Articles | Volume 18, issue 22
https://doi.org/10.5194/amt-18-6933-2025
© Author(s) 2025. 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-18-6933-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
24 Nov 2025
Research article |
| 24 Nov 2025
| 24 Nov 2025
The Carbon Mapper emissions monitoring system
Carbon Mapper, Pasadena, 91105, USA
Daniel Cusworth
Carbon Mapper, Pasadena, 91105, USA
Alana Ayasse
Carbon Mapper, Pasadena, 91105, USA
Katherine Howell
Carbon Mapper, Pasadena, 91105, USA
Alex Diamond
Carbon Mapper, Pasadena, 91105, USA
Tia Scarpelli
Carbon Mapper, Pasadena, 91105, USA
Jinsol Kim
Carbon Mapper, Pasadena, 91105, USA
Kelly O'neill
Carbon Mapper, Pasadena, 91105, USA
Judy Lai-Norling
Carbon Mapper, Pasadena, 91105, USA
Andrew Thorpe
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, 91109, USA
Sander R. Zandbergen
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, 91109, USA
Lucas Shaw
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, 91109, USA
Mark Keremedjiev
Planet Labs PBC, San Francisco, 94107, USA
Jeff Guido
Planet Labs PBC, San Francisco, 94107, USA
Paul Giuliano
Planet Labs PBC, San Francisco, 94107, USA
Malkam Goldstein
Planet Labs PBC, San Francisco, 94107, USA
Ravi Nallapu
Planet Labs PBC, San Francisco, 94107, USA
Geert Barentsen
Planet Labs PBC, San Francisco, 94107, USA
David R. Thompson
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, 91109, USA
Keely Roth
Planet Labs PBC, San Francisco, 94107, USA
Daniel Jensen
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, 91109, USA
Michael Eastwood
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, 91109, USA
Frances Reuland
Department of Energy Science and Engineering, Stanford University, Stanford, 94305, USA
Taylor Adams
Climate and Space Sciences and Engineering, University of Michigan, Ann Arbor, 48109, USA
Adam Brandt
Department of Energy Science and Engineering, Stanford University, Stanford, 94305, USA
Eric A. Kort
Climate and Space Sciences and Engineering, University of Michigan, Ann Arbor, 48109, USA
James Mason
Planet Labs PBC, San Francisco, 94107, USA
Robert O. Green
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, 91109, USA
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Sandro Meier, Marius Vögtli, Andreas Hueni, Audrey McManemin, Adam R. Brandt, Catherine Juéry, Vincent Blandin, Dominik Brunner, and Gerrit Kuhlmann
EGUsphere, https://doi.org/10.5194/egusphere-2025-5012, https://doi.org/10.5194/egusphere-2025-5012, 2025
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We tested a new airborne imaging instrument to detect and measure methane emissions. Flying over controlled test releases in France, we compared our measurements with known release rates. The instrument detected emissions as low as 5.5 kilograms per hour in good weather and 1.45 kilograms per hour in ideal conditions. Results show that better wind information is crucial for accurate totals. Our new instrument is important for helping target methane leaks in energy and waste systems.
Taylor J. Adams, Genevieve Plant, and Eric A. Kort
EGUsphere, https://doi.org/10.5194/egusphere-2025-4201, https://doi.org/10.5194/egusphere-2025-4201, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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Nitrous oxide (N2O) is a potent greenhouse gas and ozone-depleting substance emitted from agriculture. Emissions cannot presently be observed from space. We leverage the co-emission of reactive nitrogen oxides (NO+NO2=NOx) from croplands by determining N2O:NOx emissions ratios with aircraft. We apply these ratios to daily estimates of NOx emissions derived from space-based observations, thus generating a space-based proxy for N2O emissions, with close agreement against independent observations.
Audrey McManemin, Catherine Juéry, Vincent Blandin, James L. France, Philippine Burdeau, and Adam R. Brandt
EGUsphere, https://doi.org/10.5194/egusphere-2025-3793, https://doi.org/10.5194/egusphere-2025-3793, 2025
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
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This experiment tested the ability of different technologies to detect and measure methane emissions. Participating teams used satellites, drones, and other systems to estimate methane leak rates without knowing the true rate. Some systems were more accurate than others, and wind and other environmental conditions made measurements harder. Our findings help improve these tools and support efforts to track and reduce methane emissions as new environmental rules take shape in Europe and beyond.
Edward H. Bair, Dar A. Roberts, David R. Thompson, Philip G. Brodrick, Brenton A. Wilder, Niklas Bohn, Christopher J. Crawford, Nimrod Carmon, Carrie M. Vuyovich, and Jeff Dozier
The Cryosphere, 19, 2315–2320, https://doi.org/10.5194/tc-19-2315-2025, https://doi.org/10.5194/tc-19-2315-2025, 2025
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Key to the success of future satellite missions is understanding snowmelt in our warming climate, as this has implications for nearly 2 billion people. An obstacle is that an artifact, called the hook, is often mistaken for soot or dust. Instead, it is caused by three amplifying effects: (1) background reflectance that is too dark, (2) an assumption of level terrain, and (3) differences in optical constants of ice. Sensor calibration and directional effects may also contribute. Solutions are presented.
Gerrit Kuhlmann, Foteini Stavropoulou, Stefan Schwietzke, Daniel Zavala-Araiza, Andrew Thorpe, Andreas Hueni, Lukas Emmenegger, Andreea Calcan, Thomas Röckmann, and Dominik Brunner
Atmos. Chem. Phys., 25, 5371–5385, https://doi.org/10.5194/acp-25-5371-2025, https://doi.org/10.5194/acp-25-5371-2025, 2025
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A measurement campaign in 2019 found that methane emissions from oil and gas in Romania were significantly higher than reported. In 2021, our follow-up campaign using airborne remote sensing showed a marked decreases in emissions by 20 %–60 % due to improved infrastructure. The study highlights the importance of measurement-based emission monitoring and illustrates the value of a multi-scale assessment integrating ground-based observations with large-scale airborne remote sensing campaigns.
Niklas Bohn, Edward H. Bair, Philip G. Brodrick, Nimrod Carmon, Robert O. Green, Thomas H. Painter, and David R. Thompson
The Cryosphere, 19, 1279–1302, https://doi.org/10.5194/tc-19-1279-2025, https://doi.org/10.5194/tc-19-1279-2025, 2025
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A new type of Earth-observing satellite is measuring reflected sunlight in all its colors. These measurements can be used to characterize snow properties, which give us important information about climate change. In our work, we emphasize the difficulties of obtaining these properties from rough mountainous regions and present a solution to the problem. Our research was inspired by the growing number of new satellite technologies and the increasing challenges associated with climate change.
