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AbstractSince its first confirmed case in December 2019, coronavirus disease 2019 (COVID-19) has become a worldwide pandemic with more than 90 million confirmed cases by January 2021. Countries around the world have enforced lockdown measures to prevent the spread of the virus, introducing a temporal change of air pollutants such as nitrogen dioxide (NO2) that are strongly related to transportation, industry, and energy. In this study, NO2 variations over regions with strong responses to COVID-19 are analysed using datasets from the Global Ozone Monitoring Experiment-2 (GOME-2) sensor aboard the EUMETSAT Metop satellites and TROPOspheric Monitoring Instrument (TROPOMI) aboard the EU/ESA Sentinel-5 Precursor satellite. The global GOME-2 and TROPOMI NO2 datasets are generated at the German Aerospace Center (DLR) using harmonized retrieval algorithms; potential influences of the long-term trend and seasonal cycle, as well as the short-term meteorological variation, are taken into account statistically. We present the application of the GOME-2 data to analyze the lockdown-related NO2 variations for morning conditions. Consistent NO2 variations are observed for the GOME-2 measurements and the early afternoon TROPOMI data: regions with strong social responses to COVID-19 in Asia, Europe, North America, and South America show strong NO2 reductions of $\sim $
∼
30–50% on average due to restriction of social and economic activities, followed by a gradual rebound with lifted restriction measures.

In this study we present an updated perspective on near-global total ozone trends for the period 1995–2020. We use the GOME-type Total Ozone Essential Climate Variable (GTO-ECV) satellite data record which has been extended and generated as part of the European Space Agency's Climate Change Initiative (ESA-CCI) and European Union Copernicus Climate Change Service (EU-C3S) ozone projects. The focus of our work is the analysis of regional patterns in the ozone trend as well as the investigation of its seasonal dependence. In the Southern Hemisphere we found regions that indicate statistically significant positive trends increasing from 0.6 ± 0.5 % decade −1 in the subtropics to 1.0 ± 0.9 % decade −1 in the middle latitudes and 2.8 ± 2.6 % decade −1 in the latitude band 60°–70° S. In the middle latitudes of the Northern Hemisphere the trend exhibits distinct regional patterns, i.e. latitudinal and longitudinal structures. Significant positive trends (∼1.5 ± 1.0 % decade −1 ) over the North Atlantic region as well as negative trends (−1.0 ± 1.0 % decade −1 ) over Eastern Europe were found. Moreover, these trends indicate a correlation with long-term changes in tropopause pressure. Total ozone trends in the tropics are not significant. Regarding the seasonal dependence of the trends we found only very small variations over the course of the year. However, we identified different behavior depending on latitude. In the latitude band 40°–70° N the positive trend maximizes in boreal winter from December to February. In the middle latitudes of the Southern Hemisphere (35°–50° S) the trend is maximum from March to May. Further south toward the high latitudes (55°–70° S) the trend denotes a relatively strong seasonal cycle which varies from 2 % decade −1 in December and January to 3.8 % decade −1 in June and July.

The accurate determination of the location, height, and loading of sulfur dioxide (SO2) plumes emitted by volcanic eruptions is essential for aviation safety. The SO2 layer height is also one of the most critical parameters with respect to determining the impact on the climate. Retrievals of SO2 plume height have been carried out using satellite UV backscatter measurements, but, until now, such algorithms are very time-consuming. We have developed an extremely fast yet accurate SO2 layer height retrieval using the Full-Physics Inverse Learning Machine (FP_ILM) algorithm. This is the first time the algorithm has been applied to measurements from the TROPOMI instrument onboard the Sentinel-5 Precursor platform. In this paper, we demonstrate the ability of the FP_ILM algorithm to retrieve SO2 plume layer heights in near-real-time applications with an accuracy of better than 2 km for SO2 total columns larger than 20 DU. We present SO2 layer height results for the volcanic eruptions of Sinabung in February 2018, Sierra Negra in June 2018, and Raikoke in June 2019, observed by TROPOMI. ; SCOPUS: ar.j ; info:eu-repo/semantics/published

