Monitoring of atmospheric nitrogen dioxide using Ozone Monitoring Instrument remote sensing data

Abstract. We present a new and improved version (V4.0) of the NASA standard nitrogen dioxide (NO2) product from the Ozone Monitoring Instrument (OMI) on the Aura satellite. This version incorporates the most salient improvements for OMI NO2 products suggested by expert users and enhances the NO2 data quality in several ways through improvements to the air mass factors (AMFs) used in the retrieval algorithm. The algorithm is based on the geometry-dependent surface Lambertian equivalent reflectivity (GLER) operational product that is available on an OMI pixel basis. GLER is calculated using the vector linearized discrete ordinate radiative transfer (VLIDORT) model, which uses as input high-resolution bidirectional reflectance distribution function (BRDF) information from NASA's Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) instruments over land and the wind-dependent Cox–Munk wave-facet slope distribution over water, the latter with a contribution from the water-leaving radiance. The GLER combined with consistently retrieved oxygen dimer (O2–O2) absorption-based effective cloud fraction (ECF) and optical centroid pressure (OCP) provide improved information to the new NO2 AMF calculations. The new AMFs increase the retrieved tropospheric NO2 by up to 50 % in highly polluted areas; these differences arise from both cloud and surface BRDF effects as well as biases between the new MODIS-based and previously used OMI-based climatological surface reflectance data sets. We quantitatively evaluate the new NO2 product using independent observations from ground-based and airborne instruments. The new V4.0 data and relevant explanatory documentation are publicly available from the NASA Goddard Earth Sciences Data and Information Services Center (https://disc.gsfc.nasa.gov/datasets/OMNO2_V003/summary/, last access: 8 November 2020), and we encourage their use over previous versions of OMI NO2 products.

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Ozone profile climatology for remote sensing retrieval algorithms

Atmospheric Measurement Techniques ◽

10.5194/amt-12-4745-2019 ◽

2019 ◽

Vol 12 (9) ◽

pp. 4745-4778 ◽

Cited By ~ 1

Author(s):

Kai Yang ◽

Xiong Liu

Keyword(s):

Remote Sensing ◽

A Priori ◽

Uv Spectra ◽

Empirical Orthogonal Functions ◽

Ozone Monitoring Instrument ◽

Orthogonal Functions ◽

Monitoring Instrument ◽

Retrieval Algorithms ◽

Ozone Monitoring ◽

Priori Information

Abstract. New ozone (O3) profile climatologies are created from the Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2) O3 record between 2005 and 2016, within the period of Aura Microwave Limb Sounder (MLS) and Aura Ozone Monitoring Instrument (OMI) assimilation. These two climatologies consist of monthly mean O3 profiles and the corresponding covariances dependent on the local solar time, longitude (15∘), and latitude (10∘), which are parameterized by tropopause pressure and total O3 column. They are validated through comparisons, which show good agreements with previous O3 profile climatologies. Compared to a monthly zonal mean climatology, both tropopause- and column-dependent climatologies provide improved a priori information for profile and total O3 retrievals from remote sensing measurements. Furthermore, parameterization of the O3 profile with total column O3 usually reduces the natural variability of the resulting climatological profile in the upper stratosphere further than the tropopause parameterization, which usually performs better in the upper troposphere and lower stratosphere (UTLS). Therefore tropopause-dependent climatology is more appropriate for profile O3 retrieval for complementing the vertical resolution of backscattered ultraviolet (UV) spectra, while the column-dependent climatology is more suited for use in total O3 retrieval algorithms, with an advantage of complete profile specification without requiring ancillary information. Compared to previous column-dependent climatologies, the new MERRA-2 column-dependent climatology better captures the diurnal, seasonal, and spatial variations and dynamical changes in O3 profiles with higher resolutions in O3, latitude, longitude, and season. The new MERRA-2 climatologies contain the first quantitative characterization of O3 profile covariances, which facilitate a new approach to improve O3 profiles using the most probable patterns of profile adjustments represented by the empirical orthogonal functions (EOFs) of the covariance matrices. The MERRA-2 daytime column-dependent climatology is used in the combo O3 and SO2 algorithm for retrieval from the Earth Polychromatic Imaging Camera (EPIC) on board the Deep Space Climate Observatory (DSCOVR) satellite, the Ozone Mapping and Profiler Suite Nadir Mapper (OMPS-NM) on the Suomi National Polar Partnership (SNPP), and the Ozone Monitoring Instrument (OMI) on the Aura spacecraft.

