4 research outputs found

    Validation of Sentinel-5P TROPOMI tropospheric NO2 products by comparison with NO2 measurements from airborne imaging, ground-based stationary, and mobile car DOAS measurements during the S5P-VAL-DE-Ruhr campaign

    Get PDF
    Airborne imaging differential optical absorption spectroscopy (DOAS), ground-based stationary and car DOAS measurements were conducted during the S5P-VAL-DE-Ruhr campaign in September 2020. The campaign area is located in the Rhine-Ruhr region of North Rhine-Westphalia, Western Germany, which is a pollution hotspot in Europe comprising urban and large industrial emitters. The measurements are used to validate space-borne NO2 tropospheric vertical column density data products from the Sentinel-5 Precursor (S5P) TROPOspheric Monitoring Instrument (TROPOMI). Seven flights were performed with the airborne imaging DOAS instrument for measurements of atmospheric pollution (AirMAP), providing measurements which were used to create continuous maps of NO2 in the layer below the aircraft. These flights cover many S5P ground pixels within an area of 30 km x 35 km and were accompanied by ground-based stationary measurements and three mobile car DOAS instruments. Stationary measurements were conducted by two Pandora, two zenith-sky and two MAX-DOAS instruments distributed over three target areas. Ground-based stationary and car DOAS measurements are used to evaluate the AirMAP tropospheric NO2 vertical column densities and show high Pearson correlation coefficients of 0.87 and 0.89 and slopes of 0.93 &plusmn; 0.09 and 0.98 &plusmn; 0.02 for the stationary and car DOAS, respectively. Having a spatial resolution of about 100 m x 30 m, the AirMAP tropospheric NO2 vertical column density (VCD) data creates a link between the ground-based and the TROPOMI measurements with a resolution of 3.5 km x 5.5 km and is therefore well suited to validate the TROPOMI tropospheric NO2 VCD. The measurements on the seven flight days show strong NO2 variability, which is dependent on the different target areas, the weekday, and the meteorological conditions. The AirMAP campaign dataset is compared to the TROPOMI NO2 operational off-line (OFFL) V01.03.02 data product, the reprocessed NO2 data, using the V02.03.01 of the official L2 processor, provided by the Product Algorithm Laboratory (PAL), and several scientific TROPOMI NO2 data products. The TROPOMI data products and the AirMAP data are highly correlated with correlation coefficients between 0.72 and 0.87, and slopes of 0.38 &plusmn; 0.02 to 1.02 &plusmn; 0.07. On average, TROPOMI tropospheric NO2 VCDs are lower than the AirMAP NO2 results. The slope increased from 0.38 &plusmn; 0.02 for the operational OFFL V01.03.02 product to 0.83 &plusmn; 0.06 after the improvements in the retrieval of the PAL V02.03.01 product were implemented. Different auxiliary data, such as spatially higher resolved a priori NO2 vertical profiles, surface reflectivity and the cloud treatment, are investigated using scientific TROPOMI tropospheric NO2 VCD data products to evaluate their impact on the operational TROPOMI NO2 VCD data product. The comparison of the AirMAP campaign dataset to the scientific data products shows that the choice of surface reflectivity data base has a minor impact on the tropospheric NO2 VCD retrieval in the campaign region and season. In comparison, the replacement of the a priori NO2 profile in combination with the improvements in the retrieval of the PAL V02.03.01 product regarding cloud heights has a major impact on the tropospheric NO2 VCD retrieval and increases the slope from 0.88 &plusmn; 0.06 to 1.00 &plusmn; 0.07. This study demonstrates that the underestimation of the TROPOMI tropospheric NO2 VCD product with respect to the validation dataset has been and can be further significantly improved.</p

    Estimating real driving emissions from multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements at the A60 motorway near Mainz, Germany

    No full text
    In urban areas, road traffic is a dominant source of nitrogen oxides (NOx=NO+NO2). Although the emissions from individual vehicles are regulated by the European emission standards, real driving emissions often exceed these limits. In this study, two multi-axis differential optical absorption spectroscopy (MAX-DOAS) instruments on opposite sides of the motorway were used to measure the NO2 absorption caused by road traffic at the A60 motorway close to Mainz, Germany. In combination with wind data, the total NOx emissions for the occurring traffic volume can be estimated. Hereto, the ozone-dependent photochemical equilibrium between NO and NO2 is considered. We show that for 10 May 2019 the measured emissions exceed the maximum expected emissions calculated from the European emission standards for standardised test cycles by a factor of 11±7. One major advantage of the method used here is that MAX-DOAS measurements are very sensitive to the integrated NO2 concentration close to the surface. Thus, all emitted NO2 molecules are detected independently from their altitude, and therefore the whole emission plume originating from the nearby motorway is captured, which is a key advantage compared to other approaches such as in situ measurements

