Effects of local meteorology and aerosols on ozone and nitrogen dioxide retrievals from OMI and pandora spectrometers in Maryland, USA during DISCOVER-AQ 2011

An analysis is presented for both ground- and satellite-based retrievals of total column ozone and nitrogen dioxide levels from the Washington, D.C., and Baltimore, Maryland, metropolitan area during the NASA-sponsored July 2011 campaign of Deriving Information on Surface COnditions from Column and VERtically Resolved Observations Relevant to Air Quality (DISCOVER-AQ). Satellite retrievals of total column ozone and nitrogen dioxide from the Ozone Monitoring Instrument (OMI) on the Aura satellite are used, while Pandora spectrometers provide total column ozone and nitrogen dioxide amounts from the ground. We found that OMI and Pandora agree well (residuals within ±25 % for nitrogen dioxide, and ±4.5 % for ozone) for a majority of coincident observations during July 2011. Comparisons with surface nitrogen dioxide from a Teledyne API 200 EU NOx Analyzer showed nitrogen dioxide diurnal variability that was consistent with measurements by Pandora. However, the wide OMI field of view, clouds, and aerosols affected retrievals on certain days, resulting in differences between Pandora and OMI of up to ±65 % for total column nitrogen dioxide, and ±23 % for total column ozone. As expected, significant cloud cover (cloud fraction \u3e0.2) was the most important parameter affecting comparisons of ozone retrievals; however, small, passing cumulus clouds that do not coincide with a high (\u3e0.2) cloud fraction, or low aerosol layers which cause significant backscatter near the ground affected the comparisons of total column nitrogen dioxide retrievals. Our results will impact post-processing satellite retrieval algorithms and quality control procedures

New observations of NO2 in the upper troposphere from TROPOMI

Nitrogen oxides (NOx≡NO+NO2) in the NOx-limited upper troposphere (UT) are long-lived and so have a large influence on the oxidizing capacity of the troposphere and formation of the greenhouse gas ozone. Models misrepresent NOx in the UT, and observations to address deficiencies in models are sparse. Here we obtain a year of near-global seasonal mean mixing ratios of NO2 in the UT (450–180 hPa) at 1∘×1∘ by applying cloud-slicing to partial columns of NO2 from TROPOMI. This follows refinement of the cloud-slicing algorithm with synthetic partial columns from the GEOS-Chem chemical transport model. TROPOMI, prior to cloud-slicing, is corrected for a 13 % underestimate in stratospheric NO2 variance and a 50 % overestimate in free-tropospheric NO2 determined by comparison to Pandora total columns at high-altitude free-tropospheric sites at Mauna Loa, Izaña, and Altzomoni and MAX-DOAS and Pandora tropospheric columns at Izaña. Two cloud-sliced seasonal mean UT NO2 products for June 2019 to May 2020 are retrieved from corrected TROPOMI total columns using distinct TROPOMI cloud products that assume clouds are reflective boundaries (FRESCO-S) or water droplet layers (ROCINN-CAL). TROPOMI UT NO2 typically ranges from 20–30 pptv over remote oceans to >80 pptv over locations with intense seasonal lightning. Spatial coverage is mostly in the tropics and subtropics with FRESCO-S and extends to the midlatitudes and polar regions with ROCINN-CAL, due to its greater abundance of optically thick clouds and wider cloud-top altitude range. TROPOMI UT NO2 seasonal means are spatially consistent (R=0.6–0.8) with an existing coarser spatial resolution (5∘ latitude × 8∘ longitude) UT NO2 product from the Ozone Monitoring Instrument (OMI). UT NO2 from TROPOMI is 12–26 pptv more than that from OMI due to increase in NO2 with altitude from the OMI pressure ceiling (280 hPa) to that for TROPOMI (180 hPa), but possibly also due to altitude differences in TROPOMI and OMI cloud products and NO2 retrieval algorithms. The TROPOMI UT NO2 product offers potential to evaluate and improve representation of UT NOx in models and supplement aircraft observations that are sporadic and susceptible to large biases in the UT.This research has been supported by the European Research Council under the European Union’s Horizon 2020 research and innovation programme (through the Starting Grant awarded to Eloise A. Marais, UpTrop (grant no. 851854))

Regional Characteristics of NO2 Column Densities from Pandora Observations during the MAPS-Seoul Campaign

