Articles | Volume 15, issue 18
https://doi.org/10.5194/amt-15-5497-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-15-5497-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A new machine-learning-based analysis for improving satellite-retrieved atmospheric composition data: OMI SO2 as an example
Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD 20740, USA
Atmospheric Chemistry and Dynamics Laboratory, NASA Goddard Space
Flight Center, Greenbelt, MD 20771, USA
Joanna Joiner
Atmospheric Chemistry and Dynamics Laboratory, NASA Goddard Space
Flight Center, Greenbelt, MD 20771, USA
Atmospheric Chemistry and Dynamics Laboratory, NASA Goddard Space
Flight Center, Greenbelt, MD 20771, USA
Goddard Earth Sciences Technology and Research (GESTAR) II, Morgan
State University, Baltimore, MD 21251, USA
Nickolay A. Krotkov
Atmospheric Chemistry and Dynamics Laboratory, NASA Goddard Space
Flight Center, Greenbelt, MD 20771, USA
Vitali Fioletov
Environment and Climate Change Canada, Toronto, Ontario, Canada
Chris McLinden
Environment and Climate Change Canada, Toronto, Ontario, Canada
Related authors
Robert James Duncan Spurr, Matt Christi, Nickolay Anatoly Krotkov, Won-Ei Choi, Simon Carn, Can Li, Natalya Kramarova, David Haffner, Eun-Su Yang, Nick Gorkavyi, Alexander Vasilkov, Krzysztof Wargan, Omar Torres, Diego Loyola, Serena Di Pede, Joris Pepijn Veefkind, and Pawan Kumar Bhartia
EGUsphere, https://doi.org/10.5194/egusphere-2025-2938, https://doi.org/10.5194/egusphere-2025-2938, 2025
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
Short summary
Short summary
An eruption of the submarine Hunga volcano injected a massive plume of water vapor, sulfur dioxide and aerosols into the Southern tropical stratosphere. The high-altitude Hunga aerosol plume showed up as strongly enhanced solar backscattered ultraviolet (BUV) radiation compromising satellite BUV ozone retrievals. In this paper, we have developed a new technique to retrieve the aerosol amount and height, based on satellite solar BUV radiances from the TROPOMI and OMPS nadir profiler instruments.
Zachary Watson, Can Li, Fei Liu, Sean W. Freeman, Huanxin Zhang, Jun Wang, and Shan-Hu Lee
EGUsphere, https://doi.org/10.5194/egusphere-2025-1735, https://doi.org/10.5194/egusphere-2025-1735, 2025
Short summary
Short summary
Air pollutants like sulfur dioxide cause direct impacts on human health and the environment. Our work estimated surface concentrations from satellite data using atmospheric models and machine learning compared to an air quality monitoring network. We found that both methods can accurately determine the locations and changes in sulfur dioxide, but the machine learning method had better accuracy. Both methods are useful for monitoring air quality in locations without ground-based measurements.
Bryan N. Duncan, Daniel C. Anderson, Arlene M. Fiore, Joanna Joiner, Nickolay A. Krotkov, Can Li, Dylan B. Millet, Julie M. Nicely, Luke D. Oman, Jason M. St. Clair, Joshua D. Shutter, Amir H. Souri, Sarah A. Strode, Brad Weir, Glenn M. Wolfe, Helen M. Worden, and Qindan Zhu
Atmos. Chem. Phys., 24, 13001–13023, https://doi.org/10.5194/acp-24-13001-2024, https://doi.org/10.5194/acp-24-13001-2024, 2024
Short summary
Short summary
Trace gases emitted to or formed within the atmosphere may be chemically or physically removed from the atmosphere. One trace gas, the hydroxyl radical (OH), is responsible for initiating the chemical removal of many trace gases, including some greenhouse gases. Despite its importance, scientists have not been able to adequately measure OH. In this opinion piece, we discuss promising new methods to indirectly constrain OH using satellite data of trace gases that control the abundance of OH.
Can Li, Nickolay A. Krotkov, Joanna Joiner, Vitali Fioletov, Chris McLinden, Debora Griffin, Peter J. T. Leonard, Simon Carn, Colin Seftor, and Alexander Vasilkov
Earth Syst. Sci. Data, 16, 4291–4309, https://doi.org/10.5194/essd-16-4291-2024, https://doi.org/10.5194/essd-16-4291-2024, 2024
Short summary
Short summary
Sulfur dioxide (SO2), a poisonous gas from human activities and volcanoes, causes air pollution, acid rain, and changes to climate and the ozone layer. Satellites have been used to monitor SO2 globally, including remote areas. Here we describe a new satellite SO2 dataset from the OMPS instrument that flies on the N20 satellite. Results show that the new dataset agrees well with the existing ones from other satellites and can help to continue the global monitoring of SO2 from space.
Vitali E. Fioletov, Chris A. McLinden, Debora Griffin, Nickolay A. Krotkov, Can Li, Joanna Joiner, Nicolas Theys, and Simon Carn
Atmos. Meas. Tech., 16, 5575–5592, https://doi.org/10.5194/amt-16-5575-2023, https://doi.org/10.5194/amt-16-5575-2023, 2023
Short summary
Short summary
Snow-covered terrain, with its high reflectance in the UV, typically enhances satellite sensitivity to boundary layer pollution. However, a significant fraction of high-quality cloud-free measurements over snow is currently excluded from analyses. In this study, we investigated how satellite SO2 measurements over snow-covered surfaces can be used to improve estimations of annual SO2 emissions.
Joanna Joiner, Sergey Marchenko, Zachary Fasnacht, Lok Lamsal, Can Li, Alexander Vasilkov, and Nickolay Krotkov
Atmos. Meas. Tech., 16, 481–500, https://doi.org/10.5194/amt-16-481-2023, https://doi.org/10.5194/amt-16-481-2023, 2023
Short summary
Short summary
Nitrogen dioxide (NO2) is an important trace gas for both air quality and climate. NO2 affects satellite ocean color products. A new ocean color instrument – OCI (Ocean Color Instrument) – will be launched in 2024 on a NASA satellite. We show that it will be possible to measure NO2 from OCI even though it was not designed for this. The techniques developed here, based on machine learning, can also be applied to instruments already in space to speed up algorithms and reduce the effects of noise.
Jing Wei, Zhanqing Li, Jun Wang, Can Li, Pawan Gupta, and Maureen Cribb
Atmos. Chem. Phys., 23, 1511–1532, https://doi.org/10.5194/acp-23-1511-2023, https://doi.org/10.5194/acp-23-1511-2023, 2023
Short summary
Short summary
This study estimated the daily seamless 10 km ambient gaseous pollutants (NO2, SO2, and CO) across China using machine learning with extensive input variables measured on monitors, satellites, and models. Our dataset yields a high data quality via cross-validation at varying spatiotemporal scales and outperforms most previous related studies, making it most helpful to future (especially short-term) air pollution and environmental health-related studies.
Vitali E. Fioletov, Chris A. McLinden, Debora Griffin, Ihab Abboud, Nickolay Krotkov, Peter J. T. Leonard, Can Li, Joanna Joiner, Nicolas Theys, and Simon Carn
Earth Syst. Sci. Data, 15, 75–93, https://doi.org/10.5194/essd-15-75-2023, https://doi.org/10.5194/essd-15-75-2023, 2023
Short summary
Short summary
Sulfur dioxide (SO2) measurements from three satellite instruments were used to update and extend the previously developed global catalogue of large SO2 emission sources. This version 2 of the global catalogue covers the period of 2005–2021 and includes a total of 759 continuously emitting point sources. The catalogue data show an approximate 50 % decline in global SO2 emissions between 2005 and 2021, although emissions were relatively stable during the last 3 years.
