scholarly journals Quantitative bias estimates for tropospheric NO<sub>2</sub> columns retrieved from SCIAMACHY, OMI, and GOME-2 using a common standard for East Asia

2012 ◽  
Vol 5 (10) ◽  
pp. 2403-2411 ◽  
Author(s):  
H. Irie ◽  
K. F. Boersma ◽  
Y. Kanaya ◽  
H. Takashima ◽  
X. Pan ◽  
...  
Keyword(s):  
Regression Line ◽  
Correlation Coefficients ◽  
Satellite Observation ◽  
Optical Absorption Spectroscopy ◽  
Data Sets ◽  
Vertical Column ◽  
Vertical Column Density ◽  
Satellite Sensors ◽  
Single Set ◽  
Japan And China

Abstract. For the intercomparison of tropospheric nitrogen dioxide (NO2) vertical column density (VCD) data from three different satellite sensors (SCIAMACHY, OMI, and GOME-2), we use a common standard to quantitatively evaluate the biases for the respective data sets. As the standard, a regression analysis using a single set of collocated ground-based Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) observations at several sites in Japan and China from 2006–2011 is adopted. Examinations of various spatial coincidence criteria indicates that the slope of the regression line can be influenced by the spatial distribution of NO2 over the area considered. While the slope varies systematically with the distance between the MAX-DOAS and satellite observation points around Tokyo in Japan, such a systematic dependence is not clearly seen and correlation coefficients are generally higher in comparisons at sites in China. On the basis of these results, we focus mainly on comparisons over China and estimate the biases in SCIAMACHY, OMI, and GOME-2 data (TM4NO2A and DOMINO version 2 products) against the MAX-DOAS observations to be −5 ± 14%, −10 ± 14%, and +1 ± 14%, respectively, which are all small and insignificant. We suggest that these small biases now allow for analyses combining these satellite data for air quality studies, which are more systematic and quantitative than previously possible.

scholarly journals First quantitative bias estimates for tropospheric NO<sub>2</sub> columns retrieved from SCIAMACHY, OMI, and GOME-2 using a common standard

2012 ◽  
Vol 5 (3) ◽  
pp. 3953-3971 ◽  
Author(s):  
H. Irie ◽  
K. F. Boersma ◽  
Y. Kanaya ◽  
H. Takashima ◽  
X. Pan ◽  
...  
Keyword(s):  
Regression Line ◽  
Correlation Coefficients ◽  
Satellite Observation ◽  
Optical Absorption Spectroscopy ◽  
Data Sets ◽  
Vertical Column ◽  
Vertical Column Density ◽  
Satellite Sensors ◽  
Single Set ◽  
Japan And China

Abstract. For the intercomparison of tropospheric nitrogen dioxide NO2 vertical column density (VCD) data from three different satellite sensors (SCIAMACHY, OMI, and GOME-2), we use a common standard to quantitatively evaluate the biases for the respective data sets. As the standard, a regression analysis using a single set of collocated ground-based Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) observations at several sites in Japan and China in 2006–2011 is adopted. Examination of various spatial coincidence criteria indicates that the slope of the regression line can be influenced by the spatial distribution of NO2 over the area considered. While the slope varies systematically with the distance between the MAX-DOAS and satellite observation points around Tokyo in Japan, such a systematic dependence is not clearly seen and correlation coefficients are generally higher in comparisons at sites in China. On the basis of these results, we focus mainly on comparisons over China and best estimate the biases in SCIAMACHY, OMI, and GOME-2 data (TM4NO2A and DOMINO version 2 products) against the MAX-DOAS observations to be −5±14 %, −10±14 %, and +1±14 %, respectively, which are all small and insignificant. We suggest that these small biases now allow analyses combining these satellite data for air quality studies that are more systematic and quantitative than previously possible.

scholarly journals Total column water vapour measurements from GOME-2 MetOp-A and MetOp-B