Tia R. Scarpelli, Elfie Roy, Daniel J. Jacob, Melissa P. Sulprizio, Ryan D. Tate, and Daniel H. Cusworth
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-552, https://doi.org/10.5194/essd-2024-552, 2025
Revised manuscript accepted for ESSD
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We present an update of the Global Fuel Exploitation Inventory (GFEI), a global inventory of methane emissions from oil, gas, and coal exploitation. GFEI v3 uses emissions as reported by countries in national inventories for 2020, and new infrastructure information, including a new dataset on coal mine locations. The goal of updating GFEI is to provide a more accurate spatial representation of the country-reported national inventories, allowing comparison with methane monitoring data.
Ingrid Super, Tia Scarpelli, Arjan Droste, and Paul I. Palmer
Geosci. Model Dev., 17, 7263–7284, https://doi.org/10.5194/gmd-17-7263-2024, https://doi.org/10.5194/gmd-17-7263-2024, 2024
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Monitoring greenhouse gas emission reductions requires a combination of models and observations, as well as an initial emission estimate. Each component provides information with a certain level of certainty and is weighted to yield the most reliable estimate of actual emissions. We describe efforts for estimating the uncertainty in the initial emission estimate, which significantly impacts the outcome. Hence, a good uncertainty estimate is key for obtaining reliable information on emissions.
Tia R. Scarpelli, Paul I. Palmer, Mark Lunt, Ingrid Super, and Arjan Droste
Atmos. Chem. Phys., 24, 10773–10791, https://doi.org/10.5194/acp-24-10773-2024, https://doi.org/10.5194/acp-24-10773-2024, 2024
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Under the Paris Agreement, countries must track their anthropogenic greenhouse gas emissions. This study describes a method to determine self-consistent estimates for combustion emissions and natural fluxes of CO2 from atmospheric data. We report consistent estimates inferred using this approach from satellite data and ground-based data over Europe, suggesting that satellite data can be used to determine national anthropogenic CO2 emissions for countries where ground-based CO2 data are absent.
Cynthia D. Nevison, Qing Liang, Paul A. Newman, Britton B. Stephens, Geoff Dutton, Xin Lan, Roisin Commane, Yenny Gonzalez, and Eric Kort
Atmos. Chem. Phys., 24, 10513–10529, https://doi.org/10.5194/acp-24-10513-2024, https://doi.org/10.5194/acp-24-10513-2024, 2024
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This study examines the drivers of interannual variability in tropospheric N2O. New insights are obtained from aircraft data and a chemistry–climate model that explicitly simulates stratospheric N2O. The stratosphere is found to be the dominant driver of N2O variability in the Northern Hemisphere, while both the stratosphere and El Niño cycles are important in the Southern Hemisphere. These results are consistent with known atmospheric dynamics and differences between the hemispheres.
Adolfo González-Romero, Cristina González-Flórez, Agnesh Panta, Jesús Yus-Díez, Patricia Córdoba, Andres Alastuey, Natalia Moreno, Melani Hernández-Chiriboga, Konrad Kandler, Martina Klose, Roger N. Clark, Bethany L. Ehlmann, Rebecca N. Greenberger, Abigail M. Keebler, Phil Brodrick, Robert Green, Paul Ginoux, Xavier Querol, and Carlos Pérez García-Pando
Atmos. Chem. Phys., 24, 9155–9176, https://doi.org/10.5194/acp-24-9155-2024, https://doi.org/10.5194/acp-24-9155-2024, 2024
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In this research, we studied the dust-emitting properties of crusts and aeolian ripples from the Mojave Desert. These properties are key to understanding the effect of dust upon climate. We found two different playa lakes according to the groundwater regime, which implies differences in crusts' cohesion state and mineralogy, which can affect the dust emission potential and properties. We also compare them with Moroccan Sahara crusts and Icelandic top sediments.
Adolfo González-Romero, Cristina González-Flórez, Agnesh Panta, Jesús Yus-Díez, Patricia Córdoba, Andres Alastuey, Natalia Moreno, Konrad Kandler, Martina Klose, Roger N. Clark, Bethany L. Ehlmann, Rebecca N. Greenberger, Abigail M. Keebler, Phil Brodrick, Robert O. Green, Xavier Querol, and Carlos Pérez García-Pando
Atmos. Chem. Phys., 24, 6883–6910, https://doi.org/10.5194/acp-24-6883-2024, https://doi.org/10.5194/acp-24-6883-2024, 2024
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The knowledge of properties from dust emitted in high latitudes such as in Iceland is scarce. This study focuses on the particle size, mineralogy, cohesion, and iron mode of occurrence and reflectance spectra of dust-emitting sediments. Icelandic top sediments have lower cohesion state, coarser particle size, distinctive mineralogy, and 3-fold bulk Fe content, with a large presence of magnetite compared to Saharan crusts.
Evan D. Sherwin, Sahar H. El Abbadi, Philippine M. Burdeau, Zhan Zhang, Zhenlin Chen, Jeffrey S. Rutherford, Yuanlei Chen, and Adam R. Brandt
Atmos. Meas. Tech., 17, 765–782, https://doi.org/10.5194/amt-17-765-2024, https://doi.org/10.5194/amt-17-765-2024, 2024
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Countries and companies increasingly rely on a growing fleet of satellites to find large emissions of climate-warming methane, particularly from oil and natural gas systems across the globe. We independently assessed the performance of nine such systems by releasing controlled, undisclosed amounts of methane as satellites passed overhead. The tested systems produced reliable detection and quantification results, including the smallest-ever emission detected from space in such a test.
Magdalena Pühl, Anke Roiger, Alina Fiehn, Alan M. Gorchov Negron, Eric A. Kort, Stefan Schwietzke, Ignacio Pisso, Amy Foulds, James Lee, James L. France, Anna E. Jones, Dave Lowry, Rebecca E. Fisher, Langwen Huang, Jacob Shaw, Prudence Bateson, Stephen Andrews, Stuart Young, Pamela Dominutti, Tom Lachlan-Cope, Alexandra Weiss, and Grant Allen
Atmos. Chem. Phys., 24, 1005–1024, https://doi.org/10.5194/acp-24-1005-2024, https://doi.org/10.5194/acp-24-1005-2024, 2024
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In April–May 2019 we carried out an airborne field campaign in the southern North Sea with the aim of studying methane emissions of offshore gas installations. We determined methane emissions from elevated methane measured downstream of the sampled installations. We compare our measured methane emissions with estimated methane emissions from national and global annual inventories. As a result, we find inconsistencies of inventories and large discrepancies between measurements and inventories.