Catherine Hardacre, Jane P. Mulcahy, Richard J. Pope, Colin G. Jones, Steven T. Rumbold, Can Li, Colin Johnson, and Steven T. Turnock
Atmos. Chem. Phys., 21, 18465–18497, https://doi.org/10.5194/acp-21-18465-2021, https://doi.org/10.5194/acp-21-18465-2021, 2021
Short summary
Short summary
We investigate UKESM1's ability to represent the sulfur (S) cycle in the recent historical period. The S cycle is a key driver of historical radiative forcing. Earth system models such as UKESM1 should represent the S cycle well so that we can have confidence in their projections of future climate. We compare UKESM1 to observations of sulfur compounds, finding that the model generally performs well. We also identify areas for UKESM1’s development, focussing on how SO2 is removed from the air.
Nick Gorkavyi, Nickolay Krotkov, Can Li, Leslie Lait, Peter Colarco, Simon Carn, Matthew DeLand, Paul Newman, Mark Schoeberl, Ghassan Taha, Omar Torres, Alexander Vasilkov, and Joanna Joiner
Atmos. Meas. Tech., 14, 7545–7563, https://doi.org/10.5194/amt-14-7545-2021, https://doi.org/10.5194/amt-14-7545-2021, 2021
Short summary
Short summary
The 21 June 2019 eruption of the Raikoke volcano produced significant amounts of volcanic aerosols (sulfate and ash) and sulfur dioxide (SO2) gas that penetrated into the lower stratosphere. We showed that the amount of SO2 decreases with a characteristic period of 8–18 d and the peak of sulfate aerosol lags the initial peak of SO2 by 1.5 months. We also examined the dynamics of an unusual stratospheric coherent circular cloud of SO2 and aerosol observed from 18 July to 22 September 2019.
Nicolas Theys, Vitali Fioletov, Can Li, Isabelle De Smedt, Christophe Lerot, Chris McLinden, Nickolay Krotkov, Debora Griffin, Lieven Clarisse, Pascal Hedelt, Diego Loyola, Thomas Wagner, Vinod Kumar, Antje Innes, Roberto Ribas, François Hendrick, Jonas Vlietinck, Hugues Brenot, and Michel Van Roozendael
Atmos. Chem. Phys., 21, 16727–16744, https://doi.org/10.5194/acp-21-16727-2021, https://doi.org/10.5194/acp-21-16727-2021, 2021
Short summary
Short summary
We present a new algorithm to retrieve sulfur dioxide from space UV measurements. We apply the technique to high-resolution TROPOMI measurements and demonstrate the high sensitivity of the approach to weak SO2 emissions worldwide with an unprecedented limit of detection of 8 kt yr−1. This result has broad implications for atmospheric science studies dealing with improving emission inventories and identifying and quantifying missing sources, in the context of air quality and climate.
Nikita M. Fedkin, Can Li, Nickolay A. Krotkov, Pascal Hedelt, Diego G. Loyola, Russell R. Dickerson, and Robert Spurr
Atmos. Meas. Tech., 14, 3673–3691, https://doi.org/10.5194/amt-14-3673-2021, https://doi.org/10.5194/amt-14-3673-2021, 2021
Short summary
Short summary
This study presents a new volcanic sulfur dioxide (SO2) layer height retrieval algorithm for the Ozone Monitoring Instrument (OMI). We generated a large spectral dataset with a radiative transfer model and used it to train neural networks to predict SO2 height from OMI radiance data. The algorithm is fast and takes less than 10 min for a single orbit. Retrievals were tested on four eruption cases, and results had reasonable agreement (within 2 km) with other retrievals and previous studies.
Can Li, Nickolay A. Krotkov, Peter J. T. Leonard, Simon Carn, Joanna Joiner, Robert J. D. Spurr, and Alexander Vasilkov
Atmos. Meas. Tech., 13, 6175–6191, https://doi.org/10.5194/amt-13-6175-2020, https://doi.org/10.5194/amt-13-6175-2020, 2020
Short summary
Short summary
Sulfur dioxide (SO2) is an important pollutant that causes haze and acid rain. The Ozone Monitoring Instrument (OMI) has been providing global observation of SO2 from space for over 15 years. In this paper, we introduce a new OMI SO2 dataset for global pollution monitoring. The dataset better accounts for the influences of different factors such as location and sun and satellite angles, leading to improved data quality. The new OMI SO2 dataset is publicly available through NASA's data center.
Robert James Duncan Spurr, Matt Christi, Nickolay Anatoly Krotkov, Won-Ei Choi, Simon Carn, Can Li, Natalya Kramarova, David Haffner, Eun-Su Yang, Nick Gorkavyi, Alexander Vasilkov, Krzysztof Wargan, Omar Torres, Diego Loyola, Serena Di Pede, Joris Pepijn Veefkind, and Pawan Kumar Bhartia
EGUsphere, https://doi.org/10.5194/egusphere-2025-2938, https://doi.org/10.5194/egusphere-2025-2938, 2025
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
Short summary
Short summary
An eruption of the submarine Hunga volcano injected a massive plume of water vapor, sulfur dioxide and aerosols into the Southern tropical stratosphere. The high-altitude Hunga aerosol plume showed up as strongly enhanced solar backscattered ultraviolet (BUV) radiation compromising satellite BUV ozone retrievals. In this paper, we have developed a new technique to retrieve the aerosol amount and height, based on satellite solar BUV radiances from the TROPOMI and OMPS nadir profiler instruments.
África Barreto, Francisco Quirós, Omaira E. García, Jorge Pereda-de-Pablo, Daniel González-Fernández, Andrés Bedoya-Velásquez, Michael Sicard, Carmen Córdoba-Jabonero, Marco Iarlori, Vincenzo Rizi, Nickolay Krotkov, Simon Carn, Reijo Roininen, Antonio J. Molina-Arias, A. Fernando Almansa, Óscar Álvarez-Losada, Carla Aramo, Juan José Bustos, Romain Ceolato, Adolfo Comerón, Alicia Felpeto, Rosa D. García, Pablo González-Sicilia, Yenny González, Pascal Hedelt, Miguel Hernández, María-Ángeles López-Cayuela, Diego Loyola, Stavros Meletlidis, Constantino Muñoz-Porcar, Ermanno Pietropaolo, Ramón Ramos, Alejandro Rodríguez-Gómez, Roberto Román, Pedro M. Romero-Campos, Martin Stuefer, Carlos Toledano, and Elsworth Welton
EGUsphere, https://doi.org/10.5194/egusphere-2025-3164, https://doi.org/10.5194/egusphere-2025-3164, 2025
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
Short summary
Short summary
This manuscript describes the instrumental coverage deployed during the Tajogaite eruption (19 September–25 December 2021) by the Instituto Geográfico Nacional (IGN), the Spanish State Meteorological Agency (AEMET), and other Spanish members of ACTRIS (Aerosol, Clouds and Trace Gases Research Infrastructure) to monitor its atmospheric impact. Two complementary methods provide consistent plume height data for future operational surveillance.
Chris A. McLinden, Debora Griffin, Vitali Fioletov, Junhua Zhang, Enrico Dammers, Cristen Adams, Mallory Loria, Nickolay Krotkov, and Lok N. Lamsal
Atmos. Chem. Phys., 25, 6093–6120, https://doi.org/10.5194/acp-25-6093-2025, https://doi.org/10.5194/acp-25-6093-2025, 2025
Short summary
Short summary
The Ozone Monitoring Instrument (OMI) was used to understand the evolution of NOx emissions from the Canadian oil sands. OMI NO2 combined with winds and reported stack emissions found emissions from the heavy-hauler mine fleet have remained flat since 2005, whereas the total oil sands mined have more than doubled. This difference is a result of emissions standards that limit NOx emissions becoming more stringent over this period, confirming the efficacy of the policy enacting these standards.
Ramina Alwarda, Kristof Bognar, Xiaoyi Zhao, Vitali Fioletov, Jonathan Davies, Sum Chi Lee, Debora Griffin, Alexandru Lupu, Udo Frieß, Alexander Cede, Yushan Su, and Kimberly Strong
Atmos. Meas. Tech., 18, 2397–2423, https://doi.org/10.5194/amt-18-2397-2025, https://doi.org/10.5194/amt-18-2397-2025, 2025
Short summary
Short summary
Nitrogen dioxide (NO2) is a pollutant with a short lifetime and large variability, but there are limited measurements of its distribution in the lower atmosphere. We present a new 3-year dataset of NO2 vertical profiles in Toronto, Canada, and evaluate it using NO2 from satellite and surface monitoring networks and simulations by an air quality forecast model. We quantify and explain the differences among the datasets to provide information that can be used to understand NO2 variability.