2014 ◽  
Vol 7 (3) ◽  
pp. 3021-3073 ◽  
Author(s):  
M. Grossi ◽  
P. Valks ◽  
D. Loyola ◽  
B. Aberle ◽  
S. Slijkhuis ◽  
...  
Keyword(s):  
Water Vapour ◽  
Optical Absorption Spectroscopy ◽  
Retrieval Algorithm ◽  
Data Sets ◽  
Vertical Column ◽  
Data Set ◽  
Vertical Column Density ◽  
Data Processor ◽  
Climate Analysis ◽  
Total Column

Abstract. The knowledge of the total column water vapour (TCWV) global distribution is fundamental for climate analysis and weather monitoring. In this work, we present the retrieval algorithm used to derive the operational TCWV from the GOME-2 sensors and perform an extensive inter-comparison and validation in order to estimate their absolute accuracy and long-term stability. We use the recently reprocessed data sets retrieved by the GOME-2 instruments aboard EUMETSAT's MetOp-A and MetOp-B satellites and generated by DLR in the framework of the O3M-SAF using the GOME Data Processor (GDP) version 4.7. The retrieval algorithm is based on a classical Differential Optical Absorption Spectroscopy (DOAS) method and combines H2O/O2 retrieval for the computation of the trace gas vertical column density. We introduce a further enhancement in the quality of the H2O column by optimizing the cloud screening and developing an empirical correction in order to eliminate the instrument scan angle dependencies. We evaluate the overall consistency between about 8 months measurements from the newer GOME-2 instrument on the MetOp-B platform with the GOME-2/MetOp-A data in the overlap period. Furthermore, we compare GOME-2 results with independent TCWV data from ECMWF and with SSMIS satellite measurements during the full period January 2007–August 2013 and we perform a validation against the combined SSM/I + MERIS satellite data set developed in the framework of the ESA DUE GlobVapour project. We find global mean biases as small as ± 0.03 g cm−2 between GOME-2A and all other data sets. The combined SSM/I-MERIS sample is typically drier than the GOME-2 retrievals (−0.005 g cm−2), while on average GOME-2 data overestimate the SSMIS measurements by only 0.028 g cm−2. However, the size of some of these biases are seasonally dependent. Monthly average differences can be as large as 0.1 g cm−2, based on the analysis against SSMIS measurements, but are not as evident in the validation with the ECMWF and the SSM/I + MERIS data. Studying two exemplary months, we estimate regional differences and identify a very good agreement between GOME-2 total columns and all three independent data sets, especially for land areas, although some discrepancies over ocean and over land areas with high humidity and a relatively large surface albedo are also present.

scholarly journals Intercomparison of four airborne imaging DOAS systems for tropospheric NO<sub>2</sub> mapping – the AROMAPEX campaign

2019 ◽  
Vol 12 (1) ◽  
pp. 211-236 ◽  
Author(s):  
Frederik Tack ◽  
Alexis Merlaud ◽  
Andreas C. Meier ◽  
Tim Vlemmix ◽  
Thomas Ruhtz ◽  
...  
Keyword(s):  
Pearson Correlation ◽  
Wavelength Region ◽  
Correlation Coefficients ◽  
Horizontal Distribution ◽  
Primary Objective ◽  
Optical Absorption Spectroscopy ◽  
Data Sets ◽  
Vertical Column ◽  
Airborne Imaging ◽  
The City

Abstract. 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 in 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 look-up table, 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.

scholarly journals Total columns of H<sub>2</sub>O measured from the ground and from space at Observatoire de Haute-Provence in France (44° N)

2013 ◽  
Vol 6 (3) ◽  
pp. 4249-4277
Author(s):  
S. Alkasm ◽  
A. Sarkissian ◽  
P. Keckhut ◽  
A. Pazmino ◽  
F. Goutail ◽  
...  
Keyword(s):  
Water Vapour ◽  
Column Density ◽  
Data Sets ◽  
Satellite Measurements ◽  
Vertical Column ◽  
Vertical Column Density ◽  
Satellite Sensors ◽  
Global Agreement ◽  
Density Of Water ◽  
Total Column

