scholarly journals Sulfur dioxide vertical column DOAS retrievals from the Ozone Monitoring Instrument: Global observations and comparison to ground-based and satellite data

2015 ◽  
Vol 120 (6) ◽  
pp. 2470-2491 ◽  
Author(s):  
N. Theys ◽  
I. De Smedt ◽  
J. van Gent ◽  
T. Danckaert ◽  
T. Wang ◽  
...  
Keyword(s):  
Sulfur Dioxide ◽  
Satellite Data ◽  
Ozone Monitoring Instrument ◽  
Vertical Column ◽  
Monitoring Instrument ◽  
Ozone Monitoring

Algorithm for NO/sub 2/ vertical column retrieval from the ozone monitoring instrument

2006 ◽  
Vol 44 (5) ◽  
pp. 1245-1258 ◽  
Author(s):  
E.J. Bucsela ◽  
E.A. Celarier ◽  
M.O. Wenig ◽  
J.F. Gleason ◽  
J.P. Veefkind ◽  
...  
Keyword(s):  
Ozone Monitoring Instrument ◽  
Vertical Column ◽  
Monitoring Instrument ◽  
Ozone Monitoring

scholarly journals First estimates of global free-tropospheric NO<sub>2</sub> abundances derived using a cloud-slicing technique applied to satellite observations from the Aura Ozone Monitoring Instrument (OMI)

2014 ◽  
Vol 14 (19) ◽  
pp. 10565-10588 ◽  
Author(s):  
S. Choi ◽  
J. Joiner ◽  
Y. Choi ◽  
B. N. Duncan ◽  
A. Vasilkov ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Profile Analysis ◽  
Middle Latitude ◽  
Optical Absorption Spectroscopy ◽  
Ozone Monitoring Instrument ◽  
Vertical Column ◽  
Monitoring Instrument ◽  
Single Orbit ◽  
Tropospheric No2 ◽  
Ozone Monitoring

Abstract. We derive free-tropospheric NO2 volume mixing ratios (VMRs) by applying a cloud-slicing technique to data from the Ozone Monitoring Instrument (OMI) on the Aura satellite. In the cloud-slicing approach, the slope of the above-cloud NO2 column versus the cloud scene pressure is proportional to the NO2 VMR. In this work, we use a sample of nearby OMI pixel data from a single orbit for the linear fit. The OMI data include cloud scene pressures from the rotational-Raman algorithm and above-cloud NO2 vertical column density (VCD) (defined as the NO2 column from the cloud scene pressure to the top of the atmosphere) from a differential optical absorption spectroscopy (DOAS) algorithm. We compare OMI-derived NO2 VMRs with in situ aircraft profiles measured during the NASA Intercontinental Chemical Transport Experiment Phase B (INTEX-B) campaign in 2006. The agreement is generally within the estimated uncertainties when appropriate data screening is applied. We then derive a global seasonal climatology of free-tropospheric NO2 VMR in cloudy conditions. Enhanced NO2 in the free troposphere commonly appears near polluted urban locations where NO2 produced in the boundary layer may be transported vertically out of the boundary layer and then horizontally away from the source. Signatures of lightning NO2 are also shown throughout low and middle latitude regions in summer months. A profile analysis of our cloud-slicing data indicates signatures of lightning-generated NO2 in the upper troposphere. Comparison of the climatology with simulations from the global modeling initiative (GMI) for cloudy conditions (cloud optical depth > 10) shows similarities in the spatial patterns of continental pollution outflow. However, there are also some differences in the seasonal variation of free-tropospheric NO2 VMRs near highly populated regions and in areas affected by lightning-generated NOx.

scholarly journals Version 2 Ozone Monitoring Instrument SO<sub>2</sub> Product (OMSO2 V2): New Anthropogenic SO<sub>2</sub> Vertical Column Density Dataset

2020 ◽  
Author(s):  
Can Li ◽  
Nickolay A. Krotkov ◽  
Peter J. T. Leonard ◽  
Simon Carn ◽  
Joanna Joiner ◽  
...  
Keyword(s):  
Column Density ◽  
A Priori ◽  
Principal Component ◽  
Ozone Monitoring Instrument ◽  
Vertical Column ◽  
Monitoring Instrument ◽  
Spectral Fitting ◽  
Vertical Column Density ◽  
Ozone Monitoring ◽  
So2 Pollution