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Validation of Ozone Monitoring Instrument nitrogen dioxide columns

Journal of Geophysical Research Atmospheres ◽

10.1029/2007jd008908 ◽

2008 ◽

Vol 113 (D15) ◽

Cited By ~ 156

Author(s):

E. A. Celarier ◽

E. J. Brinksma ◽

J. F. Gleason ◽

J. P. Veefkind ◽

A. Cede ◽

...

Keyword(s):

Nitrogen Dioxide ◽

Ozone Monitoring Instrument ◽

Monitoring Instrument ◽

Ozone Monitoring

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The impact of the 2005 Gulf hurricanes on pollution emissions as inferred from Ozone Monitoring Instrument (OMI) nitrogen dioxide

Atmospheric Environment ◽

10.1016/j.atmosenv.2010.01.037 ◽

2010 ◽

Vol 44 (11) ◽

pp. 1443-1448 ◽

Cited By ~ 5

Author(s):

Yasuko Yoshida ◽

Bryan N. Duncan ◽

Christian Retscher ◽

Kenneth E. Pickering ◽

Edward A. Celarier ◽

...

Keyword(s):

Nitrogen Dioxide ◽

Ozone Monitoring Instrument ◽

Monitoring Instrument ◽

Ozone Monitoring ◽

Pollution Emissions ◽

The Impact

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Revising the slant column density retrieval of nitrogen dioxide observed by the Ozone Monitoring Instrument

Journal of Geophysical Research Atmospheres ◽

10.1002/2014jd022913 ◽

2015 ◽

Vol 120 (11) ◽

pp. 5670-5692 ◽

Cited By ~ 43

Author(s):

S. Marchenko ◽

N. A. Krotkov ◽

L. N. Lamsal ◽

E. A. Celarier ◽

W. H. Swartz ◽

...

Keyword(s):

Nitrogen Dioxide ◽

Column Density ◽

Ozone Monitoring Instrument ◽

Monitoring Instrument ◽

Ozone Monitoring

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Retrieving tropospheric nitrogen dioxide from the Ozone Monitoring Instrument: effects of aerosols, surface reflectance anisotropy, and vertical profile of nitrogen dioxide

Atmospheric Chemistry and Physics ◽

10.5194/acp-14-1441-2014 ◽

2014 ◽

Vol 14 (3) ◽

pp. 1441-1461 ◽

Cited By ~ 113

Author(s):

J.-T. Lin ◽

R. V. Martin ◽

K. F. Boersma ◽

M. Sneep ◽

P. Stammes ◽

...

Keyword(s):

