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Multi-axis differential optical absorption spectroscopy (MAX-DOAS) and direct sun NO2 vertical column network data are used to investigate the accuracy of tropospheric NO2 column measurements of the GOME-2 instrument on the MetOp-A satellite platform and the OMI instrument on Aura. The study is based on 23 MAX-DOAS and 16 direct sun instruments at stations distributed worldwide. A method to quantify and correct for horizontal dilution effects in heterogeneous NO2 field conditions is proposed. After systematic application of this correction to urban sites, satellite measurements are found to present smaller biases compared to ground-based reference data in almost all cases. We investigate the seasonal dependence of the validation results as well as the impact of using different approaches to select satellite ground pixels in coincidence with ground-based data. In optimal comparison conditions (satellite pixels containing the station) the median bias between satellite tropospheric NO2 column measurements and the ensemble of MAX-DOAS and direct sun measurements is found to be significant and equal to −34 % for GOME-2A and −24 % for OMI. These biases are further reduced to −24 % and −18 % respectively, after application of the dilution correction. Comparisons with the QA4ECV satellite product for both GOME-2A and OMI are also performed, showing less scatter but also a slightly larger median tropospheric NO2 column bias with respect to the ensemble of MAX-DOAS and direct sun measurements.

MAX-DOAS and direct sun NO2 vertical column network data are used to investigate the accuracy of tropospheric NO2 column measurements of the GOME-2 instrument on the MetOP-A satellite platform and the OMI instrument on Aura. The study is based on 23 MAX-DOAS and 16 direct sun instruments at stations distributed worldwide. A method to quantify and correct for horizontal dilution effects in heterogeneous NO2 field conditions is proposed. After systematic application of this correction to urban sites, satellite measurements are found to present smaller biases compared to ground-based reference data in almost all cases. We investigate the seasonal dependence of the validation results, as well as the impact of using different approaches to select satellite ground pixels in coincidence with ground-based data. In optimal comparison conditions (satellite pixels containing the station) the median bias between satellite tropospheric NO2 column measurements and the ensemble of MAX-DOAS and direct sun measurements is found to be significant and equal to −36 % for GOME-2A and −20 % for OMI. These biases are further reduced to −24 % and −8 % respectively, after application of the dilution correction. Comparisons with the QA4ECV satellite product for both GOME-2A and OMI is also performed, showing less scatter but also a slightly larger median tropospheric NO2 column bias with respect to the ensemble of MAX-DOAS and direct sun measurements.

For the validation of Sentinel-5p/TROPOMI the TROpomi vaLIdation eXperiment (TROLIX) was held in the Netherlands based at the Cabauw Experimental Site for Atmospheric Research during September 2019. TROLIX consisted of active and passive remote sensing platforms in conjunction with several balloon-borne and surface measurements.The intensive observations will serve to establish the quality of TROPOMI L2 main data products (UVAI, Aerosol Layer Height, NO2, O3, HCHO, Clouds) under realistic conditions with varying cloud cover and a wide range of atmospheric conditions.Since TROPOMI is a hyperspectral imager with a very high spatial resolution of 3.6 x 5.6 km2, understanding local effects such as inhomogeneous sources of pollution, sub-pixel clouds and variations in ground albedo is important to interpret TROPOMI results. Therefore, the campaign included sub-pixel resolution local networks of sensors, involving MAXDOAS and Pandora instruments, around Cabauw (rural) and within the city of Rotterdam (urban). Utilising its comprehensive in-situ and remote sensing observation program in and around the 213 m meteorological tower, Cabauw was the main site of the campaign with focus on vertical profiling using lidar instruments for aerosols, clouds, water vapor, tropospheric and stratospheric ozone, as well as balloon-borne sensors for NO2 and ozone.The data set collected can be directly compared to the TROPOMI L2 data products, while measurements of parameters related to a-priori data and auxiliary parameters that infuence the quality of the L2 products such as aerosol and cloud profiles and in-situ aerosol and atmospheric chemistry were also collected.This paper gives an overview of the campaign, and an overview of the participating main and ancillary instrumentation and preliminary results.Future activities include the deployment in 2020 of an airborne hyperspectral imager.