Zachary Watson, Can Li, Fei Liu, Sean W. Freeman, Huanxin Zhang, Jun Wang, and Shan-Hu Lee
EGUsphere, https://doi.org/10.5194/egusphere-2025-1735, https://doi.org/10.5194/egusphere-2025-1735, 2025
Short summary
Short summary
Air pollutants like sulfur dioxide cause direct impacts on human health and the environment. Our work estimated surface concentrations from satellite data using atmospheric models and machine learning compared to an air quality monitoring network. We found that both methods can accurately determine the locations and changes in sulfur dioxide, but the machine learning method had better accuracy. Both methods are useful for monitoring air quality in locations without ground-based measurements.
Debora Griffin, Colin Hempel, Chris McLinden, Shailesh Kumar Kharol, Colin Lee, Andre Fogal, Christopher Sioris, Mark Shephard, and Yuan You
EGUsphere, https://doi.org/10.5194/egusphere-2025-1681, https://doi.org/10.5194/egusphere-2025-1681, 2025
Short summary
Short summary
Surface NO2 concentrations are obtained across North America using satellite data and machine learning, and compared to traditional approaches to determine surface NO2 from satellite observations.
Vitali Fioletov, Chris A. McLinden, Debora Griffin, Xiaoyi Zhao, and Henk Eskes
Atmos. Chem. Phys., 25, 575–596, https://doi.org/10.5194/acp-25-575-2025, https://doi.org/10.5194/acp-25-575-2025, 2025
Short summary
Short summary
Satellite data were used to estimate urban per capita emissions for 261 major cities worldwide. Three components in tropospheric NO2 data (background NO2, NO2 from urban sources, and NO2 from industrial point sources) were isolated, and then each of these components was analyzed separately. The largest per capita emissions were found in the Middle East and the smallest in India and southern Africa. Urban weekend emissions are 20 %–50 % less than workday emissions for all regions except China.
Xiaoyi Zhao, Vitali Fioletov, Debora Griffin, Chris McLinden, Ralf Staebler, Cristian Mihele, Kevin Strawbridge, Jonathan Davies, Ihab Abboud, Sum Chi Lee, Alexander Cede, Martin Tiefengraber, and Robert Swap
Atmos. Meas. Tech., 17, 6889–6912, https://doi.org/10.5194/amt-17-6889-2024, https://doi.org/10.5194/amt-17-6889-2024, 2024
Short summary
Short summary
This study explores differences between remote sensing and in situ instruments in terms of their vertical, horizontal, and temporal sampling differences. Understanding and resolving these differences are critical for future analyses linking satellite, ground-based remote sensing, and in situ observations in air quality monitoring. It shows that the meteorological conditions (wind directions, speed, and boundary layer conditions) will strongly affect the agreement between the two measurements.
Bryan N. Duncan, Daniel C. Anderson, Arlene M. Fiore, Joanna Joiner, Nickolay A. Krotkov, Can Li, Dylan B. Millet, Julie M. Nicely, Luke D. Oman, Jason M. St. Clair, Joshua D. Shutter, Amir H. Souri, Sarah A. Strode, Brad Weir, Glenn M. Wolfe, Helen M. Worden, and Qindan Zhu
Atmos. Chem. Phys., 24, 13001–13023, https://doi.org/10.5194/acp-24-13001-2024, https://doi.org/10.5194/acp-24-13001-2024, 2024
Short summary
Short summary
Trace gases emitted to or formed within the atmosphere may be chemically or physically removed from the atmosphere. One trace gas, the hydroxyl radical (OH), is responsible for initiating the chemical removal of many trace gases, including some greenhouse gases. Despite its importance, scientists have not been able to adequately measure OH. In this opinion piece, we discuss promising new methods to indirectly constrain OH using satellite data of trace gases that control the abundance of OH.
Can Li, Nickolay A. Krotkov, Joanna Joiner, Vitali Fioletov, Chris McLinden, Debora Griffin, Peter J. T. Leonard, Simon Carn, Colin Seftor, and Alexander Vasilkov
Earth Syst. Sci. Data, 16, 4291–4309, https://doi.org/10.5194/essd-16-4291-2024, https://doi.org/10.5194/essd-16-4291-2024, 2024
Short summary
Short summary
Sulfur dioxide (SO2), a poisonous gas from human activities and volcanoes, causes air pollution, acid rain, and changes to climate and the ozone layer. Satellites have been used to monitor SO2 globally, including remote areas. Here we describe a new satellite SO2 dataset from the OMPS instrument that flies on the N20 satellite. Results show that the new dataset agrees well with the existing ones from other satellites and can help to continue the global monitoring of SO2 from space.
Debora Griffin, Jack Chen, Kerry Anderson, Paul Makar, Chris A. McLinden, Enrico Dammers, and Andre Fogal
Atmos. Chem. Phys., 24, 10159–10186, https://doi.org/10.5194/acp-24-10159-2024, https://doi.org/10.5194/acp-24-10159-2024, 2024
Short summary
Short summary
Satellite-derived CO emissions provide new insights into the understanding of global CO emission rates from wildfires. We use TROPOMI satellite data to create a global inventory database of wildfire CO emissions. These satellite-derived wildfire emissions are used for the evaluation and improvement of existing fire emission inventories and to examine how the wildfire CO emissions have changed over the past 2 decades.
Enrico Dammers, Janot Tokaya, Christian Mielke, Kevin Hausmann, Debora Griffin, Chris McLinden, Henk Eskes, and Renske Timmermans
Geosci. Model Dev., 17, 4983–5007, https://doi.org/10.5194/gmd-17-4983-2024, https://doi.org/10.5194/gmd-17-4983-2024, 2024
Short summary
Short summary
Nitrogen dioxide (NOx) is produced by sources such as industry and traffic and is directly linked to negative impacts on health and the environment. The current construction of emission inventories to keep track of NOx emissions is slow and time-consuming. Satellite measurements provide a way to quickly and independently estimate emissions. In this study, we apply a consistent methodology to derive NOx emissions over Germany and illustrate the value of having such a method for fast projections.
Fei Liu, Steffen Beirle, Joanna Joiner, Sungyeon Choi, Zhining Tao, K. Emma Knowland, Steven J. Smith, Daniel Q. Tong, Siqi Ma, Zachary T. Fasnacht, and Thomas Wagner
Atmos. Chem. Phys., 24, 3717–3728, https://doi.org/10.5194/acp-24-3717-2024, https://doi.org/10.5194/acp-24-3717-2024, 2024
Short summary
Short summary
Using satellite data, we developed a coupled method independent of the chemical transport model to map NOx emissions across US cities. After validating our technique with synthetic data, we charted NOx emissions from 2018–2021 in 39 cities. Our results closely matched EPA estimates but also highlighted some inconsistencies in both magnitude and spatial distribution. This research can help refine strategies for monitoring and managing air quality.
Lukas Fehr, Chris McLinden, Debora Griffin, Daniel Zawada, Doug Degenstein, and Adam Bourassa
Geosci. Model Dev., 16, 7491–7507, https://doi.org/10.5194/gmd-16-7491-2023, https://doi.org/10.5194/gmd-16-7491-2023, 2023
Short summary
Short summary
This work highlights upgrades to SASKTRAN, a model that simulates sunlight interacting with the atmosphere to help measure trace gases. The upgrades were verified by detailed comparisons between different numerical methods. A case study was performed using SASKTRAN’s multidimensional capabilities, which found that ignoring horizontal variation in the atmosphere (a common practice in the field) can introduce non-negligible errors where there is snow or high pollution.
