Formaldehyde (HCHO) is the most abundant aldehyde in the atmosphere. HCHO ground-based Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) measurements have been performed in Uccle, Belgium during one year and a half from May 2018 to December 2019. The MAX-DOAS instrument was measuring in a dual-scan viewing mode consisting of one scan in elevation in a main azimuthal direction followed by an azimuth scan at a fixed low elevation angle. Aerosols and HCHO vertical profiles are retrieved in the main azimuthal direction by applying a profile inversion algorithm based on the Optimal Estimation Method. With the aid of these vertical profiles and the dual-scan MAX-DOAS retrieval strategy, near-surface HCHO concentrations and columns are retrieved in all directions of the azimuth scan. This ground-based dataset is then used for two main purposes: (1) the characterization of the HCHO horizontal distribution around the station and (2) the validation of HCHO columns measured by the TROPOMI satellite instrument over the Brussels area. This study reveals that (1) the HCHO horizontal distribution differs per season and (2) the use of dual-scan MAX-DOAS measurements improves the TROPOMI HCHO column validation results.

Abstract. The Airborne ROmanian Measurements of Aerosols and Trace gases (AROMAT) campaigns took place in Romania in September 2014 and August 2015. They focused on two sites: the Bucharest urban area and the power plants in the Jiu Valley. Their main objectives were to test recently developed airborne observation systems dedicated to air quality studies and to verify the concept of such campaigns in support of the validation of spaceborne atmospheric missions such as TROPOspheric Monitoring Instrument (TROPOMI)/Sentinel-5 Precursor (S5P). We show that tropospheric NO2 vertical column density (VCD) measurements using airborne mapping instruments are valuable for satellite validation. The signal to noise ratio of the airborne NO2 measurements is one order of magnitude higher than its spaceborne counterpart when the airborne measurements are averaged at the TROPOMI pixel scale. A significant source of comparison error appears to be the time variation of the NO2 VCDs during a flight, which we estimated at about 4 x 1015 molec cm-2 in the AROMAT conditions. Considering the random error of the TROPOMI tropospheric NO2 VCD (σ), the dynamic range of the NO2 VCDs field extends from detection limit up to 37σ (2.6 x 1016 molec cm-2) or 29σ (2 x 1016 molec cm-2) for Bucharest and the Jiu Valley, respectively. For the two areas, we simulate validation exercises of the TROPOMI tropospheric NO2 product using airborne measurements. These simulations indicate that we can closely approach the TROPOMI optimal target accuracy of 25 % by adding NO2 and aerosol profile information to the mapping data, which constrains the investigated accuracy within 28 %. In addition to NO2, we also measured significant amounts of SO2 in the Jiu Valley, as well as a hotspot of H2CO in the center of Bucharest. For these two species, we conclude that the best validation strategy would consist in deploying ground-based measurement systems at key locations which the AROMAT observations help identify.

Ground-based Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) measurements of aerosols and tropospheric nitrogen dioxide (NO2) were carried out in Uccle (50.8° N, 4.35° E) Brussels, during one year from March 2018 until March 2019. The instrument was operated 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 to the Northeast and (2) an azimuthal scan in a fixed low elevation angle (2°). By applying a vertical profile inversion algorithm in the main azimuthal direction and a parameterization technique in the other azimuthal directions, near-surface NO2 concentrations (VMRs) and vertical column densities (VCDs) were retrieved in ten different azimuthal directions. The dual-scan MAX-DOAS dataset allows partly resolving the horizontal distribution of NO2 around the measurement site and studying its seasonal variations. Furthermore, we show that measuring the tropospheric NO2 VCDs in different azimuthal directions improves the spatial colocation with measurements from the Sentinel-5 Precursor (S5P), leading to a reduction of the spread in validation results. By using NO2 vertical profile information derived from the MAX-DOAS measurements, we also resolve a systematic underestimation in S5P NO2 data due to the use of inadequate a-priori NO2 profile shape data in the satellite retrieval.

As part of the STEREO-III BUMBA (Belgian Urban NO2 Monitoring Based on APEX hyperspectral data) project, we try to exploit the synergy between NO2 column measurements derived from the aircraft-based APEX hyperspectral imaging system and high-resolution model data from a combined land use regression-Gaussian plume model system for the complex city-port region of Antwerp (Belgium). The resulting model maps are then used to determine the NO2-exposure of the population of the region. Several difficulties are encountered when attempting to reconcile measurements and model results. These stem from four main different reasons: In conclusion, our study shows that the use of APEX data to constrain NO2-exposure estimations is a complex process involving a number of uncertainties that need to be properly characterised. In particular we find that a robust methodology for relating concentration profiles to surface concentrations is needed before aircraft data can eventually help improving the model input data (e.g. time factors). This is further studied in the project.

We present an algorithm for retrieving tropospheric nitrogen dioxide (NO2) vertical column densities (VCDs) from ground-based zenith–sky (ZS) measurements of scattered sunlight. The method is based on a four-step approach consisting of (1) the differential optical absorption spectroscopy (DOAS) analysis of ZS radiance spectra using a fixed reference spectrum corresponding to low NO2 absorption, (2) the determination of the residual amount in the reference spectrum using a Langley-plot-type method, (3) the removal of the stratospheric content from the daytime total measured slant column based on stratospheric VCDs measured at sunrise and sunset, and simulation of the rapid NO2 diurnal variation, (4) the retrieval of tropospheric VCDs by dividing the resulting tropospheric slant columns by appropriate air mass factors (AMFs). These steps are fully characterized and recommendations are given for each of them. The retrieval algorithm is applied on a ZS data set acquired with a multi-axis (MAX-) DOAS instrument during the Cabauw (51.97° N, 4.93° E, sea level) Intercomparison campaign for Nitrogen Dioxide measuring Instruments (CINDI) held from 10 June to 21 July 2009 in the Netherlands. A median value of 7.9 × 1015 molec cm−2 is found for the retrieved tropospheric NO2 VCDs, with maxima up to 6.0 × 1016 molec cm−2. The error budget assessment indicates that the overall error σTVCD on the column values is less than 28%. In the case of low tropospheric contribution, σTVCD is estimated to be around 39% and is dominated by uncertainties in the determination of the residual amount in the reference spectrum. For strong tropospheric pollution events, σTVCD drops to approximately 22% with the largest uncertainties on the determination of the stratospheric NO2 abundance and tropospheric AMFs. The tropospheric VCD amounts derived from ZS observations are compared to VCDs retrieved from off-axis and direct-sun measurements of the same MAX-DOAS instrument as well as to data from a co-located Système d'Analyse par Observations Zénithales (SAOZ) spectrometer. The retrieved tropospheric VCDs are in good agreement with the different data sets with correlation coefficients and slopes close to or larger than 0.9. The potential of the presented ZS retrieval algorithm is further demonstrated by its successful application on a 2-year data set, acquired at the NDACC (Network for the Detection of Atmospheric Composition Change) station Observatoire de Haute Provence (OHP; Southern France).