scholarly journals A new discrete wavelength BUV algorithm for consistent volcanic SO<sub>2</sub> retrievals from multiple satellite missions

2019 ◽  
Author(s):  
Bradford L. Fisher ◽  
Nickolay A. Krotkov ◽  
Pawan K. Bhartia ◽  
Can Li ◽  
Simon Carn ◽  
...  
Keyword(s):  
Sulfur Dioxide ◽  
Principal Component ◽  
Volcanic Eruptions ◽  
Climate Data ◽  
Ozone Monitoring Instrument ◽  
Vertical Column ◽  
Earth Observing System ◽  
Paper Supplement ◽  
Process Measurements ◽  
Pca Algorithm

Abstract. This paper describes a new discrete wavelength algorithm developed for retrieving volcanic sulfur dioxide (SO2) vertical column density (VCD) from UV observing satellites. The Multi-Satellite SO2 algorithm (MS_SO2) simultaneously retrieves column densities of sulfur dioxide, ozone, Lambertian Effective Reflectivity (LER) and its spectral dependence. It is used operationally to process measurements from the heritage Total Ozone Mapping Spectrometer (TOMS) on board NASA's Nimbus-7 satellite (N7/TOMS: 1978–1993) and from the current Earth Polychromatic Imaging Camera (EPIC) on board Deep Space Climate Observatory (DSCOVR: 2015–) from the Earth-Sun Lagrange (L1) orbit. Results from MS_SO2 algorithm for several volcanic cases were validated using the more sensitive principal component analysis (PCA) algorithm. The PCA is an operational algorithm used by NASA to retrieve SO2 from hyperspectral UV spectrometers, such as Ozone Monitoring Instrument (OMI) on board NASA’s Earth Observing System Aura satellite and Ozone Mapping and Profiling Suite (OMPS) on board NASA-NOAA Suomi National Polar Partnership (S-NPP) satellite. For this comparative study, the PCA algorithm was modified to use the discrete wavelengths of the Nimbus7/TOMS instrument, described in S1 of the paper supplement. Our results demonstrate good agreement between the two retrievals for the largest volcanic eruptions of the satellite era, such as 1991 Pinatubo eruption. To estimate SO2 retrieval uncertainties we use radiative transfer simulations explicitly accounting for volcanic sulfate and ash aerosols. Our results suggest that the discrete-wavelength MS_SO2 algorithm, although less sensitive than hyperspectral PCA algorithm, can be adapted to retrieve volcanic SO2 VCDs from contemporary hyperspectral UV instruments, such as OMI and OMPS, to create consistent, multi-satellite, long-term volcanic SO2 climate data records.

scholarly journals A new discrete wavelength backscattered ultraviolet algorithm for consistent volcanic SO<sub>2</sub> retrievals from multiple satellite missions

2019 ◽  
Vol 12 (9) ◽  
pp. 5137-5153
Author(s):  
Bradford L. Fisher ◽  
Nickolay A. Krotkov ◽  
Pawan K. Bhartia ◽  
Can Li ◽  
Simon A. Carn ◽  
...  
Keyword(s):  
Sulfur Dioxide ◽  
Principal Component ◽  
Volcanic Eruptions ◽  
Climate Data ◽  
Ozone Monitoring Instrument ◽  
Vertical Column ◽  
Earth Observing System ◽  
Vertical Column Density ◽  
Process Measurements ◽  
Pca Algorithm

Abstract. This paper describes a new discrete wavelength algorithm developed for retrieving volcanic sulfur dioxide (SO2) vertical column density (VCD) from UV observing satellites. The Multi-Satellite SO2 algorithm (MS_SO2) simultaneously retrieves column densities of sulfur dioxide, ozone, and Lambertian effective reflectivity (LER) and its spectral dependence. It is used operationally to process measurements from the heritage Total Ozone Mapping Spectrometer (TOMS) onboard NASA's Nimbus-7 satellite (N7/TOMS: 1978–1993) and from the current Earth Polychromatic Imaging Camera (EPIC) onboard Deep Space Climate Observatory (DSCOVR: 2015–ongoing) from the Earth–Sun Lagrange (L1) orbit. Results from MS_SO2 algorithm for several volcanic cases were assessed using the more sensitive principal component analysis (PCA) algorithm. The PCA is an operational algorithm used by NASA to retrieve SO2 from hyperspectral UV spectrometers, such as the Ozone Monitoring Instrument (OMI) onboard NASA's Earth Observing System Aura satellite and Ozone Mapping and Profiling Suite (OMPS) onboard NASA–NOAA Suomi National Polar Partnership (SNPP) satellite. For this comparative study, the PCA algorithm was modified to use the discrete wavelengths of the Nimbus-7/TOMS instrument, described in Sect. S1 of the Supplement. Our results demonstrate good agreement between the two retrievals for the largest volcanic eruptions of the satellite era, such as the 1991 Pinatubo eruption. To estimate SO2 retrieval systematic uncertainties, we use radiative transfer simulations explicitly accounting for volcanic sulfate and ash aerosols. Our results suggest that the discrete-wavelength MS_SO2 algorithm, although less sensitive than hyperspectral PCA algorithm, can be adapted to retrieve volcanic SO2 VCDs from contemporary hyperspectral UV instruments, such as OMI and OMPS, to create consistent, multi-satellite, long-term volcanic SO2 climate data records.

