Articles | Volume 24, issue 11
https://doi.org/10.5194/acp-24-6845-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-24-6845-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
13 Jun 2024
Research article |
| 13 Jun 2024
| 13 Jun 2024
Assessing methane emissions from collapsing Venezuelan oil production using TROPOMI
SRON Netherlands Institute for Space Research, Leiden, the Netherlands
Joannes D. Maasakkers
SRON Netherlands Institute for Space Research, Leiden, the Netherlands
Stijn Naus
SRON Netherlands Institute for Space Research, Leiden, the Netherlands
Ritesh Gautam
Environmental Defense Fund, Washington, DC, USA
Mark Omara
Environmental Defense Fund, Washington, DC, USA
Daniel J. Varon
School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
Melissa P. Sulprizio
School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
Lucas A. Estrada
School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
Alba Lorente
SRON Netherlands Institute for Space Research, Leiden, the Netherlands
Tobias Borsdorff
SRON Netherlands Institute for Space Research, Leiden, the Netherlands
Robert J. Parker
National Centre for Earth Observation, University of Leicester, Leicester, UK
Earth Observation Science, School of Physics and Astronomy, University of Leicester, Leicester, UK
Ilse Aben
SRON Netherlands Institute for Space Research, Leiden, the Netherlands
Department of Earth Sciences, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
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Sarah E. Hancock, Daniel J. Jacob, Nicholas Balasus, Carlos Andres Garzon, Ciniro Costa Junior, Matthew R. Johnson, Nikolai Calderón-Cangrejo, Scott Winton, Megan He, Lauren Potyk, Lucas A. Estrada, Rodrigo Jimenez, Andrés Ardila, Luis Morales-Rincon, and James L. France
EGUsphere, https://doi.org/10.5194/egusphere-2026-5754, https://doi.org/10.5194/egusphere-2026-5754, 2026
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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Satellite observations reveal why methane emissions rose in Colombia during 2019–2024. Wetlands drove most of the increase, with emissions peaking during the wet La Niña years of 2021–2022. Human activities showed a steadier rise, led by livestock, waste, and fossil fuels. Wetland emissions tracked changes in water storage more closely than flooded area alone. These findings help distinguish natural variability from human sources when tracking progress on methane mitigation.
Chris Huntingford, Jesse F. Abrams, Peter Ashwin, Niklas Boers, Chris A. Boulton, Joshua E. Buxton, Joseph Clarke, Peter M. Cox, Andrew M. Cunliffe, Henk A. Dijkstra, Bahar Emirzade, Darren Ghent, Daniel Giles, Sneha Kachhara, Timothy M. Lenton, Valerio Lucarini, Helen Millman, Robert J. Parker, Sergei Petrovskii, Paul D. L. Ritchie, Cristina Ruiz Villena, Mark S. Williamson, and Niccolò Zagli
EGUsphere, https://doi.org/10.5194/egusphere-2026-5606, https://doi.org/10.5194/egusphere-2026-5606, 2026
This preprint is open for discussion and under review for Earth System Dynamics (ESD).
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Future tipping of key parts of the Earth system, driven by human-induced climate change, poses serious risks to society. These concerns have spurred the development of Early Warning Systems (EWSs) that use data to show how close we are to tipping. However, existing EWSs are often generic statistical forms. We first review current EWS methods, then present a broad set of hypotheses that may help improve them. We argue strongly for process knowledge to guide more refined EWS forms.
Daniel Cusworth, Daniel Varon, Dylan Jervis, Jason McKeever, Alexander Turner, Christian Frankenberg, John Worden, Andrew Thorpe, Jay Fahlen, Sudhanshu Pandey, Joannes Maasakkers, Ilse Aben, Annmarie Eldering, Riley Duren, Bradley Conrad, Tia Scarpelli, Daniel Bon, Mackenzie Huffman, Itziar Irakulis-Loitxate, Luis Guanter, Jason Schroeder, Benjamin Hmiel, Evan Sherwin, Sean Crowell, Eric Kort, Adam Brandt, Frances Reuland, Maryann Sargent, James East, and Daniel Jacob
EGUsphere, https://doi.org/10.5194/egusphere-2026-6060, https://doi.org/10.5194/egusphere-2026-6060, 2026
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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In this review, we summarize the current and anticipated state of satellite remote sensing for point sources. In particular, we are provide and update to the fleet of point source imaging satellites, summarize the nuance around data availability and revisit, detail data processing pipelines and validation procedures, describe how to benchmark detection performance, and finally, describe demonstrated use-cases for satellite point source observations.
Dandan Zhang, Daniel J. Jacob, Elizabeth W. Lundgren, Melissa P. Sulprizio, Nicholas Balasus, Lucas A. Estrada, Emily Reidy, and Daniel J. Varon
EGUsphere, https://doi.org/10.5194/egusphere-2026-4399, https://doi.org/10.5194/egusphere-2026-4399, 2026
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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Dense satellite observations call for global high-resolution inversions to infer surface fluxes. The computational cost for explicit Jacobian construction has limited global analytical inversions to coarse resolution despite the availability of fine-resolution satellite observations. Here we show the stretched-grid high-performance GEOS-Chem model can considerably reduce the computational and storage costs while closely reproducing the posterior fluxes from the standard inversion results.
Jacob B. H. Bushey, Michael Bertolacci, Joshua Benmergui, Julian Kostinek, Maryann Sargent, Marvin Knapp, Ethan Kyzivat, Sasha Ayvazov, Marcus Russi, Zhan Zhang, Apisada Chulakadabba, Jia Chen, Christopher Chan Miller, Sébastien Roche, Lucas A. Estrada, James D. East, Luna Yin, James P. Williams, Anthony Himmelberger, Ritesh Gautam, Mark Omara, and Steven C. Wofsy
EGUsphere, https://doi.org/10.5194/egusphere-2026-4693, https://doi.org/10.5194/egusphere-2026-4693, 2026
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
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MethaneSAT was a designed to measure the concentration of methane in the atmosphere over oil and gas producing regions. Our modeling framework uses observations from MethaneSAT to estimate emissions from the Permian Basin. We show that the model accurately captures spatial patterns in emissions and compares well to other models that rely on different atmospheric transport. This data set is valuable for emissions monitoring and mitigation at high spatial resolution and with high precision.
Clayton Roberts, Joannes D. Maasakkers, Tobias A. de Jong, Berend J. Schuit, Shubham Sharma, Theo Huegens, Anne-Wil van den Berg, Sander Houweling, and Ilse Aben
Atmos. Meas. Tech., 19, 5659–5682, https://doi.org/10.5194/amt-19-5659-2026, https://doi.org/10.5194/amt-19-5659-2026, 2026
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Methane is a powerful greenhouse gas, and cutting its emissions can slow climate change in the near term. We have created ML-SPERE, a new machine-learning based method that uses TROPOMI observations and weather data to better estimate emission rates for large methane plumes. It has proved more accurate than the Integrated Mass Enhancement (IME) method when tested on simulated satellite observations. When applied to real TROPOMI plumes, ML-SPERE produces estimates that agree with other methods.
Daniel A. Potts, Harjinder Sembhi, Matthieu Dogniaux, Joannes D. Maasakkers, Berend J. Schuit, Dirk Schuettemeyer, Timon Hummel, Rocio Barrio Guillo, Oliver Schneising, Luis Guanter, and Ilse Aben
EGUsphere, https://doi.org/10.5194/egusphere-2026-3797, https://doi.org/10.5194/egusphere-2026-3797, 2026
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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Routine monitoring of industrial emissions is vital to understand the location, frequency, and intensity of methane emissions. We used satellite and aircraft measurements to understand methane emissions from Madrid across various scales and sectors. Using a range of methods, we identify a clear gap between top-down and bottom-up approaches, discuss challenges associated with satellite interpretation, connect emissions to on-site practices, and make recommendations towards operational use.
