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The evolution of NO2, considered as a proxy for air pollution, was analyzed to evaluate the impact of the first lockdown (17 March–10 May 2020) over the Île-de-France region (Paris and surroundings). Tropospheric NO2 columns measured by two UV-Visible Système d'Analyse par Observation Zénithale (SAOZ) spectrometers were analyzed to compare the evolution of NO2 between urban and suburban sites during the lockdown. The urban site is the observation platform QualAir (48∘50′ N / 2∘21′ E) at the Sorbonne University Pierre and Marie Curie Campus in the center of Paris. The suburban site is located at Guyancourt (48∘46′N / 2∘03′E), Versailles Saint-Quentin-en-Yvelines University, 24 km southwest of Paris. Tropospheric NO2 columns above Paris and Guyancourt have shown similar values during the whole lockdown period from March to May 2020. A decade of data sets were filtered to consider air masses at both sites with similar meteorological conditions. The median NO2 columns and the surface measurements of Airparif (Air Quality Observatory in Île de France) during the lockdown period in 2020 were compared to the extrapolated values estimated from a linear trend analysis for the 2011–2019 period at each station. Negative NO2 trends of −1.5 Pmolec. cm−2 yr−1 (∼ −6.3 % yr−1) are observed from the columns, and trends of −2.2 µg m−3 yr−1 (∼ −3.6 % yr−1) are observed from the surface concentration. The negative anomaly in tropospheric columns in 2020 attributed to the lockdown (and related emission reductions) was found to be 56 % at Paris and 46 % at Guyancourt, respectively. A similar anomaly was found in the data of surface concentrations, amounting to 53 % and 28 % at the urban and suburban sites, accordingly.

This paper reports on consolidated ground-based validation results of the atmospheric NO2 data produced operationally since April 2018 by the TROPOspheric Monitoring Instrument (TROPOMI) on board of the ESA/EU Copernicus Sentinel-5 Precursor (S5P) satellite. Tropospheric, stratospheric, and total NO2 column data from S5P are compared to correlative measurements collected from, respectively, 19 Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS), 26 Network for the Detection of Atmospheric Composition Change (NDACC) Zenith-Scattered-Light DOAS (ZSL-DOAS), and 25 Pandonia Global Network (PGN)/Pandora instruments distributed globally. The validation methodology gives special care to minimizing mismatch errors due to imperfect spatio-temporal co-location of the satellite and correlative data, e.g. by using tailored observation operators to account for differences in smoothing and in sampling of atmospheric structures and variability and photochemical modelling to reduce diurnal cycle effects. Compared to the ground-based measurements, S5P data show, on average, (i) a negative bias for the tropospheric column data, of typically −23 % to −37 % in clean to slightly polluted conditions but reaching values as high as −51 % over highly polluted areas; (ii) a slight negative median difference for the stratospheric column data, of about −0.2 Pmolec cm−2, i.e. approx. −2 % in summer to −15 % in winter; and (iii) a bias ranging from zero to −50 % for the total column data, found to depend on the amplitude of the total NO2 column, with small to slightly positive bias values for columns below 6 Pmolec cm−2 and negative values above. The dispersion between S5P and correlative measurements contains mostly random components, which remain within mission requirements for the stratospheric column data (0.5 Pmolec cm−2) but exceed those for the tropospheric column data (0.7 Pmolec cm−2). While a part of the biases and dispersion may be due to representativeness differences such as different area averaging and measurement times, it is known that errors in the S5P tropospheric columns exist due to shortcomings in the (horizontally coarse) a priori profile representation in the TM5-MP chemical transport model used in the S5P retrieval and, to a lesser extent, to the treatment of cloud effects and aerosols. Although considerable differences (up to 2 Pmolec cm−2 and more) are observed at single ground-pixel level, the near-real-time (NRTI) and offline (OFFL) versions of the S5P NO2 operational data processor provide similar NO2 column values and validation results when globally averaged, with the NRTI values being on average 0.79 % larger than the OFFL values.