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 Validation of Aura-OMI QA4ECV NO<sub>2</sub> climate data records with ground-based DOAS networks: the role of measurement and comparison uncertainties

2020 ◽  
Vol 20 (13) ◽  
pp. 8017-8045 ◽  
Author(s):  
Steven Compernolle ◽  
Tijl Verhoelst ◽  
Gaia Pinardi ◽  
José Granville ◽  
Daan Hubert ◽  
...  
Keyword(s):  
Scattered Light ◽  
A Priori ◽  
Sampling Bias ◽  
Atmospheric Composition ◽  
Optical Absorption Spectroscopy ◽  
Climate Data ◽  
Ozone Monitoring Instrument ◽  
Vertical Column ◽  
Standard Data ◽  
The Difference

Abstract. The QA4ECV (Quality Assurance for Essential Climate Variables) version 1.1 stratospheric and tropospheric NO2 vertical column density (VCD) climate data records (CDRs) from the OMI (Ozone Monitoring Instrument) satellite sensor are validated using NDACC (Network for the Detection of Atmospheric Composition Change) zenith-scattered light differential optical absorption spectroscopy (ZSL-DOAS) and multi-axis DOAS (MAX-DOAS) data as a reference. The QA4ECV OMI stratospheric VCDs have a small bias of ∼0.2 Pmolec.cm-2 (5 %–10 %) and a dispersion of 0.2 to 1 Pmolec.cm-2 with respect to the ZSL-DOAS measurements. QA4ECV tropospheric VCD observations from OMI are restricted to near-cloud-free scenes, leading to a negative sampling bias (with respect to the unrestricted scene ensemble) of a few peta molecules per square centimetre (Pmolec.cm-2) up to −10 Pmolec.cm-2 (−40 %) in one extreme high-pollution case. The QA4ECV OMI tropospheric VCD has a negative bias with respect to the MAX-DOAS data (−1 to −4 Pmolec.cm-2), which is a feature also found for the OMI OMNO2 standard data product. The tropospheric VCD discrepancies between satellite measurements and ground-based data greatly exceed the combined measurement uncertainties. Depending on the site, part of the discrepancy can be attributed to a combination of comparison errors (notably horizontal smoothing difference error), measurement/retrieval errors related to clouds and aerosols, and the difference in vertical smoothing and a priori profile assumptions.

Dispersion Model Evaluation for the Sulfur Dioxide Plume from the 2019 Raikoke Eruption using Satellite Measurements.

2020 ◽  
Author(s):  
Johannes de Leeuw ◽  
Anja Schmidt ◽  
Claire Witham ◽  
Nicolas Theys ◽  
Richard Pope ◽  
...  
Keyword(s):  
Sulfur Dioxide ◽  
Dispersion Model ◽  
European Space Agency ◽  
Volcanic Eruptions ◽  
Numerical Dispersion ◽  
Aviation Industry ◽  
Volcanic Plume ◽  
Satellite Measurements ◽  
Volcanic Gas ◽  
Vertical Column

