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We present a database of MAX-DOAS (Multi-AXis Differential Optical Absorption Spectroscopy) ground-based observations of NO2 and H2CO tropospheric vertical column densities (VCDtropo) performed for the first time in the city of Kinshasa. These measurements were conducted between November 2019 and July 2021 and processed using the standardized inversion tools developed in the ESA FRM4DOAS (Fiducial Reference Measurements for Ground-Based DOAS Air-Quality Observations) project. The retrieved geophysical quantities are used to validate column observations from the TROPOspheric Monitoring Instrument (TROPOMI) over Kinshasa. In the validation, we experiment with three different comparison cases of increasing complexity. In the first case, a direct comparison between MAX-DOAS observations (hourly average of MAX-DOAS VCDtropo at overpass) and TROPOMI shows an underestimation of TROPOMI with a median bias of -38 % for NO2 and -39 % for H2CO based on monthly comparison. The second case takes into account the different vertical sensitivities of the two instruments and the a priori profile. We note significant changes in the median bias for both compounds: -12 % for NO2 and +11 % for H2CO. The third case builds on the second case by considering also the direction of sight of the MAX-DOAS. For this third case, we find a median bias of +44 % for NO2 and a median bias of +4 % for H2CO. However this case is impacted by low sampling and is considered less reliable. The findings from this study underscore the significance of employing a realistic a priori profile in TROPOMI column extraction, particularly within heavily polluted urban zones like Kinshasa. The investigation also highlights the necessity for prudence when integrating the MAX-DOAS line of sight due to the noise generated during subsampling and the limited horizontal sensitivity of MAX-DOAS observations. Importantly, the study further reveals the pronounced pollution levels of NO2, H2CO and aerosols in both the city of Kinshasa and its adjacent regions, underscoring the imperative for consistent monitoring and effective regulatory measures by local authorities.

We present the first ground-based remote sensing measurements of NO 2 made in Kinshasa. They were performed from 2017 to 2019. The motivation of making observations on air pollution in Kinshasa comes from its geographical location, its demography, its climatic conditions and the many different sources of NO 2 existing in its surroundings. A method for recovering the vertical density of the NO 2 tropospheric column (VCDtropo) based on the Differential Optical Absorption Spectroscopy (DOAS) applied to observations at the zenith and 35° elevation angle is described. The mean value of VCDtropo observed in Kinshasa is 3 × 10 15 molecules cm −2 . We further present first comparisons with the OMI and TROPOMI satellite observations. When comparing OMI data with our observations and using a linear regression analysis, we find a slope of 0.34 and a correlation coefficient of 0.50 for 51 days of coincidences over 2017−2019. Similar comparisons with TROPOMI for 44 days show a slope of 0.41 and a correlation coefficient of 0.72. This study opens up perspectives for further air quality related studies in Kinshasa and central Africa.

We present a database of MAX-DOAS (Multi-AXis Differential Optical Absorption Spectroscopy) ground-based observations of NO2 and H2CO tropospheric vertical column densities (VCDtropo) performed for the first time in the city of Kinshasa. These measurements were conducted between November 2019 and July 2021 and processed using the standardized inversion tools developed in the ESA FRM4DOAS (Fiducial Reference Measurements for Ground-Based DOAS Air-Quality Observations) project. The retrieved geophysical quantities are used to validate column observations from the TROPOspheric Monitoring Instrument (TROPOMI) over Kinshasa. In the validation, we experiment with three different comparison cases of increasing complexity. In the first case, a direct comparison between MAX-DOAS observations (hourly average of MAX-DOAS VCDtropo at overpass) and TROPOMI shows an underestimation of TROPOMI with a median bias of −38 % for NO2 and −39 % for H2CO based on monthly comparison. The second case takes into account the different vertical sensitivities of the two instruments and the a priori profile. We note significant changes in the median bias for both compounds: −12 % for NO2 and +11 % for H2CO. The third case builds on the second case by considering also the direction of sight of the MAX-DOAS. For this third case, we find a median bias of +44 % for NO2 and a median bias of +4 % for H2CO. However this case is impacted by low sampling and is considered less reliable. The findings from this study underscore the significance of employing a realistic a priori profile in TROPOMI column extraction, particularly within heavily polluted urban zones like Kinshasa. The investigation also highlights the necessity for prudence when integrating the MAX-DOAS line of sight due to the noise generated during subsampling and the limited horizontal sensitivity of MAX-DOAS observations. Importantly, the study further reveals the pronounced pollution levels of NO2, H2CO and aerosols in both the city of Kinshasa and its adjacent regions, underscoring the imperative for consistent monitoring and effective regulatory measures by local authorities.