Abstract. In this work, we compare vertical column density of water vapour measured at Observatoire de Haute-Provence, Southern France (5° 42' E, +43° 55' N). Data were obtained by three satellite sensors, GOME, GOME 2 and SCIAMACHY, and by two ground-based spectrometers, Elodie and SAOZ. These five instruments are able to measure total column density of water vapour in the visible and have different principles of observation. All these instruments reproduce the total column water vapour with good accuracy. The mean difference between the satellite measurements, ground-based measurements, and between both types, are quantified. The diurnal cycle of water vapour above the station and its variability with latitude have been investigated. The differences between these data sets are due sometimes to the differences in the time of the measurements, or to the differences in the geometry of observations, or also due to both effects. The effect of land and sea and the effect of the season on the total column water vapour has been analysed. The global agreement between our data sets range from 10% in summer to 25% in winter, improved significantly when observations are closer in time and location.

scholarly journals MAX-DOAS NO<sub>2</sub> observations over Guangzhou, China; ground-based and satellite comparisons

2018 ◽  
Vol 11 (4) ◽  
pp. 2239-2255 ◽  
Author(s):  
Theano Drosoglou ◽  
Maria Elissavet Koukouli ◽  
Natalia Kouremeti ◽  
Alkiviadis F. Bais ◽  
Irene Zyrichidou ◽  
...  
Keyword(s):  
Time Window ◽  
Correlation Coefficients ◽  
Urban Site ◽  
Reference Case ◽  
Vertical Column ◽  
Time Period ◽  
Tropospheric No2 ◽  
Vertical Column Density ◽  
Satellite Sensors ◽  
Academy Of Sciences

Abstract. In this study, the tropospheric NO2 vertical column density (VCD) over an urban site in Guangzhou megacity in China is investigated by means of MAX-DOAS measurements during a campaign from late March 2015 to mid-March 2016. A MAX-DOAS system was deployed at the Guangzhou Institute of Geochemistry of the Chinese Academy of Sciences and operated there for about 1 year, during the spring and summer months. The tropospheric NO2 VCDs retrieved by the MAX-DOAS are presented and compared with space-borne observations from GOME-2/MetOp-A, GOME-2/MetOp-B and OMI/Aura satellite sensors. The comparisons reveal good agreement between satellite and MAX-DOAS observations over Guangzhou, with correlation coefficients ranging between 0.795 for GOME-2B and 0.996 for OMI. However, the tropospheric NO2 loadings are underestimated by the satellite sensors on average by 25.1, 10.3 and 5.7 %, respectively, for OMI, GOME-2A and GOME-2B. Our results indicate that GOME-2B retrievals are closer to those of the MAX-DOAS instrument due to the lower tropospheric NO2 concentrations during the days with valid GOME-2B observations. In addition, the effect of the main coincidence criteria is investigated, namely the cloud fraction (CF), the distance (d) between the satellite pixel center and the ground-based measurement site, as well as the time period within which the MAX-DOAS data are averaged around the satellite overpass time. The effect of CF and time window criteria is more profound on the selection of OMI overpass data, probably due to its smaller pixel size. The available data pairs are reduced to half and about one-third for CF  ≤  0.3 and CF  ≤  0.2, respectively, while, compared to larger CF thresholds, the correlation coefficient is improved to 0.996 from about 0.86, the slope value is very close to unity ( ∼  0.98) and the mean satellite underestimation is reduced to about half (from  ∼  7 to  ∼  3.5  ×  1015 molecules cm−2). On the other hand, the distance criterion affects mostly GOME-2B data selection, because GOME-2B pixels are quite evenly distributed among the different radii used in the sensitivity test. More specifically, the number of collocations is notably reduced when stricter radius limits are applied, the r value is improved from 0.795 (d ≤  50 km) to 0.953 (d ≤  20 km), and the absolute mean bias decreases about 6 times for d ≤  30 km compared to the reference case (d ≤  50 km).