Robert J. Parker, Michael P. Cartwright, Dan Orr, Lakshmi N. Bharathan, Neil Humpage, Alex J. Webb, Peter Somkuti, Hartmut Boesch, Antonio Di Noia, Hiroshi Suto, Matthias Buschmann, Nicholas M. Deutscher, David W. T. Griffith, Frank Hase, Rigel Kivi, Erin McGee, Isamu Morino, Hirofumi Ohyama, Christof Petri, John Robinson, Coleen M. Roehl, Mahesh Kumar Sha, Kei Shiomi, Kimberly Strong, Ralf Sussmann, Yao Té, Voltaire A. Velazco, Mihalis Vrekoussis, Wei Wang, Thorsten Warneke, Damien Weidmann, Debra Wunch, and Minqiang Zhou
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2026-625, https://doi.org/10.5194/essd-2026-625, 2026
Preprint under review for ESSD
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Methane is a powerful greenhouse gas and its concentration in the atmosphere is rising rapidly. We present a new record of atmospheric methane measured from space by the Japanese GOSAT-2 satellite, covering 2019 to 2025. The measurements are processed identically to those from its predecessor GOSAT and checked against ground-based instruments around the world. Together the two satellites provide a continuous 17-year record that helps track where methane comes from and how quickly it is changing.
Matthew L. Loman, Lee T. Murray, Peter D. Ivatt, Róisín Commane, Andrew Hallward-Driemeier, Raghav Dhall, Eric M. Leibensperger, Nicholas Balasus, Lucas Estrada, Melissa P. Sulprizio, Maryann R. Sargent, and Felix Vogel
EGUsphere, https://doi.org/10.5194/egusphere-2026-3153, https://doi.org/10.5194/egusphere-2026-3153, 2026
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We evaluate methane emissions and their trends in New York State based on observations of methane from 29 sites, including four new long-term sites. These observations are most sensitive to emissions in southeastern New York State, including New York City. We find regional trends and biases in some locations, including underestimated emissions in the New York City area. Our results also demonstrate that policy-relevant validation of methane emissions needs a combination of observation platforms.
Lucas A. Estrada, Daniel J. Jacob, Megan He, James D. East, Daniel J. Varon, Nicholas Balasus, Sarah E. Hancock, Melissa Sulprizio, Kevin W. Bowman, John R. Worden, Emily Reidy, and Benjamin R. K. Runkle
Atmos. Chem. Phys., 26, 10629–10646, https://doi.org/10.5194/acp-26-10629-2026, https://doi.org/10.5194/acp-26-10629-2026, 2026
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We use satellite observations to track US methane emissions from 2019–2024 at national, state, and oil and gas field scales. While total emissions remain stable, oil and gas emissions decline even as production rises, indicating progress in emissions management for the oil and gas sector.
Sarah E. Hancock, Daniel J. Jacob, Rodrigo Jimenez, Andrés Ardila, Luis Morales-Rincon, Néstor Rojas, Lucas A. Estrada, Nicholas Balasus, James D. East, Melissa P. Sulprizio, Xiaolin Wang, James L. France, Lauren Potyk, Elise Penn, Zichong Chen, Daniel J. Varon, Christian Frankenberg, Marci Baranski, Andreea Calcan, and Robert J. Parker
Atmos. Chem. Phys., 26, 10455–10476, https://doi.org/10.5194/acp-26-10455-2026, https://doi.org/10.5194/acp-26-10455-2026, 2026
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We combined satellite observations with detailed national data to improve estimates of Colombia’s methane emissions. Our results show that total methane emissions are higher than reported, with the biggest differences from fossil fuels. This approach demonstrates how satellite data can make national greenhouse gas reporting more accurate and transparent under the Paris Agreement.
Aurélien Sicsik-Paré, Audrey Fortems-Cheiney, Isabelle Pison, Grégoire Broquet, Alvin Opler, Elise Potier, Adrien Martinez, Oliver Schneising, Michael Buchwitz, Joannes D. Maasakkers, Tobias Borsdorff, and Antoine Berchet
Atmos. Chem. Phys., 26, 10423–10454, https://doi.org/10.5194/acp-26-10423-2026, https://doi.org/10.5194/acp-26-10423-2026, 2026
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Assimilating satellite methane observations provides top-down quantification of regional methane emissions. This study compares European emissions in 2019 estimated from the inversion of three satellite datasets. We find inconsistencies in national budgets and spatial patterns, with no product clearly superior. We disentangle drivers of the differences in emissions, highlighting the impact of differences in coverage, observations and errors on the consistency of methane emission estimates.
Mari C. Martinez-Velarte, Jochen Landgraf, Ben Veihelmann, Bernd Sierk, and Tobias Borsdorff
Atmos. Meas. Tech., 19, 4703–4720, https://doi.org/10.5194/amt-19-4703-2026, https://doi.org/10.5194/amt-19-4703-2026, 2026
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Launched in August 2025, Sentinel-5 provides daily CH4 and CO retrievals and is sensitive to CO2. Its shortwave-infrared (SWIR) mercury-cadmium-telluride (MCT) detectors exhibit persistence effects causing scene-dependent biases. This study quantifies these biases for CH4, CO, CO2, and the CH4/CO2 proxy using RemoTeC over regions with high radiance variability. Typical biases are small (<0.34 %), but outliers reach 1.59–4.01 %. Targeted post-filtering can reduce outliers and meet mission performance.
Zhan Zhang, Maryann Sargent, Ethan Manninen, Jack D. Warren, Apisada Chulakadabba, Marcus Russi, Sasha Ayvazov, Joshua Benmergui, Marvin Knapp, Ethan Kyzivat, Christopher C. Miller, Sébastien Roche, Bingkun Luo, David J. Miller, Maya Nasr, Manuel Perez-Carrasco, Kang Sun, James P. Williams, Katlyn MacKay, Mark Omara, Jia Chen, Luis Guanter, Ritesh Gautam, Jonathan Franklin, Xiong Liu, and Steven C. Wofsy
Atmos. Meas. Tech., 19, 4637–4651, https://doi.org/10.5194/amt-19-4637-2026, https://doi.org/10.5194/amt-19-4637-2026, 2026
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Methane released into the atmosphere is often difficult to detect in satellite imagery because the signals can be weak and hidden by background noise. We developed an automated method that improves the visibility of methane plumes while reducing false detections, decreasing the need for time-consuming manual inspection. The method identifies more small emission sources across different instruments, helping build a more complete understanding of methane emissions and their impacts.
Tobias Borsdorff, Maarten Krol, Pepijn Veefkind, and Jochen Landgraf
Atmos. Meas. Tech., 19, 4617–4636, https://doi.org/10.5194/amt-19-4617-2026, https://doi.org/10.5194/amt-19-4617-2026, 2026
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Industrial facilities release carbon dioxide and nitrogen dioxide. The Twin Anthropogenic Greenhouse Gas Observers (TANGO) mission, launching in 2028, will monitor both gases from ten thousand facilities per year using two satellites. We studied whether combining both improves carbon dioxide emission estimates and reveals plume chemistry. While this produces cleaner carbon dioxide images, precision does not improve as noise is redistributed not eliminated. Their ratio captures how nitrogen oxide converts to nitrogen dioxide within plumes.
Xin Zhang, Joannes D. Maasakkers, Tobias A. de Jong, Paul Tol, Frances Reuland, Adam R. Brandt, Eric A. Kort, Taylor J. Adams, and Ilse Aben
Geosci. Model Dev., 19, 5979–6000, https://doi.org/10.5194/gmd-19-5979-2026, https://doi.org/10.5194/gmd-19-5979-2026, 2026
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Reducing emissions of greenhouse gases such as methane and carbon dioxide is essential for addressing climate change. We developed HyperGas, an open tool that uses hyperspectral satellite images to retrieve and detect greenhouse gas plumes. It helps scientists locate emission sources, estimate their strength, and examine uncertainties through an easy workflow and visual app. Our goal is to make tracking human-made emissions more accurate and accessible, supporting better climate monitoring.