International agreements to reduce CO2 emissions call for an independent mechanism for evaluating the compliance with emission reduction targets. Atmospheric measurements can provide important information in support of this goal. However, to do this globally requires a drastic expansion of the existing monitoring network, using a combination of surface measurements and satellites. CO2 sensing satellites can deliver the required spatial coverage, filling in the gaps that are difficult to cover on ground. However, to reach the accuracy that is required for monitoring CO2 from space is a challenge, and even more so for anthropogenic CO2.The European space agency is preparing for the launch of a constellation of satellites for monitoring anthropogenic CO2 within the Copernicus program, starting in 2025. Scientific support studies have been carried out to define this mission in terms of payload and observational requirements. We report on the AeroCarb study, which investigated the impact retrieval errors due to aerosols in CO2 plumes downwind of large cities, and the potential benefit of an onboard aerosol sensor to help mitigate such errors. In this study, CO2 and aerosol plumes have been simulated at high-resolution for the cities of Berlin and Beijing. The impact of aerosol scattering on spaceborne CO2 measurements has been assessed using a combined CO2-aerosol retrieval scheme, with and without the use of an onboard multi-angular spectropolarimeter (MAP) for measuring aerosols. The results have been used to quantify the accuracy at which the CO2 emissions of Berlin and Beijing can be quantified using inverse modelling and the impact of aerosols depending on the chosen satellite payload. In this presentation we summarize the outcome of this study, and discuss the implications for the space borne monitoring of anthropogenic CO2 emissions from large cities.

U.S. oil and natural gas production volumes have grown by up to 100% in key production areas between January 2017 and August 2019. Here we show that recent trends are visible from space and can be attributed to drilling, production, and gas flaring activities. By using oil and gas activity data as predictors in a multivariate regression to satellite measurements of tropospheric NO2 columns, observed changes in NO2 over time could be attributed to NOx emissions associated with drilling, production and gas flaring for three select regions: the Permian, Bakken, and Eagle Ford basins. We find that drilling had been the dominant NOx source contributing around 80% before the downturn in drilling activity in 2015. Thereafter, NOx contributions from drilling activities and combined production and flaring activities are similar. Comparison of our top-down source attribution with a bottom-up fuel-based oil and gas NOx emission inventory shows agreement within error margins.

Multi-axis differential optical absorption spectroscopy (MAX-DOAS) is a widely used measurement technique for the detection of a variety of atmospheric trace gases. Using inverse modelling, the observation of trace gas column densities along different lines of sight enables the retrieval of aerosol and trace gas vertical profiles in the atmospheric boundary layer using appropriate retrieval algorithms. In this study, the ability of eight profile retrieval algorithms to reconstruct vertical profiles is assessed on the basis of synthetic measurements. Five of the algorithms are based on the optimal estimation method, two on parametrised approaches, and one using an analytical approach without involving any radiative transfer modelling. The synthetic measurements consist of the median of simulated slant column densities of O4 at 360 and 477 nm, as well as of HCHO at 343 nm and NO2 at 477 nm, from seven datasets simulated by five different radiative transfer models. Simulations are performed for a combination of 10 trace gas and 11 aerosol profiles, as well as 11 elevation angles, three solar zenith, and three relative azimuth angles. Overall, the results from the different algorithms show moderate to good performance for the retrieval of vertical profiles, surface concentrations, and total columns. Except for some outliers, the root-mean-square difference between the true and retrieved state ranges between (0.05–0.1) km−1 for aerosol extinction and (2.5–5.0) ×1010 molec cm−3 for HCHO and NO2 concentrations.