Alana K. Ayasse, Daniel Cusworth, Kelly O'Neill, Justin Fisk, Andrew K. Thorpe, and Riley Duren
Atmos. Meas. Tech., 16, 6065–6074, https://doi.org/10.5194/amt-16-6065-2023, https://doi.org/10.5194/amt-16-6065-2023, 2023
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Methane is a powerful greenhouse gas, and a significant portion of methane comes from large individual plumes. Recently, airplane-mounted infrared technologies have proven very good at detecting and quantifying these plumes. In order to extract the methane signal from the infrared image, there are two widely used approaches. In this study, we assess the performance of both approaches using controlled-release experiments. We also examine the minimum detection limit of the infrared technology.
Apisada Chulakadabba, Maryann Sargent, Thomas Lauvaux, Joshua S. Benmergui, Jonathan E. Franklin, Christopher Chan Miller, Jonas S. Wilzewski, Sébastien Roche, Eamon Conway, Amir H. Souri, Kang Sun, Bingkun Luo, Jacob Hawthrone, Jenna Samra, Bruce C. Daube, Xiong Liu, Kelly Chance, Yang Li, Ritesh Gautam, Mark Omara, Jeff S. Rutherford, Evan D. Sherwin, Adam Brandt, and Steven C. Wofsy
Atmos. Meas. Tech., 16, 5771–5785, https://doi.org/10.5194/amt-16-5771-2023, https://doi.org/10.5194/amt-16-5771-2023, 2023
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We show that MethaneAIR, a precursor to the MethaneSAT satellite, demonstrates accurate point source quantification during controlled release experiments and regional observations in 2021 and 2022. Results from our two independent quantification methods suggest the accuracy of our sensor and algorithms is better than 25 % for sources emitting 200 kg h−1 or more. Insights from these measurements help establish the capabilities of MethaneSAT and MethaneAIR.
Daniel H. Cusworth, Andrew K. Thorpe, Charles E. Miller, Alana K. Ayasse, Ralph Jiorle, Riley M. Duren, Ray Nassar, Jon-Paul Mastrogiacomo, and Robert R. Nelson
Atmos. Chem. Phys., 23, 14577–14591, https://doi.org/10.5194/acp-23-14577-2023, https://doi.org/10.5194/acp-23-14577-2023, 2023
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Carbon dioxide (CO2) emissions from combustion sources are uncertain in many places across the globe. Satellites have the ability to detect and quantify emissions from large CO2 point sources, including coal-fired power plants. In this study, we tasked two satellites to routinely observe CO2 emissions at 30 coal-fired power plants between 2021 and 2022. These results present the largest dataset of space-based CO2 emission estimates to date.
Berend J. Schuit, Joannes D. Maasakkers, Pieter Bijl, Gourav Mahapatra, Anne-Wil van den Berg, Sudhanshu Pandey, Alba Lorente, Tobias Borsdorff, Sander Houweling, Daniel J. Varon, Jason McKeever, Dylan Jervis, Marianne Girard, Itziar Irakulis-Loitxate, Javier Gorroño, Luis Guanter, Daniel H. Cusworth, and Ilse Aben
Atmos. Chem. Phys., 23, 9071–9098, https://doi.org/10.5194/acp-23-9071-2023, https://doi.org/10.5194/acp-23-9071-2023, 2023
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Using two machine learning models, which were trained on TROPOMI methane satellite data, we detect 2974 methane plumes, so-called super-emitters, in 2021. We detect methane emissions globally related to urban areas or landfills, coal mining, and oil and gas production. Using our monitoring system, we identify 94 regions with frequent emissions. For 12 locations, we target high-resolution satellite instruments to enlarge and identify the exact infrastructure responsible for the emissions.
María Gonçalves Ageitos, Vincenzo Obiso, Ron L. Miller, Oriol Jorba, Martina Klose, Matt Dawson, Yves Balkanski, Jan Perlwitz, Sara Basart, Enza Di Tomaso, Jerónimo Escribano, Francesca Macchia, Gilbert Montané, Natalie M. Mahowald, Robert O. Green, David R. Thompson, and Carlos Pérez García-Pando
Atmos. Chem. Phys., 23, 8623–8657, https://doi.org/10.5194/acp-23-8623-2023, https://doi.org/10.5194/acp-23-8623-2023, 2023
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Dust aerosols affect our climate differently depending on their mineral composition. We include dust mineralogy in an atmospheric model considering two existing soil maps, which still have large associated uncertainties. The soil data and the distribution of the minerals in different aerosol sizes are key to our model performance. We find significant regional variations in climate-relevant variables, which supports including mineralogy in our current models and the need for improved soil maps.
Zhan Zhang, Evan D. Sherwin, Daniel J. Varon, and Adam R. Brandt
Atmos. Meas. Tech., 15, 7155–7169, https://doi.org/10.5194/amt-15-7155-2022, https://doi.org/10.5194/amt-15-7155-2022, 2022
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This work developed a multi-band–multi-pass–multi-comparison-date Sentinel-2 methane retrieval algorithm, and the method was calibrated by data from a controlled release test. To our knowledge, this is the first study that validates the performance of a Sentinel-2 methane detection algorithm by calibration with a ground-truth testing. It illustrates the potential for additional validation with systematic future experiments wherein algorithms can be tuned to meet different detection expectations.
Broghan M. Erland, Cristen Adams, Andrea Darlington, Mackenzie L. Smith, Andrew K. Thorpe, Gregory R. Wentworth, Steve Conley, John Liggio, Shao-Meng Li, Charles E. Miller, and John A. Gamon
Atmos. Meas. Tech., 15, 5841–5859, https://doi.org/10.5194/amt-15-5841-2022, https://doi.org/10.5194/amt-15-5841-2022, 2022
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Accurately estimating greenhouse gas (GHG) emissions is essential to reaching net-zero goals to combat the climate crisis. Airborne box-flights are ideal for assessing regional GHG emissions, as they can attain small error. We compare two box-flight algorithms and found they produce similar results, but daily variability must be considered when deriving emissions inventories. Increasing the consistency and agreement between airborne methods moves us closer to achieving more accurate estimates.