Christopher Chan Miller, Sébastien Roche, Jonas Wilzweski, Xiong Liu, Kelly V. Chance, Bingkun Luo, Kang Sun, Jonathan E. Franklin, Joshua S. Benmergui, Maya Nasr, David J. Miller, Sean Crowell, Nathan Leisso, Eleanor Walker, Ritesh Gautam, Nicholas LoFaso, Sasha Ayvazov, David Wells, Carlos Cervantes, Christopher Hairfield, and Steven Wofsy
EGUsphere, https://doi.org/10.5194/egusphere-2026-3365, https://doi.org/10.5194/egusphere-2026-3365, 2026
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Reducing oil and gas methane emissions is among the fastest ways to slow near-term climate change, and satellites offer a transparent means of verifying progress. MethaneSAT fills a gap between existing instruments, which either measure methane accurately but at coarse scales, or detect large leaks at fine resolution without the accuracy to account for all sources. We present the first measurements and show they meet the accuracy requirements for regional emissions mapping at the 2–4 km2 scale.
John Worden, Sudhanshu Pandey, Hannah Nesser, Kevin Bowman, Colin Harkins, Congmeng Lyu, Joannes D. Maasakkers, Deborah Gordon, Daniel Jacob, Lucas Estrada, Daniel J. Varon, James D. East, Lauren Schmeisser, and Zhen Qu
Atmos. Chem. Phys., 26, 8855–8873, https://doi.org/10.5194/acp-26-8855-2026, https://doi.org/10.5194/acp-26-8855-2026, 2026
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To support methane reduction, we compared three widely used maps of methane emissions in the United States with estimates derived from a methane-measuring satellite from 2012 to 2020. The satellite indicates higher emissions from oil and gas production and from livestock in several regions, while other sources were harder to pin down. Neither approach shows a clear change over time. The results point to where better measurements can most improve emissions reporting and guide mitigation.
Liang Feng, Paul I. Palmer, Haolin Wang, Robert Parker, Hartmut Boesch, Sébastien C. Biraud, Łukasz Chmura, Emanuel Gloor, László Haszpra, Elena Kozlova, Euan G. Nisbet, Steffen M. Noe, Thomas Röckmann, Rodrigo Augusto Ferreira de Souza, and Martin Steinbacher
EGUsphere, https://doi.org/10.5194/egusphere-2026-2662, https://doi.org/10.5194/egusphere-2026-2662, 2026
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This study examines the relative roles of emissions and oxidation in recent rapid methane growth. Using an ensemble Kalman filter, we quantify global methane sources and sinks for 2018–2024. Emission changes dominate the increase, except in 2020 when a COVID‑19‑related OH decline strongly affected sinks. Atmospheric photochemistry—including OH and CH₄ variability and temperature‑dependent oxidation—also significantly shapes the methane budget.
David J. Miller, Kang Sun, Jonathan E. Franklin, Nathan Leisso, Sébastien Roche, Bingkun Luo, Christopher Chan Miller, Sasha Ayvazov, Sean Crowell, Nick LoFaso, Tom Kampe, Peter Spuhler, Betsy Farris, Eleanor Walker, Tom Melendez, Ritesh Gautam, Xiong Liu, and Steven C. Wofsy
EGUsphere, https://doi.org/10.5194/egusphere-2026-2675, https://doi.org/10.5194/egusphere-2026-2675, 2026
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
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With a focus on mitigating climate change, the MethaneSAT satellite mission aims to catalyze methane emission reductions. MethaneSAT has provided high-resolution emissions products across global oil and gas basins. We present novel calibration methods of MethaneSAT's instrumentation that demonstrate stable on-orbit performance compared with ground-based calibration. Our results are important for similar satellite missions focused on monitoring climate-relevant emissions.
Xiaolin Wang, Melissa P. Sulprizio, Yuyao Zhuge, Randall V. Martin, and Daniel J. Jacob
Atmos. Chem. Phys., 26, 6857–6867, https://doi.org/10.5194/acp-26-6857-2026, https://doi.org/10.5194/acp-26-6857-2026, 2026
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We implement a new 12-km global nested simulation capability in GEOS-Chem, an open-source global 3-D model of atmospheric chemistry. Compared with the standard 25-km simulation, the 12-km simulation features stronger vertical transport due to better resolved horizontal convergence, along with improved representation of urban NO2 and ozone titration. Application to methane emission inversion yields higher information content and resolves finer spatial structure in emission sectors.
James P. Williams, Joshua Benmergui, Marvin Knapp, Mark Omara, Anthony Himmelberger, Ethan Kyzivat, Kaiya Weatherby, Ben Lyke, Jack Warren, Katlyn MacKay, Sasha Ayvazov, Marcus Russi, Nicholas LoFaso, Tom Melendez, Christopher C. Miller, Sebastien Roche, Maryann Sargent, Jonathan Franklin, Maya Nasr, Zhan Zhang, David J. Miller, Bingkun Luo, Luis Guanter, Steven P. Hamburg, Steven C. Wofsy, and Ritesh Gautam
Atmos. Chem. Phys., 26, 5961–5981, https://doi.org/10.5194/acp-26-5961-2026, https://doi.org/10.5194/acp-26-5961-2026, 2026
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Methane is a potent greenhouse gas, and satellite observations are critical for reducing emissions. Using 2024–2025 MethaneSAT data, we quantify methane emissions across six major oil and gas basins at high resolution, revealing substantial underestimation at basin, subbasin, and local levels. Our results underscore the need for new, spatially resolved measurements and the continued advancement of remote sensing capabilities to provide more detailed, actionable insights for methane mitigation.
Nicholas Balasus, Daniel J. Jacob, A. Anthony Bloom, James D. East, Lucas A. Estrada, Sarah E. Hancock, Megan He, Todd A. Mooring, Alexander J. Turner, and John R. Worden
Atmos. Chem. Phys., 26, 4601–4617, https://doi.org/10.5194/acp-26-4601-2026, https://doi.org/10.5194/acp-26-4601-2026, 2026
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We use satellite observations of methane to determine the amount of methane coming from Africa and relate this to the physical processes responsible, with relevance for climate change given methane's potency as a greenhouse gas. We find that the amount of methane coming from Africa has increased by a third across 2019–2024, driven primarily by steady increases in emissions from livestock, in addition to irregular surges from wetlands.
Kanwal Shahzadi, Matthias Schneider, Nga Ying Lo, Frank Hase, Jörg Meyer, Ugur Cayoglu, Tobias Borsdorff, and Mari C. Martinez-Velarte
Earth Syst. Sci. Data, 18, 2153–2177, https://doi.org/10.5194/essd-18-2153-2026, https://doi.org/10.5194/essd-18-2153-2026, 2026
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We merge TROPOMI and IASI L2 methane data from January 2018 to June 2021 on a global scale. The data merging yields total column-averaged and upper tropospheric/stratospheric partial column-averaged mole fractions (already provided by the individual data sets). In addition, it outputs tropospheric partial column-averaged mole fractions (not provided by any of the two individual data sets). We briefly document their increased potential for quantifying near-surface methane emissions.
Lakshmi N. Bharathan, Robert J. Parker, Michael Cartwright, Dan Orr, Antonio Di Noia, Peter Somkuti, Alex Webb, and Hartmut Bösch
EGUsphere, https://doi.org/10.5194/egusphere-2026-1029, https://doi.org/10.5194/egusphere-2026-1029, 2026
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The study aims to enhance satellite- based methane measurements over the Arctic high-latitudes, a critical region where rapid warming feeds the permafrost thawing-methane cycle and poise high concern for global climate stability. A 20 % gain in GOSAT satellite methane data throughput has been achieved using a Genetic algorithm optimisation approach, enhancing our capacity to track methane emissions over most rapidly warming, climatically sensitive regions on the Earth.
Luis Guanter, Javier Roger, Jack Warren, Maryann Sargent, Zhan Zhang, Sébastien Roche, Christopher Chan Miller, Michael Steiner, Harvey Hadfield, Mark Omara, James Williams, Katlyn MacKay, Jonathan E. Franklin, Bingkun Luo, Steven C. Wofsy, Steven P. Hamburg, and Ritesh Gautam
Atmos. Chem. Phys., 26, 2941–2963, https://doi.org/10.5194/acp-26-2941-2026, https://doi.org/10.5194/acp-26-2941-2026, 2026
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We evaluate the potential of the MethaneSAT satellite mission to detect and quantify methane plumes from high emitting point sources and use the existing MethaneSAT data archive to evaluate super-emissions from the most important oil and gas basins in the world.
