Abstract. The aim of this paper is to highlight how TROPOspheric Monitoring Instrument (TROPOMI) trace gas data can best be used and interpreted to understand event-based impacts on air quality from regional to city scales around the globe. For this study, we present the observed changes in the atmospheric column amounts of five trace gases (NO2, SO2, CO, HCHO, and CHOCHO) detected by the Sentinel-5P TROPOMI instrument and driven by reductions in anthropogenic emissions due to COVID-19 lockdown measures in 2020. We report clear COVID-19-related decreases in TROPOMI NO2 column amounts on all continents. For megacities, reductions in column amounts of tropospheric NO2 range between 14 % and 63 %. For China and India, supported by NO2 observations, where the primary source of anthropogenic SO2 is coal-fired power generation, we were able to detect sector-specific emission changes using the SO2 data. For HCHO and CHOCHO, we consistently observe anthropogenic changes in 2-week-averaged column amounts over China and India during the early phases of the lockdown periods. That these variations over such a short timescale are detectable from space is due to the high resolution and improved sensitivity of the TROPOMI instrument. For CO, we observe a small reduction over China, which is in concert with the other trace gas reductions observed during lockdown; however, large interannual differences prevent firm conclusions from being drawn. The joint analysis of COVID-19-lockdown-driven reductions in satellite-observed trace gas column amounts using the latest operational and scientific retrieval techniques for five species concomitantly is unprecedented. However, the meteorologically and seasonally driven variability of the five trace gases does not allow for drawing fully quantitative conclusions on the reduction in anthropogenic emissions based on TROPOMI observations alone. We anticipate that in future the combined use of inverse modeling techniques with the high spatial resolution data from S5P/TROPOMI for all observed trace gases presented here will yield a significantly improved sector-specific, space-based analysis of the impact of COVID-19 lockdown measures as compared to other existing satellite observations. Such analyses will further enhance the scientific impact and societal relevance of the TROPOMI mission.

Abstract. Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) is a well-established ground-based measurement technique for the detection of aerosols and trace gases particularly in the boundary layer and the lower troposphere: ultraviolet- and visible radiation spectra of skylight are analysed to obtain information on different atmospheric parameters, integrated over the light path from space to the instrument. An appropriate set of spectra recorded under different viewing geometries ("Multi-Axis") allows retrieval of tropospheric aerosol and trace gas vertical distributions by applying numerical inversion methods. The second Cabauw Intercomparison of Nitrogen Dioxide measuring Instruments (CINDI-2) took place in Cabauw (The Netherlands) in September 2016 with the aim of assessing the consistency of MAX-DOAS measurements of tropospheric species (NO2, HCHO, O3, HONO, CHOCHO and O4). This was achieved through the coordinated operation of 36 spectrometers operated by 24 groups from all over the world, together with a wide range of supporting reference observations (in situ analysers, balloon sondes, lidars, Long-Path DOAS, sun photometer and others). In the presented study, the retrieved CINDI-2 MAX-DOAS trace gas (NO2, HCHO) and aerosol vertical profiles of 15 participating groups using different inversion algorithms are compared and validated against the colocated supporting observations. The profiles were found to be in good qualitative agreement: most participants obtained the same features in the retrieved vertical trace gas and aerosol distributions, however sometimes at different altitudes and of different intensity. Under clear sky conditions, the root-mean-square differences of aerosol optical thicknesses, trace gas (NO2, HCHO) vertical columns and surface concentrations among the results of individual participants vary between 0.01–0.1, (1.5–15) x 1014 molec cm-2 and (0.3–8) x 1010 molec cm-3, respectively. For the comparison against supporting observations, these values increase to 0.02–0.2, (11–55) x 1014 molec cm-2 and (0.8–9) x 1010 molec cm-3. It is likely that a large part of this increase is caused by imperfect spatio-temporal overlap of the different observations. In contrast to what is often assumed, the MAX-DOAS vertically integrated extinction profiles and the sun photometer total aerosol optical thickness were found to not necessarily being comparable quantities, unless information on the real aerosol vertical distribution is available to account for the low sensitivity of MAX-DOAS observations at higher altitudes.

Abstract. This overview paper highlights the successes of the Ozone Monitoring Instrument (OMI) spanning more than 12 25 years of the OMI data record. Data from OMI has been used in a wide range of applications. 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, including new research findings using these satellite data. Due to 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 early development of operational services in the atmospheric chemistry domain. 30

Abstract. The ultraviolet (UV) Absorbing Aerosol Index (AAI) is widely used as an indicator for the presence of absorbing aerosols in the atmosphere. Here we consider the TROPOMI AAI based on the 340/380 nm wavelength pair. We investigate the effects of clouds on the AAI observed at small and large scales. The large scale effects are studied using an aggregate of TROPOMI measurements over an area mostly devoid of absorbing aerosols (Pacific Ocean). The study reveals that several structural features can be distinguished in the AAI, such as the cloud bow, viewing zenith angle dependence, sunglint, and a previously unexplained increase in AAI values at extreme viewing and solar geometries. We explain these features in terms of the Bidirectional Reflectance Distribution Function (BRDF) of the scene in combination with the different ratio of diffuse and direct illumination of the surface at 340 and 380 nm. To reduce the dependency on the BRDF and homogenize the AAI distribution across the orbit, we present three different AAI retrieval models: the traditional Lambertian Scene Model (LSM), a Lambertian Cloud Model (LCM), and a Scattering Cloud Model (SCM). We perform a model study to assess the propagation of errors in auxiliary databases used in the cloud models. The three models are then applied to the same low-aerosol region. Results show that using the LCM and SCM gives on average a higher AAI than the LSM. Additionally, a more homogeneous distribution is retrieved across the orbit. At the small scale, related to the high spatial resolution of TROPOMI, strong local increases and decreases in AAI are observed in the presence of clouds. This effect was not observed in previous instruments with larger ground pixels such as GOME-2 and OMI. More research is needed to explain these small scale effects.

<p>The lockdown measures taken to combat the COVID-19 virus implemented in a majority of countries worldwide have had a dramatic impact on the anthropogenic pollutant emissions, related to a drastic reduction of road and air traffic, as well as part of the industrial activities. In our contribution we investigate the presence of COVID-19-related imprints in air quality as observed from space, focussing on worldwide industrial/highly populated regions where strong lockdown measures have been taken (e.g., China, Europe, US). This is done by exploiting the observations of the TROPOMI instrument onboard the Copernicus Sentinel-5P platform, for a number of trace gases which are indicators of anthropogenic activity. We make use of the TROPOMI operational product portfolio, which includes tropospheric NO2, CO, SO2, and HCHO. These operational data products are complemented by other scientific products such as the BIRA-IASB glyoxal (CHOCHO) retrievals and a new SO2 retrieval algorithm called COBRA. The reductions in NO2 observed by TROPOMI have been documented already in the recent literature for several regions and countries worldwide. In our contribution we focus on the combined observations of multiple trace gases, which provides not only information about how much primary (NOx) emissions decreased, but also gives region-to-region insights and constraints on the overall changes in atmospheric composition as a result of these lockdowns.</p>