scholarly journals MAX-DOAS NO<sub>2</sub> observations over Guangzhou, China; ground-based and satellite comparisons

2017 ◽  
Author(s):  
Theano Drosoglou ◽  
Maria Elissavet Koukouli ◽  
Natalia Kouremeti ◽  
Alkiviadis F. Bais ◽  
Irene Zyrichidou ◽  
...  
Keyword(s):  
Time Window ◽  
Correlation Coefficients ◽  
Urban Site ◽  
Reference Case ◽  
Vertical Column ◽  
Tropospheric No2 ◽  
Vertical Column Density ◽  
Satellite Sensors ◽  
D 20 ◽  
One Year

Abstract. In this study, the tropospheric NO2 vertical column density (VCD) over an urban site in Guangzhou megacity in China is investigated, by means of MAX-DOAS measurements during a campaign from late March 2015 to mid-March 2016. A MAX-DOAS system was deployed at the Guangzhou Institute of Geochemistry of the Chinese Academy of Sciences and operated there for about one year, during the spring and summer months. The tropospheric NO2 VCDs retrieved by the MAX-DOAS are presented and compared with space-borne observations from GOME-2/MetOp-A, GOME-2/MetOp-B and OMI/Aura satellite sensors. The comparisons reveal good agreement between satellite and MAX-DOAS observations over Guangzhou, with correlation coefficients ranging between 0.76 for GOME-2B and 0.99 for GOME-2A. However, the tropospheric NO2 loadings are underestimated by the satellite sensors on average by 25.1 %, 10.3 % and 5.7 %, respectively for OMI, GOME-2A and GOME-2B. Our results indicate that GOME-2B retrievals are closer to those of the MAX-DOAS instrument due to the lower tropospheric NO2 concentrations during the days with valid GOME-2B observations. In addition, the effect of the main coincidence criteria is investigated, namely the cloud fraction (CF), the distance (d) between the satellite pixel center and the ground-based measurement site, as well as the time period within which the MAX-DOAS data are averaged around the satellite overpass time. The effect of CF and time window criteria is more profound on the selection of OMI overpass data, probably due to its smaller pixel size. The available data pairs are reduced to half and about one third for CF ≤ 0.3 and CF ≤ 0.2, respectively, while, compared to larger CF thresholds, the correlation coefficient is improved to 0.99 from about 0.6, the slope value is almost doubled (~ 0.8) and the mean satellite underestimation is reduced to about half (from ~ 7 to ~ 3.5 × 1015 molecules/cm2). On the other hand, the distance criterion affects mostly GOME-2B data selection, because GOME-2B pixels are quite evenly distributed among the different radii used in the sensitivity test. More specifically, the number of collocations is notably reduced when stricter radius limits are applied, the r value is improved from 0.76 (d ≤ 50 km) to 0.93 (d ≤ 20 km), and the absolute mean bias decreases about 6 times for d ≤ 30 km compared to the reference case (d ≤ 50 km).

scholarly journals Intercomparison of four airborne imaging DOAS systems for tropospheric NO<sub>2</sub> mapping – The AROMAPEX campaign

2018 ◽  
Author(s):  
Frederik Tack ◽  
Alexis Merlaud ◽  
Andreas C. Meier ◽  
Tim Vlemmix ◽  
Thomas Ruhtz ◽  
...  
Keyword(s):  
Pearson Correlation ◽  
Wavelength Region ◽  
Correlation Coefficients ◽  
Horizontal Distribution ◽  
Primary Objective ◽  
Optical Absorption Spectroscopy ◽  
Data Sets ◽  
Vertical Column ◽  
Airborne Imaging ◽  
The City

Abstract. 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.

scholarly journals Total column water vapour measurements from GOME-2 MetOp-A and MetOp-B