&lt;p&gt;Volcanic eruptions pose a serious threat to the aviation industry causing widespread disruption. To identify any potential impacts, nine Volcanic Ash Advisory Centres (VAACs) provide global monitoring of all eruptions, informing stakeholders how each volcanic eruption might interfere with aviation. Numerical dispersion models represent a vital infrastructure when assessing and forecasting the atmospheric conditions from a volcanic plume.&lt;/p&gt;&lt;p&gt;In this study we investigate the 2019 Raikoke eruption, which emitted approximately 1.5 Tg of sulfur dioxide (SO&lt;sub&gt;2&lt;/sub&gt;) representing the largest volcanic emission of SO&lt;sub&gt;2&lt;/sub&gt; into the stratosphere since the Nabro eruption in 2011. Using the UK Met Office&amp;#8217;s Numerical Atmospheric-dispersion Modelling Environment (NAME), we simulate the evolution of the volcanic gas and aerosol particle plumes (SO&lt;sub&gt;2&lt;/sub&gt; and sulfate, SO&lt;sub&gt;4&lt;/sub&gt;) across the Northern Hemisphere between 21&lt;sup&gt;st&lt;/sup&gt; June and 17&lt;sup&gt;th &lt;/sup&gt;July. We evaluate the skills and limitations of NAME in terms of modelling volcanic SO&lt;sub&gt;2 &lt;/sub&gt;plumes, by comparing our simulations to high-resolution measurements from the Tropospheric Monitoring Instrument (TROPOMI) on-board the European Space Agency (ESA)&amp;#8217;s Sentinel 5 &amp;#8211; Precursor (S5P) satellite.&lt;/p&gt;&lt;p&gt;Our comparisons show that NAME accurately simulates the observed location and shape of the SO&lt;sub&gt;2&lt;/sub&gt; plume in the first few weeks after the eruption. NAME also reproduces the magnitude of the observed SO&lt;sub&gt;2 &lt;/sub&gt;vertical column densities, when emitting 1.5 Tg of SO&lt;sub&gt;2&lt;/sub&gt;, during the first 48 hours after the eruption. On longer timescales, we find that the model-simulated SO&lt;sub&gt;2 &lt;/sub&gt;plume in NAME is more diffuse than in the TROPOMI measurements, resulting in an underestimation of the peak SO&lt;sub&gt;2&lt;/sub&gt; vertical column densities in the model. This suggests that the diffusion parameters used in NAME are too large in the upper troposphere and lower stratosphere.&lt;/p&gt;&lt;p&gt;Finally, NAME underestimates the total mass of SO&lt;sub&gt;2&lt;/sub&gt; when compared to estimates from TROPOMI, however emitting 2 Tg of SO&lt;sub&gt;2&lt;/sub&gt; in the model improves the comparison, resulting in very good agreement with the satellite measurements.&lt;/p&gt;

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 A Sulfur Dioxide Covariance-Based Retrieval Algorithm (COBRA): application to TROPOMI reveals new emission sources

2021 ◽  
Author(s):  
Nicolas Theys ◽  
Vitali Fioletov ◽  
Can Li ◽  
Isabelle De Smedt ◽  
Christophe Lerot ◽  
...  
Keyword(s):  
Sulfur Dioxide ◽  
Principal Component ◽  
Great Sensitivity ◽  
Detection Methods ◽  
Retrieval Algorithm ◽  
Ozone Monitoring Instrument ◽  
So2 Emissions ◽  
Data Set ◽  
So2 Emission ◽  
Monitoring Instrument

Abstract. Sensitive and accurate detection of sulfur dioxide (SO2) from space is important for monitoring and estimating global sulfur emissions. Inspired by detection methods applied in the thermal infrared, we present here a new scheme to retrieve SO2 columns from satellite observations of ultraviolet back-scattered radiances. The retrieval is based on a measurement error covariance matrix to fully represent the SO2-free radiance variability, so that the SO2 slant column density is the only retrieved parameter of the algorithm. We demonstrate this approach, named COBRA, on measurements from the TROPOspheric Monitoring Instrument (TROPOMI) aboard the Sentinel-5 Precursor (S-5P) satellite. We show that the method reduces significantly both the noise and biases present in the current TROPOMI operational DOAS SO2 retrievals. The performance of this technique is also benchmarked against that of the Principal Component Algorithm (PCA) approach. We find that the quality of the data is similar and even slightly better with the proposed COBRA approach. The ability of the algorithm to retrieve SO2 accurately is also further supported by comparison with ground-based observations. We illustrate the great sensitivity of the method with a high-resolution global SO2 map, considering two and a half years of TROPOMI data. In addition to the known sources, we detect many new SO2 emission hotspots worldwide. For the largest sources, we use the COBRA data to estimate SO2 emission rates. Results are comparable to other recently published TROPOMI-based SO2 emissions estimates, but the associated uncertainties are significantly lower than with the operational data. Next, for a limited number of weak sources, we demonstrate the potential of our data for quantifying SO2 emissions with a detection limit of about 8 kt yr-1, a factor of 4 better than the emissions derived from the Ozone Monitoring Instrument (OMI). We anticipate that the systematic use of our TROPOMI COBRA SO2 column data set at a global scale will allow identifying and quantifying missing sources, and help improving SO2 emission inventories.

scholarly journals Detecting volcanic sulfur dioxide plumes in the Northern Hemisphere using the Brewer spectrophotometers, other networks, and satellite observations