In October 2017, the Sentinel-5 Precursor (S5P) mission was launched, carrying the TROPOspheric Monitoring Instrument (TROPOMI), which provides a daily global coverage at a spatial resolution as high as 7 km × 3.5 km and is expected to extend the European atmospheric composition record initiated with GOME/ERS-2 in 1995, enhancing our scientific knowledge of atmospheric processes with its unprecedented spatial resolution. Due to the ongoing need to understand and monitor the recovery of the ozone layer, as well as the evolution of tropospheric pollution, total ozone remains one of the leading species of interest during this mission. In this work, the TROPOMI near real time (NRTI) and offline (OFFL) total ozone column (TOC) products are presented and compared to daily ground-based quality-assured Brewer and Dobson TOC measurements deposited in the World Ozone and Ultraviolet Radiation Data Centre (WOUDC). Additional comparisons to individual Brewer measurements from the Canadian Brewer Network and the European Brewer Network (Eubrewnet) are performed. Furthermore, twilight zenith-sky measurements obtained with ZSL-DOAS (Zenith Scattered Light Differential Optical Absorption Spectroscopy) instruments, which form part of the SAOZ network (Système d'Analyse par Observation Zénitale), are used for the validation. The quality of the TROPOMI TOC data is evaluated in terms of the influence of location, solar zenith angle, viewing angle, season, effective temperature, surface albedo and clouds. For this purpose, globally distributed ground-based measurements have been utilized as the background truth. The overall statistical analysis of the global comparison shows that the mean bias and the mean standard deviation of the percentage difference between TROPOMI and ground-based TOC is within 0 –1.5 % and 2.5 %–4.5 %, respectively. The mean bias that results from the comparisons is well within the S5P product requirements, while the mean standard deviation is very close to those limits, especially considering that the statistics shown here originate both from the satellite and the ground-based measurements. Additionally, the TROPOMI OFFL and NRTI products are evaluated against already known spaceborne sensors, namely, the Ozone Mapping Profiler Suite, on board the Suomi National Polar-orbiting Partnership (OMPS/Suomi-NPP), NASA v2 TOCs, and the Global Ozone Monitoring Experiment 2 (GOME-2), on board the Metop-A (GOME-2/Metop-A) and Metop-B (GOME-2/Metop-B) satellites. This analysis shows a very good agreement for both TROPOMI products with well-established instruments, with the absolute differences in mean bias and mean standard deviation being below +0.7 % and 1 %, respectively. These results assure the scientific community of the good quality of the TROPOMI TOC products during its first year of operation and enhance the already prevalent expectation that TROPOMI/S5P will play a very significant role in the continuity of ozone monitoring from space.

This paper reports on consolidated ground-based validation results of the atmospheric NO2 data produced operationally since April 2018 by the TROPOMI instrument on board of the ESA/EU Copernicus Sentinel-5 Precursor (S5p) satellite. Tropospheric, stratospheric, and total NO2 column data from S5p are compared to correlative measurements collected from, respectively, 19 Multi-Axis DOAS (MAX-DOAS), 26 NDACC Zenith-Scattered-Light DOAS (ZSL-DOAS), and 25 PGN/Pandora instruments distributed globally. The validation methodology gives special care to minimizing mismatch errors due to imperfect spatio-temporal co-location of the satellite and correlative data, e.g., by using tailored observation operators to account for differences in smoothing and in sampling of atmospheric structures and variability, and photochemical modelling to reduce diurnal cycle effects. Compared to the ground-based measurements, S5p data show, on an average: (i) a negative bias for the tropospheric column data, of typically −23 to −37 % in clean to slightly polluted conditions, but reaching values as high as −51 % over highly polluted areas; (ii) a slight negative bias for the stratospheric column data, of about −0.2 Pmolec/cm2, i.e. approx. −2 % in summer to −15 % in winter; and (iii) a bias ranging from zero to −50 % for the total column data, found to depend on the amplitude of the total NO2 column, with small to slightly positive bias values for columns below 6 Pmolec/cm2 and negative values above. The dispersion between S5p and correlative measurements contains mostly random components, which remain within mission requirements for the stratospheric column data (0.5 Pmolec/cm2), but exceed those for the tropospheric column data (0.7 Pmolec/cm2). While a part of the biases and dispersion may be due to representativeness differences, it is known that errors in the S5p tropospheric columns exist due to shortcomings in the (horizontally coarse) a-priori profile representation in the TM5-MP chemistry transport model used in the S5p retrieval, and to a lesser extent, to the treatment of cloud effects. Although considerable differences (up to 2 Pmolec/cm2 and more) are observed at single ground-pixel level, the near-real-time (NRTI) and off-line (OFFL) versions of the S5p NO2 operational data processor provide similar NO2 column values and validation results when globally averaged, with the NRTI values being on average 0.79 % larger than the OFFL values.

