scholarly journals Anthropogenic and volcanic point source SO<sub>2</sub> emissions derived from TROPOMI on board Sentinel-5 Precursor: first results

2020 ◽  
Vol 20 (9) ◽  
pp. 5591-5607 ◽  
Author(s):  
Vitali Fioletov ◽  
Chris A. McLinden ◽  
Debora Griffin ◽  
Nicolas Theys ◽  
Diego G. Loyola ◽  
...  
Keyword(s):  
Absolute Magnitude ◽  
Point Sources ◽  
Ozone Monitoring Instrument ◽  
So2 Emissions ◽  
Large Area ◽  
Vertical Column ◽  
Monitoring Instrument ◽  
Very High Spatial Resolution ◽  
First Results ◽  
Vertical Column Density

Abstract. The paper introduces the first TROPOMI-based sulfur dioxide (SO2) emissions estimates for point sources. A total of about 500 continuously emitting point sources releasing about 10 kt yr−1 to more than 2000 kt yr−1 of SO2, previously identified from Ozone Monitoring Instrument (OMI) observations, were analyzed using TROPOMI (TROPOspheric Monitoring Instrument) measurements for 1 full year from April 2018 to March 2019. The annual emissions from these sources were estimated and compared to similar estimates from OMI and Ozone Mapping Profiling Suite (OMPS) measurements. Note that emissions from many of these 500 sources have declined significantly since 2005, making their quantification more challenging. We were able to identify 274 sources where annual emissions are significant and can be reliably estimated from TROPOMI. The standard deviations of TROPOMI vertical column density data, about 1 Dobson unit (DU, where 1 DU =2.69×1016 molecules cm−2) over the tropics and 1.5 DU over high latitudes, are larger than those of OMI (0.6–1 DU) and OMPS (0.3–0.4 DU). Due to its very high spatial resolution, TROPOMI produces 12–20 times more observations over a certain area than OMI and 96 times more than OMPS. Despite higher uncertainties of individual TROPOMI observations, TROPOMI data averaged over a large area have roughly 2–3 times lower uncertainties compared to OMI and OMPS data. Similarly, TROPOMI annual emissions can be estimated with uncertainties that are 1.5–2 times lower than the uncertainties of annual emissions estimates from OMI. While there are area biases in TROPOMI data over some regions that have to be removed from emission calculations, the absolute magnitude of these are modest, typically within ±0.25 DU, which can be comparable with SO2 values over large sources.

scholarly journals Anthropogenic and volcanic point source SO<sub>2</sub> emissions derived from TROPOMI onboard Sentinel 5 Precursor: first results

2020 ◽  
Author(s):  
Vitali Fioletov ◽  
Chris A. McLinden ◽  
Debora Griffin ◽  
Nicolas Theys ◽  
Diego G. Loyola ◽  
...  
Keyword(s):  
Absolute Magnitude ◽  
Point Sources ◽  
Ozone Monitoring Instrument ◽  
So2 Emissions ◽  
Large Area ◽  
Vertical Column ◽  
Very High Spatial Resolution ◽  
First Results ◽  
Vertical Column Density ◽  
Very High

Abstract. The paper introduces the first TROPOMI-based sulfur dioxide (SO2) emissions estimates for point sources. A total of about 500 continuously emitting point sources releasing from about 10 kT y−1 to more than 2000 kT y−1 of SO2 per year, previously identified from Ozone Monitoring Instrument (OMI) observations, were analysed using TROPOMI measurements for one full year, from April 2018 to March 2019. The annual emissions from these sources were estimated and compared to similar estimates from OMI and Ozone Mapping Profiling Suite (OMPS) measurements. Note that emissions from many of these 500 sources declined significantly since 2005 making their quantification more challenging. We were able to identify 278 sources where annual emissions are significant and can be reliably estimated from TROPOMI. The standard deviations of TROPOMI vertical column density data, about 1 Dobson Unit (DU, where 1 DU = 2.69 × 1016 molecules/cm2) over tropics and 1.5 DU over high latitudes, are larger than those of OMI (0.6–1 DU) and OMPS (0.3–0.4 DU). Due to its very high spatial resolution, TROPOMI produces 12–20 times more observations over a certain area than OMI and 96 times more than OMPS. Despite higher uncertainties of individual TROPOMI observations, TROPOMI data averaged over a large area have roughly two-three times lower uncertainties compared to OMI and OMPS data. Similarly, TROPOMI annual emissions can be estimated with uncertainties that are 1.5–2 times lower than the uncertainties of annual emissions estimates from OMI. While there are area biases in TROPOMI data over some regions that have to be removed for emission calculations, the absolute magnitude of these are modest, typically within ±0.25 DU, it can be comparable to SO2 values over large sources.

