scholarly journals Near-real time retrieval of tropospheric NO<sub>2</sub> from OMI

2007 ◽  
Vol 7 (8) ◽  
pp. 2103-2118 ◽  
Author(s):  
K. F. Boersma ◽  
H. J. Eskes ◽  
J. P. Veefkind ◽  
E. J. Brinksma ◽  
R. J. van der A ◽  
...  
Keyword(s):  
Real Time ◽  
Transport Model ◽  
Optical Absorption Spectroscopy ◽  
Retrieval Algorithm ◽  
Satellite Measurement ◽  
Ozone Monitoring Instrument ◽  
Similar Frequency ◽  
Line System ◽  
Cloud Data ◽  
Tropospheric No2

Abstract. We present a new algorithm for the near-real time retrieval – within 3 h of the actual satellite measurement – of tropospheric NO2 columns from the Ozone Monitoring Instrument (OMI). The retrieval is based on the combined retrieval-assimilation-modelling approach developed at KNMI for off-line tropospheric NO2 from the GOME and SCIAMACHY satellite instruments. We have adapted the off-line system such that the required a priori information – profile shapes and stratospheric background NO2 – is now immediately available upon arrival (within 80 min of observation) of the OMI NO2 slant columns and cloud data at KNMI. Slant columns for NO2 are retrieved using differential optical absorption spectroscopy (DOAS) in the 405–465 nm range. Cloud fraction and cloud pressure are provided by a new cloud retrieval algorithm that uses the absorption of the O2-O2 collision complex near 477 nm. On-line availability of stratospheric slant columns and NO2 profiles is achieved by running the TM4 chemistry transport model (CTM) forward in time based on forecast ECMWF meteo and assimilated NO2 information from all previously observed orbits. OMI NO2 slant columns, after correction for spurious across-track variability, show a random error for individual pixels of approximately 0.7×1015 molec cm−2. Cloud parameters from OMI's O2-O2 algorithm have similar frequency distributions as retrieved from SCIAMACHY's Fast Retrieval Scheme for Cloud Observables (FRESCO) for August 2006. On average, OMI cloud fractions are higher by 0.011, and OMI cloud pressures exceed FRESCO cloud pressures by 60 hPa. A sequence of OMI observations over Europe in October 2005 shows OMI's capability to track changeable NOx air pollution from day to day in cloud-free situations.

scholarly journals Near-real time retrieval of tropospheric NO<sub>2</sub> from OMI

2006 ◽  
Vol 6 (6) ◽  
pp. 12301-12345 ◽  
Author(s):  
K. F. Boersma ◽  
H. J. Eskes ◽  
J. P. Veefkind ◽  
E. J. Brinksma ◽  
R. J. van der A ◽  
...  
Keyword(s):  
Real Time ◽  
Local Time ◽  
Cloud Fraction ◽  
Optical Absorption Spectroscopy ◽  
Retrieval Algorithm ◽  
Satellite Measurement ◽  
Similar Frequency ◽  
Line System ◽  
Cloud Parameters ◽  
Tropospheric No2

Abstract. We present a new algorithm for the near-real time retrieval – within 3 h of the actual satellite measurement – of tropospheric NO2 columns from the Ozone Monitoring Instrument (OMI). The retrieval system is based on the combined retrieval-assimilation-modelling approach developed at KNMI for off-line tropospheric NO2 from the GOME and SCIAMACHY satellite instruments. We have adapted the off-line system such that the required a priori information ndash; profile shapes and stratospheric background NO2 ndash; is now immediately available upon arrival of the OMI NO2 slant columns and cloud data at KNMI. Slant column NO2 and cloud information arrives at KNMI typically within 80 min of actual OMI observations. Slant columns for NO2 are retrieved using differential optical absorption spectroscopy (DOAS) in the 405–465 nm range. Cloud fraction and cloud pressure are provided by a new cloud retrieval algorithm that uses the absorption of the O2–O2 collision complex near 477 nm. On-line availability of stratospheric slant columns and NO2 profiles is achieved by running the TM4 chemistry transport model (CTM) forward in time based on forecast ECMWF meteo and assimilated NO2 information from all previously observed orbits. OMI NO2 slant columns, after correction for spurious across-track variability, show a random error for individual pixels of approximately 0.7×1015molec.cm–2. As NO2 retrievals are very sensitive to clouds, we evaluated the consistency of cloud fraction and cloud pressure from the new O2–O2 (OMI) algorithm and from the Fast Retrieval Scheme for Cloud Observables (FRESCO). Cloud parameters from the O2–O2 (OMI) algorithm have similar frequency distributions as cloud parameters retrieved from FRESCO (SCIAMACHY) for August 2006. On average, OMI cloud fractions are higher by 0.011, and OMI cloud pressures exceed FRESCO cloud pressures by 60 hPa. As a consistency check, we intercompared OMI near-real time NO2 columns measured at 13:45 h local time to SCIAMACHY off-line NO2 columns measured at 10:00 h local time. In August 2006, both instruments observe very similar spatial patterns of tropospheric NO2 columns, and small differences for most locations on Earth where tropospheric NO2 columns are small. For regions that are strongly polluted, SCIAMACHY observes higher tropospheric NO2 columns than OMI.