This paper assesses the quality of IASI (Infrared Atmospheric Sounding Interferometer)/Metop-A (IASI-A) and IASI/Metop-B (IASI-B) ozone (O3) products (total and partial O3 columns) retrieved with the Fast Optimal Retrievals on Layers for IASI Ozone (FORLI-O3; v20151001) software for 9 years (2008-July 2017) through an extensive intercomparison and validation exercise using independent observations (satellite, ground-based and ozonesonde). Compared with the previous version of FORLI-O3 (v20140922), several improvements have been introduced in FORLI-O3 v20151001, including absorbance look-up tables recalculated to cover a larger spectral range, with additional numerical corrections. This leads to a change of ĝ1/4 4 % in the total ozone column (TOC) product, which is mainly associated with a decrease in the retrieved O3 concentration in the middle stratosphere (above 30 hPa/25 km). IASI-A and IASI-B TOCs are consistent, with a global mean difference of less than 0.3 % for both daytime and nighttime measurements; IASI-A is slightly higher than IASI-B. A global difference of less than 2.4 % is found for the tropospheric (TROPO) O3 column product (IASI-A is lower than IASI-B), which is partly due to a temporary issue related to the IASI-A viewing angle in 2015. Our validation shows that IASI-A and IASI-B TOCs are consistent with GOME-2 (Global Ozone Monitoring Experiment-2), Dobson, Brewer, SAOZ (Système d'Analyse par Observation Zénithale) and FTIR (Fourier transform infrared) TOCs, with global mean differences in the range of 0.1 %-2 % depending on the instruments compared. The worst agreement with UV-vis retrieved TOC (satellite and ground) is found at the southern high latitudes. The IASI-A and ground-based TOC comparison for the period from 2008 to July 2017 shows the long-Term stability of IASI-A, with insignificant or small negative drifts of 1 %-3 % decadeĝ'1. The comparison results of IASI-A and IASI-B against smoothed FTIR and ozonesonde partial O3 columns vary with altitude and latitude, with the maximum ...

This paper presents an extensive intercomparison and validation for the ozone (O3) product measured by the two Infrared Atmospheric Sounding Interferometers (IASIs) launched on board the MetOp-A and MetOp-B satellites in 2006 and in 2012 respectively. IASI O3 total columns and vertical profiles obtained from Fast Optimal Retrievals on Layers for IASI (FORLI) v20140922 software (running up until recently) are validated against independent observations during the period 2008-2014 on a global scale. On average for the period 2013-2014, IASI-A and IASI-B total ozone columns (TOCs) retrieved using FORLI are consistent, with IASI-B providing slightly lower values with a global difference of only 0.2±0.8%. The comparison between IASI-A and IASI-B O3 vertical profiles shows differences within ±2% over the entire altitude range. Global validation results for 7 years of IASI TOCs from FORLI against the Global Ozone Monitoring Experiment-2 (GOME-2) launched on board MetOp-A and Brewer-Dobson data show that, on average, IASI overestimates the ultraviolet (UV) data by 5-6% with the largest differences found in the southern high latitudes. The comparison with UV-visible SAOZ (Système d'Analyse par Observation Zénithale) measurements shows a mean bias between IASI and SAOZ TOCs of 2-4% in the midlatitudes and tropics and 7% at the polar circle. Part of the discrepancies found at high latitudes can be attributed to the limited information content in the observations due to low brightness temperatures. The comparison with ozonesonde vertical profiles (limited to 30km) shows that on average IASI with FORLI processing underestimates O3 by ∼ 5-15% in the troposphere while it overestimates O3 by ∼ 10-40% in the stratosphere, depending on the latitude. The largest relative differences are found in the tropical tropopause region; this can be explained by the low O3 amounts leading to large relative errors. In this study, we also evaluate an updated version of FORLI-O3 retrieval software (v20151001), using look-up tables recalculated ...