Srijana Lama, Joannes D. Maasakkers, Xin Zhang, Marianne Girard, Swarna Dutt, Suyash Nandgaonkar, Daniel J. Varon, Melissa P. Sulprizio, Lucas A. Estrada, Nicholas Balasus, Robert J. Parker, Yukio Terao, and Ilse Aben
EGUsphere, https://doi.org/10.5194/egusphere-2025-6528, https://doi.org/10.5194/egusphere-2025-6528, 2026
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Methane is the second most important anthropogenic greenhouse gas in terms of radiative forcing, with a global warming potential 27–30 times that of CO2 over a 100-year timescale. Effective mitigation requires a detailed understanding of the spatial distribution and magnitude of emissions. Here, we quantify India’s 2021 methane emissions at a resolution of up to 0.25° × 0.3125° using TROPOMI observations within the Bayesian Integrated Methane Inversion framework.
Katlyn MacKay, Joshua Benmergui, James P. Williams, Mark Omara, Anthony Himmelberger, Maryann Sargent, Jack D. Warren, Christopher C. Miller, Sébastien Roche, Zhan Zhang, Jonathan Franklin, Luis Guanter, Steven Wofsy, and Ritesh Gautam
Atmos. Chem. Phys., 26, 1179–1192, https://doi.org/10.5194/acp-26-1179-2026, https://doi.org/10.5194/acp-26-1179-2026, 2026
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Reducing methane emissions from the oil/gas sector can mitigate near-term climate warming and the losses of a valuable energy resource. We analyze data collected using MethaneAIR to assess methane emissions in regions accounting for 70 % of United States onshore oil/gas production in 2023. We estimate total oil/gas methane emissions across all measured regions to be ~8 Tg/yr, equivalent to 1.6 % of produced gas, which is five times higher than reported by the US Environmental Protection Agency.
Tia R. Scarpelli, Elfie Roy, Daniel J. Jacob, Melissa P. Sulprizio, Ryan D. Tate, and Daniel H. Cusworth
Earth Syst. Sci. Data, 17, 7019–7033, https://doi.org/10.5194/essd-17-7019-2025, https://doi.org/10.5194/essd-17-7019-2025, 2025
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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.
Hannah Nesser, Kevin W. Bowman, Matthew D. Thill, Daniel J. Varon, Cynthia A. Randles, Ashutosh Tewari, Felipe J. Cardoso-Saldaña, Emily Reidy, Joannes D. Maasakkers, and Daniel J. Jacob
Geosci. Model Dev., 18, 9279–9291, https://doi.org/10.5194/gmd-18-9279-2025, https://doi.org/10.5194/gmd-18-9279-2025, 2025
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Regional analyses of atmospheric trace gases can improve knowledge of fluxes at high resolution but rely on specified boundary conditions (BCs) at the domain edges. Biases in the often-uncertain BCs propagate to the inferred fluxes. We develop a framework to explain how errors in the BCs influence the optimized fluxes, derive two metrics to estimate this influence, and compare two methods to correct for the biases. We demonstrate correcting BCs directly is more effective at reducing bias.
Jack H. Bruno, Daniel J. Jacob, Xiaolin Wang, Melissa P. Sulprizio, Lucas A. Estrada, Daniel J. Varon, Steven C. Wofsy, Mark Omara, and Ritesh Gautam
EGUsphere, https://doi.org/10.5194/egusphere-2025-4626, https://doi.org/10.5194/egusphere-2025-4626, 2025
Preprint archived
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We use data from both aircraft (MethaneAIR) and satellite (TROPOMI) based measurements of methane in the atmosphere to better understand methane emissions from fossil fuel extraction. Data from these instruments are combined with a computer model of the atmosphere to improve estimates of methane emissions. We find that combining data from multiple sources provides more information than either source on its own. The tools and data we use are freely available.
Andrew Gerald Barr, Jochen Landgraf, Mari Martinez-Velarte, Mihalis Vrekoussis, Ralf Sussmann, Isamu Morino, Kimberly Strong, Minqiang Zhou, Voltaire A. Velazco, Hirofumi Ohyama, Thorsten Warneke, Frank Hase, and Tobias Borsdorff
Atmos. Meas. Tech., 18, 6093–6123, https://doi.org/10.5194/amt-18-6093-2025, https://doi.org/10.5194/amt-18-6093-2025, 2025
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The Greenhouse Gases Observing Satellite-2 (GOSAT-2) is a satellite dedicated to measuring concentrations of greenhouse gases from space. Since its launch, the increase of CH4 and CO2 concentrations in the atmosphere is clear. The datasets obtained from GOSAT-2 are used in the Copernicus atmospheric services to monitor the climate, in light of the Paris Agreement. Here we present robust datasets of these gases from GOSAT-2, including a novel machine learning approach to data quality filtering.
Drew C. Pendergrass, Daniel J. Jacob, Nicholas Balasus, Lucas Estrada, Daniel J. Varon, James D. East, Megan He, Todd A. Mooring, Elise Penn, Hannah Nesser, and John R. Worden
Atmos. Chem. Phys., 25, 14353–14369, https://doi.org/10.5194/acp-25-14353-2025, https://doi.org/10.5194/acp-25-14353-2025, 2025
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We use satellite observations of atmospheric methane, a greenhouse gas, to calculate emissions from both human and natural sources. We find that methane emissions surged in 2020–2021 before declining in 2022–2023. We attribute the surge in large part to emissions from eastern Africa, which experienced large methane-generating floods. Wetland models underestimate emissions in that region, which has led some previous work to incorrectly attribute the African surge in methane emissions to livestock.
Jack D. Warren, Maryann Sargent, James P. Williams, Mark Omara, Christopher C. Miller, Sebastien Roche, Katlyn MacKay, Ethan Manninen, Apisada Chulakadabba, Anthony Himmelberger, Joshua Benmergui, Zhan Zhang, Luis Guanter, Steve Wofsy, and Ritesh Gautam
Atmos. Chem. Phys., 25, 10661–10675, https://doi.org/10.5194/acp-25-10661-2025, https://doi.org/10.5194/acp-25-10661-2025, 2025
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Mitigating anthropogenic methane emissions requires a detailed understanding of emitting facilities. We use observations of methane point sources from the MethaneAIR instrument from 2021–2023 that covered ~80 % of US onshore oil and gas production regions. We attribute these observations to facility types to explore how emissions vary by industrial sectors. Oil and gas facilities make up most point source emissions nationally, but in certain basins other sectors can make up the majority.
Luis Guanter, Jack Warren, Mark Omara, Apisada Chulakadabba, Javier Roger, Maryann Sargent, Jonathan E. Franklin, Steven C. Wofsy, and Ritesh Gautam
Atmos. Meas. Tech., 18, 3857–3872, https://doi.org/10.5194/amt-18-3857-2025, https://doi.org/10.5194/amt-18-3857-2025, 2025
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This study presents a data processing scheme for the detection and quantification of methane emissions using the MethaneAIR airborne spectrometer. We show that the proposed methods enable the detection of smaller plumes (compared with those detectable using other existing methods) and improve the potential of MethaneAIR to survey methane point sources across large regions.
Santiago Botía, Saqr Munassar, Thomas Koch, Danilo Custodio, Luana S. Basso, Shujiro Komiya, Jost V. Lavric, David Walter, Manuel Gloor, Giordane Martins, Stijn Naus, Gerbrand Koren, Ingrid T. Luijkx, Stijn Hantson, John B. Miller, Wouter Peters, Christian Rödenbeck, and Christoph Gerbig
Atmos. Chem. Phys., 25, 6219–6255, https://doi.org/10.5194/acp-25-6219-2025, https://doi.org/10.5194/acp-25-6219-2025, 2025
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This study uses dry CO2 mole fractions from the Amazon Tall Tower Observatory together with airborne profiles to estimate net carbon exchange in tropical South America. We found that the biogeographic Amazon is a net carbon sink, while the Cerrado and Caatinga biomes are net carbon sources, resulting in an overall neutral balance. Finally, to further reduce the uncertainty in our estimates we call for an expansion of the monitoring capacity, especially in the Amazon–Andes foothills.