scholarly journals Comparisons of ground-based tropospheric NO<sub>2</sub> MAX-DOAS measurements to satellite observations with the aid of an air quality model over the Thessaloniki area, Greece

2017 ◽  
Vol 17 (9) ◽  
pp. 5829-5849 ◽  
Author(s):  
Theano Drosoglou ◽  
Alkiviadis F. Bais ◽  
Irene Zyrichidou ◽  
Natalia Kouremeti ◽  
Anastasia Poupkou ◽  
...  
Keyword(s):  
Air Quality ◽  
Transport Model ◽  
Optical Absorption Spectroscopy ◽  
Monitoring Site ◽  
Air Quality Model ◽  
Ozone Monitoring Instrument ◽  
Quality Model ◽  
Meteorological Model ◽  
Tropospheric No2 ◽  
Ozone Monitoring

Abstract. One of the main issues arising from the comparison of ground-based and satellite measurements is the difference in spatial representativeness, which for locations with inhomogeneous spatial distribution of pollutants may lead to significant differences between the two data sets. In order to investigate the spatial variability of tropospheric NO2 within a sub-satellite pixel, a campaign which lasted for about 6 months was held in the greater area of Thessaloniki, Greece. Three multi-axial differential optical absorption spectroscopy (MAX-DOAS) systems performed measurements of tropospheric NO2 columns at different sites representative of urban, suburban and rural conditions. The direct comparison of these ground-based measurements with corresponding products from the Ozone Monitoring Instrument onboard NASA's Aura satellite (OMI/Aura) showed good agreement over the rural and suburban areas, while the comparison with the Global Ozone Monitoring Experiment-2 (GOME-2) onboard EUMETSAT's Meteorological Operational satellites' (MetOp-A and MetOp-B) observations is good only over the rural area. GOME-2A and GOME-2B sensors show an average underestimation of tropospheric NO2 over the urban area of about 10.51 ± 8.32  ×  1015 and 10.21 ± 8.87  × 1015 molecules cm−2, respectively. The mean difference between ground-based and OMI observations is significantly lower (6.60 ± 5.71  ×  1015 molecules cm−2). The differences found in the comparisons of MAX-DOAS data with the different satellite sensors can be attributed to the higher spatial resolution of OMI, as well as the different overpass times and NO2 retrieval algorithms of the satellites. OMI data were adjusted using factors calculated by an air quality modeling tool, consisting of the Weather Research and Forecasting (WRF) mesoscale meteorological model and the Comprehensive Air Quality Model with Extensions (CAMx) multiscale photochemical transport model. This approach resulted in significant improvement of the comparisons over the urban monitoring site. The average difference of OMI observations from MAX-DOAS measurements was reduced to −1.68 ± 5.01  ×  1015 molecules cm−2.

scholarly journals An improved tropospheric NO<sub>2</sub> column retrieval algorithm for TROPOMI over Europe

2021 ◽  
Author(s):  
Song Liu ◽  
Pieter Valks ◽  
Gaia Pinardi ◽  
Jian Xu ◽  
Ka Lok Chan ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Transport Model ◽  
Estimation Algorithm ◽  
Point Sources ◽  
Optical Absorption Spectroscopy ◽  
Retrieval Algorithm ◽  
Vertical Column ◽  
Chemistry Transport Model ◽  
Total Uncertainty ◽  
Tropospheric No2

