Abstract. 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.

Anthropogenic CO2 emissions from fossil fuel combustion have large impacts on climate. In order to monitor the increasing CO2 concentrations in the atmosphere, accurate spaceborne observations—as available from the Orbiting Carbon Observatory‐2 (OCO‐2)—are needed. This work provides the first direct observation of anthropogenic CO2 from OCO‐2 over the main pollution regions: eastern USA, central Europe, and East Asia. This is achieved by deseasonalizing and detrending OCO‐2 CO2 observations to derive CO2 anomalies. Several small isolated emission areas (such as large cities) are detectable from the anomaly maps. The spatial distribution of the CO2 anomaly matches the features observed in the maps of the Ozone Monitoring Instrument NO2 tropospheric columns, used as an indicator of atmospheric pollution. The results of a cluster analysis confirm the spatial correlation between CO2 and NO2 data over areas with different amounts of pollution. We found positive correlation between CO2 anomalies and emission inventories. The results demonstrate the power of spaceborne data for monitoring anthropogenic CO2 emissions.

The 2014-2015 Bárðarbunga-Veiðivötn fissure eruption at Holuhraun produced about 1.5 km 3 of lava, making it the largest eruption in Iceland in more than 200 years. Over the course of the eruption, daily volcanic sulfur dioxide (SO 2 ) emissions exceeded daily SO 2 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 SO 2 for September 2014. We show that volcanic SO 2 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 SO 2 mass burden of 99 ± 49 kilotons (kt) of SO 2 from OMI and 61 ± 18 kt of SO 2 from IASI for September 2014. This volcanic burden is at least a factor of 2 greater than the average SO 2 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 SO 2 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 SO 2 during September 2014, in good agreement with ground-based remote sensing and petrological estimates. Although satellite-derived and model-simulated vertical column densities of SO 2 agree well, the model simulations are biased low by up to a factor of 8 when compared to surface observations of volcanic SO 2 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 SO 2 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 SO 2 and other volcanic pollutants.

Abstract. 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.

[1] Several validation studies of surface UV irradiance based on the Ozone Monitoring Instrument (OMI) satellite data have shown a high correlation with ground-based measurements but a positive bias in many locations. The main part of the bias can be attributed to the boundary layer aerosol absorption that is not accounted for in the current satellite UV algorithms. To correct for this shortfall, a postcorrection procedure was applied, based on global climatological fields of aerosol absorption optical depth. These fields were obtained by using global aerosol optical depth and aerosol single scattering albedo data assembled by combining global aerosol model data and ground-based aerosol measurements from AERONET. The resulting improvements in the satellite-based surface UV irradiance were evaluated by comparing satellite and ground-based spectral irradiances at various European UV monitoring sites. The results generally showed a significantly reduced bias by 5 -20%, a lower variability, and an unchanged, high correlation coefficient.