    Estimating real driving emissions from MAX-DOAS measurements at the A60 motorway near Mainz, Germany

    No full text
    In urban areas, road traffic is a dominant source of nitrogen oxides (NOx = NO + NO2). Although the emissions from individual vehicles are regulated by the European emission standards, real driving emissions often exceed these limits. In this study, two MAX-DOAS instruments on opposite sides of the motorway were used to measure the NO2 absorption caused by road traffic at the A60 motorway close to Mainz, Germany. In combination with wind data, the total NOx emissions for the occurring traffic volume can be estimated. We show that the measured emissions exceed the maximum expected emissions calculated from the European emission standards by a factor of 11 ± 7. One major advantage of the method used here is that from MAX-DOAS measurements the integrated NO2 concentration over the lowermost 2 to 3 km is determined. Thus, all emitted NO2 molecules are detected independent from their altitude and therefore the whole emission plume originating from the nearby motorway is captured by these measurements which is a key advantage compared to other approaches such as in-situ measurements

    Validation of Sentinel-5P TROPOMI tropospheric NO<sub>2</sub> products by comparison with NO<sub>2</sub> measurements from airborne imaging DOAS, ground-based stationary DOAS, and mobile car DOAS measurements during the S5P-VAL-DE-Ruhr campaign

    No full text
    Airborne imaging differential optical absorption spectroscopy (DOAS), ground-based stationary DOAS, and car DOAS measurements were conducted during the S5P-VAL-DE-Ruhr campaign in September 2020. The campaign area is located in the Rhine-Ruhr region of North Rhine-Westphalia, western Germany, which is a pollution hotspot in Europe comprising urban and large industrial sources. The DOAS measurements are used to validate spaceborne NO2 tropospheric vertical column density (VCD) data products from the Sentinel-5 Precursor (S5P) TROPOspheric Monitoring Instrument (TROPOMI). Seven flights were performed with the airborne imaging DOAS instrument for measurements of atmospheric pollution (AirMAP), providing measurements that were used to create continuous maps of NO2 in the layer below the aircraft. These flights cover many S5P ground pixels within an area of 30 km × 35 km and were accompanied by ground-based stationary measurements and three mobile car DOAS instruments. Stationary measurements were conducted by two Pandora, two Zenith-DOAS, and two MAX-DOAS instruments. Ground-based stationary and car DOAS measurements are used to evaluate the AirMAP tropospheric NO2 VCDs and show high Pearson correlation coefficients of 0.88 and 0.89 and slopes of 0.90 ± 0.09 and 0.89 ± 0.02 for the stationary and car DOAS, respectively. Having a spatial resolution of about 100 m × 30 m, the AirMAP tropospheric NO2 VCD data create a link between the ground-based and the TROPOMI measurements with a nadir resolution of 3.5 km × 5.5 km and are therefore well suited to validate the TROPOMI tropospheric NO2 VCD. The observations on the 7 flight days show strong NO2 variability, which is dependent on the three target areas, the day of the week, and the meteorological conditions. The AirMAP campaign data set is compared to the TROPOMI NO2 operational offline (OFFL) V01.03.02 data product, the reprocessed NO2 data using the V02.03.01 of the official level-2 processor provided by the Product Algorithm Laboratory (PAL), and several scientific TROPOMI NO2 data products. The AirMAP and TROPOMI OFFL V01.03.02 data are highly correlated (r=0.87) but show an underestimation of the TROPOMI data with a slope of 0.38 ± 0.02 and a median relative difference of −9 %. With the modifications in the NO2 retrieval implemented in the PAL V02.03.01 product, the slope and median relative difference increased to 0.83 ± 0.06 and +20 %. However, the modifications resulted in larger scatter and the correlation decreased significantly to r=0.72. The results can be improved by not applying a cloud correction for the TROPOMI data in conditions with high aerosol load and when cloud pressures are retrieved close to the surface. The influence of spatially more highly resolved a priori NO2 vertical profiles and surface reflectivity are investigated using scientific TROPOMI tropospheric NO2 VCD data products. The comparison of the AirMAP campaign data set to the scientific data products shows that the choice of surface reflectivity database has a minor impact on the tropospheric NO2 VCD retrieval in the campaign region and season. In comparison, the replacement of the a priori NO2 profile in combination with the improvements in the retrieval of the PAL V02.03.01 product regarding cloud heights can further increase the tropospheric NO2 VCDs. This study demonstrates that the underestimation of the TROPOMI tropospheric NO2 VCD product with respect to the validation data set has been and can be further significantly improved.</p
    corecore