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Nitrogen dioxide (NO2) is a major air pollutant. Tropospheric NO2 vertical column densities (VCDs) retrieved from sun-synchronous satellite instruments have provided abundant NO2 data for environmental studies, but such data are limited by insufficient temporal sampling (e.g., once a day). The Geostationary Environment Monitoring Spectrometer (GEMS) launched in February 2020 monitors NO2 at an unprecedented high temporal resolution. Here we present a research product for tropospheric NO2 VCDs, referred to as POMINO-GEMS. We develop a hybrid retrieval method combining GEMS and TROPOMI observations as well as GEOS-Chem simulations to generate hourly tropospheric NO2 slant column densities (SCDs). We then derive tropospheric NO2 air mass factors (AMFs) with explicit corrections for the anisotropy of surface reflectance and aerosol optical effects, through pixel-by-pixel radiative transfer calculations. Prerequisite cloud parameters are retrieved with the O2-O2 algorithm by using ancillary parameters consistent with those used in NO2 AMF calculations. Initial retrieval of POMINO-GEMS tropospheric NO2 VCDs for June–August 2021 reveals strong hotspot signals over megacities and distinctive diurnal variations over polluted and clean areas. POMINO-GEMS NO2 VCDs agree well with our POMINO-TROPOMI v1.2.2 product (R = 0.97, and NMB = 3.6 %) over Asia. Comparison with ground-based MAX-DOAS VCD data at nine sites shows a small bias of POMINO-GEMS (NMB = –15.7 %); however, the correlation for diurnal variation varies from -0.66 to 0.90, suggesting location-dependent performance. Surface NO2 concentrations estimated from POMINO-GEMS VCDs are consistent with measurements from the Ministry of Ecology and Environment of China at 855 sites (NMB = –24.1 %, and R = 0.95 for diurnal correlation averaged over all sites). POMINO-GEMS data will be made freely available for users to study the spatiotemporal variations, sources and impacts of NO2.

Ground-based Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) measurements of aerosols, tropospheric nitrogen dioxide (NO2) and formaldehyde (HCHO) have been carried out in Uccle, Brussels, during two years (March 2018 – March 2020). The MAX-DOAS instrument has been operating in both UV and visible (Vis) wavelength ranges in a dual-scan configuration consisting of two sub-modes: (1) an elevation scan in a fixed viewing azimuthal direction (the so-called main azimuthal direction) pointing and (2) an azimuthal scan in a fixed low elevation angle (2o). By applying a vertical profile inversion algorithm in the main azimuthal direction and an adapted version of the parameterization technique proposed by Sinreich et al. (2013) in the other azimuthal directions, near-surface concentrations (VMRs) and vertical column densities (VCDs) are retrieved in ten different azimuthal directions.The present work focuses on the seasonal horizontal variation of NO2 and HCHO around the measurement site. The observations show a clear seasonal cycle of these trace gases. An important application of the dual-scan MAX-DOAS measurements is the validation of satellite missions with high spatial resolution, such as TROPOMI/S5P. Measuring the tropospheric VCDs in different azimuthal directions is shown to improve the spatial colocation with satellite measurements leading to a better agreement between both datasets. By using vertical profile information derived from the MAX-DOAS measurements, we show that a persistent systematic underestimation of the TROPOMI data can be explained by uncertainties in the a-priori NO2 profile shape in the satellite retrieval. A similar validation study for TROPOMI HCHO is currently under progress and preliminary results will be presented.References:Sinreich, R., Merten, A., Molina, L., and Volkamer, R.: Parameterizing radiative transfer to convert MAX-DOAS dSCDs into near-surface box-averaged mixing ratios, Atmos. Meas. Tech., 6, 1521–1532, https://doi.org/10.5194/amt-6-1521-2013, 2013.

As part of the TROLIX'19 (TROpomi vaLIdation eXperiment) campaign (2 September to 4 October 2019), measurements of tropospheric NO2 columns and surface concentrations were made using the MAX-DOAS (Multi-AXis Differential Optical Absorption Spectroscopy) technique. To characterise any TROPOMI sub pixel (less than 3.5 km x 7 km) heterogeneity, four MAX-DOAS instruments were deployed at rural locations close to Cabauw (51.97°N, 4.93°E) and further six instruments were operated within the highly industrialized area of Rotterdam (51.92°N, 4.48°E) in the Netherlands. All instruments performed sky scanning from the horizon (from approximately 1°) to the zenith. In addition, two of the MAX-DOAS instruments (Pandoras) also measured total NO2 columns in direct sun mode.Here we present first results focusing on the measurements of NO2 spatial gradients made at sites within approximately 3-10 km distance in a rural and an urban environment. The data analysis was done in two steps. Differential slant column densities were calculated using the data processing procedures established during the CINDI-2 intercomparison campaign (Kreher et al., in review, 2019) in UV and VIS spectral ranges. Tropospheric columns, near surface concentrations and profiles were then calculated using the Pandora real time algorithm as well as the NDACC UV-Vis Central Processing system developed in the ESA FRM4DOAS project. Local heterogeneity at the surface level was evaluated using in-situ NO2 measurements available from several routine monitoring stations within the area of interest. The local NO2 heterogeneity effect on TROPOMI validation is also discussed.Reference:Kreher, K. et al.: Intercomparison of NO2, O4, O3 and HCHO slant column measurements by MAX-DOAS and zenith-sky UV-Visible spectrometers during the CINDI-2 campaign, Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2019-157, in review, 2019.

