Harmonized tropospheric NO2 retrieval for LEO and GEO constellations

Kurzfassung

Over the past few decades, the global distribution and trends of atmospheric NO2 have been monitored from space by polar sun-synchronous low-earth-orbiting (LEO) satellite instruments, such as the Global Ozone Monitoring Experiment (GOME), SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY (SCIAMACHY), Ozone Monitoring Instrument (OMI), Global Ozone Monitoring Experiment-2 (GOME-2), and Tropospheric Monitoring Instrument (TROPOMI). While these LEO measurements have greatly enhanced our understanding of global tropospheric NO2 levels and their long-term trends, they offer observations only once per day at a specific local time. To address this limitation, a constellation of geostationary orbiting satellite sensors (GEO) is being deployed, including the Geostationary Environment Monitoring Spectrometer (GEMS) for Asia, Tropospheric Emissions: Monitoring of Pollution (TEMPO) for North America, and two Sentinel-4 (S4) missions for Europe. Although the GEO monitoring system has limited spatial coverage, it provides multiple observations per day, enabling detailed monitoring of diurnal variations in NO2 due to changes in emissions and chemical reactions throughout the day. As described, LEO (daily global monitoring) and GEO (hourly monitoring over specific domains) each have distinct advantages and limitations. Therefore, by complementing each other and combining their strengths, a synergetic effect can be achieved in monitoring atmospheric compositions including NO2. However, obtaining consistent data on total, stratospheric and tropospheric NO2 columns from LEO and GEO satellites is challenging since their current operational algorithms use different retrieval approaches (e.g. stratosphere-troposphere separation, cloud corrections) and auxiliary data. In this study, we aim to develop a harmonized retrieval system for tropospheric NO2 columns applicable to both LEO and GEO satellite measurements. The DLR NO2 retrieval algorithm for LEO and GEO constellations (NO2_LGC) consists of three key steps: (1) the spectral retrieval of total NO2 slant columns, (2) the separation of slant columns into stratospheric and tropospheric contributions using the Copernicus Atmosphere Monitoring Service (CAMS) forecast model data, and (3) the conversion of tropospheric slant columns to tropospheric vertical columns using air mass factors (AMFs). Based on Seo et al. (2024), a consistent retrieval approach is applied across current LEO (e.g. TROPOMI) and GEO (e.g. GEMS and TEMPO) observations, using identical forecast model, cloud corrections, and auxiliary data. This harmonized retrieval algorithm for the LEO+GEO constellation provides more consistent NO2 data records from TROPOMI, GEMS and TEMPO and will be extended to future GEO and LEO missions including Sentinel-4 and Sentinel-5. Additionally, we demonstrate that the combination of harmonized LEO and GEO NO2_LGC retrievals is beneficial for NO2 analysis in areas with high pollution levels as well as pollution outflows.