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 A global catalogue of large SO<sub>2</sub> sources and emissions derived from the Ozone Monitoring Instrument

2016 ◽  
Author(s):  
Vitali E. Fioletov ◽  
Chris A. McLinden ◽  
Nickolay Krotkov ◽  
Can Li ◽  
Joanna Joiner ◽  
...  
Keyword(s):  
Power Plants ◽  
Oil And Gas ◽  
Principal Component ◽  
Oil And Gas Industry ◽  
Point Sources ◽  
Ozone Monitoring Instrument ◽  
So2 Emissions ◽  
Gas Industry ◽  
Monitoring Instrument ◽  
Ozone Monitoring

Abstract. Sulphur dioxide (SO2) measurements from the Ozone Monitoring Instrument (OMI) satellite sensor processed with the new Principal Component Analysis (PCA) algorithm were used to detect large point emission sources or clusters of sources. The total of 491 continuously emitting point sources releasing from about 30 kt yr−1 to more than 4000 kt yr−1 of SO2 per year have been identified and grouped by country and by primary source origin: volcanoes (76 sources); power plants (297); smelters (53); and sources related to the oil and gas industry (65). The sources were identified using different methods, including through OMI measurements themselves applied to a new emissions detection algorithm, and their evolution during the 2005–2014 period was traced by estimating annual emissions from each source. For volcanic sources, the study focused on continuous degassing, and emissions from explosive eruptions were excluded. Emissions from degassing volcanic sources were measured, many for the first time, and collectively they account for about 30 % of total SO2 emissions estimated from OMI measurements, but that fraction has increased in recent years given that cumulative global emissions from power plants and smelters are declining while emissions from oil and gas industry remained nearly constant. Anthropogenic emissions from the USA declined by 80 % over the 2005–2014 period as did emissions from western and central Europe, whereas emissions from India nearly doubled, and emissions from other large SO2-emitting regions (South Africa, Russia, Mexico, and the Middle East) remained fairly constant. In total, OMI-based estimates account for about a half of total reported anthropogenic SO2 emissions; the remaining half is likely related to sources emitting less than 30 kt yr−1 and not detected by OMI.

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 global catalogue of large SO<sub>2</sub> sources and emissions derived from the Ozone Monitoring Instrument

2016 ◽  
Vol 16 (18) ◽  
pp. 11497-11519 ◽  
Author(s):  
Vitali E. Fioletov ◽  
Chris A. McLinden ◽  
Nickolay Krotkov ◽  
Can Li ◽  
Joanna Joiner ◽  
...  
Keyword(s):  
Power Plants ◽  
Oil And Gas ◽  
Principal Component ◽  
Oil And Gas Industry ◽  
Point Sources ◽  
Ozone Monitoring Instrument ◽  
So2 Emissions ◽  
Gas Industry ◽  
Monitoring Instrument ◽  
Ozone Monitoring

Abstract. Sulfur dioxide (SO2) measurements from the Ozone Monitoring Instrument (OMI) satellite sensor processed with the new principal component analysis (PCA) algorithm were used to detect large point emission sources or clusters of sources. The total of 491 continuously emitting point sources releasing from about 30 kt yr−1 to more than 4000 kt yr−1 of SO2 per year have been identified and grouped by country and by primary source origin: volcanoes (76 sources); power plants (297); smelters (53); and sources related to the oil and gas industry (65). The sources were identified using different methods, including through OMI measurements themselves applied to a new emission detection algorithm, and their evolution during the 2005–2014 period was traced by estimating annual emissions from each source. For volcanic sources, the study focused on continuous degassing, and emissions from explosive eruptions were excluded. Emissions from degassing volcanic sources were measured, many for the first time, and collectively they account for about 30 % of total SO2 emissions estimated from OMI measurements, but that fraction has increased in recent years given that cumulative global emissions from power plants and smelters are declining while emissions from oil and gas industry remained nearly constant. Anthropogenic emissions from the USA declined by 80 % over the 2005–2014 period as did emissions from western and central Europe, whereas emissions from India nearly doubled, and emissions from other large SO2-emitting regions (South Africa, Russia, Mexico, and the Middle East) remained fairly constant. In total, OMI-based estimates account for about a half of total reported anthropogenic SO2 emissions; the remaining half is likely related to sources emitting less than 30 kt yr−1 and not detected by OMI.

scholarly journals Seasonal variation of tropospheric bromine monoxide over the Rann of Kutch salt marsh seen from space