Since it provides vertically-resolved information on atmospheric gases at a horizontal scale approaching the one from nadir backscatter satellite sensors, the ground-based MAX-DOAS technique has been recognized as a valuable source of correlative data for validating space-borne observations of air-quality-related species such as NO2, HCHO, SO2, O3, etc. In this context, the ESA Fiducial Reference Measurements for Ground-Based DOAS Air-Quality Observations (FRM4DOAS) project is aiming at developing a near-real-time (6-24h latency) central processing system for the delivery of harmonized, quality-controlled, and fully traceable data products from MAX-DOAS instruments. The first phase of the project has been dedicated to the development of a prototype version of this processing system for 3 key products (NO2 vertical profiles, total O3 columns, and tropospheric HCHO profiles) and its demonstration at 11 project partners MAX-DOAS stations.In this presentation we will describe the efforts carried out during the last months to develop the first MAX-DOAS central processing service to be operated within the Network for the Detection of Atmospheric Composition Change (NDACC). The main aspects of the service development will be presented, like the FRM4DOAS prototype algorithm optimisation, operationalisation, and validation, and the establishment of MAX-DOAS NDACC instrument and data retrieval certification procedures, user data policy, datasets DOI, etc. This operational service is expected to be launched in Spring 2020 for a limited number (5-10) of NDACC-certified MAX-DOAS instruments. Corresponding data sets will be stored in the NDACC and ESA EVDC data handling facilities.This activity and its future upscaling in terms of stations and data products will ensure that MAX-DOAS observations at a FRM quality level will be made available for the validation of present and future satellite missions like the Copernicus atmospheric Sentinels (5p, 4, 5).

In September 2016, 36 spectrometers from 24 institutes measured a number of key atmospheric pollutants for a period of 17 days during the Second Cabauw Intercomparison campaign for Nitrogen Dioxide measuring Instruments (CINDI-2) that took place at Cabauw, The Netherlands (51.97° N, 4.93° E). We report on the outcome of the formal semi-blind intercomparison exercise, which was held under the umbrella of the Network for the Detection of Atmospheric Composition Change (NDACC) and the European Space Agency (ESA). The three major goals of CINDI-2 were to characterise and better understand the differences between a large number of Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) and zenith-sky DOAS instruments and analysis methods, to discuss the performance of the various types of instruments and to contribute to a harmonisation of the measurement settings and retrieval methods. This, in turn, creates the capability to produce consistent high-quality ground-based data sets, which are an essential requirement to generate reliable long-term measurement time series suitable for trend analysis and satellite data validation. The data products investigated during the semi-blind intercomparison are slant columns of nitrogen dioxide (NO2), the oxygen dimer (O4) and ozone (O3) measured in the UV and visible wavelength region, formaldehyde (HCHO) in the UV spectral region and NO2 in an additional (smaller) wavelength range in the visible. The campaign design and implementation processes are discussed in detail including the measurement protocol, calibration procedures and slant column retrieval settings. Strong emphasis was put on the careful alignment and synchronisation of the measurement systems, resulting in an unprecedented set of measurements made under highly comparable air mass conditions. The CINDI-2 data sets were investigated using a regression analysis of the slant columns measured by each instrument and for each of the target data products. The slope and intercept of the regression analysis respectively quantify the mean systematic bias and offset of the individual data sets against the reference, and the RMS error provides an estimate of the measurement noise or dispersion. These three criteria are examined and for each of the parameters and each of the data products, performance thresholds are set and applied to all the measurements. The approach presented here has been developed based on heritage from previous intercomparison exercises. It introduces a quantitative assessment of the measurement performance of all the participating instruments for the MAX-DOAS and zenith-sky DOAS techniques.

Tropospheric NO2 is hazardous to human health and can lead to tropospheric ozone formation, eutrophication of ecosystems and acid rain production. It is therefore important to establish accurate data based on models and observations to understand and monitor tropospheric NO2 concentrations on a regional and global scale. In the present study, MAX-DOAS tropospheric NO2 column retrievals from four European measurement stations are compared to regional model ensemble simulations. The latter are based on regional air quality models which contribute to the European regional ensemble forecasts and reanalyses of the operational Copernicus Atmosphere Monitoring Service (CAMS). Compared to other observational data usually applied for regional model validation, MAX-DOAS data is closer to the regional model data in terms of horizontal and vertical resolution and measurements are available during daylight. In general, there is a good agreement between simulated and retrieved NO2 column values for individual MAX-DOAS measurements with correlations between 45 and 75 % for tropospheric NO2 VCDs, indicating that the model ensemble represents the emission and tropospheric chemistry of NOx (NO + NO2) well. Pollution transport towards the stations is on average well represented by the models. However, large differences are found for individual pollution plumes. Seasonal cycles are overestimated, weekly cycles are reproduced well and diurnal cycles poorly represented by the model ensemble. In particular, simulated morning rush hour peaks are not confirmed by MAX-DOAS retrievals. Our results demonstrate that a large number of validation points are available from MAX-DOAS measurements, which should therefore be used more extensively in future regional air quality modelling studies.