2015 ◽  
Vol 8 (3) ◽  
pp. 1111-1133 ◽  
Author(s):  
M. Grossi ◽  
P. Valks ◽  
D. Loyola ◽  
B. Aberle ◽  
S. Slijkhuis ◽  
...  
Keyword(s):  
Water Vapour ◽  
Temporal Stability ◽  
Optical Absorption Spectroscopy ◽  
Retrieval Algorithm ◽  
Data Sets ◽  
Vertical Column ◽  
Data Set ◽  
Vertical Column Density ◽  
Climate Analysis ◽  
Total Column

Abstract. Knowledge of the total column water vapour (TCWV) global distribution is fundamental for climate analysis and weather monitoring. In this work, we present the retrieval algorithm used to derive the operational TCWV from the GOME-2 sensors aboard EUMETSAT's MetOp-A and MetOp-B satellites and perform an extensive inter-comparison in order to evaluate their consistency and temporal stability. For the analysis, the GOME-2 data sets are generated by DLR in the framework of the EUMETSAT O3M-SAF project using the GOME Data Processor (GDP) version 4.7. The retrieval algorithm is based on a classical Differential Optical Absorption Spectroscopy (DOAS) method and combines a H2O and O2 retrieval for the computation of the trace gas vertical column density. We introduce a further enhancement in the quality of the H2O total column by optimizing the cloud screening and developing an empirical correction in order to eliminate the instrument scan angle dependencies. The overall consistency between measurements from the newer GOME-2 instrument on board of the MetOp-B platform and the GOME-2/MetOp-A data is evaluated in the overlap period (December 2012–June 2014). Furthermore, we compare GOME-2 results with independent TCWV data from the ECMWF ERA-Interim reanalysis, with SSMIS satellite measurements during the full period January 2007–June 2014 and against the combined SSM/I + MERIS satellite data set developed in the framework of the ESA DUE GlobVapour project (January 2007–December 2008). Global mean biases as small as ±0.035 g cm−2 are found between GOME-2A and all other data sets. The combined SSM/I-MERIS sample and the ECMWF ERA-Interim data set are typically drier than the GOME-2 retrievals, while on average GOME-2 data overestimate the SSMIS measurements by only 0.006 g cm−2. However, the size of these biases is seasonally dependent. Monthly average differences can be as large as 0.1 g cm−2, based on the analysis against SSMIS measurements, which include only data over ocean. The seasonal behaviour is not as evident when comparing GOME-2 TCWV to the ECMWF ERA-Interim and the SSM/I+MERIS data sets, since the different biases over land and ocean surfaces partly compensate each other. Studying two exemplary months, we estimate regional differences and identify a very good agreement between GOME-2 total columns and all three data sets, especially for land areas, although some discrepancies (bias larger than ±0.5 g cm−2) over ocean and over land areas with high humidity or a relatively large surface albedo are observed.

scholarly journals Ground-based MAX-DOAS observations of tropospheric formaldehyde and comparisons with CAMS model at a rural site near Beijing

2018 ◽  
Author(s):  
Xin Tian ◽  
Pinhua Xie ◽  
Jin Xu ◽  
Yang Wang ◽  
Ang Li ◽  
...  
Keyword(s):  
Correlation Coefficient ◽  
Photochemical Reactions ◽  
Control Measures ◽  
Asia Pacific ◽  
Rural Site ◽  
Optical Absorption Spectroscopy ◽  
Data Sets ◽  
Wind Fields ◽  
Vertical Column ◽  
Secondary Sources