Abstract. Launched in October 2017, the TROPOspheric Monitoring Instrument (TROPOMI) aboard Sentinel-5 Precursor provides the potential to monitor air quality over point sources across the globe with a spatial resolution as high as 5.5 km × 3.5 km (7 km × 3.5 km before 6 August 2019). The nitrogen dioxide (NO2) retrieval algorithm for the TROPOMI instrument consists of three steps: the spectral fitting of the slant column, the separation of stratospheric and tropospheric contributions, and the conversion of the slant column to a vertical column using an air mass factor (AMF) calculation. In this work, an improved tropospheric NO2 retrieval algorithm from TROPOMI measurements over Europe is presented. The stratospheric estimation is implemented using the STRatospheric Estimation Algorithm from Mainz (STREAM), which was developed as a verification algorithm for TROPOMI and does not require chemistry transport model data as input. A directionally dependent STREAM (DSTREAM) is developed to correct for the dependency of the stratospheric NO2 on the viewing geometry by up to 2 × 1014 molec/cm2. Applied to synthetic TROPOMI data, the uncertainty in the stratospheric column is 3.5 × 1014 molec/cm2 for polluted conditions. Applied to actual measurements, the smooth variation of stratospheric NO2 at low latitudes is conserved, and stronger stratospheric variation at higher latitudes are captured. For AMF calculation, the climatological surface albedo data is replaced by geometry-dependent effective Lambertian equivalent reflectivity (GE_LER) obtained directly from TROPOMI measurements with a high spatial resolution. Mesoscale-resolution a priori NO2 profiles are obtained from the regional POLYPHEMUS/DLR chemistry transport model with the TNO-MACC emission inventory. Based on the latest TROPOMI operational cloud parameters, a more realistic cloud treatment is provided by a clouds-as-layers (CAL) model, which treats the clouds as uniform layers of water droplets, instead of the clouds-as-reflecting-boundaries (CRB) model, in which clouds are simplified as Lambertian reflectors. For the error analysis, the tropospheric AMF uncertainty, which is the largest source of NO2 uncertainty for polluted scenarios, ranges between 20 % and 50 %, leading to a total uncertainty in the tropospheric NO2 column in the 30–60 % range. From a validation performed with ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements, the improved tropospheric NO2 data shows good correlations for nine European urban/suburban stations with an average correlation coefficient of 0.78. The implementation of the algorithm improvements leads to a decrease of the relative difference from −55.3 % to −34.7 % on average.

scholarly journals An improved air mass factor calculation for NO<sub>2</sub> measurements from GOME-2

2019 ◽  
Author(s):  
Song Liu ◽  
Pieter Valks ◽  
Gaia Pinardi ◽  
Jian Xu ◽  
Athina Argyrouli ◽  
...  
Keyword(s):  
Surface Albedo ◽  
Transport Model ◽  
Optical Absorption Spectroscopy ◽  
Retrieval Algorithm ◽  
Model Parameters ◽  
Air Mass ◽  
Cloud Parameters ◽  
Tropospheric No2 ◽  
Mass Factor ◽  
The Impact

Abstract. An improved tropospheric nitrogen dioxide (NO2) retrieval algorithm from the Global Ozone Monitoring Experiment-2 (GOME-2) instrument based on air mass factor (AMF) calculations performed with more realistic model parameters is presented. The viewing angle-dependency of surface albedo is taken into account by improving the GOME-2 Lambertian-equivalent reflectivity (LER) climatology with a directionally dependent LER (DLER) dataset over land and an ocean surface albedo parametrization over water. A priori NO2 profiles with higher spatial and temporal resolutions are obtained from the IFS(CB05BASCOE) chemistry transport model based on recent emission inventories. A more realistic cloud treatment is provided by a Cloud-As-Layers (CAL) approach, which treats the clouds as uniform layers of water droplets, instead of the current Clouds-as-Reflecting-Boundaries (CRB) model, which assumes the clouds as Lambertian reflectors. Improvements in the AMF calculation affect the tropospheric NO2 columns on average within ±15 % in winter and ±5 % in summer over largely polluted regions. In addition, the impact of aerosols on our tropospheric NO2 retrieval is investigated by comparing the concurrent retrievals based on ground-based aerosol measurements (explicit aerosol correction) and aerosol-induced cloud parameters (implicit aerosol correction). Compared to the implicit aerosol correction through the CRB cloud parameters, the use of CAL reduces the AMF errors by more than 10 %. Finally, to evaluate the improved GOME-2 tropospheric NO2 columns, a validation is performed using ground-based Multi-AXis Differential Optical Absorption Spectroscopy (MAXDOAS) measurements at the BIRA-IASB Xianghe station. The improved tropospheric NO2 dataset shows good agreement with coincident ground-based measurements with a correlation coefficient of 0.94 and a relative difference of −9.9 % on average.