Tianle Yuan, Fei Liu, Lok N. Lamsal, and Hua Song
EGUsphere, https://doi.org/10.22541/essoar.168771101.14987378/v1, https://doi.org/10.22541/essoar.168771101.14987378/v1, 2023
Preprint archived
Short summary
Short summary
We train and apply a state-of-the-art deep learning model to detect NO2 plumes emitted by ships using NO2 retrievals from TROPOMI. By applying the model, we can detect individual plumes with excellent fidelity. The aggregated data show major shipping routes, but miss other routes. The missing routes are due to high cloudiness. Our method can be potentially useful for monitoring ship emissions of NOx and verifying compliance of emission standards.
Vitali E. Fioletov, Chris A. McLinden, Debora Griffin, Nickolay A. Krotkov, Can Li, Joanna Joiner, Nicolas Theys, and Simon Carn
Atmos. Meas. Tech., 16, 5575–5592, https://doi.org/10.5194/amt-16-5575-2023, https://doi.org/10.5194/amt-16-5575-2023, 2023
Short summary
Short summary
Snow-covered terrain, with its high reflectance in the UV, typically enhances satellite sensitivity to boundary layer pollution. However, a significant fraction of high-quality cloud-free measurements over snow is currently excluded from analyses. In this study, we investigated how satellite SO2 measurements over snow-covered surfaces can be used to improve estimations of annual SO2 emissions.
Vitali Fioletov, Xiaoyi Zhao, Ihab Abboud, Michael Brohart, Akira Ogyu, Reno Sit, Sum Chi Lee, Irina Petropavlovskikh, Koji Miyagawa, Bryan J. Johnson, Patrick Cullis, John Booth, Glen McConville, and C. Thomas McElroy
Atmos. Chem. Phys., 23, 12731–12751, https://doi.org/10.5194/acp-23-12731-2023, https://doi.org/10.5194/acp-23-12731-2023, 2023
Short summary
Short summary
Stratospheric ozone within the Southern Hemisphere springtime polar vortex has been a subject of intense research since the discovery of the Antarctic ozone hole. The wintertime ozone in the vortex is less studied. We show that the recent wintertime ozone values over the South Pole were about 12 % below the pre-1980s level; i.e., the decline there was nearly twice as large as that over southern midlatitudes. Thus, wintertime ozone there can be used as an indicator of the ozone layer state.
Xiaoyi Zhao, Vitali Fioletov, Alberto Redondas, Julian Gröbner, Luca Egli, Franz Zeilinger, Javier López-Solano, Alberto Berjón Arroyo, James Kerr, Eliane Maillard Barras, Herman Smit, Michael Brohart, Reno Sit, Akira Ogyu, Ihab Abboud, and Sum Chi Lee
Atmos. Meas. Tech., 16, 2273–2295, https://doi.org/10.5194/amt-16-2273-2023, https://doi.org/10.5194/amt-16-2273-2023, 2023
Short summary
Short summary
The Brewer ozone spectrophotometer is one of the World Meteorological Organization (WMO) Global Atmosphere Watch (GAW)'s standard ozone monitoring instruments since the 1980s. This work is aimed at obtaining answers to (1) why Brewer primary calibration work can only be performed at certain sites (e.g., Izaña and MLO) and (2) what is needed to assure the equivalence of calibration quality from different sites.
Nick Gorkavyi, Nickolay Krotkov, and Alexander Marshak
Atmos. Meas. Tech., 16, 1527–1537, https://doi.org/10.5194/amt-16-1527-2023, https://doi.org/10.5194/amt-16-1527-2023, 2023
Short summary
Short summary
The article discusses topical issues of the visible (libration) motion of the Earth in the sky of the Moon in a rectangle measuring 13.4° × 15.8°. On the one hand, the librations of the Moon make these observations difficult. On the other hand, they can be used as a natural scanning mechanism for cameras and spectroscopes mounted on a fixed platform on the surface of the Moon.
Joanna Joiner, Sergey Marchenko, Zachary Fasnacht, Lok Lamsal, Can Li, Alexander Vasilkov, and Nickolay Krotkov
Atmos. Meas. Tech., 16, 481–500, https://doi.org/10.5194/amt-16-481-2023, https://doi.org/10.5194/amt-16-481-2023, 2023
Short summary
Short summary
Nitrogen dioxide (NO2) is an important trace gas for both air quality and climate. NO2 affects satellite ocean color products. A new ocean color instrument – OCI (Ocean Color Instrument) – will be launched in 2024 on a NASA satellite. We show that it will be possible to measure NO2 from OCI even though it was not designed for this. The techniques developed here, based on machine learning, can also be applied to instruments already in space to speed up algorithms and reduce the effects of noise.
Jing Wei, Zhanqing Li, Jun Wang, Can Li, Pawan Gupta, and Maureen Cribb
Atmos. Chem. Phys., 23, 1511–1532, https://doi.org/10.5194/acp-23-1511-2023, https://doi.org/10.5194/acp-23-1511-2023, 2023
Short summary
Short summary
This study estimated the daily seamless 10 km ambient gaseous pollutants (NO2, SO2, and CO) across China using machine learning with extensive input variables measured on monitors, satellites, and models. Our dataset yields a high data quality via cross-validation at varying spatiotemporal scales and outperforms most previous related studies, making it most helpful to future (especially short-term) air pollution and environmental health-related studies.
Vitali E. Fioletov, Chris A. McLinden, Debora Griffin, Ihab Abboud, Nickolay Krotkov, Peter J. T. Leonard, Can Li, Joanna Joiner, Nicolas Theys, and Simon Carn
Earth Syst. Sci. Data, 15, 75–93, https://doi.org/10.5194/essd-15-75-2023, https://doi.org/10.5194/essd-15-75-2023, 2023
Short summary
Short summary
Sulfur dioxide (SO2) measurements from three satellite instruments were used to update and extend the previously developed global catalogue of large SO2 emission sources. This version 2 of the global catalogue covers the period of 2005–2021 and includes a total of 759 continuously emitting point sources. The catalogue data show an approximate 50 % decline in global SO2 emissions between 2005 and 2021, although emissions were relatively stable during the last 3 years.
Aaron Pearlman, Monica Cook, Boryana Efremova, Francis Padula, Lok Lamsal, Joel McCorkel, and Joanna Joiner
Atmos. Meas. Tech., 15, 4489–4501, https://doi.org/10.5194/amt-15-4489-2022, https://doi.org/10.5194/amt-15-4489-2022, 2022
Short summary
Short summary
NOAA’s Geostationary Extended Observations (GeoXO) constellation is planned to consist of an atmospheric composition instrument (ACX) to support air quality forecasting and monitoring. As design trade-offs are being studied, we investigated one parameter, the polarization sensitivity, which has yet to be fully documented for NO2 retrievals. Our simulation study explores these impacts to inform the ACX’s development and better understand polarization’s role in trace gas retrievals.
Mark Weber, Carlo Arosio, Melanie Coldewey-Egbers, Vitali E. Fioletov, Stacey M. Frith, Jeannette D. Wild, Kleareti Tourpali, John P. Burrows, and Diego Loyola
Atmos. Chem. Phys., 22, 6843–6859, https://doi.org/10.5194/acp-22-6843-2022, https://doi.org/10.5194/acp-22-6843-2022, 2022
Short summary
Short summary
Long-term trends in column ozone have been determined from five merged total ozone datasets spanning the period 1978–2020. We show that ozone recovery due to the decline in stratospheric halogens after the 1990s (as regulated by the Montreal Protocol) is evident outside the tropical region and amounts to half a percent per decade. The ozone recovery in the Northern Hemisphere is however compensated for by the negative long-term trend contribution from atmospheric dynamics since the year 2000.
Vitali Fioletov, Chris A. McLinden, Debora Griffin, Nickolay Krotkov, Fei Liu, and Henk Eskes
Atmos. Chem. Phys., 22, 4201–4236, https://doi.org/10.5194/acp-22-4201-2022, https://doi.org/10.5194/acp-22-4201-2022, 2022
Short summary
Short summary
The COVID-19 lockdown had a large impact on anthropogenic emissions and particularly on nitrogen dioxide (NO2). A new method of isolation of background, urban, and industrial components in NO2 is applied to estimate the lockdown impact on each of them. From 16 March to 15 June 2020, urban NO2 declined by −18 % to −28 % in most regions of the world, while background NO2 typically declined by less than −10 %.