We present an intercomparison study of four airborne imaging DOAS instruments, dedicated to the retrieval and high resolution mapping of tropospheric nitrogen dioxide (NO2) vertical column densities (VCDs). The AROMAPEX campaign took place in Berlin, Germany in April, 2016 with the primary objective to test and intercompare the performance of experimental airborne imagers. The imaging DOAS instruments were operated simultaneously from two manned aircraft, performing synchronised flights: APEX (VITO/BIRA-IASB) was operated from DLR's DO-228 D-CFFU aircraft at 6.2 km altitude, while AirMAP (IUP-Bremen), SWING (BIRA-IASB) and SBI (TNO/TU Delft/KNMI) were operated from the FUB Cessna 207T D-EAFU at 3.1 km. Two synchronised flights took place on 21 April 2016. NO2 slant columns were retrieved by applying differential optical absorption spectroscopy (DOAS) in the visible wavelength region and converted to VCDs by the computation of appropriate air mass factors (AMFs). Finally, the NO2 VCDs were georeferenced and mapped at high spatial resolution. For the sake of harmonising the different data sets, efforts were made to agree on a common set of parameter settings, AMF LUT and gridding algorithm. The NO2 horizontal distribution, observed by the different DOAS imagers, shows very similar spatial patterns. The NO2 field is dominated by two large plumes related to industrial compounds, crossing the city from west to east. The major highways A100 and A113 are also identified as line sources of NO2. Retrieved NO2 VCDs range between 1 × 1015 molec cm−2 upwind of the city and 20 × 1015 molec cm−2 in the dominant plume, with a mean of 7.3 ± 1.8 × 1015 molec cm−2 for the morning flight and between 1 and 23 × 1015 molec cm−2 with a mean of 6.0 ± 1.4 × 1015 molec cm−2 for the afternoon flight. The mean NO2 VCD retrieval errors are in the range of 22 to 36 % for all sensors. The four data sets are in good agreement with Pearson correlation coefficients better than 0.9, while the linear regression analyses show slopes close to unity and generally small intercepts.

A global picture of atmospheric aerosol vertical distribution with a high temporal resolution is of key importance not only for climate, cloud formation, and air quality research studies but also for correcting scattered radiation induced by aerosols in absorbing trace gas retrievals from passive satellite sensors. Aerosol layer height (ALH) was retrieved from the OMI 477 nm O2−O2 band and its spatial pattern evaluated over selected cloud-free scenes. Such retrievals benefit from a synergy with MODIS data to provide complementary information on aerosols and cloudy pixels. We used a neural network approach previously trained and developed. Comparison with CALIOP aerosol level 2 products over urban and industrial pollution in eastern China shows consistent spatial patterns with an uncertainty in the range of 462–648 m. In addition, we show the possibility to determine the height of thick aerosol layers released by intensive biomass burning events in South America and Russia from OMI visible measurements. A Saharan dust outbreak over sea is finally discussed. Complementary detailed analyses show that the assumed aerosol properties in the forward modelling are the key factors affecting the accuracy of the results, together with potential cloud residuals in the observation pixels. Furthermore, we demonstrate that the physical meaning of the retrieved ALH scalar corresponds to the weighted average of the vertical aerosol extinction profile. These encouraging findings strongly suggest the potential of the OMI ALH product, and in more general the use of the 477 nm O2−O2 band from present and future similar satellite sensors, for climate studies as well as for future aerosol correction in air quality trace gas retrievals.

Tropospheric NO2 is hazardous to human health and can lead to tropospheric ozone formation, eutrophication of ecosystems and acid rain production. It is therefore important to establish accurate data based on models and observations to understand and monitor tropospheric NO2 concentrations on a regional and global scale. In the present study, MAX-DOAS tropospheric NO2 column retrievals from four European measurement stations are compared to regional model ensemble simulations. The latter are based on regional air quality models which contribute to the European regional ensemble forecasts and reanalyses of the operational Copernicus Atmosphere Monitoring Service (CAMS). Compared to other observational data usually applied for regional model validation, MAX-DOAS data is closer to the regional model data in terms of horizontal and vertical resolution and measurements are available during daylight. In general, there is a good agreement between simulated and retrieved NO2 column values for individual MAX-DOAS measurements with correlations between 45 and 75 % for tropospheric NO2 VCDs, indicating that the model ensemble represents the emission and tropospheric chemistry of NOx (NO + NO2) well. Pollution transport towards the stations is on average well represented by the models. However, large differences are found for individual pollution plumes. Seasonal cycles are overestimated, weekly cycles are reproduced well and diurnal cycles poorly represented by the model ensemble. In particular, simulated morning rush hour peaks are not confirmed by MAX-DOAS retrievals. Our results demonstrate that a large number of validation points are available from MAX-DOAS measurements, which should therefore be used more extensively in future regional air quality modelling studies.