Abstract. The Ozone Monitoring Instrument (OMI) has been providing global observations of SO2 pollution since 2004. Here we introduce the new anthropogenic SO2 vertical column density (VCD) dataset in the version 2 OMI SO2 product (OMSO2 V2). As with the previous version (OMSO2 V1.3), the new dataset is generated with an algorithm based on principal component analysis of OMI radiances, but features several updates. The most important among those is the use of expanded lookup tables and model a priori profiles to estimate SO2 Jacobians for individual OMI pixels, in order to better characterize pixel-to-pixel variations in SO2 sensitivity, including over snow and ice. Additionally, new data screening and spectral fitting schemes have been implemented to improve the quality of the spectral fit. As compared with the planetary boundary layer SO2 dataset in OMSO2 V1.3, the new dataset has substantially better data quality, especially over areas that are relatively clean or affected by the south Atlantic anomaly. The updated retrievals over snow/ice yield more realistic seasonal changes in SO2 at high latitudes and offer enhanced sensitivity to sources during wintertime. An error analysis has been conducted to assess uncertainties in SO2 VCDs from both the spectral fit and Jacobian calculations. The uncertainties from spectral fitting are reflected in SO2 slant column densities (SCDs) and largely depend on the signal-to-noise ratio of the measured radiances, as implied by the generally smaller SCD uncertainties over clouds or for lower solar zenith angles. The SCD uncertainties for individual pixels are estimated to be ~ 0.15–0.3 DU (Dobson Units) between ~ 40° S and ~ 40° N and to be ~ 0.2–0.5 DU at higher latitudes. The uncertainties from the Jacobians are approximately ~ 50–100 % over polluted areas, and primarily attributed to errors in SO2 a priori profiles and cloud pressures, as well as the lack of explicit treatment for aerosols. Finally, the daily mean and median SCDs over the presumably SO2-free equatorial East Pacific have increased by only ~ 0.0035 DU and ~ 0.003 DU respectively over the entire 15-year OMI record; while the standard deviation of SCDs has grown by only ~ 0.02 DU or ~ 10 %. Such remarkable long-term stability makes the new dataset particularly suitable for detecting regional changes in SO2 pollution.

scholarly journals Evaluation of Redoubt Volcano's sulfur dioxide emissions by the Ozone Monitoring Instrument

2013 ◽  
Vol 259 ◽  
pp. 290-307 ◽  
Author(s):  
Taryn Lopez ◽  
Simon Carn ◽  
Cynthia Werner ◽  
David Fee ◽  
Peter Kelly ◽  
...  
Keyword(s):  
Sulfur Dioxide ◽  
Ozone Monitoring Instrument ◽  
Monitoring Instrument ◽  
Sulfur Dioxide Emissions ◽  
Ozone Monitoring

scholarly journals Extended observations of volcanic SO<sub>2</sub> and sulfate aerosol in the stratosphere

2007 ◽  
Vol 7 (1) ◽  
pp. 2857-2871 ◽  
Author(s):  
S. A. Carn ◽  
N. A. Krotkov ◽  
K. Yang ◽  
R. M. Hoff ◽  
A. J. Prata ◽  
...  
Keyword(s):  
Climate Change ◽  
Sulfur Dioxide ◽  
Satellite Data ◽  
Volcanic Eruptions ◽  
Sulfate Aerosol ◽  
Satellite Observations ◽  
Ozone Monitoring Instrument ◽  
Ozone Monitoring ◽  
Composition Structure ◽  
Stratospheric Composition

Abstract. Sulfate aerosol produced after injection of sulfur dioxide (SO2) into the stratosphere by volcanic eruptions can trigger climate change. We present new satellite data from the Ozone Monitoring Instrument (OMI) and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) missions that reveal the composition, structure and longevity of a stratospheric SO2 cloud and derived sulfate layer following a modest eruption (0.2 Tg total SO2) of Soufriere Hills volcano, Montserrat on 20 May 2006. The SO2 cloud alone was tracked for over 3 weeks and a distance of over 20 000 km; unprecedented for an eruption of this size. Derived sulfate aerosol at an altitude of ~20 km had circled the globe by 22 June and remained visible in CALIPSO data until at least 6 July. These synergistic NASA A-Train observations permit a new appreciation of the potential effects of frequent, small-to-moderate volcanic eruptions on stratospheric composition and climate.