Lucas A. Estrada, Daniel J. Varon, Melissa Sulprizio, Hannah Nesser, Zichong Chen, Nicholas Balasus, Sarah E. Hancock, Megan He, James D. East, Todd A. Mooring, Alexander Oort Alonso, Joannes D. Maasakkers, Ilse Aben, Sabour Baray, Kevin W. Bowman, John R. Worden, Felipe J. Cardoso-Saldaña, Emily Reidy, and Daniel J. Jacob
Geosci. Model Dev., 18, 3311–3330, https://doi.org/10.5194/gmd-18-3311-2025, https://doi.org/10.5194/gmd-18-3311-2025, 2025
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Reducing emissions of methane, a powerful greenhouse gas, is a top policy concern for mitigating anthropogenic climate change. The Integrated Methane Inversion (IMI) is an advanced, cloud-based software that translates satellite observations into actionable emissions data. Here we present IMI version 2.0 with vastly expanded capabilities. These updates enable a wider range of scientific and stakeholder applications from individual basin to global scales with continuous emissions monitoring.
Marielle Saunois, Adrien Martinez, Benjamin Poulter, Zhen Zhang, Peter A. Raymond, Pierre Regnier, Josep G. Canadell, Robert B. Jackson, Prabir K. Patra, Philippe Bousquet, Philippe Ciais, Edward J. Dlugokencky, Xin Lan, George H. Allen, David Bastviken, David J. Beerling, Dmitry A. Belikov, Donald R. Blake, Simona Castaldi, Monica Crippa, Bridget R. Deemer, Fraser Dennison, Giuseppe Etiope, Nicola Gedney, Lena Höglund-Isaksson, Meredith A. Holgerson, Peter O. Hopcroft, Gustaf Hugelius, Akihiko Ito, Atul K. Jain, Rajesh Janardanan, Matthew S. Johnson, Thomas Kleinen, Paul B. Krummel, Ronny Lauerwald, Tingting Li, Xiangyu Liu, Kyle C. McDonald, Joe R. Melton, Jens Mühle, Jurek Müller, Fabiola Murguia-Flores, Yosuke Niwa, Sergio Noce, Shufen Pan, Robert J. Parker, Changhui Peng, Michel Ramonet, William J. Riley, Gerard Rocher-Ros, Judith A. Rosentreter, Motoki Sasakawa, Arjo Segers, Steven J. Smith, Emily H. Stanley, Joël Thanwerdas, Hanqin Tian, Aki Tsuruta, Francesco N. Tubiello, Thomas S. Weber, Guido R. van der Werf, Douglas E. J. Worthy, Yi Xi, Yukio Yoshida, Wenxin Zhang, Bo Zheng, Qing Zhu, Qiuan Zhu, and Qianlai Zhuang
Earth Syst. Sci. Data, 17, 1873–1958, https://doi.org/10.5194/essd-17-1873-2025, https://doi.org/10.5194/essd-17-1873-2025, 2025
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Methane (CH4) is the second most important human-influenced greenhouse gas in terms of climate forcing after carbon dioxide (CO2). A consortium of multi-disciplinary scientists synthesise and update the budget of the sources and sinks of CH4. This edition benefits from important progress in estimating emissions from lakes and ponds, reservoirs, and streams and rivers. For the 2010s decade, global CH4 emissions are estimated at 575 Tg CH4 yr-1, including ~65 % from anthropogenic sources.
Shutao Zhao, Yuzhong Zhang, Shuang Zhao, Xinlu Wang, and Daniel J. Varon
Atmos. Chem. Phys., 25, 4035–4052, https://doi.org/10.5194/acp-25-4035-2025, https://doi.org/10.5194/acp-25-4035-2025, 2025
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We target the challenge of detecting methane super-emitters in oil and gas fields, which is critical for mitigating climate change. Traditional satellite-based detectors struggle due to interference from complex surfaces. We developed a novel method using deep transfer learning that improves detection efficiency and accuracy by reducing artifacts and adapting methane knowledge to different regions. Application revealed significant methane emissions, demonstrating the potential of our method.
Elise Penn, Daniel J. Jacob, Zichong Chen, James D. East, Melissa P. Sulprizio, Lori Bruhwiler, Joannes D. Maasakkers, Hannah Nesser, Zhen Qu, Yuzhong Zhang, and John Worden
Atmos. Chem. Phys., 25, 2947–2965, https://doi.org/10.5194/acp-25-2947-2025, https://doi.org/10.5194/acp-25-2947-2025, 2025
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The hydroxyl radical (OH) destroys many air pollutants, including methane. Global-mean OH cannot be directly measured, and thus it is inferred with the methyl chloroform (MCF) proxy. MCF is decreasing, and a replacement is needed. We use satellite observations of methane in two spectral ranges as a proxy for OH. We find shortwave infrared observations can characterize yearly OH and its seasonality but not the latitudinal distribution. Thermal infrared observations add little information.
James P. Williams, Mark Omara, Anthony Himmelberger, Daniel Zavala-Araiza, Katlyn MacKay, Joshua Benmergui, Maryann Sargent, Steven C. Wofsy, Steven P. Hamburg, and Ritesh Gautam
Atmos. Chem. Phys., 25, 1513–1532, https://doi.org/10.5194/acp-25-1513-2025, https://doi.org/10.5194/acp-25-1513-2025, 2025
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We utilize peer-reviewed facility-level oil and gas methane emission rate data gathered in prior work to estimate the relative contributions of methane sources emitting at different emission rates in the United States. We find that the majority of total methane emissions in the US oil and gas sector stem from a large number of small sources emitting in aggregate, corroborating findings from several other studies.
Sarah E. Hancock, Daniel J. Jacob, Zichong Chen, Hannah Nesser, Aaron Davitt, Daniel J. Varon, Melissa P. Sulprizio, Nicholas Balasus, Lucas A. Estrada, María Cazorla, Laura Dawidowski, Sebastián Diez, James D. East, Elise Penn, Cynthia A. Randles, John Worden, Ilse Aben, Robert J. Parker, and Joannes D. Maasakkers
Atmos. Chem. Phys., 25, 797–817, https://doi.org/10.5194/acp-25-797-2025, https://doi.org/10.5194/acp-25-797-2025, 2025
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We quantify 2021 methane emissions in South America at up to 25 km × 25 km resolution using satellite methane observations. We find a 55 % upward adjustment to anthropogenic emission inventories, including those reported to the UN Framework Convention on Climate Change under the Paris Agreement. Our estimates match inventories for Brazil, Bolivia, and Paraguay but are much higher for other countries. Livestock emissions (65 % of anthropogenic emissions) show the largest discrepancies.
Gijs Leguijt, Joannes D. Maasakkers, Hugo A. C. Denier van der Gon, Arjo J. Segers, Tobias Borsdorff, Ivar R. van der Velde, and Ilse Aben
Atmos. Chem. Phys., 25, 555–574, https://doi.org/10.5194/acp-25-555-2025, https://doi.org/10.5194/acp-25-555-2025, 2025
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The production of steel coincides with large emissions of greenhouse gases and air pollutants including carbon monoxide. European facilities are required to report their emissions, which are estimated using a variety of methods. We evaluate these estimates using carbon monoxide concentrations measured via satellite. We find generally good agreement between our values and those reported but also identify some uncertainties, showing that satellites can provide insights into these emissions.