scholarly journals An improved TROPOMI tropospheric NO<sub>2</sub> research product over Europe

2021 ◽  
Vol 14 (11) ◽  
pp. 7297-7327
Author(s):  
Song Liu ◽  
Pieter Valks ◽  
Gaia Pinardi ◽  
Jian Xu ◽  
Ka Lok Chan ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Transport Model ◽  
A Priori ◽  
Relative Difference ◽  
Point Sources ◽  
Optical Absorption Spectroscopy ◽  
Retrieval Algorithm ◽  
Chemistry Transport Model ◽  
Total Uncertainty ◽  
Tropospheric No2

Abstract. Launched in October 2017, the TROPOspheric Monitoring Instrument (TROPOMI) aboard Sentinel-5 Precursor provides the potential to monitor air quality over point sources across the globe with a spatial resolution as high as 5.5 km × 3.5 km (7 km × 3.5 km before 6 August 2019). The DLR nitrogen dioxide (NO2) retrieval algorithm for the TROPOMI instrument consists of three steps: the spectral fitting of the slant column, the separation of stratospheric and tropospheric contributions, and the conversion of the slant column to a vertical column using an air mass factor (AMF) calculation. In this work, an improved DLR tropospheric NO2 retrieval algorithm from TROPOMI measurements over Europe is presented. The stratospheric estimation is implemented using the STRatospheric Estimation Algorithm from Mainz (STREAM), which was developed as a verification algorithm for TROPOMI and does not require chemistry transport model data as input. A directionally dependent STREAM (DSTREAM) is developed to correct for the dependency of the stratospheric NO2 on the viewing geometry by up to 2×1014 molec./cm2. Applied to synthetic TROPOMI data, the uncertainty in the stratospheric column is 3.5×1014 molec./cm2 in the case of significant tropospheric sources. Applied to actual measurements, the smooth variation of stratospheric NO2 at low latitudes is conserved, and stronger stratospheric variation at higher latitudes is captured. For AMF calculation, the climatological surface albedo data are replaced by geometry-dependent effective Lambertian equivalent reflectivity (GE_LER) obtained directly from TROPOMI measurements with a high spatial resolution. Mesoscale-resolution a priori NO2 profiles are obtained from the regional POLYPHEMUS/DLR chemistry transport model with the TNO-MACC emission inventory. Based on the latest TROPOMI operational cloud parameters, a more realistic cloud treatment is provided by a Clouds-As-Layers (CAL) model, which treats the clouds as uniform layers of water droplets, instead of the Clouds-As-Reflecting-Boundaries (CRB) model, in which clouds are simplified as Lambertian reflectors. For the error analysis, the tropospheric AMF uncertainty, which is the largest source of NO2 uncertainty for polluted scenarios, ranges between 20 % and 50 %, leading to a total uncertainty in the tropospheric NO2 column in the 30 %–60 % range. From a validation performed with ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements, the new DLR tropospheric NO2 data show good correlations for nine European urban/suburban stations, with an average correlation coefficient of 0.78. The implementation of the algorithm improvements leads to a decrease of the relative difference from −55.3 % to −34.7 % on average in comparison with the DLR reference retrieval. When the satellite averaging kernels are used to remove the contribution of a priori profile shape, the relative difference decreases further to ∼ −20 %.

scholarly journals Top-Down NOX Emissions of European Cities Based on the Downwind Plume of Modelled and Space-Borne Tropospheric NO2 Columns