scholarly journals Version 2 Ozone Monitoring Instrument SO<sub>2</sub> product (OMSO2 V2): new anthropogenic SO<sub>2</sub> vertical column density dataset

2020 ◽  
Vol 13 (11) ◽  
pp. 6175-6191
Author(s):  
Can Li ◽  
Nickolay A. Krotkov ◽  
Peter J. T. Leonard ◽  
Simon Carn ◽  
Joanna Joiner ◽  
...  
Keyword(s):  
Column Density ◽  
A Priori ◽  
Principal Component ◽  
Ozone Monitoring Instrument ◽  
Vertical Column ◽  
Monitoring Instrument ◽  
Spectral Fitting ◽  
Vertical Column Density ◽  
Ozone Monitoring ◽  
So2 Pollution

Abstract. The Ozone Monitoring Instrument (OMI) has been providing global observations of SO2 pollution since 2004. Here we introduce the new anthropogenic SO2 vertical column density (VCD) dataset in the version 2 OMI SO2 product (OMSO2 V2). As with the previous version (OMSO2 V1.3), the new dataset is generated with an algorithm based on principal component analysis of OMI radiances but features several updates. The most important among those is the use of expanded lookup tables and model a priori profiles to estimate SO2 Jacobians for individual OMI pixels, in order to better characterize pixel-to-pixel variations in SO2 sensitivity including over snow and ice. Additionally, new data screening and spectral fitting schemes have been implemented to improve the quality of the spectral fit. As compared with the planetary boundary layer SO2 dataset in OMSO2 V1.3, the new dataset has substantially better data quality, especially over areas that are relatively clean or affected by the South Atlantic Anomaly. The updated retrievals over snow/ice yield more realistic seasonal changes in SO2 at high latitudes and offer enhanced sensitivity to sources during wintertime. An error analysis has been conducted to assess uncertainties in SO2 VCDs from both the spectral fit and Jacobian calculations. The uncertainties from spectral fitting are reflected in SO2 slant column densities (SCDs) and largely depend on the signal-to-noise ratio of the measured radiances, as implied by the generally smaller SCD uncertainties over clouds or for smaller solar zenith angles. The SCD uncertainties for individual pixels are estimated to be ∼ 0.15–0.3 DU (Dobson units) between ∼ 40∘ S and ∼ 40∘ N and to be ∼ 0.2–0.5 DU at higher latitudes. The uncertainties from the Jacobians are approximately ∼ 50 %–100 % over polluted areas and are primarily attributed to errors in SO2 a priori profiles and cloud pressures, as well as the lack of explicit treatment for aerosols. Finally, the daily mean and median SCDs over the presumably SO2-free equatorial east Pacific have increased by only ∼ 0.0035 DU and ∼ 0.003 DU respectively over the entire 15-year OMI record, while the standard deviation of SCDs has grown by only ∼ 0.02 DU or ∼ 10%. Such remarkable long-term stability makes the new dataset particularly suitable for detecting regional changes in SO2 pollution.

scholarly journals Validation of OMI, GOME-2A and GOME-2B tropospheric NO<sub>2</sub>, SO<sub>2</sub> and HCHO products using MAX-DOAS observations from 2011 to 2014 in Wuxi, China

2016 ◽  
Author(s):  
Yang Wang ◽  
Steffen Beirle ◽  
Johannes lampel ◽  
Mariliza Koukouli ◽  
Isabelle De Smedt ◽  
...  
Keyword(s):  
Satellite Data ◽  
Trace Gases ◽  
Satellite Observations ◽  
Urban Region ◽  
Ozone Monitoring Instrument ◽  
Vertical Column ◽  
Shape Factors ◽  
Weekly Cycle ◽  
Comparison Results ◽  
Ozone Monitoring

