The Geostationary Environment Monitoring Spectrometer (GEMS) is scheduled for launch in February 2020 to monitor air quality (AQ) at an unprecedented spatial and temporal resolution from a geostationary Earth orbit (GEO) for the first time. With the development of UV–visible spectrometers at sub-nm spectral resolution and sophisticated retrieval algorithms, estimates of the column amounts of atmospheric pollutants (O₃, NO₂, SO₂, HCHO, CHOCHO, and aerosols) can be obtained. To date, all the UV–visible satellite missions monitoring air quality have been in low Earth orbit (LEO), allowing one to two observations per day. With UV–visible instruments on GEO platforms, the diurnal variations of these pollutants can now be determined. Details of the GEMS mission are presented, including instrumentation, scientific algorithms, predicted performance, and applications for air quality forecasts through data assimilation. GEMS will be on board the Geostationary Korea Multi-Purpose Satellite 2 (GEO-KOMPSAT-2) satellite series, which also hosts the Advanced Meteorological Imager (AMI) and Geostationary Ocean Color Imager 2 (GOCI-2). These three instruments will provide synergistic science products to better understand air quality, meteorology, the long-range transport of air pollutants, emission source distributions, and chemical processes. Faster sampling rates at higher spatial resolution will increase the probability of finding cloud-free pixels, leading to more observations of aerosols and trace gases than is possible from LEO. GEMS will be joined by NASA’s Tropospheric Emissions: Monitoring of Pollution (TEMPO) and ESA’s Sentinel-4 to form a GEO AQ satellite constellation in early 2020s, coordinated by the Committee on Earth Observation Satellites (CEOS).

The Geostationary Environmental Monitoring Spectrometer (GEMS) is a UV-visible (UV-Vis) spectrometer on board the GEO-KOMPSAT-2B (Geostationary Korea Multi-Purpose Satellite 2B) satellite launched into a geostationary orbit in February 2020. To evaluate the GEMS NO₂ total column data, a comparison was carried out using the NO₂ vertical column density (VCD) that measured direct sunlight using the Pandora spectrometer system at four sites in Seosan, South Korea, from November 2020 to January 2021. Correlation coefficients between GEMS and Pandora NO₂ data at four sites ranged from 0.35 to 0.48, with root mean square errors (RMSEs) from 4.7×10¹⁵ to 5.5×10¹⁵ molec. cm⁻² for a cloud fraction (CF) <0.7. Higher correlation coefficients of 0.62–0.78 with lower RMSEs from 3.3×10¹⁵ to 5.0×10¹⁵ molec. cm⁻² were found with CF <0.3, indicating the higher sensitivity of GEMS to atmospheric NO₂ in less cloudy conditions. Overall, the GEMS NO₂ total column data tended to be lower than the Pandora data, owing to differences in the representative spatial coverage, with a large negative bias under high CF conditions. With a correction for horizontal representativeness in the Pandora measurement coverage, correlation coefficients ranging from 0.69 to 0.81, with RMSEs from 3.2×10¹⁵ to 4.9×10¹⁵ molec. cm⁻², were achieved for CF <0.3, showing a better correlation with the correction than without the correction.

The Geostationary Environment Monitoring Spectrometer (GEMS) launched in February 2020 is now providing continuous daytime hourly observations of nitrogen dioxide (NO₂) columns over eastern Asia (5° S–45° N, 75–145° E) with 3.5 × 7.7 km² pixel resolution. These data provide unique information to improve understanding of the sources, chemistry, and transport of nitrogen oxides (NO_x) with implications for atmospheric chemistry and air quality, but opportunities for direct validation are very limited. Here we correct the operational level-2 (L2) NO₂ vertical column densities (VCDs) from GEMS with a machine learning (ML) model to match the much sparser but more mature observations from the low Earth orbit TROPOspheric Monitoring Instrument (TROPOMI), preserving the data density of GEMS but making them consistent with TROPOMI. We first reprocess the GEMS and TROPOMI operational L2 products to use common prior vertical NO₂ profiles (shape factors) from the GEOS-Chem chemical transport model. This removes a major inconsistency between the two satellite products and greatly improves their agreement with ground-based Pandora NO₂ VCD data in source regions. We then apply the ML model to correct the remaining differences, Δ(GEMS–TROPOMI), using the GEMS NO₂ VCDs and retrieval parameters as predictor variables. We train the ML model with colocated GEMS and TROPOMI NO₂ VCDs, taking advantage of TROPOMI off-track viewing to cover the wide range of effective zenith angles (EZAs) observed by GEMS. The two most important predictor variables for Δ(GEMS–TROPOMI) are GEMS NO₂ VCD and EZA. The corrected GEMS product is unbiased relative to TROPOMI and shows a diurnal variation over source regions more consistent with Pandora than the operational product.