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2893 ◽  
Author(s):  
Willem W. Verstraeten ◽  
Klaas Folkert Boersma ◽  
John Douros ◽  
Jason E. Williams ◽  
Henk Eskes ◽  
...  
Keyword(s):  
Urban Areas ◽  
Transport Model ◽  
Nox Emissions ◽  
Inventory Data ◽  
Ozone Monitoring Instrument ◽  
Top Down ◽  
Chemistry Transport Model ◽  
European Cities ◽  
Tropospheric No2

Top-down estimates of surface NOX emissions were derived for 23 European cities based on the downwind plume decay of tropospheric nitrogen dioxide (NO2) columns from the LOTOS-EUROS (Long Term Ozone Simulation-European Ozone Simulation) chemistry transport model (CTM) and from Ozone Monitoring Instrument (OMI) satellite retrievals, averaged for the summertime period (April–September) during 2013. Here we show that the top-down NOX emissions derived from LOTOS-EUROS for European urban areas agree well with the bottom-up NOX emissions from the MACC-III inventory data (R2 = 0.88) driving the CTM demonstrating the potential of this method. OMI top-down NOX emissions over the 23 European cities are generally lower compared with the MACC-III emissions and their correlation is slightly lower (R2 = 0.79). The uncertainty on the derived NO2 lifetimes and NOX emissions are on average ~55% for OMI and ~63% for LOTOS-EUROS data. The downwind NO2 plume method applied on both LOTOS-EUROS and OMI tropospheric NO2 columns allows to estimate NOX emissions from urban areas, demonstrating that this is a useful method for real-time updates of urban NOX emissions with reasonable accuracy.

scholarly journals Description of a formaldehyde retrieval algorithm for the Geostationary Environment Monitoring Spectrometer (GEMS)

2019 ◽  
Vol 12 (7) ◽  
pp. 3551-3571 ◽  
Author(s):  
Hyeong-Ahn Kwon ◽  
Rokjin J. Park ◽  
Gonzalo González Abad ◽  
Kelly Chance ◽  
Thomas P. Kurosu ◽  
...  
Keyword(s):  
Optical Absorption ◽  
Absorption Spectroscopy ◽  
Cross Sections ◽  
Correlation Coefficients ◽  
Optical Absorption Spectroscopy ◽  
Retrieval Algorithm ◽  
Environment Monitoring ◽  
Ozone Monitoring Instrument ◽  
Nonlinear Fitting ◽  
Regression Slopes

Abstract. We describe a formaldehyde (HCHO) retrieval algorithm for the Geostationary Environment Monitoring Spectrometer (GEMS) that will be launched by the Korean Ministry of Environment in 2019. The algorithm comprises three steps: preprocesses, radiance fitting, and postprocesses. The preprocesses include a wavelength calibration, as well as interpolation and convolution of absorption cross sections; radiance fitting is conducted using a nonlinear fitting method referred to as basic optical absorption spectroscopy (BOAS); and postprocesses include air mass factor calculations and bias corrections. In this study, several sensitivity tests are conducted to examine the retrieval uncertainties using the GEMS HCHO algorithm. We evaluate the algorithm with the Ozone Monitoring Instrument (OMI) Level 1B irradiance/radiance data by comparing our retrieved HCHO column densities with OMI HCHO products of the Smithsonian Astrophysical Observatory (OMHCHO) and of the Quality Assurance for Essential Climate Variables project (OMI QA4ECV). Results show that OMI HCHO slant columns retrieved using the GEMS algorithm are in good agreement with OMHCHO, with correlation coefficients of 0.77–0.91 and regression slopes of 0.94–1.04 for March, June, September, and December 2005. Spatial distributions of HCHO slant columns from the GEMS algorithm are consistent with the OMI QA4ECV products, but relatively poorer correlation coefficients of 0.52–0.76 are found compared to those against the OMHCHO products. Also, we compare the satellite results with ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) observations. OMI GEMS HCHO vertical columns are 9 %–25 % lower than those of MAX-DOAS at Haute-Provence Observatory (OHP) in France, Bremen in Germany, and Xianghe in China. We find that the OMI GEMS retrievals have less bias than the OMHCHO and OMI QA4ECV products at OHP and Bremen in comparison with MAX-DOAS.

