This overview paper highlights the successes of the Ozone Monitoring Instrument (OMI) on board the Aura satellite spanning a period of nearly 14 years. Data from OMI has been used in a wide range of applications and research resulting in many new findings. Due to its unprecedented spatial resolution, in combination with daily global coverage, OMI plays a unique role in measuring trace gases important for the ozone layer, air quality, and climate change. With the operational very fast delivery (VFD; direct readout) and near real-time (NRT) availability of the data, OMI also plays an important role in the development of operational services in the atmospheric chemistry domain.

We present a comparison between satellite-based TROPOMI (TROPOspheric Monitoring Instrument) NO₂ products and ground-based observations in Helsinki (Finland). TROPOMI NO₂ total (summed) columns are compared with the measurements performed by the Pandora spectrometer between April and September 2018. The mean relative and absolute bias between the TROPOMI and Pandora NO₂ total columns is about 10 % and 0.12×10¹⁵ molec. cm⁻² respectively. The dispersion of these differences (estimated as their standard deviation) is 2.2×10¹⁵ molec. cm⁻². We find high correlation (r = 0.68) between satellite- and ground-based data, but also that TROPOMI total columns underestimate ground-based observations for relatively large Pandora NO₂ total columns, corresponding to episodes of relatively elevated pollution. This is expected because of the relatively large size of the TROPOMI ground pixel (3.5×7 km) and the a priori used in the retrieval compared to the relatively small field-of-view of the Pandora instrument. On the other hand, TROPOMI slightly overestimates (within the retrieval uncertainties) relatively small NO₂ total columns. Replacing the coarse a priori NO₂ profiles with high-resolution profiles from the CAMS chemical transport model improves the agreement between TROPOMI and Pandora total columns for episodes of NO₂ enhancement. When only the low values of NO₂ total columns or the whole dataset are taken into account, the mean bias slightly increases. The change in bias remains mostly within the uncertainties. We also analyse the consistency between satellite-based data and in situ NO₂ surface concentrations measured at the Helsinki–Kumpula air quality station (located a few metres from the Pandora spectrometer). We find similar day-to-day variability between TROPOMI, Pandora and in situ measurements, with NO₂ enhancements observed during the same days. Both satellite- and ground-based data show a similar weekly cycle, with lower NO₂ levels during the weekend compared to the weekdays as a result of reduced emissions from traffic and industrial activities (as expected in urban sites). The TROPOMI NO₂ maps reveal also spatial features, such as the main traffic ways and the airport area, as well as the effect of the prevailing south-west wind patterns. This is one of the first works in which TROPOMI NO₂ retrievals are validated against ground-based observations and the results provide an early evaluation of their applicability for monitoring pollution levels in urban sites. Overall, TROPOMI retrievals are valuable to complement the ground-based air quality data (available with high temporal resolution) for describing the spatio-temporal variability of NO₂, even in a relatively small city like Helsinki.

The 2014–2015 Bárðarbunga‐Veiðivötn fissure eruption at Holuhraun produced about 1.5 km³ of lava, making it the largest eruption in Iceland in more than 200 years. Over the course of the eruption, daily volcanic sulfur dioxide (SO₂) emissions exceeded daily SO₂ emissions from all anthropogenic sources in Europe in 2010 by at least a factor of 3. We present surface air quality observations from across Northern Europe together with satellite remote sensing data and model simulations of volcanic SO₂ for September 2014. We show that volcanic SO₂ was transported in the lowermost troposphere over long distances and detected by air quality monitoring stations up to 2750 km away from the source. Using retrievals from the Ozone Monitoring Instrument (OMI) and the Infrared Atmospheric Sounding Interferometer (IASI), we calculate an average daily SO₂ mass burden of 99 ± 49 kilotons (kt) of SO₂ from OMI and 61 ± 18 kt of SO₂ from IASI for September 2014. This volcanic burden is at least a factor of 2 greater than the average SO₂ mass burden between 2007 and 2009 due to anthropogenic emissions from the whole of Europe. Combining the observational data with model simulations using the United Kingdom Met Office's Numerical Atmospheric‐dispersion Modelling Environment model, we are able to constrain SO₂ emission rates to up to 120 kilotons per day (kt/d) during early September 2014, followed by a decrease to 20–60 kt/d between 6 and 22 September 2014, followed by a renewed increase to 60–120 kt/d until the end of September 2014. Based on these fluxes, we estimate that the eruption emitted a total of 2.0 ± 0.6 Tg of SO₂ during September 2014, in good agreement with ground‐based remote sensing and petrological estimates. Although satellite‐derived and model‐simulated vertical column densities of SO₂ agree well, the model simulations are biased low by up to a factor of 8 when compared to surface observations of volcanic SO₂ on 6–7 September 2014 in Ireland. These biases are mainly due to relatively small horizontal and vertical positional errors in the simulations of the volcanic plume occurring over transport distances of thousands of kilometers. Although the volcanic air pollution episodes were transient and lava‐dominated volcanic eruptions are sporadic events, the observations suggest that (i) during an eruption, volcanic SO₂ measurements should be assimilated for near real‐time air quality forecasting and (ii) existing air quality monitoring networks should be retained or extended to monitor SO₂ and other volcanic pollutants.

NASA’s carbon dioxide mission, Orbiting Carbon Observatory-2, began operating in September 2014. In this paper, we analyze four years (2015–2018) of global (60°S–60°N) XCO₂ anomalies and their annual variations and seasonal patterns. We show that the anomaly patterns in the column-averaged CO₂ dry air mole fraction, XCO₂, are robust and consistent from year-to-year. We evaluate the method by comparing the anomalies to fluxes from anthropogenic, biospheric, and biomass burning and to model-simulated local concentration enhancements. We find that, despite the simplicity of the method, the anomalies describe the spatio-temporal variability of XCO₂ (including anthropogenic emissions and seasonal variability related to vegetation and biomass burning) consistently with more complex model-based approaches. We see, for example, that positive anomalies correspond to fossil fuel combustion over the major industrial areas (e.g., China, eastern USA, central Europe, India, and the Highveld region in South Africa), shown as large positive XCO₂ enhancements in the model simulations. We also find corresponding positive anomalies and fluxes over biomass burning areas during different fire seasons. On the other hand, the largest negative anomalies correspond to the growing season in the northern middle latitudes, characterized by negative XCO₂ enhancements from simulations and high solar-induced chlorophyll fluorescence (SIF) values (indicating the occurrence of photosynthesis). The largest discrepancies between the anomaly patterns and the model-based results are observed in the tropical regions, where OCO-2 shows persistent positive anomalies over every season of every year included in this study. Finally, we demonstrate how XCO₂ anomalies enable the detection of anthropogenic signatures for several local scale case studies, both in the Northern and Southern Hemisphere. In particular, we analyze the XCO₂ anomalies collocated with the recent TROPOspheric Monitoring Instrument NO₂ observations (used as indicator of anthropogenic fossil fuel combustion) over the Highveld region in South Africa. The results highlight the capability of satellite-based observations to monitor natural and man-made CO₂ signatures on global scale.