2016 ◽  
Vol 16 (20) ◽  
pp. 13015-13034 ◽  
Author(s):  
Christoph Hörmann ◽  
Holger Sihler ◽  
Steffen Beirle ◽  
Marloes Penning de Vries ◽  
Ulrich Platt ◽  
...  
Keyword(s):  
Salt Marsh ◽  
Monsoon Season ◽  
Point Sources ◽  
Optical Absorption Spectroscopy ◽  
Polar Regions ◽  
Ambient Conditions ◽  
Ozone Monitoring Instrument ◽  
Vertical Column ◽  
Monitoring Instrument ◽  
Ozone Monitoring

Abstract. The Rann of Kutch (India and Pakistan) is one of the largest salt deserts in the world. Being a so-called "seasonal salt marsh", it is regularly flooded during the Indian summer monsoon. We present 10 years of bromine monoxide (BrO) satellite observations by the Ozone Monitoring Instrument (OMI) over the Great and Little Rann of Kutch. OMI spectra were analysed using Differential Optical Absorption Spectroscopy (DOAS) and revealed recurring high BrO vertical column densities (VCDs) of up to 1.4  ×  1014 molec cm−2 during April/May, but no significantly enhanced column densities during the monsoon season (June–September). In the following winter months, the BrO VCDs are again slightly enhanced while the salty surface dries up. We investigate a possible correlation of enhanced reactive bromine concentrations with different meteorological parameters and find a strong relationship between incident UV radiation and the total BrO abundance. In contrast, the second Global Ozone Monitoring Instrument (GOME-2) shows about 4 times lower BrO VCDs over the Rann of Kutch than found by OMI and no clear seasonal cycle is observed. One reason for this finding might be the earlier local overpass time of GOME-2 compared to OMI (around 09:30 vs. 13:30 LT), as the ambient conditions significantly differ for both satellite instruments at the time of the measurements. Further possible reasons are discussed and mainly attributed to instrumental issues. OMI additionally confirms the presence of enhanced BrO concentrations over the Dead Sea valley (Israel/Jordan), as suggested by former ground-based observations. The measurements indicate that the Rann of Kutch salt marsh is probably one of the strongest natural point sources of reactive bromine compounds outside the polar regions and is therefore supposed to have a significant impact on local and regional ozone chemistry.

scholarly journals Multi-source SO<sub>2</sub> emissions retrievals and consistency of satellite and surface measurements with reported emissions

2017 ◽  
Author(s):  
Vitali Fioletov ◽  
Chris A. McLinden ◽  
Shailesh K. Kharol ◽  
Nickolay A. Krotkov ◽  
Can Li ◽  
...  
Keyword(s):  
Point Source ◽  
Single Point ◽  
Control Measures ◽  
Ozone Monitoring Instrument ◽  
So2 Emissions ◽  
Vertical Column ◽  
Wind Speeds ◽  
Surface Measurements ◽  
Best Fit

Abstract. Reported sulfur dioxide (SO2) emissions from U.S. and Canadian sources have declined dramatically since the 1990s as a result of emissions control measures. Observations from the Ozone Monitoring Instrument (OMI) on NASA's Aura satellite and ground-based in-situ measurements are examined to verify whether the observed changes from SO2 abundance measurements are quantitatively consistent with the reported changes in emissions. To make this connection, a new method to link SO2 emissions and satellite SO2 measurements was developed. The method is based on fitting satellite SO2 vertical column densities (VCDs) to a set of functions of OMI pixel coordinates and wind speeds, where each function represents a statistical model of a plume from a single point source. The concept is first demonstrated using sources in North America, and then applied to Europe. The correlation coefficient between OMI-measured VCDs (with a local bias removed) and SO2 VCDs derived here using reported emissions for 1° by 1° gridded data is 0.91 and the best-fit line has a slope near unity, confirming a very good agreement between observed SO2 VCDs and reported emissions. Having demonstrated their consistency, seasonal and annual mean SO2 VCD distributions are calculated, based on reported point-source emissions for the period 1980–2015, as would have been seen by OMI. This consistency is further substantiated as the emissions-derived VCDs also show a high correlation with annual mean SO2 surface concentrations at 50 regional monitoring stations.

scholarly journals A high spatial resolution retrieval of NO<sub>2</sub> column densities from OMI: method and evaluation