Lu Shen, Ritesh Gautam, Mark Omara, Daniel Zavala-Araiza, Joannes D. Maasakkers, Tia R. Scarpelli, Alba Lorente, David Lyon, Jianxiong Sheng, Daniel J. Varon, Hannah Nesser, Zhen Qu, Xiao Lu, Melissa P. Sulprizio, Steven P. Hamburg, and Daniel J. Jacob
Atmos. Chem. Phys., 22, 11203–11215, https://doi.org/10.5194/acp-22-11203-2022, https://doi.org/10.5194/acp-22-11203-2022, 2022
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We use 22 months of TROPOMI satellite observations to quantity methane emissions from the oil (O) and natural gas (G) sector in the US and Canada at the scale of both individual basins as well as country-wide aggregates. We find that O/G-related methane emissions are underestimated in these inventories by 80 % for the US and 40 % for Canada, and 70 % of the underestimate in the US is from five O/G basins, including Permian, Haynesville, Anadarko, Eagle Ford, and Barnett.
Daniel J. Jacob, Daniel J. Varon, Daniel H. Cusworth, Philip E. Dennison, Christian Frankenberg, Ritesh Gautam, Luis Guanter, John Kelley, Jason McKeever, Lesley E. Ott, Benjamin Poulter, Zhen Qu, Andrew K. Thorpe, John R. Worden, and Riley M. Duren
Atmos. Chem. Phys., 22, 9617–9646, https://doi.org/10.5194/acp-22-9617-2022, https://doi.org/10.5194/acp-22-9617-2022, 2022
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We review the capability of satellite observations of atmospheric methane to quantify methane emissions on all scales. We cover retrieval methods, precision requirements, inverse methods for inferring emissions, source detection thresholds, and observations of system completeness. We show that current instruments already enable quantification of regional and national emissions including contributions from large point sources. Coverage and resolution will increase significantly in coming years.
John R. Worden, Daniel H. Cusworth, Zhen Qu, Yi Yin, Yuzhong Zhang, A. Anthony Bloom, Shuang Ma, Brendan K. Byrne, Tia Scarpelli, Joannes D. Maasakkers, David Crisp, Riley Duren, and Daniel J. Jacob
Atmos. Chem. Phys., 22, 6811–6841, https://doi.org/10.5194/acp-22-6811-2022, https://doi.org/10.5194/acp-22-6811-2022, 2022
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This paper is intended to accomplish two goals: 1) describe a new algorithm by which remotely sensed measurements of methane or other tracers can be used to not just quantify methane fluxes, but also attribute these fluxes to specific sources and regions and characterize their uncertainties, and 2) use this new algorithm to provide methane emissions by sector and country in support of the global stock take.
Dustin Roten, John C. Lin, Lewis Kunik, Derek Mallia, Dien Wu, Tomohiro Oda, and Eric A. Kort
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2022-315, https://doi.org/10.5194/acp-2022-315, 2022
Revised manuscript not accepted
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The systems used to monitor carbon dioxide (CO2) emissions from urban areas provides a means to observe and quantify emissions reductions from policy-related reduction efforts. Space-based instruments, such as NASA's Orbiting Carbon Observatory-3 (OCO-3), provides detailed "snapshots" of CO2 emissions from many megacities around the world. This work quantifies the amount of emission "information" contained in these snapshots and uses this information to update previous estimates of urban CO2.
Tia R. Scarpelli, Daniel J. Jacob, Shayna Grossman, Xiao Lu, Zhen Qu, Melissa P. Sulprizio, Yuzhong Zhang, Frances Reuland, Deborah Gordon, and John R. Worden
Atmos. Chem. Phys., 22, 3235–3249, https://doi.org/10.5194/acp-22-3235-2022, https://doi.org/10.5194/acp-22-3235-2022, 2022
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We present a spatially explicit version of the national inventories of oil, gas, and coal methane emissions as submitted by individual countries to the United Nations Framework Convention on Climate Change (UNFCCC) in 2021. We then use atmospheric modeling to compare our inventory emissions to atmospheric methane observations with the goal of identifying potential under- and overestimates of oil–gas methane emissions in the national inventories.
Jennifer D. Hegarty, Karen E. Cady-Pereira, Vivienne H. Payne, Susan S. Kulawik, John R. Worden, Valentin Kantchev, Helen M. Worden, Kathryn McKain, Jasna V. Pittman, Róisín Commane, Bruce C. Daube Jr., and Eric A. Kort
Atmos. Meas. Tech., 15, 205–223, https://doi.org/10.5194/amt-15-205-2022, https://doi.org/10.5194/amt-15-205-2022, 2022
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Carbon monoxide (CO) is produced by combustion of substances such as fossil fuels and plays an important role in atmospheric pollution and climate. We evaluated estimates of atmospheric CO derived from outgoing radiation measurements of the Atmospheric Infrared Sounder (AIRS) on a satellite orbiting the Earth against CO measurements from aircraft to show that these satellite measurements are reliable for continuous global monitoring of atmospheric CO concentrations.
Xiao Lu, Daniel J. Jacob, Haolin Wang, Joannes D. Maasakkers, Yuzhong Zhang, Tia R. Scarpelli, Lu Shen, Zhen Qu, Melissa P. Sulprizio, Hannah Nesser, A. Anthony Bloom, Shuang Ma, John R. Worden, Shaojia Fan, Robert J. Parker, Hartmut Boesch, Ritesh Gautam, Deborah Gordon, Michael D. Moran, Frances Reuland, Claudia A. Octaviano Villasana, and Arlyn Andrews
Atmos. Chem. Phys., 22, 395–418, https://doi.org/10.5194/acp-22-395-2022, https://doi.org/10.5194/acp-22-395-2022, 2022
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We evaluate methane emissions and trends for 2010–2017 in the gridded national emission inventories for the United States, Canada, and Mexico by inversion of in situ and satellite methane observations. We find that anthropogenic methane emissions for all three countries are underestimated in the national inventories, largely driven by oil emissions. Anthropogenic methane emissions in the US peak in 2014, in contrast to the report of a steadily decreasing trend over 2010–2017 from the US EPA.
Mark T. Richardson, David R. Thompson, Marcin J. Kurowski, and Matthew D. Lebsock
Atmos. Meas. Tech., 15, 117–129, https://doi.org/10.5194/amt-15-117-2022, https://doi.org/10.5194/amt-15-117-2022, 2022
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Sunlight can pass diagonally through the atmosphere, cutting through the 3-D water vapour field in a way that
smears2-D maps of imaging spectroscopy vapour retrievals. In simulations we show how this smearing is
towardsor
away fromthe Sun, so calculating
across the solar direction allows sub-kilometre information about water vapour's spatial scaling to be calculated. This could be tested by airborne campaigns and used to obtain new information from upcoming spaceborne data products.