scholarly journals Long-term MAX-DOAS network observations of NO<sub>2</sub> in Russia and Asia (MADRAS) during the period 2007–2012: instrumentation, elucidation of climatology, and comparisons with OMI satellite observations and global model simulations

2014 ◽  
Vol 14 (15) ◽  
pp. 7909-7927 ◽  
Author(s):  
Y. Kanaya ◽  
H. Irie ◽  
H. Takashima ◽  
H. Iwabuchi ◽  
H. Akimoto ◽  
...  
Keyword(s):  
Satellite Data ◽  
Transport Model ◽  
Satellite Observations ◽  
Global Model ◽  
Optical Absorption Spectroscopy ◽  
Ozone Monitoring Instrument ◽  
Vertical Column ◽  
Data Set ◽  
Model Simulations

Abstract. We conducted long-term network observations using standardized Multi-Axis Differential optical absorption spectroscopy (MAX-DOAS) instruments in Russia and ASia (MADRAS) from 2007 onwards and made the first synthetic data analysis. At seven locations (Cape Hedo, Fukue and Yokosuka in Japan, Hefei in China, Gwangju in Korea, and Tomsk and Zvenigorod in Russia) with different levels of pollution, we obtained 80 927 retrievals of tropospheric NO2 vertical column density (TropoNO2VCD) and aerosol optical depth (AOD). In the technique, the optimal estimation of the TropoNO2VCD and its profile was performed using aerosol information derived from O4 absorbances simultaneously observed at 460–490 nm. This large data set was used to analyze NO2 climatology systematically, including temporal variations from the seasonal to the diurnal scale. The results were compared with Ozone Monitoring Instrument (OMI) satellite observations and global model simulations. Two NO2 retrievals of OMI satellite data (NASA ver. 2.1 and Dutch OMI NO2 (DOMINO) ver. 2.0) generally showed close correlations with those derived from MAX-DOAS observations, but had low biases of up to ~50%. The bias was distinct when NO2 was abundantly present near the surface and when the AOD was high, suggesting a possibility of incomplete accounting of NO2 near the surface under relatively high aerosol conditions for the satellite observations. Except for constant biases, the satellite observations showed nearly perfect seasonal agreement with MAX-DOAS observations, suggesting that the analysis of seasonal features of the satellite data were robust. Weekend reduction in the TropoNO2VCD found at Yokosuka and Gwangju was absent at Hefei, implying that the major sources had different weekly variation patterns. While the TropoNO2VCD generally decreased during the midday hours, it increased exceptionally at urban/suburban locations (Yokosuka, Gwangju, and Hefei) during winter. A global chemical transport model, MIROC-ESM-CHEM (Model for Interdisciplinary Research on Climate–Earth System Model–Chemistry), was validated for the first time with respect to background NO2 column densities during summer at Cape Hedo and Fukue in the clean marine atmosphere.

scholarly journals A Retrieval of Glyoxal from OMI over China: Investigation of the Effects of Tropospheric NO2

2019 ◽  
Vol 11 (2) ◽  
pp. 137 ◽  
Author(s):  
Yapeng Wang ◽  
Jinhua Tao ◽  
Liangxiao Cheng ◽  
Chao Yu ◽  
Zifeng Wang ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Temporal Distribution ◽  
Temporal Variations ◽  
Mean Value ◽  
River Delta ◽  
Optical Absorption Spectroscopy ◽  
Synthetic Spectrum ◽  
Ozone Monitoring Instrument ◽  
Tropospheric No2 ◽  
Fitting Parameters