Christopher Chan Miller, Sébastien Roche, Jonas S. Wilzewski, Xiong Liu, Kelly Chance, Amir H. Souri, Eamon Conway, Bingkun Luo, Jenna Samra, Jacob Hawthorne, Kang Sun, Carly Staebell, Apisada Chulakadabba, Maryann Sargent, Joshua S. Benmergui, Jonathan E. Franklin, Bruce C. Daube, Yang Li, Joshua L. Laughner, Bianca C. Baier, Ritesh Gautam, Mark Omara, and Steven C. Wofsy
Atmos. Meas. Tech., 17, 5429–5454, https://doi.org/10.5194/amt-17-5429-2024, https://doi.org/10.5194/amt-17-5429-2024, 2024
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MethaneSAT is an upcoming satellite mission designed to monitor methane emissions from the oil and gas (O&G) industry globally. Here, we present observations from the first flight campaign of MethaneAIR, a MethaneSAT-like instrument mounted on an aircraft. MethaneAIR can map methane with high precision and accuracy over a typically sized oil and gas basin (~200 km2) in a single flight. This paper demonstrates the capability of the upcoming satellite to routinely track global O&G emissions.
Mark Omara, Anthony Himmelberger, Katlyn MacKay, James P. Williams, Joshua Benmergui, Maryann Sargent, Steven C. Wofsy, and Ritesh Gautam
Earth Syst. Sci. Data, 16, 3973–3991, https://doi.org/10.5194/essd-16-3973-2024, https://doi.org/10.5194/essd-16-3973-2024, 2024
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We review, analyze, and synthesize previous peer-reviewed measurement-based data on facility-level oil and gas methane emissions and use these data to develop a high-resolution spatially explicit inventory of US basin-level and national methane emissions. This work provides an improved assessment of national methane emissions relative to government inventories in support of accurate and comprehensive methane emissions assessment, attribution, and mitigation.
Matthieu Dogniaux, Joannes D. Maasakkers, Daniel J. Varon, and Ilse Aben
Atmos. Meas. Tech., 17, 2777–2787, https://doi.org/10.5194/amt-17-2777-2024, https://doi.org/10.5194/amt-17-2777-2024, 2024
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We analyze Landsat 8 (L8) and Sentinel-2B (S-2B) observations of the 2022 Nord Stream 2 methane leak and show how challenging this case is for usual data analysis methods. We provide customized calibrations for this Nord Stream 2 case and assess that no firm conclusion can be drawn from L8 or S-2B single overpasses. However, if we opportunistically assume that L8 and S-2B results are independent, we find an averaged L8 and S-2B combined methane leak rate of 502 ± 464 t h−1.
Jack H. Bruno, Dylan Jervis, Daniel J. Varon, and Daniel J. Jacob
Atmos. Meas. Tech., 17, 2625–2636, https://doi.org/10.5194/amt-17-2625-2024, https://doi.org/10.5194/amt-17-2625-2024, 2024
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Methane is a potent greenhouse gas and a current high-priority target for short- to mid-term climate change mitigation. Detection of individual methane emitters from space has become possible in recent years, and the volume of data for this task has been rapidly growing, outpacing processing capabilities. We introduce an automated approach, U-Plume, which can detect and quantify emissions from individual methane sources in high-spatial-resolution satellite data.
Hannah Nesser, Daniel J. Jacob, Joannes D. Maasakkers, Alba Lorente, Zichong Chen, Xiao Lu, Lu Shen, Zhen Qu, Melissa P. Sulprizio, Margaux Winter, Shuang Ma, A. Anthony Bloom, John R. Worden, Robert N. Stavins, and Cynthia A. Randles
Atmos. Chem. Phys., 24, 5069–5091, https://doi.org/10.5194/acp-24-5069-2024, https://doi.org/10.5194/acp-24-5069-2024, 2024
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We quantify 2019 methane emissions in the contiguous US (CONUS) at a ≈ 25 km × 25 km resolution using satellite methane observations. We find a 13 % upward correction to the 2023 US Environmental Protection Agency (EPA) Greenhouse Gas Emissions Inventory (GHGI) for 2019, with large corrections to individual states, urban areas, and landfills. This may present a challenge for US climate policies and goals, many of which target significant reductions in methane emissions.
Piyushkumar N. Patel, Jonathan H. Jiang, Ritesh Gautam, Harish Gadhavi, Olga Kalashnikova, Michael J. Garay, Lan Gao, Feng Xu, and Ali Omar
Atmos. Chem. Phys., 24, 2861–2883, https://doi.org/10.5194/acp-24-2861-2024, https://doi.org/10.5194/acp-24-2861-2024, 2024
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Global measurements of cloud condensation nuclei (CCN) are essential for understanding aerosol–cloud interactions and predicting climate change. To address this gap, we introduced a remote sensing algorithm that retrieves vertically resolved CCN number concentrations from airborne and spaceborne lidar systems. This innovation offers a global distribution of CCN concentrations from space, facilitating model evaluation and precise quantification of aerosol climate forcing.
Lee de Mora, Ranjini Swaminathan, Richard P. Allan, Jerry C. Blackford, Douglas I. Kelley, Phil Harris, Chris D. Jones, Colin G. Jones, Spencer Liddicoat, Robert J. Parker, Tristan Quaife, Jeremy Walton, and Andrew Yool
Earth Syst. Dynam., 14, 1295–1315, https://doi.org/10.5194/esd-14-1295-2023, https://doi.org/10.5194/esd-14-1295-2023, 2023
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We investigate the flux of carbon from the atmosphere into the land surface and ocean for multiple models and over a range of future scenarios. We did this by comparing simulations after the same change in the global-mean near-surface temperature. Using this method, we show that the choice of scenario can impact the carbon allocation to the land, ocean, and atmosphere. Scenarios with higher emissions reach the same warming levels sooner, but also with relatively more carbon in the atmosphere.
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.
Tim A. van Kempen, Tim J. Rotmans, Richard M. van Hees, Carol Bruegge, Dejian Fu, Ruud Hoogeveen, Thomas J. Pongetti, Robert Rosenberg, and Ilse Aben
Atmos. Meas. Tech., 16, 4507–4527, https://doi.org/10.5194/amt-16-4507-2023, https://doi.org/10.5194/amt-16-4507-2023, 2023
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Validation of satellite measurements is essential for providing reliable and consistent products. In this paper, a validation method for TROPOMI-SWIR (Tropospheric Measurement Instrument in the short-wavelength infrared) is explored. TROPOMI-SWIR has been shown to be exceptionally stable, a necessity to explore the methodology. Railroad Valley, Nevada, is a prime location to perform the necessary measurements to validate the satellite measurements of TROPOMI-SWIR.
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.
Luana S. Basso, Chris Wilson, Martyn P. Chipperfield, Graciela Tejada, Henrique L. G. Cassol, Egídio Arai, Mathew Williams, T. Luke Smallman, Wouter Peters, Stijn Naus, John B. Miller, and Manuel Gloor
Atmos. Chem. Phys., 23, 9685–9723, https://doi.org/10.5194/acp-23-9685-2023, https://doi.org/10.5194/acp-23-9685-2023, 2023
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The Amazon’s carbon balance may have changed due to forest degradation, deforestation and warmer climate. We used an atmospheric model and atmospheric CO2 observations to quantify Amazonian carbon emissions (2010–2018). The region was a small carbon source to the atmosphere, mostly due to fire emissions. Forest uptake compensated for ~ 50 % of the fire emissions, meaning that the remaining forest is still a small carbon sink. We found no clear evidence of weakening carbon uptake over the period.
Manu Goudar, Juliëtte C. S. Anema, Rajesh Kumar, Tobias Borsdorff, and Jochen Landgraf
Geosci. Model Dev., 16, 4835–4852, https://doi.org/10.5194/gmd-16-4835-2023, https://doi.org/10.5194/gmd-16-4835-2023, 2023
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A framework was developed to automatically detect plumes and compute emission estimates with cross-sectional flux method (CFM) for biomass burning events in TROPOMI CO datasets using Visible Infrared Imaging Radiometer Suite active fire data. The emissions were more reliable when changing plume height in downwind direction was used instead of constant injection height. The CFM had uncertainty even when the meteorological conditions were accurate; thus there is a need for better inversion models.