Siraput Jongaramrungruang, Georgios Matheou, Andrew K. Thorpe, Zhao-Cheng Zeng, and Christian Frankenberg
Atmos. Meas. Tech., 14, 7999–8017, https://doi.org/10.5194/amt-14-7999-2021, https://doi.org/10.5194/amt-14-7999-2021, 2021
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This study shows how precision error and bias in column methane retrieval change with different instrument specifications and the impact of spectrally complex surface albedos on retrievals. We show how surface interferences can be mitigated with an optimal spectral resolution and a higher polynomial degree in a retrieval process. The findings can inform future satellite instrument designs to have robust observations capable of separating real CH4 plume enhancements from surface interferences.
Eric J. Hintsa, Fred L. Moore, Dale F. Hurst, Geoff S. Dutton, Bradley D. Hall, J. David Nance, Ben R. Miller, Stephen A. Montzka, Laura P. Wolton, Audra McClure-Begley, James W. Elkins, Emrys G. Hall, Allen F. Jordan, Andrew W. Rollins, Troy D. Thornberry, Laurel A. Watts, Chelsea R. Thompson, Jeff Peischl, Ilann Bourgeois, Thomas B. Ryerson, Bruce C. Daube, Yenny Gonzalez Ramos, Roisin Commane, Gregory W. Santoni, Jasna V. Pittman, Steven C. Wofsy, Eric Kort, Glenn S. Diskin, and T. Paul Bui
Atmos. Meas. Tech., 14, 6795–6819, https://doi.org/10.5194/amt-14-6795-2021, https://doi.org/10.5194/amt-14-6795-2021, 2021
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We built UCATS to study atmospheric chemistry and transport. It has measured trace gases including CFCs, N2O, SF6, CH4, CO, and H2 with gas chromatography, as well as ozone and water vapor. UCATS has been part of missions to study the tropical tropopause; transport of air into the stratosphere; greenhouse gases, transport, and chemistry in the troposphere; and ozone chemistry, on both piloted and unmanned aircraft. Its design, capabilities, and some results are shown and described here.
Zhen Qu, Daniel J. Jacob, Lu Shen, Xiao Lu, Yuzhong Zhang, Tia R. Scarpelli, Hannah Nesser, Melissa P. Sulprizio, Joannes D. Maasakkers, A. Anthony Bloom, John R. Worden, Robert J. Parker, and Alba L. Delgado
Atmos. Chem. Phys., 21, 14159–14175, https://doi.org/10.5194/acp-21-14159-2021, https://doi.org/10.5194/acp-21-14159-2021, 2021
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The recent launch of TROPOMI offers an unprecedented opportunity to quantify the methane budget from a top-down perspective. We use TROPOMI and the more mature GOSAT methane observations to estimate methane emissions and get consistent global budgets. However, TROPOMI shows biases over regions where surface albedo is small and provides less information for the coarse-resolution inversion due to the larger error correlations and spatial variations in the number of observations.
Mark T. Richardson, David R. Thompson, Marcin J. Kurowski, and Matthew D. Lebsock
Atmos. Meas. Tech., 14, 5555–5576, https://doi.org/10.5194/amt-14-5555-2021, https://doi.org/10.5194/amt-14-5555-2021, 2021
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Modern and upcoming hyperspectral imagers will take images with spatial resolutions as fine as 20 m. They can retrieve column water vapour, and we show evidence that from these column measurements you can get statistics of planetary boundary layer (PBL) water vapour. This is important information for climate models that need to account for sub-grid mixing of water vapour near the surface in their PBL schemes.
Hannah Nesser, Daniel J. Jacob, Joannes D. Maasakkers, Tia R. Scarpelli, Melissa P. Sulprizio, Yuzhong Zhang, and Chris H. Rycroft
Atmos. Meas. Tech., 14, 5521–5534, https://doi.org/10.5194/amt-14-5521-2021, https://doi.org/10.5194/amt-14-5521-2021, 2021
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Analytical inversions of satellite observations of atmospheric composition can improve emissions estimates and quantify errors but are computationally expensive at high resolutions. We propose two methods to decrease this cost. The methods reproduce a high-resolution inversion at a quarter of the cost. The reduced-dimension method creates a multiscale grid. The reduced-rank method solves the inversion where information content is highest.
Dien Wu, John C. Lin, Henrique F. Duarte, Vineet Yadav, Nicholas C. Parazoo, Tomohiro Oda, and Eric A. Kort
Geosci. Model Dev., 14, 3633–3661, https://doi.org/10.5194/gmd-14-3633-2021, https://doi.org/10.5194/gmd-14-3633-2021, 2021
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A model (SMUrF) is presented that estimates biogenic CO2 fluxes over cities around the globe to separate out biogenic fluxes from anthropogenic emissions. The model leverages satellite-based solar-induced fluorescence data and a machine-learning technique. We evaluate the biogenic fluxes against flux observations and show contrasts between biogenic and anthropogenic fluxes over cities, revealing urban–rural flux gradients, diurnal cycles, and the resulting imprints on atmospheric-column CO2.
David R. Lyon, Benjamin Hmiel, Ritesh Gautam, Mark Omara, Katherine A. Roberts, Zachary R. Barkley, Kenneth J. Davis, Natasha L. Miles, Vanessa C. Monteiro, Scott J. Richardson, Stephen Conley, Mackenzie L. Smith, Daniel J. Jacob, Lu Shen, Daniel J. Varon, Aijun Deng, Xander Rudelis, Nikhil Sharma, Kyle T. Story, Adam R. Brandt, Mary Kang, Eric A. Kort, Anthony J. Marchese, and Steven P. Hamburg
Atmos. Chem. Phys., 21, 6605–6626, https://doi.org/10.5194/acp-21-6605-2021, https://doi.org/10.5194/acp-21-6605-2021, 2021
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The Permian Basin (USA) is the world’s largest oil field. We use tower- and aircraft-based approaches to measure how methane emissions in the Permian Basin changed throughout 2020. In early 2020, 3.3 % of the region’s gas was emitted; then in spring 2020, the loss rate temporarily dropped to 1.9 % as oil price crashed. We find this short-term reduction to be a result of reduced well development, less gas flaring, and fewer abnormal events despite minimal reductions in oil and gas production.
David R. Thompson, Brian H. Kahn, Philip G. Brodrick, Matthew D. Lebsock, Mark Richardson, and Robert O. Green
Atmos. Meas. Tech., 14, 2827–2840, https://doi.org/10.5194/amt-14-2827-2021, https://doi.org/10.5194/amt-14-2827-2021, 2021
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Concentrations of water vapor in the atmosphere vary dramatically over space and time. Mapping this variability can provide insights into atmospheric processes that help us understand atmospheric processes in the Earth system. Here we use a new measurement strategy based on imaging spectroscopy to map atmospheric water vapor concentrations at very small spatial scales. Experiments demonstrate the accuracy of this technique and some initial results from an airborne remote sensing experiment.