Nitrogen Dioxide ◽

Vertical Profile ◽

Measurement Errors ◽

Surface Reflectance ◽

Ozone Monitoring Instrument ◽

Monitoring Instrument ◽

Reflectance Anisotropy ◽

Cloud Properties ◽

Optical Effects ◽

Ozone Monitoring

Abstract. Retrievals of tropospheric nitrogen dioxide (NO2) from the Ozone Monitoring Instrument (OMI) are subject to errors in the treatments of aerosols, surface reflectance anisotropy, and vertical profile of NO2. Here we quantify the influences over China via an improved retrieval process. We explicitly account for aerosol optical effects (simulated by nested GEOS-Chem at 0.667° long. × 0.5° lat. and constrained by aerosol measurements), surface reflectance anisotropy, and high-resolution vertical profiles of NO2 (simulated by GEOS-Chem). Prior to the NO2 retrieval, we derive the cloud information using consistent ancillary assumptions. We compare our retrieval to the widely used DOMINO v2 product, using MAX-DOAS measurements at three urban/suburban sites in East China as reference and focusing the analysis on the 127 OMI pixels (in 30 days) closest to the MAX-DOAS sites. We find that our retrieval reduces the interference of aerosols on the retrieved cloud properties, thus enhancing the number of valid OMI pixels by about 25%. Compared to DOMINO v2, our retrieval better captures the day-to-day variability in MAX-DOAS NO2 data (R2 = 0.96 versus 0.72), due to pixel-specific radiative transfer calculations rather than the use of a look-up table, explicit inclusion of aerosols, and consideration of surface reflectance anisotropy. Our retrieved NO2 columns are 54% of the MAX-DOAS data on average, reflecting the inevitable spatial inconsistency between the two types of measurement, errors in MAX-DOAS data, and uncertainties in our OMI retrieval related to aerosols and vertical profile of NO2. Sensitivity tests show that excluding aerosol optical effects can either increase or decrease the retrieved NO2 for individual OMI pixels with an average increase by 14%. Excluding aerosols also complexly affects the retrievals of cloud fraction and particularly cloud pressure. Employing various surface albedo data sets slightly affects the retrieved NO2 on average (within 10%). The retrieved NO2 columns increase when the NO2 profiles are taken from MAX-DOAS retrievals (by 19% on average) or TM4 simulations (by 13%) instead of GEOS-Chem simulations. Our findings are also relevant to retrievals of other pollutants (e.g., sulfur dioxide, ormaldehyde, glyoxal) from UV–visible backscatter satellite instruments.

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Retrieving tropospheric nitrogen dioxide over China from the Ozone Monitoring Instrument: effects of aerosols, surface reflectance anisotropy and vertical profile of nitrogen dioxide

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-13-21203-2013 ◽

2013 ◽

Vol 13 (8) ◽

pp. 21203-21257 ◽

Cited By ~ 3

Author(s):

J.-T. Lin ◽

R. V. Martin ◽

K. F. Boersma ◽

M. Sneep ◽

P. Stammes ◽

...

Keyword(s):

Nitrogen Dioxide ◽

Vertical Profile ◽

Absolute Difference ◽

Surface Reflectance ◽

Ozone Monitoring Instrument ◽

Mean Absolute Difference ◽

Monitoring Instrument ◽

Reflectance Anisotropy ◽

Cloud Properties ◽

Ozone Monitoring

Abstract. Retrievals of tropospheric nitrogen dioxide (NO2) from the Ozone Monitoring Instrument (OMI) are subject to errors in the treatments of aerosols, surface reflectance anisotropy, and vertical profile of NO2. Here we quantify the influences over China via an improved retrieval process. We explicitly account for aerosol optical effects (simulated by nested GEOS-Chem at 0.667° lon × 0.5° lat and constrained by aerosol measurements), surface reflectance anisotropy, and high-resolution vertical profiles of NO2 (simulated by GEOS-Chem). Prior to the NO2 retrieval, we derive the cloud information using consistent ancillary assumptions. We compare our retrieval to the widely used DOMINO v2 product, using as reference MAX-DOAS measurements at three urban/suburban sites in East China and focusing the analysis on the 127 OMI pixels (in 30 days) closest to the MAX-DOAS sites. We find that our retrieval reduces the interference of aerosols on the retrieved cloud properties, thus enhancing the number of valid OMI pixels by about 25%. Compared to DOMINO v2, our retrieval improves the correlation with the MAX-DOAS data in the day-to-day variability of NO2 (R2 = 0.96 vs. 0.72). Our retrieved NO2 columns are about 50% of the MAX-DOAS data on average. This reflects the inevitable spatial inconsistency between the two types of measurement, uncertainties in MAX-DOAS data, and residual uncertainties in our OMI retrievals related to aerosols and vertical profile of NO2. Through a series of tests, we find that excluding aerosol scattering/absorption can either increase or decrease the retrieved NO2, with a mean absolute difference by about 20%. Concentrating aerosols at the boundary layer top enhances the retrieved NO2 by 8% on average with a mean absolute difference by 23%. The aerosol perturbations also affect nonlinearly the retrieved cloud fraction and particularly cloud pressure. Employing various surface albedo datasets alters the retrieved NO2 by 0–7% on average. The retrieved NO2 columns increase when the NO2 profiles are taken from MAX-DOAS retrievals (by 20% on average) or TM4 simulations (by 10%) instead of GEOS-Chem simulations. Our findings are also relevant to retrievals of other pollutants (e.g., sulfur dioxide, formaldehyde, glyoxal) from UV-vis backscatter satellite instruments.