East China is the ‘hotspot’ of glyoxal (CHOCHO), especially over the Pearl River Delta (PRD) region, where glyoxal is yielded from the oxidation of aromatics. To better understand the glyoxal spatial-temporal characteristics over China and evaluate the effectiveness of atmospheric prevention efforts on the reduction of volatile organic compound (VOC) emissions, we present an algorithm for glyoxal retrieval using the Ozone Monitoring instrument (OMI) over China. The algorithm is based on the differential optical absorption spectroscopy (DOAS) and accounts for the interference of the tropospheric nitrogen dioxide (NO2) spatial-temporal distribution on glyoxal retrieval. We conduct a sensitively test based on a synthetic spectrum to optimize the fitting parameters set. It shows that the fitting interval of 430–458 nm and a 4th order polynomial are optimal for glyoxal retrieval when using the daily mean value of the earthshine spectrum in the Pacific region as a reference. In addition, tropospheric NO2 pre-fitted during glyoxal retrieval is first proposed and tested, which shows a ±10% variation compared with the reference scene. The interference of NO2 on glyoxal was further investigated based on the OMI observations, and the spatial distribution showed that changes in the NO2 concentration can affect the glyoxal result depending on the NO2 spatial distribution. A method to prefix NO2 during glyoxal retrieval is proposed in this study and is referred to as OMI-CAS. We perform an intercomparison of the glyoxal from the OMI-CAS with the seasonal datasets provided by different institutions for North China (NC), South China (SC), the Yangtze River Delta (YRD) and the ChuanYu (CY) region in southwestern China in the year 2005. The results show that our algorithm can obtain the glyoxal spatial and temporal variations in different regions over China. OMI-CAS has the best correlations with other datasets in summer, with the correlations between OMI-CAS and OMI-Harvard, OMI-CAS and OMI-IUP, and OMI-CAS and Sciamachy-IUP being 0.63, 0.67 and 0.67, respectively. Autumn results followed, with the correlations of 0.58, 0.36 and 0.48, respectively, over China. However, the correlations are less or even negative for spring and winter. From the regional perspective, SC has the best correlation compared with other regions, with R reaching 0.80 for OMI-CAS and OMI-IUP in summer. The discrepancies between different glyoxal datasets can be attributed to the fitting parameters and larger glyoxal retrieval uncertainties. Finally, useful recommendations are given based on the results comparison according to region and season.

scholarly journals Operational total and tropospheric NO<sub>2</sub> column retrieval for GOME-2

2011 ◽  
Vol 4 (7) ◽  
pp. 1491-1514 ◽  
Author(s):  
P. Valks ◽  
G. Pinardi ◽  
A. Richter ◽  
J.-C. Lambert ◽  
N. Hao ◽  
...  
Keyword(s):  
Atmospheric Chemistry ◽  
Transport Model ◽  
Optical Absorption Spectroscopy ◽  
Chemistry Transport Model ◽  
Air Mass ◽  
Cloud Properties ◽  
The Pacific ◽  
Tropospheric No2 ◽  
Data Processor ◽  
Radiance Data

Abstract. This paper presents the algorithm for the operational near real time retrieval of total and tropospheric NO2 columns from the Global Ozone Monitoring Experiment (GOME-2). The retrieval is performed with the GOME Data Processor (GDP) version 4.4 as used by the EUMETSAT Satellite Application Facility on Ozone and Atmospheric Chemistry Monitoring (O3M-SAF). The differential optical absorption spectroscopy (DOAS) method is used to determine NO2 slant columns from GOME-2 (ir)radiance data in the 425–450 nm range. Initial total NO2 columns are computed using stratospheric air mass factors, and GOME-2 derived cloud properties are used to calculate the air mass factors for scenarios in the presence of clouds. To obtain the stratospheric NO2 component, a spatial filtering approach is used, which is shown to be an improvement on the Pacific reference sector method. Tropospheric air mass factors are computed using monthly averaged NO2 profiles from the MOZART-2 chemistry transport model. An error analysis shows that the random error in the GOME-2 NO2 slant columns is approximately 0.45 × 1015 molec cm−2. As a result of the improved quartz diffuser plate used in the GOME-2 instrument, the systematic error in the slant columns is strongly reduced compared to GOME/ERS-2. The estimated uncertainty in the GOME-2 tropospheric NO2 column for polluted conditions ranges from 40 to 80 %. An end-to-end ground-based validation approach for the GOME-2 NO2 columns is illustrated based on multi-axis MAXDOAS measurements at the Observatoire de Haute Provence (OHP). The GOME-2 stratospheric NO2 columns are found to be in good overall agreement with coincident ground-based measurements at OHP. A time series of the MAXDOAS and the GOME-2 tropospheric NO2 columns shows that pollution episodes at OHP are well captured by GOME-2. Monthly mean tropospheric columns are in very good agreement, with differences generally within 0.5 × 1015 molec cm−2.

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