Drew C. Pendergrass, Daniel J. Jacob, Hannah Nesser, Daniel J. Varon, Melissa Sulprizio, Kazuyuki Miyazaki, and Kevin W. Bowman
Geosci. Model Dev., 16, 4793–4810, https://doi.org/10.5194/gmd-16-4793-2023, https://doi.org/10.5194/gmd-16-4793-2023, 2023
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We have built a tool called CHEEREIO that allows scientists to use observations of pollutants or gases in the atmosphere, such as from satellites or surface stations, to update supercomputer models that simulate the Earth. CHEEREIO uses the difference between the model simulations of the atmosphere and real-world observations to come up with a good guess for the actual composition of our atmosphere, the true emissions of various pollutants, and whatever else they may want to study.
Mark Omara, Ritesh Gautam, Madeleine A. O'Brien, Anthony Himmelberger, Alex Franco, Kelsey Meisenhelder, Grace Hauser, David R. Lyon, Apisada Chulakadabba, Christopher Chan Miller, Jonathan Franklin, Steven C. Wofsy, and Steven P. Hamburg
Earth Syst. Sci. Data, 15, 3761–3790, https://doi.org/10.5194/essd-15-3761-2023, https://doi.org/10.5194/essd-15-3761-2023, 2023
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We acquire, integrate, and analyze ~ 6 million geospatial oil and gas infrastructure data records based on information available in the public domain and develop an open-access global database including all the major oil and gas facility types that are important sources of methane emissions. This work helps fulfill a crucial geospatial data need, in support of the assessment, attribution, and mitigation of global oil and gas methane emissions at high resolution.
Nicholas Balasus, Daniel J. Jacob, Alba Lorente, Joannes D. Maasakkers, Robert J. Parker, Hartmut Boesch, Zichong Chen, Makoto M. Kelp, Hannah Nesser, and Daniel J. Varon
Atmos. Meas. Tech., 16, 3787–3807, https://doi.org/10.5194/amt-16-3787-2023, https://doi.org/10.5194/amt-16-3787-2023, 2023
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We use machine learning to remove biases in TROPOMI satellite observations of atmospheric methane, with GOSAT observations serving as a reference. We find that the TROPOMI biases relative to GOSAT are related to the presence of aerosols and clouds, the surface brightness, and the specific detector that makes the observation aboard TROPOMI. The resulting blended TROPOMI+GOSAT product is more reliable for quantifying methane emissions.
Gijs Leguijt, Joannes D. Maasakkers, Hugo A. C. Denier van der Gon, Arjo J. Segers, Tobias Borsdorff, and Ilse Aben
Atmos. Chem. Phys., 23, 8899–8919, https://doi.org/10.5194/acp-23-8899-2023, https://doi.org/10.5194/acp-23-8899-2023, 2023
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We present a fast method to evaluate carbon monoxide emissions from cities in Africa. Carbon monoxide is important for climate change in an indirect way, as it is linked to ozone, methane, and carbon dioxide. Our measurements are made with a satellite that sees the entire globe every single day. This means that we can check from space whether the current knowledge of emission rates is up to date. We make the comparison and show that the emission rates in northern Africa are underestimated.
Alice Drinkwater, Paul I. Palmer, Liang Feng, Tim Arnold, Xin Lan, Sylvia E. Michel, Robert Parker, and Hartmut Boesch
Atmos. Chem. Phys., 23, 8429–8452, https://doi.org/10.5194/acp-23-8429-2023, https://doi.org/10.5194/acp-23-8429-2023, 2023
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Changes in atmospheric methane over the last few decades are largely unexplained. Previous studies have proposed different hypotheses to explain short-term changes in atmospheric methane. We interpret observed changes in atmospheric methane and stable isotope source signatures (2004–2020). We argue that changes over this period are part of a large-scale shift from high-northern-latitude thermogenic energy emissions to tropical biogenic emissions, particularly from North Africa and South America.
Ruosi Liang, Yuzhong Zhang, Wei Chen, Peixuan Zhang, Jingran Liu, Cuihong Chen, Huiqin Mao, Guofeng Shen, Zhen Qu, Zichong Chen, Minqiang Zhou, Pucai Wang, Robert J. Parker, Hartmut Boesch, Alba Lorente, Joannes D. Maasakkers, and Ilse Aben
Atmos. Chem. Phys., 23, 8039–8057, https://doi.org/10.5194/acp-23-8039-2023, https://doi.org/10.5194/acp-23-8039-2023, 2023
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We compare and evaluate East Asian methane emissions inferred from different satellite observations (GOSAT and TROPOMI). The results show discrepancies over northern India and eastern China. Independent ground-based observations are more consistent with TROPOMI-derived emissions in northern India and GOSAT-derived emissions in eastern China.
Daniel J. Varon, Daniel J. Jacob, Benjamin Hmiel, Ritesh Gautam, David R. Lyon, Mark Omara, Melissa Sulprizio, Lu Shen, Drew Pendergrass, Hannah Nesser, Zhen Qu, Zachary R. Barkley, Natasha L. Miles, Scott J. Richardson, Kenneth J. Davis, Sudhanshu Pandey, Xiao Lu, Alba Lorente, Tobias Borsdorff, Joannes D. Maasakkers, and Ilse Aben
Atmos. Chem. Phys., 23, 7503–7520, https://doi.org/10.5194/acp-23-7503-2023, https://doi.org/10.5194/acp-23-7503-2023, 2023
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We use TROPOMI satellite observations to quantify weekly methane emissions from the US Permian oil and gas basin from May 2018 to October 2020. We find that Permian emissions are highly variable, with diverse economic and activity drivers. The most important drivers during our study period were new well development and natural gas price. Permian methane intensity averaged 4.6 % and decreased by 1 % per year.
Tobias Borsdorff, Teresa Campos, Natalie Kille, Kyle J. Zarzana, Rainer Volkamer, and Jochen Landgraf
Atmos. Meas. Tech., 16, 3027–3038, https://doi.org/10.5194/amt-16-3027-2023, https://doi.org/10.5194/amt-16-3027-2023, 2023
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ECMWF plans to assimilate TROPOMI CO with their CAMS-IFS model. This will constrain the total column and the vertical CO distribution of the model. To show this, we combine individual TROPOMI CO column retrievals with different vertical sensitivities and obtain a vertical CO concentration profile. We test the approach on three CO pollution events in comparison with CAMS-IFS simulations that do not assimilate TROPOMI CO data and in situ airborne measurements of the BB-FLUX campaign.
Zichong Chen, Daniel J. Jacob, Ritesh Gautam, Mark Omara, Robert N. Stavins, Robert C. Stowe, Hannah Nesser, Melissa P. Sulprizio, Alba Lorente, Daniel J. Varon, Xiao Lu, Lu Shen, Zhen Qu, Drew C. Pendergrass, and Sarah Hancock
Atmos. Chem. Phys., 23, 5945–5967, https://doi.org/10.5194/acp-23-5945-2023, https://doi.org/10.5194/acp-23-5945-2023, 2023
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We quantify methane emissions from individual countries in the Middle East and North Africa by inverse analysis of 2019 TROPOMI satellite observations of atmospheric methane. We show that the ability to simply relate oil/gas emissions to activity metrics is compromised by stochastic nature of local infrastructure and management practices. We find that the industry target for oil/gas methane intensity is achievable through associated gas capture, modern infrastructure, and centralized operations.
Liang Feng, Paul I. Palmer, Robert J. Parker, Mark F. Lunt, and Hartmut Bösch
Atmos. Chem. Phys., 23, 4863–4880, https://doi.org/10.5194/acp-23-4863-2023, https://doi.org/10.5194/acp-23-4863-2023, 2023
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Our understanding of recent changes in atmospheric methane has defied explanation. Since 2007, the atmospheric growth of methane has accelerated to record-breaking values in 2020 and 2021. We use satellite observations of methane to show that (1) increasing emissions over the tropics are mostly responsible for these recent atmospheric changes, and (2) changes in the OH sink during the 2020 Covid-19 lockdown can explain up to 34% of changes in atmospheric methane for that year.