This paper presents an exploratory study on the retrieval of aerosol layer height (ALH) from the OMI 477 nm O2–O2 spectral band. We have developed algorithms based on the Multilayer Perceptron (MLP) Neural Network (NN) approach and applied them on 3-year (2005–2007) OMI cloud-free scenes over North-East Asia, collocated with MODIS-Aqua aerosol product. In addition to the importance of aerosol altitude for climate and air quality objectives, the main motivation of this study is to evaluate the possibility of retrieving ALH for potential future improvements of trace gas retrievals (e.g. NO2, HCHO, SO2, etc..) from UV-Vis air quality satellite measurements over scenes including high aerosol concentrations. ALH retrieval relies on the analysis of the O2–O2 slant column density (SCD) and requires an accurate knowledge of the aerosol optical thickness τ. Using the MODIS-Aqua aerosol optical thickness at 550 nm as a prior information, comparison with the LIdar climatology of vertical Aerosol Structure for space-based lidar simulation (LIVAS) shows that ALH average biases over scenes with MODIS τ ≥ are in the range of 260–800 m. These results depend on the assumed aerosol single scattering albedo (sensitivity up to 600 m) and the chosen surface albedo (variation less than 200 m). Scenes with τ ≤ 0.5 are expected to show too large biases due to the little impacts of particles on the O2–O2 SCD changes. In addition, NN algorithms also enable aerosol optical thickness retrieval by exploring the OMI reflectance in the continuum. Comparisons with collocated MODIS-Aqua show agreements between −0.02 ± 0.45 and −0.18 ± 0.24 depending on the season. Improvements may be obtained from a better knowledge of the surface albedo, and higher accuracy of the aerosol model. This study shows the first encouraging aerosol layer height retrieval results over land from satellite observations of the 477 nm O2–O2 spectral band.

In June 2009, 22 spectrometers from 14 institutes measured tropospheric and stratospheric NO2 from the ground for more than 11 days during the Cabauw Intercomparison Campaign of Nitrogen Dioxide measuring Instruments (CINDI), at Cabauw, NL (51.97° N, 4.93° E). All visible instruments used a common wavelength range and set of cross sections for the spectral analysis. Most of the instruments were of the multi-axis design with analysis by differential spectroscopy software (MAX-DOAS), whose non-zenith slant columns were compared by examining slopes of their least-squares straight line fits to mean values of a selection of instruments, after taking 30-min averages. Zenith slant columns near twilight were compared by fits to interpolated values of a reference instrument, then normalised by the mean of the slopes of the best instruments. For visible MAX-DOAS instruments, the means of the fitted slopes for NO2 and O4 of all except one instrument were within 10% of unity at almost all non-zenith elevations, and most were within 5%. Values for UV MAX-DOAS instruments were almost as good, being 12% and 7%, respectively. For visible instruments at zenith near twilight, the means of the fitted slopes of all instruments were within 5% of unity. This level of agreement is as good as that of previous intercomparisons, despite the site not being ideal for zenith twilight measurements. It bodes well for the future of measurements of tropospheric NO2, as previous intercomparisons were only for zenith instruments focussing on stratospheric NO2, with their longer heritage.

Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) is a technique to measure trace gas amounts in the lower troposphere from ground-based scattered sunlight observations. MAX-DOAS observations are especially suitable for validation of tropospheric trace gas observations from satellite, since they have a representative range of several kilometers, both in the horizontal and in the vertical dimension. A two-step retrieval scheme is presented here, to derive aerosol corrected tropospheric NO2 columns from MAX-DOAS observations. In a first step, boundary layer aerosols, characterized in terms of aerosol optical thickness (AOT), are estimated from relative intensity observations, which are defined as the ratio of the sky radiance at elevation α and the sky radiance in the zenith. Relative intensity measurements have the advantage of a strong dependence on boundary layer AOT and almost no dependence on boundary layer height. In a second step, tropospheric NO2 columns are derived from differential slant columns, based on AOT-dependent air mass factors. This two-step retrieval scheme was applied to cloud free periods in a twelve month data set of observations in De Bilt, The Netherlands. In a comparison with AERONET (Cabauw site) a mean difference in AOT (AERONET minus MAX-DOAS) of −0.01±0.08 was found, and a correlation of 0.85. Tropospheric-NO2 columns were compared with OMI-satellite tropospheric NO2. For ground-based observations restricted to uncertainties below 10%, no significant difference was found, and a correlation of 0.88.

