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 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 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.

scholarly journals Assessment of air pollution control technologies to reduce SOx emission from thermal oxidizer for oil and gas industry

2021 ◽  
Vol 1195 (1) ◽  
pp. 012046
Author(s):  
N H B Haji Nawawi ◽  
M N Jaafar
Keyword(s):  
Flue Gas ◽  
Power Plants ◽  
Oil And Gas ◽  
Oil And Gas Industry ◽  
Technical Solution ◽  
Air Pollution Control ◽  
Process Technology ◽  
Gas Industry ◽  
Emission Limit ◽  
Emission Limits

Abstract Many countries have put in place, various legislations that govern air emission limits/pollutants from the industries. The common pollutants being monitored are Sulphur Oxides (SOx), Nitrogen Oxides (NOx), Carbon Monoxide (CO), Carbon Dioxide (CO2), Volatile Organic Compounds (VOCs), particulate matters and dioxins. In Malaysia, the regulatory requirement aims to regulate emissions of air pollutants from industrial activities including oil and gas, power plants, waste fuel plants and asphalt mixing plants. One of the emission limits under Clean Air Regulation (CAR2014) is emission level for SOx should be less than 600 mg/m3 (reference condition at 3 % of O2, 273 K, 101.3 kPa) whereby sum of SO2 and SO3 expressed as SOx. Excessive SOx emission can affect both health and the environment. Aligning with the regulation requirement, Group Technical Solution (GTS) under PETRONAS has embarked on assessment of technology solutions to meet the emission limit on SOx emission limit for thermal oxidizers which cover new and existing facilities. This paper describes on the work methodology and approach adopted during the assessment. The objective of the assessment is to determine the suitable process technology to reduce SOx emission in order to achieve the desired emission limit for flue gas at outlet stream of thermal oxidizer. Thorough evaluation was carried out based on proposal submission from various technology providers and Vendors. The selection criteria was developed and established. For existing thermal oxidizers, the assessment is more complex taking into consideration the nature of brownfield project and to ensure the proposed modification has minor impact to operability and maintainability of existing facilities. This study has successfully enabled identification of feasible process technologies such as Caustic Scrubber, Seawater Flue Gas Desulfurization and Ammonia based Desulfurization to meet the desired emission limit at thermal oxidizer outlet for Oil and Gas Industry and supporting environmental protection. The selected technology is varies based on plant/project specific requirement. Among main considerations are the by-product management, consumable and utility consumption as well as compatibility of the technology with existing plant on shutdown requirement.

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 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)

2017 ◽  
Vol 10 (2) ◽  
pp. 445-458 ◽  
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 predefined 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 maximum 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.

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 Improving automated global detection of volcanic SO<sub>2</sub> plumes using the Ozone Monitoring Instrument (OMI)

2016 ◽  
Author(s):  
Verity J. B. Flower ◽  
Thomas Oommen ◽  
Simon A. Carn
Keyword(s):  
Traffic Control ◽  
Service Providers ◽  
Volcanic Eruptions ◽  
Volcano Monitoring ◽  
Volcanic Plume ◽  
Human Populations ◽  
Ozone Monitoring Instrument ◽  
So2 Emissions ◽  
Monitoring Instrument ◽  
Ozone Monitoring

Abstract. Volcanic eruptions pose an ever-present threat to human populations around the globe, but many active volcanoes remain poorly monitored. In regions where ground-based monitoring is present the effects of volcanic eruptions can be moderated through observational alerts to both local populations and service providers such as air traffic control. However, in regions where volcano monitoring is limited satellite-based remote sensing provides a global data source that can be utilised to provide near real time identification of volcanic activity. This paper details the development of an automated volcanic plume detection method utilizing daily, global observations of sulphur dioxide (SO2) by the Ozone Monitoring Instrument (OMI) on NASA's Aura satellite. Following identification and classification of known volcanic eruptions in 2005–2009, the OMI SO2 data are analysed using a logistic regression analysis which permits the identification of volcanic events with an overall accuracy of over 80 %, and consistent plume identification when the volcanic plume SO2 loading exceeds ~ 400 tons. The accuracy and minimal user input requirements of the developed procedure provide a basis for the creation of an automated SO2 alert system providing volcanic alerts in regions where ground based volcano monitoring capabilities are limited. The technique could easily be adapted for use with satellite measurements of volcanic SO2 emissions from other platforms.

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