33 pags., 23 figs., 5 tabs. ; The TROPOspheric Monitoring Instrument(TROPOMI), launched in October 2017 on board the Sentinel-5 Precursor (S5P) satellite, monitors the composition of the Earth's atmosphere at an unprecedented horizontal resolution as fine as 3.5×5.5 km2. This paper assesses the performances of the TROPOMI formaldehyde(HCHO) operational product compared to its predecessor, the OMI (Ozone Monitoring Instrument) HCHO QA4ECV product, at different spatial and temporal scales. The parallel development of the two algorithms favoured the consistency of the products, which facilitates the production of long-term combined time series. The main difference between the two satellite products is related to the use of different cloud algorithms, leading to a positive bias of OMI compared to TROPOMI of up to 30% in tropical regions. We show that after switching off the explicit correction for cloud effects, the two datasets come into an excellent agreement. For medium to large HCHO vertical columns(larger than 5×1015 molec. cm-2) the median bias between OMI and TROPOMI HCHO columns is not larger than 10% (<0.4×1015 molec. cm-2). For lower columns, OMI observations present a remaining positive bias of about 20% (<0.8×1015 molec. cm-2) compared to TROPOMI in midlatitude regions. Here, we also use a global network of 18 MAX-DOAS (multi-axis differential optical absorption spectroscopy) instruments to validate both satellite sensors for a large range of HCHO columns. This work complements the study by Vigouroux et al. (2020), where a global FTIR(Fourier transform infrared) network is used to validate the TROPOMI HCHO operational product. Consistent with the FTIR validation study, we find that for elevated HCHO columns, TROPOMI data are systematically low (-25% for HCHO columns larger than 8 × 1015 molec. cm-2), while no significant bias is found for medium-range column values. We further show that OMI and TROPOMI data present equivalent biases for large HCHO levels. However, TROPOMI significantly improves the precision of the HCHO observations at short temporal scales and for low HCHO columns. We show that compared to OMI, the precision of the TROPOMI HCHO columns is improved by 25% for individual pixels and by up to a factor of 3 when considering daily averages in 20 km radius circles. The validation precision obtained with daily TROPOMI observations is comparable to the one obtained with monthly OMI observations. To illustrate the improved performances of TROPOMI in capturing weak HCHO signals, we present clear detection of HCHO column enhancements related to shipping emissions in the Indian Ocean. This is achieved by averaging data over a much shorter period (3 months) than required with previous sensors (5 years) and opens new perspectives to study shipping emissions of VOCs (volatile organic compounds) and related atmospheric chemical interactions. ; Part of the reported work was carried out in the framework of the Copernicus Sentinel-5 Precursor Mission Performance Centre (S5p MPC), contracted by the European Space Agency (ESA/ESRIN, contract no. 4000117151/16/I-LG) and supported by the Belgian Federal Science Policy Office (BELSPO), the Royal Belgian Institute for Space Aeronomy (BIRA-IASB) and the German Aerospace Centre (DLR). BIRA-IASB acknowledges national funding from BELSPO and ESA through the ProDEx projects TRACE-S5P (TRACE-S5P project) and TROVA. Part of this work was also carried out in the framework of the S5p Validation Team (S5PVT) AO projects NIDFORVAL (ID no. 28607, PI Gaia Pinardi, Corinne Vigouroux, BIRA-IASB). Multi-sensor HCHO developments have been funded by the EU FP7 QA4ECV project (grant no. 607405), in close cooperation with KNMI, University of Bremen, MPIC-Mainz and WUR. Work by Hitoshi Irie was supported by the Environment Research and Technology Development Fund (JPMEERF20192001 and JPMEERF20215005) of the Environmental Restoration and Conservation Agency of Japan, JSPS KAKENHI (grant numbers JP19H04235 and JP20H04320) and the JAXA 2nd Research Announcement on the Earth Observations (grant number 19RT000351).