Xiao Lu, Daniel J. Jacob, Yuzhong Zhang, Joannes D. Maasakkers, Melissa P. Sulprizio, Lu Shen, Zhen Qu, Tia R. Scarpelli, Hannah Nesser, Robert M. Yantosca, Jianxiong Sheng, Arlyn Andrews, Robert J. Parker, Hartmut Boesch, A. Anthony Bloom, and Shuang Ma
Atmos. Chem. Phys., 21, 4637–4657, https://doi.org/10.5194/acp-21-4637-2021, https://doi.org/10.5194/acp-21-4637-2021, 2021
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We use an analytical solution to the Bayesian inverse problem to quantitatively compare and combine the information from satellite and in situ observations, and to estimate global methane budget and their trends over the 2010–2017 period. We find that satellite and in situ observations are to a large extent complementary in the inversion for estimating global methane budget, and reveal consistent corrections of regional anthropogenic and wetland methane emissions relative to the prior inventory.
Joannes D. Maasakkers, Daniel J. Jacob, Melissa P. Sulprizio, Tia R. Scarpelli, Hannah Nesser, Jianxiong Sheng, Yuzhong Zhang, Xiao Lu, A. Anthony Bloom, Kevin W. Bowman, John R. Worden, and Robert J. Parker
Atmos. Chem. Phys., 21, 4339–4356, https://doi.org/10.5194/acp-21-4339-2021, https://doi.org/10.5194/acp-21-4339-2021, 2021
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We use 2010–2015 GOSAT satellite observations of atmospheric methane over North America in a high-resolution inversion to estimate methane emissions. We find general consistency with the gridded EPA inventory but higher oil and gas production emissions, with oil production emissions twice as large as in the latest EPA Greenhouse Gas Inventory. We find lower wetland emissions than predicted by WetCHARTs and a small increasing trend in the eastern US, apparently related to unconventional oil/gas.
Longlei Li, Natalie M. Mahowald, Ron L. Miller, Carlos Pérez García-Pando, Martina Klose, Douglas S. Hamilton, Maria Gonçalves Ageitos, Paul Ginoux, Yves Balkanski, Robert O. Green, Olga Kalashnikova, Jasper F. Kok, Vincenzo Obiso, David Paynter, and David R. Thompson
Atmos. Chem. Phys., 21, 3973–4005, https://doi.org/10.5194/acp-21-3973-2021, https://doi.org/10.5194/acp-21-3973-2021, 2021
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For the first time, this study quantifies the range of the dust direct radiative effect due to uncertainty in the soil mineral abundance using all currently available information. We show that the majority of the estimated direct radiative effect range is due to uncertainty in the simulated mass fractions of iron oxides and thus their soil abundance, which is independent of the model employed. We therefore prove the necessity of considering mineralogy for understanding dust–climate interactions.
Yuzhong Zhang, Daniel J. Jacob, Xiao Lu, Joannes D. Maasakkers, Tia R. Scarpelli, Jian-Xiong Sheng, Lu Shen, Zhen Qu, Melissa P. Sulprizio, Jinfeng Chang, A. Anthony Bloom, Shuang Ma, John Worden, Robert J. Parker, and Hartmut Boesch
Atmos. Chem. Phys., 21, 3643–3666, https://doi.org/10.5194/acp-21-3643-2021, https://doi.org/10.5194/acp-21-3643-2021, 2021
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We use 2010–2018 satellite observations of atmospheric methane to interpret the factors controlling atmospheric methane and its accelerating increase during the period. The 2010–2018 increase in global methane emissions is driven by tropical and boreal wetlands and tropical livestock (South Asia, Africa, Brazil), with an insignificant positive trend in emissions from the fossil fuel sector. The peak methane growth rates in 2014–2015 are also contributed by low OH and high fire emissions.
Jakob Borchardt, Konstantin Gerilowski, Sven Krautwurst, Heinrich Bovensmann, Andrew K. Thorpe, David R. Thompson, Christian Frankenberg, Charles E. Miller, Riley M. Duren, and John Philip Burrows
Atmos. Meas. Tech., 14, 1267–1291, https://doi.org/10.5194/amt-14-1267-2021, https://doi.org/10.5194/amt-14-1267-2021, 2021
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The AVIRIS-NG hyperspectral imager has been used successfully to identify and quantify anthropogenic methane sources utilizing different retrieval and inversion methods. Here, we examine the adaption and application of the WFM-DOAS algorithm to AVIRIS-NG measurements to retrieve local methane column enhancements, compare the results with other retrievals, and quantify the uncertainties resulting from the retrieval method. Additionally, we estimate emissions from five detected methane plumes.
Xueying Yu, Dylan B. Millet, Kelley C. Wells, Daven K. Henze, Hansen Cao, Timothy J. Griffis, Eric A. Kort, Genevieve Plant, Malte J. Deventer, Randall K. Kolka, D. Tyler Roman, Kenneth J. Davis, Ankur R. Desai, Bianca C. Baier, Kathryn McKain, Alan C. Czarnetzki, and A. Anthony Bloom
Atmos. Chem. Phys., 21, 951–971, https://doi.org/10.5194/acp-21-951-2021, https://doi.org/10.5194/acp-21-951-2021, 2021
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Methane concentrations have doubled since 1750. The US Upper Midwest is a key region contributing to such trends, but sources are poorly understood. We collected and analyzed aircraft data to resolve spatial and timing biases in wetland and livestock emission estimates and uncover errors in inventory treatment of manure management. We highlight the importance of intensive agriculture for the regional and US methane budgets and the potential for methane mitigation through improved management.
Macey W. Sandford, David R. Thompson, Robert O. Green, Brian H. Kahn, Raffaele Vitulli, Steve Chien, Amruta Yelamanchili, and Winston Olson-Duvall
Atmos. Meas. Tech., 13, 7047–7057, https://doi.org/10.5194/amt-13-7047-2020, https://doi.org/10.5194/amt-13-7047-2020, 2020
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We demonstrate an onboard cloud-screening approach to significantly reduce the amount of cloud-contaminated data transmitted from orbit. We have produced location-specific models that improve performance by taking into account the unique cloud statistics in different latitudes. We have shown that screening clouds based on their location or surface type will improve the ability for a cloud-screening tool to improve the volume of usable science data.