International audience; We have analyzed aerosol properties at the regional scale over high Arctic north of Svalbard between October 2014 and June 2015 from version 4 (V4) CALIOP (Cloud and Aerosol Lidar with Orthogonal Polarization) space-borne observations and compared results with surface lidar observations from IAOOS (Ice-Atmosphere-Ocean Observing System) platforms. CALIOP data indicate a maximum in aerosol occurrence at the end of winter attributed to low–level (0-2 km) and mid–tropospheric (2-5 km) particles identified in CALIOP V4 product as being mostly of dust origin. Another maximum was observed in October–December attributed to clean marine particles below 2 km and smoke and dust above. The 532 nm aerosol extinction was in the range 1-8 Mm-1 (0–2 km), 1-18 Mm-1 (2–5 km), and 0-6 Mm-1 (5–10 km), a factor 2 lower compared to values previously reported using CALIOP V3 dataset. Aerosols are identified from trajectory analyses to originate mostly from Russia/Europe at all altitudes, and also North America above 2 km, and it is concluded that dust and clean marine types are most probably overrepresented in the analyzed CALIOP dataset. It is proposed that most part of dust types are diamond dust, while part of clean marine are polluted species, as corroborated from co–located polarized lidar IAOOS observations. IAOOS observations allowed confirming the identified sensitivity of CALIOP with a particle backscatter coefficient of ~0.001 km-1sr-1 at 532 nm. For optically thicker layers CALIOP is shown to be a valuable tool to follow transport of aerosol layers in the Arctic and identify their possible modifications.

Long-range transport of biomass burning (BB) aerosols between North America and the Mediterranean region took place in June 2013. A large number of ground-based and airborne lidar measurements were deployed in the western Mediterranean during the Chemistry-AeRosol Mediterranean EXperiment (ChArMEx) intensive observation period. A detailed analysis of the potential North American aerosol sources is conducted including the assessment of their transport to Europe using forward simulations of the FLEXPART Lagrangian particle dispersion model initialized using satellite observations by MODIS and CALIOP. The three-dimensional structure of the aerosol distribution in the ChArMEx domain observed by the ground-based lidars (Minorca, Barcelona and Lampedusa), a Falcon-20 aircraft flight and three CALIOP tracks, agrees very well with the model simulation of the three major sources considered in this work: Canadian and Colorado fires, a dust storm from western US and the contribution of Saharan dust streamers advected from the North Atlantic trade wind region into the westerlies region. Four aerosol types were identified using the optical properties of the observed aerosol layers (aerosol depolarization ratio, lidar ratio) and the transport model analysis of the contribution of each aerosol source: (i) pure BB layer, (ii) weakly dusty BB, (iii) significant mixture of BB and dust transported from the trade wind region, and (iv) the outflow of Saharan dust by the subtropical jet and not mixed with BB aerosol. The contribution of the Canadian fires is the major aerosol source during this episode while mixing of dust and BB is only significant at an altitude above 5 km. The mixing corresponds to a 20–30 % dust contribution in the total aerosol backscatter. The comparison with the MODIS aerosol optical depth horizontal distribution during this episode over the western Mediterranean Sea shows that the Canadian fire contributions were as large as the direct northward dust outflow from Sahara.

The Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) instrument was launched aboard the environmental satellite ENVISAT into its sun-synchronous orbit on 1 March 2002. The short-lived species NO2 is one of the key target products of MIPAS that are operationally retrieved from limb emission spectra measured in the stratosphere and mesosphere. Within the MIPAS validation activities, a large number of independent observations from balloons, satellites and ground-based stations have been compared to European Space Agency (ESA) version 4.61 operational NO2 data comprising the time period from July 2002 until March 2004 where MIPAS measured with full spectral resolution. Comparisons between MIPAS and balloon-borne observations carried out in 2002 and 2003 in the Arctic, at mid-latitudes, and in the tropics show a very good agreement below 40 km altitude with a mean deviation of roughly 3%, virtually without any significant bias. The comparison to ACE satellite observations exhibits only a small negative bias of MIPAS which appears not to be significant. The independent satellite instruments HALOE, SAGE II, and POAM III confirm in common for the spring-summer time period a negative bias of MIPAS in the Arctic and a positive bias in the Antarctic middle and upper stratosphere exceeding frequently the combined systematic error limits. In contrast to the ESA operational processor, the IMK/IAA retrieval code allows accurate inference of NO2 volume mixing ratios under consideration of all important non-LTE processes. Large differences between both retrieval results appear especially at higher altitudes, above about 50 to 55 km. These differences might be explained at least partly by non-LTE under polar winter conditions but not at mid-latitudes. Below this altitude region mean differences between both processors remain within 5% (during night) and up to 10% (during day) under undisturbed (September 2002) conditions and up to 40% under perturbed polar night conditions (February and March 2004). The intercomparison of ground-based NDACC observations shows no significant bias between the FTIR measurements in Kiruna (68° N) and MIPAS in summer 2003 but larger deviations in autumn and winter. The mean deviation over the whole comparison period remains within 10%. A mean negative bias of 15% for MIPAS daytime and 8% for nighttime observations has been determined for UV-vis comparisons over Harestua (60° N). Results of a pole-to-pole comparison of ground-based DOAS/UV-visible sunrise and MIPAS mid-morning column data has shown that the mean agreement in 2003 falls within the accuracy limit of the comparison method. Altogether, it can be indicated that MIPAS NO2 profiles yield valuable information on the vertical distribution of NO2 in the lower and middle stratosphere (below about 45 km) during day and night with an overall accuracy of about 10–20% and a precision of typically 5–15% such that the data are useful for scientific studies. In cases where extremely high NO2 occurs in the mesosphere (polar winter) retrieval results in the lower and middle stratosphere are less accurate than under undisturbed atmospheric conditions.

This paper presents the validation study of stratospheric NO2 profiles retrieved from Odin/OSIRIS measurements of limb-scattered sunlight (version 2.4). The Optical Spectrograph and Infrared Imager System (OSIRIS) NO2 data set is compared to coincident solar occultation measurements by the Halogen Occultation Experiment (HALOE), Stratospheric Aerosol and Gas Experiment (SAGE) II, SAGE III, and Polar Ozone and Aerosol Measurement (POAM) III during the 2002–2004 period. Comparisons with seven Systeme d'Analyse par Observation Zenithal (SAOZ) balloon measurements are also presented. All comparisons show good agreement, with differences, both random and systematic, of less than 20% between 25 km and 35 km. Inconsistencies with SAGE III below 25 km are found to be caused primarily by diurnal effects from varying NO2 concentrations along the SAGE III line-of-sight. On the basis of the differences, the OSIRIS random uncertainty is estimated to be 16% between 15 km and 25 km, 6% between 25 km and 35 km, and 9% between 35 km and 40 km. The estimated systematic uncertainty is about 22% between 15 and 25 km, 11–21% between 25 km and 35 km, and 11–31% between 35 km and 40 km. The uncertainties for AM (sunrise) profiles are generally largest and systematic deviations are found to be larger at equatorial latitudes. The results of this validation study show that the OSIRIS NO2 profiles are well behaved, with reasonable uncertainty estimates between 15 km and 40 km. This unique NO2 data set, with more than hemispheric coverage and high vertical resolution will be of particular interest for studies of nitrogen chemistry in the middle atmosphere, which is closely linked to ozone depletion.