Fei Liu, Zhining Tao, Steffen Beirle, Joanna Joiner, Yasuko Yoshida, Steven J. Smith, K. Emma Knowland, and Thomas Wagner
Atmos. Chem. Phys., 22, 1333–1349, https://doi.org/10.5194/acp-22-1333-2022, https://doi.org/10.5194/acp-22-1333-2022, 2022
Short summary
Short summary
In this work, we present a novel method to infer NOx emissions and lifetimes based on tropospheric NO2 observations together with reanalysis wind fields for cities located in polluted backgrounds. We evaluate the accuracy of the method using synthetic NO2 observations derived from a high-resolution model simulation. Our work provides an estimate for uncertainties in satellite-derived emissions inferred from chemical transport model (CTM)-independent approaches.
Mahtab Majdzadeh, Craig A. Stroud, Christopher Sioris, Paul A. Makar, Ayodeji Akingunola, Chris McLinden, Xiaoyi Zhao, Michael D. Moran, Ihab Abboud, and Jack Chen
Geosci. Model Dev., 15, 219–249, https://doi.org/10.5194/gmd-15-219-2022, https://doi.org/10.5194/gmd-15-219-2022, 2022
Short summary
Short summary
A new lookup table for aerosol optical properties based on a Mie scattering code was calculated and adopted within an improved version of the photolysis module in the GEM-MACH in-line chemical transport model. The modified version of the photolysis module makes use of online interactive aerosol feedback and applies core-shell parameterizations to the black carbon absorption efficiency based on Bond et al. (2006) to the size bins with black carbon mass fraction of less than 40 %.
Debora Griffin, Chris A. McLinden, Enrico Dammers, Cristen Adams, Chelsea E. Stockwell, Carsten Warneke, Ilann Bourgeois, Jeff Peischl, Thomas B. Ryerson, Kyle J. Zarzana, Jake P. Rowe, Rainer Volkamer, Christoph Knote, Natalie Kille, Theodore K. Koenig, Christopher F. Lee, Drew Rollins, Pamela S. Rickly, Jack Chen, Lukas Fehr, Adam Bourassa, Doug Degenstein, Katherine Hayden, Cristian Mihele, Sumi N. Wren, John Liggio, Ayodeji Akingunola, and Paul Makar
Atmos. Meas. Tech., 14, 7929–7957, https://doi.org/10.5194/amt-14-7929-2021, https://doi.org/10.5194/amt-14-7929-2021, 2021
Short summary
Short summary
Satellite-derived NOx emissions from biomass burning are estimated with TROPOMI observations. Two common emission estimation methods are applied, and sensitivity tests with model output were performed to determine the accuracy of these methods. The effect of smoke aerosols on TROPOMI NO2 columns is estimated and compared to aircraft observations from four different aircraft campaigns measuring biomass burning plumes in 2018 and 2019 in North America.
Catherine Hardacre, Jane P. Mulcahy, Richard J. Pope, Colin G. Jones, Steven T. Rumbold, Can Li, Colin Johnson, and Steven T. Turnock
Atmos. Chem. Phys., 21, 18465–18497, https://doi.org/10.5194/acp-21-18465-2021, https://doi.org/10.5194/acp-21-18465-2021, 2021
Short summary
Short summary
We investigate UKESM1's ability to represent the sulfur (S) cycle in the recent historical period. The S cycle is a key driver of historical radiative forcing. Earth system models such as UKESM1 should represent the S cycle well so that we can have confidence in their projections of future climate. We compare UKESM1 to observations of sulfur compounds, finding that the model generally performs well. We also identify areas for UKESM1’s development, focussing on how SO2 is removed from the air.
Nick Gorkavyi, Nickolay Krotkov, Can Li, Leslie Lait, Peter Colarco, Simon Carn, Matthew DeLand, Paul Newman, Mark Schoeberl, Ghassan Taha, Omar Torres, Alexander Vasilkov, and Joanna Joiner
Atmos. Meas. Tech., 14, 7545–7563, https://doi.org/10.5194/amt-14-7545-2021, https://doi.org/10.5194/amt-14-7545-2021, 2021
Short summary
Short summary
The 21 June 2019 eruption of the Raikoke volcano produced significant amounts of volcanic aerosols (sulfate and ash) and sulfur dioxide (SO2) gas that penetrated into the lower stratosphere. We showed that the amount of SO2 decreases with a characteristic period of 8–18 d and the peak of sulfate aerosol lags the initial peak of SO2 by 1.5 months. We also examined the dynamics of an unusual stratospheric coherent circular cloud of SO2 and aerosol observed from 18 July to 22 September 2019.
Luis Guanter, Cédric Bacour, Andreas Schneider, Ilse Aben, Tim A. van Kempen, Fabienne Maignan, Christian Retscher, Philipp Köhler, Christian Frankenberg, Joanna Joiner, and Yongguang Zhang
Earth Syst. Sci. Data, 13, 5423–5440, https://doi.org/10.5194/essd-13-5423-2021, https://doi.org/10.5194/essd-13-5423-2021, 2021
Short summary
Short summary
Sun-induced chlorophyll fluorescence (SIF) is an electromagnetic signal emitted by plants in the red and far-red parts of the spectrum. It has a functional link to photosynthesis and can be measured by satellite instruments, which makes it an important variable for the remote monitoring of the photosynthetic activity of vegetation ecosystems around the world. In this contribution we present a SIF dataset derived from the new Sentinel-5P TROPOMI missions.
Nicolas Theys, Vitali Fioletov, Can Li, Isabelle De Smedt, Christophe Lerot, Chris McLinden, Nickolay Krotkov, Debora Griffin, Lieven Clarisse, Pascal Hedelt, Diego Loyola, Thomas Wagner, Vinod Kumar, Antje Innes, Roberto Ribas, François Hendrick, Jonas Vlietinck, Hugues Brenot, and Michel Van Roozendael
Atmos. Chem. Phys., 21, 16727–16744, https://doi.org/10.5194/acp-21-16727-2021, https://doi.org/10.5194/acp-21-16727-2021, 2021
Short summary
Short summary
We present a new algorithm to retrieve sulfur dioxide from space UV measurements. We apply the technique to high-resolution TROPOMI measurements and demonstrate the high sensitivity of the approach to weak SO2 emissions worldwide with an unprecedented limit of detection of 8 kt yr−1. This result has broad implications for atmospheric science studies dealing with improving emission inventories and identifying and quantifying missing sources, in the context of air quality and climate.
Antti Arola, William Wandji Nyamsi, Antti Lipponen, Stelios Kazadzis, Nickolay A. Krotkov, and Johanna Tamminen
Atmos. Meas. Tech., 14, 4947–4957, https://doi.org/10.5194/amt-14-4947-2021, https://doi.org/10.5194/amt-14-4947-2021, 2021
Short summary
Short summary
Methods to estimate surface UV radiation from satellite measurements offer the only means to obtain global coverage, and the development of satellite-based UV algorithms has been ongoing since the early 1990s. One of the main challenges in this development has been how to account for the overall effect of absorption by atmospheric aerosols. One such method was suggested roughly a decade ago, and in this study we propose further improvements for this kind of approach.
Nikita M. Fedkin, Can Li, Nickolay A. Krotkov, Pascal Hedelt, Diego G. Loyola, Russell R. Dickerson, and Robert Spurr
Atmos. Meas. Tech., 14, 3673–3691, https://doi.org/10.5194/amt-14-3673-2021, https://doi.org/10.5194/amt-14-3673-2021, 2021
Short summary
Short summary
This study presents a new volcanic sulfur dioxide (SO2) layer height retrieval algorithm for the Ozone Monitoring Instrument (OMI). We generated a large spectral dataset with a radiative transfer model and used it to train neural networks to predict SO2 height from OMI radiance data. The algorithm is fast and takes less than 10 min for a single orbit. Retrievals were tested on four eruption cases, and results had reasonable agreement (within 2 km) with other retrievals and previous studies.