Cited articles
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Ayasse, A. K., Cusworth, D., O'Neill, K., Fisk, J., Thorpe, A. K., and Duren, R.: Performance and sensitivity of column-wise and pixel-wise methane retrievals for imaging spectrometers, Atmos. Meas. Tech., 16, 6065–6074, https://doi.org/10.5194/amt-16-6065-2023, 2023.
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Chan Miller, C., Roche, S., Wilzewski, J. S., Liu, X., Chance, K., Souri, A. H., Conway, E., Luo, B., Samra, J., Hawthorne, J., Sun, K., Staebell, C., Chulakadabba, A., Sargent, M., Benmergui, J. S., Franklin, J. E., Daube, B. C., Li, Y., Laughner, J. L., Baier, B. C., Gautam, R., Omara, M., and Wofsy, S. C.: Methane retrieval from MethaneAIR using the CO2 proxy approach: a demonstration for the upcoming MethaneSAT mission, Atmos. Meas. Tech., 17, 5429–5454, https://doi.org/10.5194/amt-17-5429-2024, 2024.
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Cusworth, D. H., Duren, R. M., Thorpe, A. K., Olson-Duvall, W., Heckler, J., Chapman, J. W., and Eastwood, M. L.: Intermittency of Large Methane Emitters in the Permian Basin, Environmental Science & Technology Letters, 8, 567–73, https://doi.org/10.1021/acs.estlett.1c00173, 2021a.
Cusworth, D. H., Duren, R. M., Thorpe, A. K., Eastwood, M. L., Green, R. O., Dennison, P. E., Frankenberg, C., Heckler, J. W., Asner, G. P., and Miller, C. E.: Quantifying Global Power Plant Carbon Dioxide Emissions With Imaging Spectroscopy, AGU Advances, 2, https://doi.org/10.1029/2020AV000350, 2021b.
Cusworth, D. H., Thorpe, A. K., Ayasse, A. K., Stepp, D., Heckler, J., Asner, G. P., Miller, C. E., Chapman, J. W., Eastwood, M. L., Green, R. O., Hmiel, B., Lyon, D., and Duren, R. M.: Strong methane point sources contribute a disproportionate fraction of total emissions across multiple basins in the U.S., Proc. Natl Acad. Sci., 119, https://doi.org/10.1073/pnas.2202338119, 2022.
Cusworth, D. H., Duren, R. M., Ayasse, A. K., Jiorle, R., Howell, K., Aubrey, A., Green, R. O., Eastwood, M. L., Chapman, J. W., Thorpe, A. K., Heckler, J., Asner, G. P., Smith, M. L., Thoma, E., Krause, M. J., Heins, D., and Thorneloe, S.: Quantifying Methane Emissions from United States Landfills, Science, 383, 1499–1504, https://doi.org/10.1126/science.adi7735, 2024.
Duren, R. M., Thorpe, A., Foster, K. T., Rafiq, T., Hopkins, F. M., Yadav, V., Bue, B., Thompson, D. R., Conley, S., Colombi, N., Frankenberg, C., McCubbin, I., Eastwood, M., Falk, M., Herner, J., Croes, B. E., Green, R., and Miller, C.: California's Methane Super emitters, Nature, 575, 180–84, https://doi.org/10.1038/s41586-019-1720-3, 2019.
El Abbadi, S. H., Chen, Z., Burdeau, P. M., Rutherford, J. S., Chen, Y., Zhang Z., Sherwin, E. D., and Brandt, A. R.: Environmental Science & Technology, 58, 9591–9600, https://doi.org/10.1021/acs.est.4c02439, 2024.
Eldering, A., Taylor, T. E., O'Dell, C. W., and Pavlick, R.: The OCO-3 mission: measurement objectives and expected performance based on 1 year of simulated data, Atmos. Meas. Tech., 12, 2341–2370, https://doi.org/10.5194/amt-12-2341-2019, 2019.
Frankenberg, C., Platt, U., and Wagner, T.: Iterative maximum a posteriori (IMAP)-DOAS for retrieval of strongly absorbing trace gases: Model studies for CH4 and CO2 retrieval from near infrared spectra of SCIAMACHY onboard ENVISAT, Atmos. Chem. Phys., 5, 9–22, https://doi.org/10.5194/acp-5-9-2005, 2005.
Frankenberg, C., Aben, I., Bergamaschi, P., Dlugokencky, E. J., van Hees, R., Houweling, S., van der Meer, P., Snel, R., and Tol, P., Global column-averaged methane mixing ratios from 2003 to 2009 as derived from SCIAMACHY: Trends and variability, J. Geophys. Res., 116, D04302, https://doi.org/10.1029/2010JD014849, 2011.
Frankenberg, C., Thorpe, A. K., Thompson, D. R., Hulley, G., Kort, E. A., Vance, N., Borchardt, J., Krings, T., Gerilowski, K., Sweeney, C., and Conley, S.: Airborne methane remote measurements reveal heavy-tail flux distribution in Four Corners region, Proc. Natl Acad. Sci., 113, 9734–9739, 2016.
Frankenberg, C., Bar-On, Y. M., Yin, Y., Wennberg, P. O., Jacob, D. J., and Michalak, A. M.: Data drought in the humid tropics: How to overcome the cloud barrier in greenhouse gas remote sensing, Geophysical Research Letters, 51, e2024GL108791, https://doi.org/10.1029/2024GL108791, 2024.
Guanter, L., Irakulis-Loitxate, I., Gorroño, J., Sánchez-García, E., Cusworth, D. H., Varon, D. J., Cogliati, S., and Colombo, R.: Mapping methane point emissions with the PRISMA spaceborne imaging spectrometer, Remote Sensing of Environment, 265, 112671, https://doi.org/10.1016/j.rse.2021.112671, 2021.
Gorchov Negron, A. M., Kort, E. A., Chen, Y., Brandt, A. R., Smith, M. L., Plant, G., Ayasse, A. K., Schwietzke, S., Zavala-Araiza, D., Hausman, C., and Adames-Corraliza Á. F.: Excess methane emissions from shallow water platforms elevate the carbon intensity of US Gulf of Mexico oil and gas production, Proc. Natl. Acad. Sci. U.S.A., 120, e2215275120, https://doi.org/10.1073/pnas.2215275120, 2023.
Green, R. O., Schaepman, M. E., Mouroulis, P., Geier, S., Shaw, L., Hueini, A., Bernas, M., McKinley, I., Smith, C., Wehbe, R., Eastwood, M., Vinckier, Q., Liggett, E., Zandbergen, S., Thompson, D., Sullivan, P., Sarture, C., Van Gorp, B., and Helmlinger, M.: Airborne Visible/Infrared Imaging Spectrometer 3 (AVIRIS-3), 2022 IEEE Aerospace Conference (AERO), Big Sky, MT, USA, 1–10, https://doi.org/10.1109/AERO53065.2022.9843565, 2022.