Abstract. Tropospheric vertical column densities (VCDs) of NO2, SO2 and HCHO derived from Ozone Monitoring Instrument (OMI) on AURA and Global Ozone Monitoring Experiment 2 aboard METOP-A (GOME-2A) and METOP-B (GOME-2B) are widely used to characterize the global distributions, trends, dominating sources of the trace gases and for comparisons with chemical transport models (CTM). We use tropospheric VCDs and vertical profiles of NO2, SO2 and HCHO derived from MAX-DOAS measurements from 2011 to 2014 in Wuxi, China, to validate the corresponding products derived from OMI, GOME-2A/B by different scientific teams (daily and bimonthly averaged data). Prior to the comparison we investigate the effects of the spatial and temporal coincidence criteria for MAX-DOAS and satellite data on the comparison results. We find that the distance of satellite data from the location of the MAX-DOAS station is the dominating effect, and we make suggestions for the spatial (20 km for OMI NO2 and SO2 products and 50 km for OMI HCHO and all GOME-2A/B products) and temporal averaging (2 hours around satellite overpass time). We also investigate the effect of clouds on both MAX-DOAS and satellite observations. Our results indicate that the discrepancies between satellite and MAX-DOAS results increase with increasing effective cloud fractions and are dominated by the cloud effect on the satellite products. Our comparison results indicate a systematic underestimation of all SO2 (40 % to 57 %) and HCHO products (about 20 %) and an overestimation of the GOME-2A/B NO2 products (about 30 %) (DOMINO NO2 product is only slightly underestimated by 1 %). To better understand the reasons for the differences, we recalculated the AMFs for satellite observations based on the shape factors (SFs) derived from MAX-DOAS. The recalculated satellite VCDs agree better with the MAX-DOAS VCDs than those from the original products by up to 10 %, 47 % and 35 % for NO2, SO2 and HCHO, respectively. The improvement is strongest for periods with large trace gas VCDs. Finally we investigate the effect of aerosols on the satellite retrievals. We find an increasing underestimation of the OMI NO2, SO2 and HCHO products with increasing AOD by up to 8 %, 12 % and 2 %, respectively. One reason for this finding is that aerosols systematically affect the satellite cloud retrievals and can lead to apparent effective cloud fractions of up to 10 % and apparent cloud top pressures of down to 830 hPa for the typical urban region in Wuxi. We show that in such cases the implicit aerosol correction could cause a strong underestimation of tropospheric VCDs by up to about 45 %, 77 % and 100 % for NO2, SO2 and HCHO, respectively. For such conditions it might be better to apply AMFs for clear sky conditions than AMFs based on the satellite cloud retrievals. We find that the satellites systematically overestimate the magnitude of the diurnal variations of NO2 and HCHO. No significant weekly cycle for all trace gases is found by either the satellites or the MAX-DOAS measurements.

scholarly journals Glyoxal retrieval from the Ozone Monitoring Instrument

2014 ◽  
Vol 7 (11) ◽  
pp. 3891-3907 ◽  
Author(s):  
C. Chan Miller ◽  
G. Gonzalez Abad ◽  
H. Wang ◽  
X. Liu ◽  
T. Kurosu ◽  
...  
Keyword(s):  
Cross Sections ◽  
Liquid Water ◽  
Monsoon Season ◽  
Anthropogenic Source ◽  
Spectral Features ◽  
Ozone Monitoring Instrument ◽  
Vertical Column ◽  
Monitoring Instrument ◽  
Offset Correction ◽  
Ozone Monitoring

Abstract. We present an algorithm for the retrieval of glyoxal from backscattered solar radiation, and apply it to spectra measured by the Ozone Monitoring Instrument (OMI). The algorithm is based on direct spectrum fitting, and adopts a two-step fitting routine to account for liquid water absorption. Previous studies have shown that glyoxal retrieval algorithms are highly sensitive to the position of the spectral fit window. This dependence was systematically tested on real and simulated OMI spectra. We find that a combination of errors resulting from uncertainties in reference cross sections and spectral features associated with the Ring effect are consistent with the fit-window dependence observed in real spectra. This implies an optimal fitting window of 435–461 nm, consistent with previous satellite glyoxal retrievals. The results from the retrieval of simulated spectra also support previous findings that have suggested that glyoxal is sensitive to NO2 cross-section temperature. The retrieval window limits of the liquid water retrieval are also tested. A retrieval window 385–470 nm reduces interference with strong spectral features associated with sand. We show that cross-track dependent offsets (stripes) present in OMI can be corrected using offsets derived from retrieved slant columns over the Sahara, and apply the correction to OMI data. Average glyoxal columns are on average lower than those of previous studies likely owing to the choice of reference sector for offset correction. OMI VCDs (vertical column densities)are lower compared to other satellites over the tropics and Asia during the monsoon season, suggesting that the new retrieval is less sensitive to water vapour abundance. Consequently we do not see significant glyoxal enhancements over tropical oceans. OMI-derived glyoxal-to-formaldehyde ratios over biogenic and anthropogenic source regions are consistent with surface observations.

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