Michaela I. Hegglin, Susann Tegtmeier, John Anderson, Adam E. Bourassa, Samuel Brohede, Doug Degenstein, Lucien Froidevaux, Bernd Funke, John Gille, Yasuko Kasai, Erkki T. Kyrölä, Jerry Lumpe, Donal Murtagh, Jessica L. Neu, Kristell Pérot, Ellis E. Remsberg, Alexei Rozanov, Matthew Toohey, Joachim Urban, Thomas von Clarmann, Kaley A. Walker, Hsiang-Jui Wang, Carlo Arosio, Robert Damadeo, Ryan A. Fuller, Gretchen Lingenfelser, Christopher McLinden, Diane Pendlebury, Chris Roth, Niall J. Ryan, Christopher Sioris, Lesley Smith, and Katja Weigel
Earth Syst. Sci. Data, 13, 1855–1903, https://doi.org/10.5194/essd-13-1855-2021, https://doi.org/10.5194/essd-13-1855-2021, 2021
Short summary
Short summary
An overview of the SPARC Data Initiative is presented, to date the most comprehensive assessment of stratospheric composition measurements spanning 1979–2018. Measurements of 26 chemical constituents obtained from an international suite of space-based limb sounders were compiled into vertically resolved, zonal monthly mean time series. The quality and consistency of these gridded datasets are then evaluated using a climatological validation approach and a range of diagnostics.
Alexander Vasilkov, Nickolay Krotkov, Eun-Su Yang, Lok Lamsal, Joanna Joiner, Patricia Castellanos, Zachary Fasnacht, and Robert Spurr
Atmos. Meas. Tech., 14, 2857–2871, https://doi.org/10.5194/amt-14-2857-2021, https://doi.org/10.5194/amt-14-2857-2021, 2021
Short summary
Short summary
To explicitly account for aerosol effects in the OMI cloud and nitrogen dioxide algorithms, we use a model of aerosol optical properties from a global aerosol assimilation system and radiative transfer computations. Accounting for anisotropic reflection of Earth's surface is an important feature of the approach. Comparisons of the cloud and tropospheric nitrogen dioxide retrievals with implicit and explicit aerosol corrections are carried out for a selected area with high pollution.
Eloise A. Marais, John F. Roberts, Robert G. Ryan, Henk Eskes, K. Folkert Boersma, Sungyeon Choi, Joanna Joiner, Nader Abuhassan, Alberto Redondas, Michel Grutter, Alexander Cede, Laura Gomez, and Monica Navarro-Comas
Atmos. Meas. Tech., 14, 2389–2408, https://doi.org/10.5194/amt-14-2389-2021, https://doi.org/10.5194/amt-14-2389-2021, 2021
Short summary
Short summary
Nitrogen oxides in the upper troposphere have a profound influence on the global troposphere, but routine reliable observations there are exceedingly rare. We apply cloud-slicing to TROPOMI total columns of nitrogen dioxide (NO2) at high spatial resolution to derive near-global observations of NO2 in the upper troposphere and show consistency with existing datasets. These data offer tremendous potential to address knowledge gaps in this oft underappreciated portion of the atmosphere.
Xiaoyi Zhao, Vitali Fioletov, Michael Brohart, Volodya Savastiouk, Ihab Abboud, Akira Ogyu, Jonathan Davies, Reno Sit, Sum Chi Lee, Alexander Cede, Martin Tiefengraber, Moritz Müller, Debora Griffin, and Chris McLinden
Atmos. Meas. Tech., 14, 2261–2283, https://doi.org/10.5194/amt-14-2261-2021, https://doi.org/10.5194/amt-14-2261-2021, 2021
Short summary
Short summary
The Brewer spectrophotometer is one of the main instruments for measurements of atmospheric total column ozone. The global Brewer network largely relies on the world reference instruments (the Brewer triad) operated by Environment and Climate Change Canada since the early 1980s. This study provides an updated assessment (1999–2019) of the reference instrument performance, in terms of random uncertainties and long-term stability.
Junjie Liu, Latha Baskaran, Kevin Bowman, David Schimel, A. Anthony Bloom, Nicholas C. Parazoo, Tomohiro Oda, Dustin Carroll, Dimitris Menemenlis, Joanna Joiner, Roisin Commane, Bruce Daube, Lucianna V. Gatti, Kathryn McKain, John Miller, Britton B. Stephens, Colm Sweeney, and Steven Wofsy
Earth Syst. Sci. Data, 13, 299–330, https://doi.org/10.5194/essd-13-299-2021, https://doi.org/10.5194/essd-13-299-2021, 2021
Short summary
Short summary
On average, the terrestrial biosphere carbon sink is equivalent to ~ 20 % of fossil fuel emissions. Understanding where and why the terrestrial biosphere absorbs carbon from the atmosphere is pivotal to any mitigation policy. Here we present a regionally resolved satellite-constrained net biosphere exchange (NBE) dataset with corresponding uncertainties between 2010–2018: CMS-Flux NBE 2020. The dataset provides a unique perspective on monitoring regional contributions to the CO2 growth rate.
Nick Gorkavyi, Zachary Fasnacht, David Haffner, Sergey Marchenko, Joanna Joiner, and Alexander Vasilkov
Atmos. Meas. Tech., 14, 961–974, https://doi.org/10.5194/amt-14-961-2021, https://doi.org/10.5194/amt-14-961-2021, 2021
Short summary
Short summary
Various instrumental or geophysical artifacts, such as saturation, stray light or obstruction of light, negatively impact satellite measured ultraviolet and visible Earthshine radiance spectra. Here, we introduce a straightforward detection method that is based on the correlation, r, between the observed Earthshine radiance and solar irradiance spectra over a 10 nm spectral range; our decorrelation index (DI for brevity) is simply defined as DI of 1–r.
Elena Spinei, Martin Tiefengraber, Moritz Müller, Manuel Gebetsberger, Alexander Cede, Luke Valin, James Szykman, Andrew Whitehill, Alexander Kotsakis, Fernando Santos, Nader Abbuhasan, Xiaoyi Zhao, Vitali Fioletov, Sum Chi Lee, and Robert Swap
Atmos. Meas. Tech., 14, 647–663, https://doi.org/10.5194/amt-14-647-2021, https://doi.org/10.5194/amt-14-647-2021, 2021
Short summary
Short summary
Plastics are widely used in everyday life and scientific equipment. This paper presents Delrin plastic off-gassing as a function of temperature on the atmospheric measurements of formaldehyde by Pandora spectroscopic instruments. The sealed telescope assembly containing Delrin components emitted large amounts of formaldehyde at 30–45 °C, interfering with the Pandora measurements. These results have a broader implication since electronic products often experience the same temperature.
Lok N. Lamsal, Nickolay A. Krotkov, Alexander Vasilkov, Sergey Marchenko, Wenhan Qin, Eun-Su Yang, Zachary Fasnacht, Joanna Joiner, Sungyeon Choi, David Haffner, William H. Swartz, Bradford Fisher, and Eric Bucsela
Atmos. Meas. Tech., 14, 455–479, https://doi.org/10.5194/amt-14-455-2021, https://doi.org/10.5194/amt-14-455-2021, 2021
Short summary
Short summary
The NASA standard nitrogen dioxide (NO2) version 4.0 product for OMI Aura incorporates the most salient improvements. It represents the first global satellite trace gas retrieval with OMI–MODIS synergy accounting for surface reflectance anisotropy in cloud and NO2 retrievals. Improved spectral fitting procedures for NO2 and oxygen dimer (for cloud) retrievals and reliance on high-resolution field-of-view-specific input information for NO2 and cloud retrievals help enhance the NO2 data quality.