2011 ◽  
Vol 11 (4) ◽  
pp. 12411-12440 ◽  
Author(s):  
A. R. Russell ◽  
A. E. Perring ◽  
L. C. Valin ◽  
E. Bucsela ◽  
E. C. Browne ◽  
...  
Keyword(s):  
Boundary Layer ◽  
The Arctic ◽  
Ozone Monitoring Instrument ◽  
Vertical Column ◽  
Aircraft Observations ◽  
Vertical Column Density ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Better Than

Abstract. We present a new retrieval of tropospheric NO2 vertical column density from the Ozone Monitoring Instrument (OMI) based on high spatial and temporal resolution terrain and profile inputs. We find non-negligible impacts on the retrieved NO2 column for terrain pressure (±20%), albedo (±40%), and NO2 vertical profile (−75%–+10%). We compare our NO2 product, the Berkeley High-Resolution (BEHR) product, with operational retrievals and find that the operational retrievals are biased high (30%) over remote areas and biased low (8%) over urban regions. We validate the operational and BEHR products using boundary layer aircraft observations from the Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS-CA) field campaign which occurred in June 2008 in California. Results indicate that columns derived using our boundary layer extrapolation method show good agreement with satellite observations (R2 = 0.65–0.83; N = 68) and provide a more robust validation of satellite-observed NO2 column than those determined using full vertical spirals (R2 = 0.26; N = 5) as in previous work. Agreement between aircraft observations and the BEHR product (R2 = 0.83) is better than agreement with the operational products (R2 = 0.65–0.72). We also show that agreement between satellite and aircraft observations for all products can be further improved (e.g. BEHR: R2 = 0.91) using cloud information from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument instead of the OMI cloud product. These results indicate that much of the variance in the operational products can be attributed to coarse resolution terrain and profile parameters.

scholarly journals New-generation NASA Aura Ozone Monitoring Instrument (OMI) volcanic SO<sub>2</sub> dataset: Algorithm description, initial results, and continuation with the Suomi-NPP Ozone Mapping and Profiler Suite (OMPS)

2016 ◽  
Author(s):  
Can Li ◽  
Nickolay A. Krotkov ◽  
Simon Carn ◽  
Yan Zhang ◽  
Robert J. D. Spurr ◽  
...  
Keyword(s):  
Lower Troposphere ◽  
Climate Impacts ◽  
Wavelength Shift ◽  
Ozone Monitoring Instrument ◽  
So2 Emissions ◽  
Monitoring Instrument ◽  
Spectral Fitting ◽  
Ozone Monitoring ◽  
Pca Algorithm ◽  
New Generation

Abstract. Since the fall of 2004, the Ozone Monitoring Instrument (OMI) has been providing global monitoring of volcanic SO2 emissions, helping to understand their climate impacts and to mitigate aviation hazards. Here we introduce a new generation OMI volcanic SO2 dataset based on a principal component analysis (PCA) retrieval technique. To reduce retrieval noise and artifacts as seen in the current operational linear fit (LF) algorithm, the new algorithm, OMSO2VOLCANO, uses characteristic features extracted directly from OMI radiances in the spectral fitting, thereby helping to minimize interferences from various geophysical processes (e.g., O3 absorption) and measurement details (e.g., wavelength shift). To solve the problem of low bias for large SO2 total columns in the LF product, the OMSO2VOLCANO algorithm employs a table lookup approach to estimate SO2 Jacobians (i.e., the instrument sensitivity to a perturbation in the SO2 column amount) and iteratively adjusts the spectral fitting window to exclude shorter wavelengths where the SO2 absorption signals are saturated. To first order, the effects of clouds and aerosols are accounted for using a simple Lambertian equivalent reflectivity approach. As with the LF algorithm, OMSO2VOLCANO provides total column retrievals based on a set of pre-defined SO2 profiles from the lower troposphere to the lower stratosphere, including a new profile peaked at 13 km for plumes in the upper troposphere. Examples given in this study indicate that the new dataset shows significant improvement over the LF product, with at least 50 % reduction in retrieval noise over the remote Pacific. For large eruptions such as Kasatochi in 2008 (~ 1700 kt total SO2) and Sierra Negra in 2005 (> 1100 DU maximal SO2), OMSO2VOLCANO generally agrees well with other algorithms that also utilize the full spectral content of satellite measurements, while the LF algorithm tends to underestimate SO2. We also demonstrate that, despite the coarser spatial and spectral resolution of the Suomi National Polar-orbiting Partnership (Suomi-NPP) Ozone Mapping and Profiler Suite (OMPS) instrument, application of the new PCA algorithm to OMPS data produces highly consistent retrievals between OMI and OMPS. The new PCA algorithm is therefore capable of continuing the volcanic SO2 data record well into the future using current and future hyperspectral UV satellite instruments.

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