because of COVID-19, although the far warmest winter season ever recorded over Europe in 2020 has favored a general NO2 decrease in comparison to the 2019 winter. Moreover, the comparison between NO2 concentrations related to weekdays and weekend days allowed us to show the strong correlation of NO2 emissions with traffic and industrial activities. To assess the quality and capability of TROPOMI NO2 observations, we have studied their relationship and correlation with in situ NO2 concentrations measured at air quality monitoring stations. We have found that the correlation increases when we pass from Level 2 to Level 3 data, showing the importance of regridding the satellite data. In particular, correlation coefficients of Level 3 data, which range between 0.50–0.90 have been found with higher correlation applying to urban, polluted locations and/or cities.

Keywords

• TROPOMI/S5P
• nitrogen dioxide
• air quality
• ordinary kriging