Can Li, Nickolay A. Krotkov, Peter J. T. Leonard, Simon Carn, Joanna Joiner, Robert J. D. Spurr, and Alexander Vasilkov
Atmos. Meas. Tech., 13, 6175–6191, https://doi.org/10.5194/amt-13-6175-2020, https://doi.org/10.5194/amt-13-6175-2020, 2020
Short summary
Short summary
Sulfur dioxide (SO2) is an important pollutant that causes haze and acid rain. The Ozone Monitoring Instrument (OMI) has been providing global observation of SO2 from space for over 15 years. In this paper, we introduce a new OMI SO2 dataset for global pollution monitoring. The dataset better accounts for the influences of different factors such as location and sun and satellite angles, leading to improved data quality. The new OMI SO2 dataset is publicly available through NASA's data center.
Cited articles
Bhartia, P. K.: OMI/Aura Ozone (O3) Total Column 1-Orbit L2 Swath 13x24
km V003, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set], Greenbelt, MD, USA, https://doi.org/10.5067/Aura/OMI/DATA2024, 2005.
Castellanos, P. and da Silva, A.: A neural network correction to the scalar
approximation in radiative transfer, J. Atmos. Ocean. Tech., 36, 819–832,
https://doi.org/10.1175/JTECH-D-18-0003.1, 2019.
Chan, K. L., Khorsandi, E., Liu, S., Baier, F., and Valks, P.: Estimation of
surface NO2 concentrations over Germany from TROPOMI satellite
observations using a machine learning method, Remote Sens., 13, 969,
https://doi.org/10.3390/rs13050969, 2021.
Chimot, J., Veefkind, J. P., Vlemmix, T., de Haan, J. F., Amiridis, V., Proestakis, E., Marinou, E., and Levelt, P. F.: An exploratory study on the aerosol height retrieval from OMI measurements of the 477 nm O2 – O2 spectral band using a neural network approach, Atmos. Meas. Tech., 10, 783–809, https://doi.org/10.5194/amt-10-783-2017, 2017.
De Santis, D., Petracca, I., Corradini, S., Guerrieri, L., Picchiani, M.,
Merucci, L., Stelitano, D., Del Frate, F., Prata, F., and Schiavon, G.:
Volcanic SO2 near-real time retrieval using TROPOMI data and neural
networks: The December 2018 Etna test case, 2021 IEEE International
Geoscience and Remote Sensing Symposium IGARSS, Brussels, Belgium, 12–16 July 2021, 8480–8483, https://doi.org/10.1109/IGARSS47720.2021.9554915, 2021.
Eisinger, M. and Burrows, J. P.: Tropospheric sulfur dioxide observed by the
ERS-2 GOME instrument, Geophys. Res. Lett., 25, 4177–4180,
https://doi.org/10.1029/1998GL900128, 1998.
Fedkin, N. M., Li, C., Krotkov, N. A., Hedelt, P., Loyola, D. G., Dickerson, R. R., and Spurr, R.: Volcanic SO2 effective layer height retrieval for the Ozone Monitoring Instrument (OMI) using a machine-learning approach, Atmos. Meas. Tech., 14, 3673–3691, https://doi.org/10.5194/amt-14-3673-2021, 2021.
Fioletov, V. E., McLinden, C., Krotkov, N. A., and Li, C.: Lifetimes and
emissions of SO2 from point sources estimated from OMI, Geophys. Res.
Lett., 42, 1969–1976, https://doi.org/10.1002/2015GL063148, 2015.
Fioletov, V. E., McLinden, C. A., Krotkov, N., Li, C., Joiner, J., Theys, N., Carn, S., and Moran, M. D.: A global catalogue of large SO2 sources and emissions derived from the Ozone Monitoring Instrument, Atmos. Chem. Phys., 16, 11497–11519, https://doi.org/10.5194/acp-16-11497-2016, 2016.
Hedelt, P., Efremenko, D. S., Loyola, D. G., Spurr, R., and Clarisse, L.: Sulfur dioxide layer height retrieval from Sentinel-5 Precursor/TROPOMI using FP_ILM, Atmos. Meas. Tech., 12, 5503–5517, https://doi.org/10.5194/amt-12-5503-2019, 2019.
Huang, C., Hu, J., Xue, T., Xu, H., and Wang, M.: High-resolution spatiotemporal modeling for ambient PM2.5 exposure assessments in China from 2013 to 2019, Environ. Sci. Technol., 55, 2152–2162,
https://doi.org/10.1021/acs.est.0c05815, 2021.
Joiner, J. and Vasilkov, A. P.: First results from the OMI rotational-Raman
scattering cloud pressure algorithm, IEEE T. Geosci. Remote, 44, 1272–1282, 2006.
Joiner, J. and Yoshida, Y.: Satellite-based reflectances capture large
fraction of variability in global gross primary production (GPP) at weekly
time scales, Agr. Forest. Meteorol., 291, 108092, https://doi.org/10.1016/j.agrformet.2020.108092, 2020.
Joiner, J., Fasnacht, Z., Gao, B.-C., and Qin, W.: Use of multi-spectral
visible and near-infrared satellite data for timely estimates of the Earth's
surface reflectance in cloudy and aerosol loaded conditions: Part 2 – image
restoration with HICO satellite data in overcast conditions, Frontiers in Remote Sensing, 2. https://doi.org/10.3389/frsen.2021.721957, 2021.
Joiner, J., Fasnacht, Z., Qin, W., Yoshida, Y., Vasilkov, A. P., Li, C.,
Lamsal, L., and Krotkov, N.: Use of hyper-spectral visible and near-infrared
satellite data for timely estimates of the Earth's surface reflectance in
cloudy and aerosol loaded conditions: Part 1 – application to RGB image
restoration over land with GOME-2, Frontiers in Remote Sensing, 2, 716430,
https://doi.org/10.3389/frsen.2021.716430, 2022.
Kingma, D. P. and Ba, J.: Adam: A method for stochastic optimization, arXiv [preprint] arXiv:1412.6980, https://doi.org/10.48550/arXiv.1412.6980, 22 December 2014.
Kleipool, Q.: OMI/Aura Level 1B UV Global Geolocated Earthshine Radiances V004 (OML1BRUG), Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set], Greenbelt, MD, USA, https://doi.org/10.5067/AURA/OMI/DATA1402, 2021.
Krotkov, N. A., Carn, S. A., Krueger, A. J., Bhartia, P. K., and Yang, K.:
Band residual difference algorithm for retrieval of SO2 from the Aura
Ozone Monitoring Instrument (OMI), IEEE T. Geosci. Remote, 44, 1259–1266, https://doi.org/10.1109/TGRS.2005.861932, 2006.
Krotkov, N. A., McClure, B., Dickerson, R. R., Carn, S. A., Li, C., Bhartia,
P. K., Yang, K., Krueger, A. J., Li, Z., Levelt, P. F., Chen, H., Wang, P.,
and Lu, D.: Validation of SO2 retrievals from the Ozone Monitoring
Instrument over NE China, J. Geophys. Res.-Atmos., 113, D16S40,
https://doi.org/10.1029/2007JD008818, 2008.
Krotkov, N. A., McLinden, C. A., Li, C., Lamsal, L. N., Celarier, E. A., Marchenko, S. V., Swartz, W. H., Bucsela, E. J., Joiner, J., Duncan, B. N., Boersma, K. F., Veefkind, J. P., Levelt, P. F., Fioletov, V. E., Dickerson, R. R., He, H., Lu, Z., and Streets, D. G.: Aura OMI observations of regional SO2 and NO2 pollution changes from 2005 to 2015, Atmos. Chem. Phys., 16, 4605–4629, https://doi.org/10.5194/acp-16-4605-2016, 2016.
Lee, C., Martin, R. V., van Donkelaar, A., Lee, H., Dickerson R. R.,
Krotkov, N., Richter, A., Vinnikov, K., and Schwab, J. J.: SO2
emissions and lifetimes: Estimates from inverse modeling using in situ and
global, space-based (SCIAMACHY and OMI) observations, J. Geophys.
Res.-Atmos., 116, D06304, https://doi.org/10.1029/2010JD014758, 2011.
