Résumé : The Earth's atmosphere has always been attracting human attention. Its study, i.e. understanding its characteristics and processes, its response to natural and anthropogenic activities, and its evolution over the years, is one of the most fascinating and complicated research domains. When focusing on the lowest part of the Earth's atmosphere, anthropogenic emissions become highly important by changing the atmosphere's composition and influencing the climate. In urban regions, one of the most critical pollutants emitted by anthropogenic activities, such as traffic, industrial activity, domestic heating, and power plants is nitrogen dioxide (NO2). NO2 is considered a proxy for air pollution. Another important tropospheric pollutant is formaldehyde (HCHO), which is emitted in the troposphere from natural, anthropogenic, and pyrogenic sources, and it is often used to monitor the biogenic and anthropogenic emissions of hydrocarbons. Finally, aerosols are crucial in the troposphere in terms of air quality and climate.The purpose of this work is the retrieval of the horizontal distributions of NO2, HCHO, and aerosols from MAX-DOAS measurements in urban conditions to support the validation of air quality satellite observations. To achieve that, dual-scan ground-based Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) measurements of tropospheric NO2, HCHO and aerosols have been carried out in Uccle (50.8 deg. N, 4.35 deg. E; Brussels region, Belgium) for two years, from March 2018 to February 2020. The MAX-DOAS instrument has been operating in both UV and Visible 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 deg.). By applying a vertical profile inversion algorithm in the main azimuthal direction and a parameterization technique in the other azimuthal directions, near-surface NO2 and HCHO volume mixing ratios (VMRs) and vertical column densities (VCDs) and near-surface aerosol extinction were retrieved in ten different azimuthal directions. In a first step, the multi-azimuthal MAX-DOAS dataset is used to characterize the NO2 and HCHO horizontal distributions around the measurement site. We show that the horizontal distributions of NO2 and HCHO differ per season as expected. Maximum NO2 values are retrieved during cold seasons and towards the Brussels city center, while maximum HCHO values are observed during warmer seasons and towards a large forested area in the Brussels region. Additionally, we demonstrate that measuring the tropospheric NO2 and HCHO VCDs in multiple azimuthal directions improves the spatial colocation with measurements from the TROPOMI/ S5P, leading to improved satellite validation results. Although there is a better agreement between both datasets, we show that the observed systematic underestimation of the tropospheric NO2 columns by TROPOMI/ S5P is rising from inadequate a priori NO2 profiles shape data in the satellite retrieval.In a second step, a new Optimal-Estimation-based inversion approach is developed by exploiting the O4 and NO2 dSCDs measured at six different wavelength intervals to retrieve the horizontal distribution of the NO2 near-surface concentrations and vertical column densities (VCDs) and the aerosols near-surface extinction coefficient along every azimuthal direction. For the first time, seasonal tropospheric NO2 column maps are constructed from MAX-DOAS observations, enabling the identification of the main NO2 hotspots in the Brussels area at a horizontal resolution of about 3km. Correlative comparisons of the retrieved horizontal NO2 distribution have been conducted with airborne, mobile, and satellite datasets collected during the S5P validation campaign over Belgium (S5PVAL-BE), and overall a good agreement is found. Furthermore, we show that this new way of characterizing the tropospheric NO2 VCD horizontal distribution from MAX-DOAS measurements, the appropriate sampling of TROPOMI pixels, and again an adequate a priori NO2 profile shape in TROPOMI retrievals lead to a significantly better agreement between satellite and ground-based datasets.