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Dynamics of nitrogen dioxide in the atmosphere of Kazakhstan based on ground observations and remote sensing data

Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa ◽

10.21046/2070-7401-2020-17-2-245-251 ◽

2020 ◽

Vol 17 (2) ◽

pp. 245-251

Author(s):

A.Kh. Akhmedzhanov ◽

◽

T.K. Karadanov ◽

Keyword(s):

Remote Sensing ◽

Nitrogen Dioxide ◽

Remote Sensing Data ◽

Sensing Data

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Ozone Profile Climatology for Remote Sensing Retrieval Algorithms

10.5194/amt-2019-116 ◽

2019 ◽

Author(s):

Kai Yang ◽

Xiong Liu

Keyword(s):

Remote Sensing ◽

A Priori ◽

Uv Spectra ◽

Empirical Orthogonal Functions ◽

Ozone Monitoring Instrument ◽

Orthogonal Functions ◽

Monitoring Instrument ◽

Retrieval Algorithms ◽

Ozone Monitoring ◽

Priori Information

Abstract. New ozone (O3) profile climatologies are created from the Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2) O3 record between 2005 and 2016, within the period of Aura Microwave Limb Sounder (MLS) and Aura Ozone Monitoring Instrument (OMI) assimilation. These two climatologies consist of local solar time, longitudinal (15°), and latitudinal (10°) dependent monthly mean O3 profiles and the corresponding covariances, which are parameterized respectively by tropopause pressure and total O3 column. They are validated through comparisons, which show good agreements with previous O3 profile climatologies. Compared to a monthly zonal mean climatology, both tropopause- and column-dependent climatologies provide improved a priori information for profile and total O3 retrievals from remote sensing measurements. Furthermore, parameterization of O3 profile with total column usually reduces the natural variability of the resulting climatological profile in the upper stratosphere further than the tropopause parameterization, which usually performs better in the upper troposphere and lower stratosphere (UTLS). Therefore tropopause-dependent climatology is more appropriate for profile O3 retrieval for complementing the vertical resolution of backscattered ultraviolet (UV) spectra, while the column-dependent climatology is more suited for use in total O3 retrieval algorithms, with an advantage of complete profile specification without requiring ancillary information. Compared to previous column-dependent climatologies, the new MERRA-2 column-dependent climatology better capture the diurnal, seasonal, and spatial variations and dynamical changes of O3 profiles with higher resolutions in O3, latitude, longitude, and season. The new MERRA-2 climatologies contain first quantitative characterization of O3 profile covariances, which facilitate a new approach to improve O3 profiles using the most probable patterns of profile adjustments represented by the empirical orthogonal functions (EOFs) of the covraniance matrices. The MERRA-2 daytime column-dependent climatology is used in the combo O3 and SO2 algorithm for retrieval from the Earth Polychromatic Imaging Camera (EPIC) onboard the Deep Space Climate Observatory (DSCOVR) satellite, the Ozone Mapping and Profiler Suite Nadir Mapper (OMPS-NM) on the Suomi National Polar Partnership (SNPP), and the Ozone Monitoring Instrument (OMI) on the Aura spacecraft.

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