Vertical column density (VCD) of nitrogen dioxide (NO2) was measured using Pandora spectrometers at six sites on the Korean Peninsula during the Megacity Air Pollution Studies-Seoul (MAPS-Seoul) campaign from May to June 2015. To estimate the tropospheric NO2 VCD, the stratospheric NO2 VCD from the Ozone Monitoring Instrument (OMI) was subtracted from the total NO2 VCD from Pandora. European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis wind data was used to analyze variations in tropospheric NO2 VCD caused by wind patterns at each site. The Yonsei/SEO site was found to have the largest tropospheric NO2 VCD (1.49 DU on average) from a statistical analysis of hourly tropospheric NO2 VCD measurements. At rural sites, remarkably low NO2 VCDs were observed. However, a wind field analysis showed that trans-boundary transport and emissions from domestic sources lead to an increase in tropospheric NO2 VCD at NIER/BYI and KMA/AMY, respectively. At urban sites, high NO2 VCD values were observed under conditions of low wind speed, which were influenced by local urban emissions. Tropospheric NO2 VCD at HUFS/Yongin increases under conditions of significant transport from urban area of Seoul according to a correlation analysis that considers the transport time lag. Significant diurnal variations were found at urban sites during the MAPS-Seoul campaign, but not at rural sites, indicating that it is associated with diurnal patterns of NO2 emissions from dense traffic

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

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

Intercomparison of NO2, O4, O3 and HCHO slant column measurements by MAX-DOAS and zenith-sky UV¿visible spectrometers during CINDI-2

40 pags., 22 figs., 13 tabs.In September 2016, 36 spectrometers from 24 institutes measured a number of key atmospheric pollutants for a period of 17¿d 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 (1) 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, (2) to define a robust methodology for performance assessment of all participating instruments, and (3) 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 collision complex (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 region. 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 a unique 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 selected reference (which is obtained from the median of either all data sets or a subset), 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 consistency between all the participating instruments for the MAX-DOAS and zenith-sky DOAS techniques.CINDI-2 received funding from the Netherlands Space Office (NSO). Funding for this study was provided by ESA through the CINDI-2 (ESA contract no. 4000118533/16/ISbo) and FRM4DOAS (ESA contract no. 4000118181/16/I-EF) projects and partly within the EU 7th Framework Programme QA4ECV project (grant agreement no. 607405). The BOKU MAX-DOAS instrument was funded and the participation of Stefan F. Schreier was supported by the Austrian Science Fund (FWF): I 2296-N29. The participation of the University of Toronto team was supported by the Canadian Space Agency (through the AVATARS project) and the Natural Sciences and Engineering Research Council (through the PAHA project). The instrument was primarily funded by the Canada Foundation for Innovation and is usually operated at the Polar Environment Atmospheric Research Laboratory (PEARL) by the Canadian Network for the Detection of Atmospheric Change (CANDAC). Funding for CISC was provided by the UVAS (“Ultraviolet and Visible Atmospheric Sounder”) projects SEOSAT/INGENIO, ESP2015-71299- R, MINECO-FEDER and UE. The activities of the IUP-Heidelberg were supported by the DFG project RAPSODI (grant no. PL 193/17-1). SAOZ and Mini-SAOZ instruments are supported by the Centre National de la Recherche Scientifique (CNRS) and the Centre National d’Etudes Spatiales (CNES). INTA recognises support from the National funding projects HELADO (CTM2013-41311-P) and AVATAR (CGL2014-55230-R). AMOIAP recognises support from the Russian Science Foundation (grant no. 16-17-10275) and the Russian Foundation for Basic Research (grant nos. 16-05- 01062 and 18-35-00682). Ka L. Chan received transnational access funding from ACTRIS-2 (H2020 grant agreement no. 654109). Rainer Volkamer recognises funding from NASA’s Atmospheric Composition Program (NASA-16-NUP2016-0001) and the US National Science Foundation (award AGS-1620530). Henning Finkenzeller is the recipient of a NASA graduate fellowship. Mihalis Vrekoussis recognises support from the University of Bremen and the DFG Research Center/Cluster of Excellence “The Ocean in the Earth System-MARUM”. Financial support through the University of Bremen Institutional Strategy in the framework of the DFG Excellence Initiative is gratefully appreciated for Anja Schönhardt. Pandora instrument deployment was supported by Luftblick through the ESA Pandonia Project and NASA Pandora Project at the Goddard Space Flight Center under NASA Headquarters’ Tropospheric Composition Program. The article processing charges for this open-access publication were covered by BK Scientific

Intercomparison of NO2, O-4, O-3 and HCHO slant column measurements by MAX-DOAS and zenith-sky UV-visible spectrometers during CINDI-2

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