Hu, H., Landgraf, J., Detmers, R., Borsdorff, T., Aan de Brugh, J., Aben, I., Butz, A., and Hasekamp, O.: Toward global mapping of methane with TROPOMI: First results and intersatellite comparison to GOSAT, Geophysical Research Letters, 45, 3682–3689, https://doi.org/10.1002/2018GL077259, 2018.
Irakulis-Loitxate, I., Guanter, L., Liu, Y., Varon, D. J., Maasakkers, J. D., Zhang, Y., Chulakadabba, A., Wofsy, S. C., Thorpe, A. K., Duren, R. M., Frankenberg, C., Lyon, D. R., Hmiel, B., Cusworth, D. H., Zhang, Y., Segl, K., Gorroño, J., Sánchez-García, E., Sulprizio, M. P., Cao, K., Zhu, H., Liang, J., Li, X., Aben, I., and Jacob, D. J.: Satellite-based survey of extreme methane emissions in the Permian basin, Sci. Adv., 7, eabf4507, https://doi.org/10.1126/sciadv.abf4507, 2021.
Jacob, D. J., Turner, A. J., Maasakkers, J. D., Sheng, J., Sun, K., Liu, X., Chance, K., Aben, I., McKeever, J., and Frankenberg, C.: Satellite observations of atmospheric methane and their value for quantifying methane emissions, Atmos. Chem. Phys., 16, 14371–14396, https://doi.org/10.5194/acp-16-14371-2016, 2016.
Jacob, D. J., Varon, D. J., Cusworth, D. H., Dennison, P. E., Frankenberg, C., Gautam, R., Guanter, L., Kelley, J., McKeever, J., Ott, L. E., Poulter, B., Qu, Z., Thorpe, A. K., Worden, J. R., and Duren, R. M.: Quantifying methane emissions from the global scale down to point sources using satellite observations of atmospheric methane, Atmos. Chem. Phys., 22, 9617–9646, https://doi.org/10.5194/acp-22-9617-2022, 2022.
Jervis, D., McKeever, J., Durak, B. O. A., Sloan, J. J., Gains, D., Varon, D. J., Ramier, A., Strupler, M., and Tarrant, E.: The GHGSat-D imaging spectrometer, Atmos. Meas. Tech., 14, 2127–2140, https://doi.org/10.5194/amt-14-2127-2021, 2021.
Jervis, D., Girard, M., MacLean, J.-P., McKeever, J., Ramier, A., Strupler, M., Tarrant, E., and Young, D.: Quantifying the Plume Detection Probability of the GHGSat Constellation, AGU Fall Meeting, Chigago, IL, USA, 12–16 December 2022, A13E, https://ui.adsabs.harvard.edu/abs/2022AGUFM.A13E..07J/abstract (last access: 19 November 2025), 2022.
Kim, J., Cusworth, D. H., Ayasse, A. K., Howell, K., O'Neill, K., and Duren, R. M.: Performance of airborne imaging spectrometers for carbon dioxide detection and emission quantification, Journal of Geophysical Research: Atmospheres, 130, e2024JD042755, https://doi.org/10.1029/2024JD042755, 2025.
Lauvaux, T., Giron, C., Mazzolini, M., d'Aspremont, A., Duren, R., Cusworth, D., Shindell, D., and Ciais, P.: Global assessment of oil and gas methane ultra-emitters, Science, 2, 557–561, https://doi.org/10.1126/science.abj4351, 2022.
McLinden, C. A., Griffin, D., Davis, Z., Hempel, C., Smith, J., Sioris, C., Nassar, R., Moeini, O., Legault-Ouellet, E., and Malo A.: An independent evaluation of GHGSat methane emissions: Performance assessment, Journal of Geophysical Research: Atmospheres, 129, https://doi.org/10.1029/2023JD039906, 2024.
Mouroulis, P. and Green, R. O.: Review of high fidelity imaging spectrometer design for remote sensing, Opt. Eng. 57, 040901, https://doi.org/10.1117/1.OE.57.4.040901, 2018.
Naus, S., Maasakkers, J. D., Gautam, R., Omara, M., Stikker, R., Veenstra, A. K., Nathan, B., Irakulis-Loitxate, I., Guanter, L., Pandey, S., Girard, M., Lorente, A., Borsdorff, T., and Aben, I.: Environmental Science & Technology, 57, 19545–19556, https://doi.org/10.1021/acs.est.3c04746, 2023.
Nassar, R., Mastrogiacomo, J.-P., Bateman-Hemphill, W., McCracken, C., MacDonald, C. G., Hill, T., O'Dell, C. W., Kiel, M., and Crisp, D.: Advances in quantifying power plant CO2 emissions with OCO-2, Remote Sensing of Environment, 264, 112579, https://doi.org/10.1016/j.rse.2021.112579, 2021.
Nesser, H., Jacob, D. J., Maasakkers, J. D., Lorente, A., Chen, Z., Lu, X., Shen, L., Qu, Z., Sulprizio, M. P., Winter, M., Ma, S., Bloom, A. A., Worden, J. R., Stavins, R. N., and Randles, C. A.: High-resolution US methane emissions inferred from an inversion of 2019 TROPOMI satellite data: contributions from individual states, urban areas, and landfills, Atmos. Chem. Phys., 24, 5069–5091, https://doi.org/10.5194/acp-24-5069-2024, 2024.
Pandey, S., Gautam, R., Houweling, S., van der Gon, H. D., Sadavarte, P., Borsdorff, T., Hasekamp, O., Landgraf, J., Tol, P., van Kempen, T., Hoogeveen, R., van Hees, R., Hamburg, S. P., Maasakkers, J. D., and Aben, I.: Satellite observations reveal extreme methane leakage from a natural gas well blowout, Proc. Natl. Acad. Sci. U.S.A., 116, 26376–26381, https://doi.org/10.1073/pnas.1908712116, 2019.
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Short summary
We describe the Carbon Mapper emissions monitoring system including methane and carbon dioxide observations from the constellation of Tanager hyperspectral satellites, a global monitoring strategy optimized for enabling mitigation impact at the scale of individual facilities, and a data platform that delivers timely and transparent information for diverse stakeholders. We present early findings from Tanager-1 including the use of our data to locate and repair a leaking oil and gas pipeline.
We describe the Carbon Mapper emissions monitoring system including methane and carbon dioxide...