Nitrogen oxide radicals $({\mathrm{NO}}_x\equiv \mathrm{NO}+{\mathrm{NO}}_{\mathrm{2}})$ emitted by fuel combustion are important precursors of ozone and particulate matter pollution, and NO₂ itself is harmful to public health. The Geostationary Environment Monitoring Spectrometer (GEMS), launched in space in 2020, now provides hourly daytime observations of NO₂ columns over East Asia. This diurnal variation offers unique information on the emission and chemistry of NO_x, but it needs to be carefully interpreted. Here we investigate the drivers of the diurnal variation in NO₂ observed by GEMS during winter and summer over Beijing and Seoul. We place the GEMS observations in the context of ground-based column observations (Pandora instruments) and GEOS-Chem chemical transport model simulations. We find good agreement between the diurnal variations in NO₂ columns in GEMS, Pandora, and GEOS-Chem, and we use GEOS-Chem to interpret these variations. NO_x emissions are 4 times higher in the daytime than at night, driving an accumulation of NO₂ over the course of the day, offset by losses from chemistry and transport (horizontal flux divergence). For the urban core, where the Pandora instruments are located, we find that NO₂ in winter increases throughout the day due to high daytime emissions and increasing ${\mathrm{NO}}_{\mathrm{2}}/{\mathrm{NO}}_x$ ratio from entrainment of ozone, partly balanced by loss from transport and with a negligible role of chemistry. In summer, by contrast, chemical loss combined with transport drives a minimum in the NO₂ column at 13:00–14:00 local time (LT). Segregation of the GEMS data by wind speed further demonstrates the effect of transport, with NO₂ in winter accumulating throughout the day at low winds but flat at high winds. The effect of transport can be minimized in summer by spatially averaging observations over the broader metropolitan scale, under which conditions the diurnal variation in NO₂ reflects a dynamic balance between emission and chemical loss.

The Geostationary Environment Monitoring Spectrometer (GEMS) over Asia is the first geostationary Earth orbit instrument in the virtual constellation of sensors for atmospheric chemistry and composition air quality research and applications. For the first time, the hourly observations enable studies of diurnal variation in several important trace gas and aerosol pollutants including nitrogen dioxide (NO₂), which is the focus of this work. NO₂ is a regulated pollutant and an indicator of anthropogenic emissions in addition to being involved in tropospheric ozone chemistry and particulate matter formation. We present new quantitative measures of NO₂ tropospheric column diurnal variation which can be greater than 50 % of the column amount, especially in polluted environments. The NO₂ distribution is seen to change hourly and can be quite different from what would be seen by a once-a-day low-Earth-orbit satellite observation. We use GEMS data in combination with TROPOspheric Monitoring Instrument (TROPOMI) satellite and Pandora ground-based remote sensing measurements and Multi-Scale Infrastructure for Chemistry and Aerosols (Version 0, MUSICAv0) 3D chemical transport model analysis to examine the NO₂ diurnal variation in January and June 2023 over Northeast Asia and Seoul, South Korea, study regions to distinguish the different emissions, chemistry, and meteorological processes that drive the variation. Understanding the relative importance of these processes will be key to including pollutant diurnal variation in models aimed at determining true pollutant exposure levels for air quality studies. The work presented here also provides a path for investigating similar NO₂ diurnal cycles in the new Earth Venture Instrument-1 Tropospheric Emissions: Monitoring Pollution (TEMPO) data over North America, and later over Europe with Sentinel-4.

Tropospheric vertical column densities (VCDs) of nitrogen dioxide (NO₂) retrieved from sun-synchronous satellite instruments have provided abundant NO₂ data for environmental studies, but such data are limited by retrieval uncertainties and insufficient temporal sampling (e.g., once a day). The Geostationary Environment Monitoring Spectrometer (GEMS) launched in February 2020 monitors NO₂ at an unprecedented hourly resolution during the daytime. Here we present a research product for tropospheric NO₂ VCDs, referred to as POMINO–GEMS (where POMINO is the Peking University OMI NO₂ algorithm). We develop a hybrid retrieval method combining GEMS, TROPOMI (TROPOspheric Monitoring Instrument) and GEOS-CF (Global Earth Observing System Composition Forecast) data to generate hourly tropospheric NO₂ slant column densities (SCDs). We then derive tropospheric NO₂ air mass factors (AMFs) with explicit corrections for surface reflectance anisotropy and aerosol optical effects through parallelized pixel-by-pixel radiative transfer calculations. Prerequisite cloud parameters are retrieved with the O₂–O₂ algorithm by using ancillary parameters consistent with those used in NO₂ AMF calculations. The initial retrieval of POMINO–GEMS tropospheric NO₂ VCDs for June–August 2021 exhibits strong hotspot signals over megacities and distinctive diurnal variations over polluted and clean areas. POMINO–GEMS NO₂ VCDs agree with the POMINO–TROPOMI v1.2.2 product (R=0.98; NMB = 4.9 %) over East Asia, with slight differences associated with satellite viewing geometries and cloud and aerosol properties affecting the NO₂ retrieval. POMINO–GEMS also shows good agreement with the following: OMNO2 (Ozone Monitoring Instrument (OMI) NO₂ Standard Product) v4 (R=0.87; NMB = −16.8 %); and GOME-2 (Global Ozone Monitoring Experiment-2) GDP (GOME Data Processor) 4.8 (R=0.83; NMB = −1.5 %) NO₂ products. POMINO–GEMS shows small biases against ground-based MAX-DOAS (multi-axis differential optical absorption spectroscopy) NO₂ VCD data at nine sites (NMB = −11.1 %), with modest or high correlation in diurnal variation at six urban and suburban sites (R from 0.60 to 0.96). The spatiotemporal variation in POMINO–GEMS correlates well with mobile car MAX-DOAS measurements in the Three Rivers source region on the Tibetan Plateau (R=0.81). Surface NO₂ concentrations estimated from POMINO–GEMS VCDs are consistent with measurements from the Ministry of Ecology and Environment of China for spatiotemporal variation (R=0.78; NMB = −26.3 %) and diurnal variation at all, urban, suburban and rural sites (R≥0.96). POMINO–GEMS data will be made freely available for users to study the spatiotemporal variations, sources and impacts of NO₂.