Abstract. Formaldehyde (HCHO), a key aerosol precursor, plays a significant role in atmospheric photo-oxidation pathways. In this study, HCHO column densities were measured using Multi-axis Differential Optical Absorption Spectroscopy (MAX-DOAS) instrument at the University of Chinese Academy of Science (UCAS) in Huairou District, Beijing, which is about 50 km away from the city center, during the period of October 1, 2014 to December 31, 2014, in which the Asia-Pacific Economic Cooperation (APEC) summit was organized on 3 to 12 November. Peak values of HCHO vertical column densities (VCDs) around noon and a good correlation coefficient of 0.87 between HCHO and O3 indicate that the secondary sources of HCHO through photochemical reactions of volatile organic compounds (VOCs) dominate HCHO values in the area around UCAS. Dependences of HCHO VCDs on wind fields and backward trajectories were identified and indicated that the HCHO values in the area around UCAS were considerably affected by the transports of pollutants (VOCs) from polluted area in the south. The effects of control measures on HCHO VCDs during the APEC period were evaluated. During the period of APEC conference, the averaged HCHO is 37.95 % and 30.75 % lower than that during the pre-APEC and post-APEC period, respectively. The phenomenon could be attributed to both effects of prevailing northwest wind fields during the APEC and strict control measures. We also compared the MAX-DOAS results with the Copernicus Atmosphere Monitoring Service (CAMS) model. The CAMS model and MAX-DOAS results are generally consistent with a good correlation coefficient of ~ 0.83. The peak values are well consistently captured by both data sets, but the low values are systematically underestimated by the CAMS model. The finding indicates the CAMS model can well simulate the effects of transports and the secondary sources of HCHO, but underestimate the local primary sources.

scholarly journals High-resolution mapping of the NO<sub>2</sub> spatial distribution over Belgian urban areas based on airborne APEX remote sensing

2017 ◽  
Vol 10 (5) ◽  
pp. 1665-1688 ◽  
Author(s):  
Frederik Tack ◽  
Alexis Merlaud ◽  
Marian-Daniel Iordache ◽  
Thomas Danckaert ◽  
Huan Yu ◽  
...  
Keyword(s):  
High Resolution ◽  
Spatial Resolution ◽  
Urban Areas ◽  
High Spatial Resolution ◽  
European Space Agency ◽  
Correlation Coefficients ◽  
Time Frame ◽  
Quantitative Information ◽  
Data Sets ◽  
Vertical Column

Abstract. We present retrieval results of tropospheric nitrogen dioxide (NO2) vertical column densities (VCDs), mapped at high spatial resolution over three Belgian cities, based on the DOAS analysis of Airborne Prism EXperiment (APEX) observations. APEX, developed by a Swiss-Belgian consortium on behalf of ESA (European Space Agency), is a pushbroom hyperspectral imager characterised by a high spatial resolution and high spectral performance. APEX data have been acquired under clear-sky conditions over the two largest and most heavily polluted Belgian cities, i.e. Antwerp and Brussels on 15 April and 30 June 2015. Additionally, a number of background sites have been covered for the reference spectra. The APEX instrument was mounted in a Dornier DO-228 aeroplane, operated by Deutsches Zentrum für Luft- und Raumfahrt (DLR). NO2 VCDs were retrieved from spatially aggregated radiance spectra allowing urban plumes to be resolved at the resolution of 60  ×  80 m2. The main sources in the Antwerp area appear to be related to the (petro)chemical industry while traffic-related emissions dominate in Brussels. The NO2 levels observed in Antwerp range between 3 and 35  ×  1015 molec cm−2, with a mean VCD of 17.4 ± 3.7  ×  1015 molec cm−2. In the Brussels area, smaller levels are found, ranging between 1 and 20  ×  1015 molec cm−2 and a mean VCD of 7.7 ± 2.1  ×  1015 molec cm−2. The overall errors on the retrieved NO2 VCDs are on average 21 and 28 % for the Antwerp and Brussels data sets. Low VCD retrievals are mainly limited by noise (1σ slant error), while high retrievals are mainly limited by systematic errors. Compared to coincident car mobile-DOAS measurements taken in Antwerp and Brussels, both data sets are in good agreement with correlation coefficients around 0.85 and slopes close to unity. APEX retrievals tend to be, on average, 12 and 6 % higher for Antwerp and Brussels, respectively. Results demonstrate that the NO2 distribution in an urban environment, and its fine-scale variability, can be mapped accurately with high spatial resolution and in a relatively short time frame, and the contributing emission sources can be resolved. High-resolution quantitative information about the atmospheric NO2 horizontal variability is currently rare, but can be very valuable for (air quality) studies at the urban scale.

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