2017 ◽  
Vol 17 (1) ◽  
pp. 551-574 ◽  
Author(s):  
Christos S. Zerefos ◽  
Kostas Eleftheratos ◽  
John Kapsomenakis ◽  
Stavros Solomos ◽  
Antje Inness ◽  
...  
Keyword(s):  
Sulfur Dioxide ◽  
Northern Hemisphere ◽  
Theoretical Calculations ◽  
Volcanic Eruptions ◽  
Ground Level ◽  
Atmospheric Composition ◽  
Ozone Monitoring Instrument ◽  
Volcanic Origin ◽  
Local Pollution ◽  
Ozone Monitoring

Abstract. This study examines the adequacy of the existing Brewer network to supplement other networks from the ground and space to detect SO2 plumes of volcanic origin. It was found that large volcanic eruptions of the last decade in the Northern Hemisphere have a positive columnar SO2 signal seen by the Brewer instruments located under the plume. It is shown that a few days after the eruption the Brewer instrument is capable of detecting significant columnar SO2 increases, exceeding on average 2 DU relative to an unperturbed pre-volcanic 10-day baseline, with a mean close to 0 and σ = 0.46, as calculated from the 32 Brewer stations under study. Intercomparisons with independent measurements from the ground and space as well as theoretical calculations corroborate the capability of the Brewer network to detect volcanic plumes. For instance, the comparison with OMI (Ozone Monitoring Instrument) and GOME-2 (Global Ozone Monitoring Experiment-2) SO2 space-borne retrievals shows statistically significant agreement between the Brewer network data and the collocated satellite overpasses in the case of the Kasatochi eruption. Unfortunately, due to sparsity of satellite data, the significant positive departures seen in the Brewer and other ground networks following the Eyjafjallajökull, Bárðarbunga and Nabro eruptions could not be statistically confirmed by the data from satellite overpasses. A model exercise from the MACC (Monitoring Atmospheric Composition and Climate) project shows that the large increases in SO2 over Europe following the Bárðarbunga eruption in Iceland were not caused by local pollution sources or ship emissions but were clearly linked to the volcanic eruption. Sulfur dioxide positive departures in Europe following Bárðarbunga could be traced by other networks from the free troposphere down to the surface (AirBase (European air quality database) and EARLINET (European Aerosol Research Lidar Network)). We propose that by combining Brewer data with that from other networks and satellites, a useful tool aided by trajectory analyses and modelling could be created which can also be used to forecast high SO2 values both at ground level and in air flight corridors following future eruptions.

scholarly journals A sulfur dioxide Covariance-Based Retrieval Algorithm (COBRA): application to TROPOMI reveals new emission sources

2021 ◽  
Vol 21 (22) ◽  
pp. 16727-16744
Author(s):  
Nicolas Theys ◽  
Vitali Fioletov ◽  
Can Li ◽  
Isabelle De Smedt ◽  
Christophe Lerot ◽  
...  
Keyword(s):  
Sulfur Dioxide ◽  
Principal Component ◽  
Great Sensitivity ◽  
Detection Methods ◽  
Retrieval Algorithm ◽  
Ozone Monitoring Instrument ◽  
So2 Emissions ◽  
Data Set ◽  
So2 Emission ◽  
Monitoring Instrument

Abstract. Sensitive and accurate detection of sulfur dioxide (SO2) from space is important for monitoring and estimating global sulfur emissions. Inspired by detection methods applied in the thermal infrared, we present here a new scheme to retrieve SO2 columns from satellite observations of ultraviolet back-scattered radiances. The retrieval is based on a measurement error covariance matrix to fully represent the SO2-free radiance variability, so that the SO2 slant column density is the only retrieved parameter of the algorithm. We demonstrate this approach, named COBRA, on measurements from the TROPOspheric Monitoring Instrument (TROPOMI) aboard the Sentinel-5 Precursor (S-5P) satellite. We show that the method reduces significantly both the noise and biases present in the current TROPOMI operational DOAS SO2 retrievals. The performance of this technique is also benchmarked against that of the principal component algorithm (PCA) approach. We find that the quality of the data is similar and even slightly better with the proposed COBRA approach. The ability of the algorithm to retrieve SO2 accurately is further supported by comparison with ground-based observations. We illustrate the great sensitivity of the method with a high-resolution global SO2 map, considering 2.5 years of TROPOMI data. In addition to the known sources, we detect many new SO2 emission hotspots worldwide. For the largest sources, we use the COBRA data to estimate SO2 emission rates. Results are comparable to other recently published TROPOMI-based SO2 emissions estimates, but the associated uncertainties are significantly lower than with the operational data. Next, for a limited number of weak sources, we demonstrate the potential of our data for quantifying SO2 emissions with a detection limit of about 8 kt yr−1, a factor of 4 better than the emissions derived from the Ozone Monitoring Instrument (OMI). We anticipate that the systematic use of our TROPOMI COBRA SO2 column data set at a global scale will allow missing sources to be identified and quantified and help improve SO2 emission inventories.

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