The research presented in this thesis focuses on the issue of air pollution in Central Africa. The deterioration of air quality in this region has been prominently observed, as evidenced by various recent studies. Based on satellite observations, these recent studies have identified significant peaks in nitrogen dioxide, formaldehyde, and aerosol pollution. Initial interpretations point to biogenic emissions from the extensive forests in the region, subject to various challenges related to biomass burning, forest fires for agricultural land preparation, as well as charcoal production widely used as an energy source and for cooking by a large part of the local population. Validating such hypotheses requires ground-level observations to understand the situation on the ground and contribute to the validation of satellite data and model simulations. Unfortunately, Africa remains significantly undersampled compared to other parts of the world, with a near absence of ground measurement stations in Central Africa and a lack of regulation.In this context, this thesis focuses on the operationalization and implementation of a remote sensing instrument to measure specific pollutants. We installed an instrument based on the the Differential Optical Absorption Spectroscopy (DOAS) technique in Kinshasa. After processing the recorded spectra from May 2017 to July 2021, a database of NO2, H2CO, and Aerosol optical depth (AOD), strong indicators of air pollution in the region, was established. Observations reveal significant pollution from these molecules in Kinshasa and its surroundings, with high tropospheric column values observed during the dry season. Daily cycles have also been identified, showing elevated values around noon. The database also facilitated the initial validation of the TROPOMI instrument aboard the S5P satellite. This validation demonstrated good agreement between TROPOMI and ground observations, using a realistic a priori profile for local conditions, with a median bias of around 10% for both compounds (NO2 and H2CO).Another aspect of this thesis involved evaluating the performance of the GEOS-Chem model, a chemistry-transport model simulating pollution in the study area. This evaluation is crucial to determine the extent to which the model can accurately replicate real atmospheric conditions in the Kinshasa region and its surroundings. The preliminary results indicate that simulations including biomass burning emissions inventory align remarkably well with TROPOMI observations, while those without accounting for biomass burning exhibit a non-cyclical seasonal behavior. The impact of biomass burning is particularly pronounced, especially during the dry season for NO2 pollution and throughout the year for H2CO.The overall results of this thesis confirm significant pollution from NO2 and H2CO in Kinshasa and its surroundings. TROPOMI satellite products align well with ground observations, taking into account the a priori measured by the ground instrument. The impact of biomass burning is strongly significant in the observed pollution. Recommen dations are made to deepen studies by installing more ground instruments in different cities in the sub-region and to use these results to raise awareness and encourage local authorities to implement control and regulation measures.

We present a database of MAX-DOAS (Multi-AXis Differential Optical Absorption Spectroscopy) ground-based observations of NO.sub.2 and H.sub.2 CO tropospheric vertical column densities (VCD.sub.tropo) performed for the first time in the city of Kinshasa. These measurements were conducted between November 2019 and July 2021 and processed using the standardized inversion tools developed in the ESA FRM4DOAS (Fiducial Reference Measurements for Ground-Based DOAS Air-Quality Observations) project. The retrieved geophysical quantities are used to validate column observations from the TROPOspheric Monitoring Instrument (TROPOMI) over Kinshasa. In the validation, we experiment with three different comparison cases of increasing complexity. In the first case, a direct comparison between MAX-DOAS observations (hourly average of MAX-DOAS VCD.sub.tropo at overpass) and TROPOMI shows an underestimation of TROPOMI with a median bias of -38 % for NO.sub.2 and -39 % for H.sub.2 CO based on monthly comparison. The second case takes into account the different vertical sensitivities of the two instruments and the a priori profile. We note significant changes in the median bias for both compounds: -12 % for NO.sub.2 and +11 % for H.sub.2 CO. The third case builds on the second case by considering also the direction of sight of the MAX-DOAS. For this third case, we find a median bias of +44 % for NO.sub.2 and a median bias of +4 % for H.sub.2 CO. However this case is impacted by low sampling and is considered less reliable. The findings from this study underscore the significance of employing a realistic a priori profile in TROPOMI column extraction, particularly within heavily polluted urban zones like Kinshasa. The investigation also highlights the necessity for prudence when integrating the MAX-DOAS line of sight due to the noise generated during subsampling and the limited horizontal sensitivity of MAX-DOAS observations. Importantly, the study further reveals the pronounced pollution levels of NO.sub.2, H.sub.2 CO and aerosols in both the city of Kinshasa and its adjacent regions, underscoring the imperative for consistent monitoring and effective regulatory measures by local authorities.