From June to July 2009 more than thirty different in-situ and remote sensing instruments from all over the world participated in the Cabauw Intercomparison campaign for Nitrogen Dioxide measuring Instruments (CINDI). The campaign took place at KNMI's Cabauw Experimental Site for Atmospheric Research (CESAR) in the Netherlands. Its main objectives were to determine the accuracy of state-of-the-art ground-based measurement techniques for the detection of atmospheric nitrogen dioxide (both in-situ and remote sensing), and to investigate their usability in satellite data validation. The expected outcomes are recommendations regarding the operation and calibration of such instruments, retrieval settings, and observation strategies for the use in ground-based networks for air quality monitoring and satellite data validation. Twenty-four optical spectrometers participated in the campaign, of which twenty-one had the capability to scan different elevation angles consecutively, the so-called Multi-axis DOAS systems, thereby collecting vertical profile information, in particular for nitrogen dioxide and aerosol. Various in-situ samplers and lidar instruments simultaneously characterized the variability of atmospheric trace gases and the physical properties of aerosol particles. A large data set of continuous measurements of these atmospheric constituents has been collected under various meteorological conditions and air pollution levels. Together with the permanent measurement capability at the CESAR site characterizing the meteorological state of the atmosphere, the CINDI campaign provided a comprehensive observational data set of atmospheric constituents in a highly polluted region of the world during summertime. First detailed comparisons performed with the CINDI data show that slant column measurements of NO2, O4 and HCHO with MAX-DOAS agree within 5 to 15%, vertical profiles of NO2 derived from several independent instruments agree within 25% of one another, and MAX-DOAS aerosol optical thickness agrees within 20–30% with AERONET data. For the in-situ NO2 instrument using a molybdenum converter, a bias was found as large as 5 ppbv during day time, when compared to the other in-situ instruments using photolytic converters.

Dutch Aerosol and Nitrogen Dioxide Experiments for Validation of OMI and SCIAMACHY (DANDELIONS) is a project that encompasses validation of spaceborne measurements of NO2 by the Ozone Monitoring Instrument (OMI) and Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY), and of aerosol by OMI and Advanced Along-Track Scanning Radiometer (AATSR), using an extensive set of ground-based and balloon measurements over the polluted area of the Netherlands. We present an extensive data set of ground-based, balloon, and satellite data on NO2, aerosols, and ozone obtained from two campaigns within the project, held during May-June 2005 and September 2006. We have used these data for first validation of OMI NO2, and the data are available through the Aura Validation Data Center website for use in other validation efforts. In this paper we describe the available data, and the methods and instruments used, including the National Institute of Public Health and the Environment (RIVM) NO2 lidar. We show that NO2 from Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) compares well with in situ measurements. We show that different MAX-DOAS instruments, operating simultaneously during the campaign, give very similar results. We also provide unique information on the spatial homogeneity and the vertical and temporal variability of NO2, showing that during a number of days, the NO2 columns derived from measurements in different directions varied significantly, which implies that, under polluted conditions, measurements in one single azimuth direction are not always representative for the averaged field that the satellite observes. In addition, we show that there is good agreement between tropospheric NO2 from OMI and MAX-DOAS, and also between total NO2 from OMI and direct-sun observations. Observations of the aerosol optical thickness (AOT) show that values derived with three ground-based instruments correspond well with each other, and with aerosol optical thicknesses observed by OMI. Copyright 2008 by the American Geophysical Union. U7 - Export Date: 2 August 2010 U7 - Source: Scopus U7 - Art. No.: D16S46