Levelt, P. F., Joiner, J., Tamminen, J., Veefkind, J. P., Bhartia, P. K., Stein Zweers, D. C., Duncan, B. N., Streets, D. G., Eskes, H., van der A, R., McLinden, C., Fioletov, V., Carn, S., de Laat, J., DeLand, M., Marchenko, S., McPeters, R., Ziemke, J., Fu, D., Liu, X., Pickering, K., Apituley, A., González Abad, G., Arola, A., Boersma, F., Chan Miller, C., Chance, K., de Graaf, M., Hakkarainen, J., Hassinen, S., Ialongo, I., Kleipool, Q., Krotkov, N., Li, C., Lamsal, L., Newman, P., Nowlan, C., Suleiman, R., Tilstra, L. G., Torres, O., Wang, H., and Wargan, K.: The Ozone Monitoring Instrument: overview of 14 years in space, Atmos. Chem. Phys., 18, 5699–5745, https://doi.org/10.5194/acp-18-5699-2018, 2018.
Li, C., Joiner, J., Krotkov, N. A., and Bhartia, P. K.: A fast and sensitive
new satellite SO2 retrieval algorithm based on principal component
analysis: application to the ozone monitoring instrument, Geophys. Res.
Lett., 40, 6314–6318, https://doi.org/10.1002/2013GL058134, 2013.
Li, C., Krotkov, N. A., Carn, S., Zhang, Y., Spurr, R. J. D., and Joiner, J.: New-generation NASA Aura Ozone Monitoring Instrument (OMI) volcanic SO2 dataset: algorithm description, initial results, and continuation with the Suomi-NPP Ozone Mapping and Profiler Suite (OMPS), Atmos. Meas. Tech., 10, 445–458, https://doi.org/10.5194/amt-10-445-2017, 2017a.
Li, C., McLinden, C., Fioletov, V., Krotkov, N., Carn, S., Joiner, J.,
Streets, D., He, H., Ren, X., Li, Z., and Dickerson, R. R.: India is
overtaking China as the world's largest emitter of anthropogenic sulfur
dioxide, Scientific Reports, 7, 14304, https://doi.org/10.1038/s41598-017-14639-8, 2017b.
Li, C., Krotkov, N. A., Leonard, P. J. T., Carn, S., Joiner, J., Spurr, R. J. D., and Vasilkov, A.: Version 2 Ozone Monitoring Instrument SO2 product (OMSO2 V2): new anthropogenic SO2 vertical column density dataset, Atmos. Meas. Tech., 13, 6175–6191, https://doi.org/10.5194/amt-13-6175-2020, 2020.
Liu, J., Weng, F., and Li, Z.: Satellite-based PM2.5 estimation
directly from reflectance at the top of the atmosphere using a machine
learning algorithm, Atmos. Environ., 208, 113–122,
https://doi.org/10.1016/j.atmosenv.2019.04.002, 2019.
McLinden, C. Fioletov, V., Shephard, M., Krotkov, N., Li, C., Martin, R. V.,
Moran, M. D., and Joiner, J.: Space-based detection of missing sulfur dioxide
sources of global air pollution, Nat. Geosci., 9, 496–500, https://doi.org/10.1038/NGEO2724, 2016.
Müller, M. D., Kaifel, A. K., Weber, M., Tellmann, S., Burrows, J. P.,
and Loyola, D.: Ozone profile retrieval from Global Ozone Monitoring Experiment (GOME) data using a neural network approach (Neural Network Ozone Retrieval System (NNORSY)), J. Geophys. Res., 108, 4497, https://doi.org/10.1029/2002JD002784, 2003.
Müller, M. D., Kaifel, A., Weber, M., and Burrows, J. P.: Neural network
scheme for the retrieval of total ozone from Global Ozone Monitoring Experiment data, Appl. Optics, 41, 5051–5058, 2004.
Nanda, S., de Graaf, M., Veefkind, J. P., ter Linden, M., Sneep, M., de Haan, J., and Levelt, P. F.: A neural network radiative transfer model approach applied to the Tropospheric Monitoring Instrument aerosol height algorithm, Atmos. Meas. Tech., 12, 6619–6634, https://doi.org/10.5194/amt-12-6619-2019, 2019.
Nowlan, C. R., Liu, X., Chance, K., Cai, Z., Kurosu, T. P., Lee, C., and
Martin, R. V.: Retrievals of sulfur dioxide from the Global Ozone Monitoring
Experiment 2 (GOME-2) using an optimal estimation approach: Algorithm and
initial validation, J. Geophys. Res., 116, D18301, https://doi.org/10.1029/2011JD015808, 2011.
Piscini, A., Picchiani, M., Chini, M., Corradini, S., Merucci, L., Del Frate, F., and Stramondo, S.: A neural network approach for the simultaneous retrieval of volcanic ash parameters and SO2 using MODIS data, Atmos. Meas. Tech., 7, 4023–4047, https://doi.org/10.5194/amt-7-4023-2014, 2014.
Theys, N., De Smedt, I., Yu, H., Danckaert, T., van Gent, J., Hörmann, C., Wagner, T., Hedelt, P., Bauer, H., Romahn, F., Pedergnana, M., Loyola, D., and Van Roozendael, M.: Sulfur dioxide retrievals from TROPOMI onboard Sentinel-5 Precursor: algorithm theoretical basis, Atmos. Meas. Tech., 10, 119–153, https://doi.org/10.5194/amt-10-119-2017, 2017.
Theys, N., Fioletov, V., Li, C., De Smedt, I., Lerot, C., McLinden, C., Krotkov, N., Griffin, D., Clarisse, L., Hedelt, P., Loyola, D., Wagner, T., Kumar, V., Innes, A., Ribas, R., Hendrick, F., Vlietinck, J., Brenot, H., and Van Roozendael, M.: A sulfur dioxide Covariance-Based Retrieval Algorithm (COBRA): application to TROPOMI reveals new emission sources, Atmos. Chem. Phys., 21, 16727–16744, https://doi.org/10.5194/acp-21-16727-2021, 2021.
Wells, K. C., Millet, D. B., Payne, V. H., Deventer, M. J., Bates, K. H., de
Gouw, J. A., Graus, M., Warneke, C., Wisthaler, A., and Fuentes, J. D.:
Satellite isoprene retrievals constrain emissions and atmospheric oxidation,
Nature, 585, 225–233, https://doi.org/10.1038/s41586-020-2664-3, 2020.
Xu, J., Schüssler, O., Loyola R., D., Romahn, F., and Doicu, A.: A novel
ozone profile shape retrieval using Full-Physics Inverse Learning Machine
(FP_ILM), IEEE J. Sel. Top. Appl., 10, 5442–5457,
https://doi.org/10.1109/JSTARS.2017.2740168, 2017.
Zhang, S., Mi, T., Wu, Q., Luo, Y., Grieneisen, M. L., Shi, G., Yang, F., and
Zhan, Y.: A data-augmentation approach to deriving long-term surface
SO2 across Northern China: Implications for interpretable machine
learning, Sci. Total Environ., 827, 154278,
https://doi.org/10.1016/j.scitotenv.2022.154278, 2022.
Zhang, Y., Gautam, R., Zavala-Araiza, D., Jacob, D. J., Zhang, R., Zhu, L.,
Sheng, J., and Scarpelli, T.: Satellite-observed changes in Mexico's
offshore gas flaring activity linked to oil/gas regulations, Geophys. Res.
Lett., 3, 1879–1888, https://doi.org/10.1029/2018gl081145, 2019.
Zheng, T., Bergin, M., Wang, G., and Carlson, D.: Local PM2.5 hotspot
detector at 300 m resolution: A random forest–convolutional neural network
joint model jointly trained on satellite images and meteorology, Remote
Sens., 13, 1356, https://doi.org/10.3390/rs13071356, 2021.
Short summary
Satellite observations provide information on the sources of SO2, an important pollutant that affects both air quality and climate. However, these observations suffer from relatively poor data quality due to weak signals of SO2. Here, we use a machine learning technique to analyze satellite SO2 observations in order to reduce the noise and artifacts over relatively clean areas while keeping the signals near pollution sources. This leads to significant improvement in satellite SO2 data.
Satellite observations provide information on the sources of SO2, an important pollutant that...