Anna Agustí-Panareda, Jérôme Barré, Sébastien Massart, Antje Inness, Ilse Aben, Melanie Ades, Bianca C. Baier, Gianpaolo Balsamo, Tobias Borsdorff, Nicolas Bousserez, Souhail Boussetta, Michael Buchwitz, Luca Cantarello, Cyril Crevoisier, Richard Engelen, Henk Eskes, Johannes Flemming, Sébastien Garrigues, Otto Hasekamp, Vincent Huijnen, Luke Jones, Zak Kipling, Bavo Langerock, Joe McNorton, Nicolas Meilhac, Stefan Noël, Mark Parrington, Vincent-Henri Peuch, Michel Ramonet, Miha Razinger, Maximilian Reuter, Roberto Ribas, Martin Suttie, Colm Sweeney, Jérôme Tarniewicz, and Lianghai Wu
Atmos. Chem. Phys., 23, 3829–3859, https://doi.org/10.5194/acp-23-3829-2023, https://doi.org/10.5194/acp-23-3829-2023, 2023
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We present a global dataset of atmospheric CO2 and CH4, the two most important human-made greenhouse gases, which covers almost 2 decades (2003–2020). It is produced by combining satellite data of CO2 and CH4 with a weather and air composition prediction model, and it has been carefully evaluated against independent observations to ensure validity and point out deficiencies to the user. This dataset can be used for scientific studies in the field of climate change and the global carbon cycle.
Alba Lorente, Tobias Borsdorff, Mari C. Martinez-Velarte, and Jochen Landgraf
Atmos. Meas. Tech., 16, 1597–1608, https://doi.org/10.5194/amt-16-1597-2023, https://doi.org/10.5194/amt-16-1597-2023, 2023
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In the TROPOMI methane data, there are few false methane anomalies that can be misinterpreted as enhancements caused by strong emission sources. These artefacts are caused by features of the underlying surfaces that are not well characterized in the retrieval algorithm. Here we improve the representation of the surface reflectance dependency with wavelength in the forward model, removing the artificial localized CH4 enhancements found in several locations like Siberia, Australia and Algeria.
Xueying Yu, Dylan B. Millet, Daven K. Henze, Alexander J. Turner, Alba Lorente Delgado, A. Anthony Bloom, and Jianxiong Sheng
Atmos. Chem. Phys., 23, 3325–3346, https://doi.org/10.5194/acp-23-3325-2023, https://doi.org/10.5194/acp-23-3325-2023, 2023
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We combine satellite measurements with a novel downscaling method to map global methane emissions at 0.1°×0.1° resolution. These fine-scale emission estimates reveal unreported emission hotspots and shed light on the roles of agriculture, wetlands, and fossil fuels for regional methane budgets. The satellite-derived emissions point in particular to missing fossil fuel emissions in the Middle East and to a large emission underestimate in South Asia that appears to be tied to monsoon rainfall.
Adriana Bailey, Franziska Aemisegger, Leonie Villiger, Sebastian A. Los, Gilles Reverdin, Estefanía Quiñones Meléndez, Claudia Acquistapace, Dariusz B. Baranowski, Tobias Böck, Sandrine Bony, Tobias Bordsdorff, Derek Coffman, Simon P. de Szoeke, Christopher J. Diekmann, Marina Dütsch, Benjamin Ertl, Joseph Galewsky, Dean Henze, Przemyslaw Makuch, David Noone, Patricia K. Quinn, Michael Rösch, Andreas Schneider, Matthias Schneider, Sabrina Speich, Bjorn Stevens, and Elizabeth J. Thompson
Earth Syst. Sci. Data, 15, 465–495, https://doi.org/10.5194/essd-15-465-2023, https://doi.org/10.5194/essd-15-465-2023, 2023
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One of the novel ways EUREC4A set out to investigate trade wind clouds and their coupling to the large-scale circulation was through an extensive network of isotopic measurements in water vapor, precipitation, and seawater. Samples were taken from the island of Barbados, from aboard two aircraft, and from aboard four ships. This paper describes the full collection of EUREC4A isotopic in situ data and guides readers to complementary remotely sensed water vapor isotope ratios.
Javier Gorroño, Daniel J. Varon, Itziar Irakulis-Loitxate, and Luis Guanter
Atmos. Meas. Tech., 16, 89–107, https://doi.org/10.5194/amt-16-89-2023, https://doi.org/10.5194/amt-16-89-2023, 2023
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We present a methane flux rate retrieval methodology using the Sentinel-2 mission, validating the algorithm for different scenes and plumes. The detection limit is 1000–2000 kg h−1 for homogeneous scenes and temporally invariant surfaces and above 5000 kg h−1 for heterogeneous ones. Dominant quantification errors are wind-related or plume mask-related. For heterogeneous scenes, the surface structure underlying the methane plume can become a dominant source of uncertainty.
Srijana Lama, Sander Houweling, K. Folkert Boersma, Ilse Aben, Hugo A. C. Denier van der Gon, and Maarten C. Krol
Atmos. Chem. Phys., 22, 16053–16071, https://doi.org/10.5194/acp-22-16053-2022, https://doi.org/10.5194/acp-22-16053-2022, 2022
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Hydroxyl radical (OH) is the important chemical species that determines the lifetime of some greenhouse gases and trace gases. OH plays a vital role in air pollution chemistry. OH has a short lifetime and is extremely difficult to measure directly. OH concentrations derived from the chemistry transport model (CTM) have uncertainties of >50 %. Therefore, in this study, OH is derived indirectly using satellite date in urban plumes.
Robert J. Parker, Chris Wilson, Edward Comyn-Platt, Garry Hayman, Toby R. Marthews, A. Anthony Bloom, Mark F. Lunt, Nicola Gedney, Simon J. Dadson, Joe McNorton, Neil Humpage, Hartmut Boesch, Martyn P. Chipperfield, Paul I. Palmer, and Dai Yamazaki
Biogeosciences, 19, 5779–5805, https://doi.org/10.5194/bg-19-5779-2022, https://doi.org/10.5194/bg-19-5779-2022, 2022
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Wetlands are the largest natural source of methane, one of the most important climate gases. The JULES land surface model simulates these emissions. We use satellite data to evaluate how well JULES reproduces the methane seasonal cycle over different tropical wetlands. It performs well for most regions; however, it struggles for some African wetlands influenced heavily by river flooding. We explain the reasons for these deficiencies and highlight how future development will improve these areas.
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.
Randall V. Martin, Sebastian D. Eastham, Liam Bindle, Elizabeth W. Lundgren, Thomas L. Clune, Christoph A. Keller, William Downs, Dandan Zhang, Robert A. Lucchesi, Melissa P. Sulprizio, Robert M. Yantosca, Yanshun Li, Lucas Estrada, William M. Putman, Benjamin M. Auer, Atanas L. Trayanov, Steven Pawson, and Daniel J. Jacob
Geosci. Model Dev., 15, 8731–8748, https://doi.org/10.5194/gmd-15-8731-2022, https://doi.org/10.5194/gmd-15-8731-2022, 2022
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Atmospheric chemistry models must be able to operate both online as components of Earth system models and offline as standalone models. The widely used GEOS-Chem model operates both online and offline, but the classic offline version is not suitable for massively parallel simulations. We describe a new generation of the offline high-performance GEOS-Chem (GCHP) that enables high-resolution simulations on thousands of cores, including on the cloud, with improved access, performance, and accuracy.
Stijn Naus, Lucas G. Domingues, Maarten Krol, Ingrid T. Luijkx, Luciana V. Gatti, John B. Miller, Emanuel Gloor, Sourish Basu, Caio Correia, Gerbrand Koren, Helen M. Worden, Johannes Flemming, Gabrielle Pétron, and Wouter Peters
Atmos. Chem. Phys., 22, 14735–14750, https://doi.org/10.5194/acp-22-14735-2022, https://doi.org/10.5194/acp-22-14735-2022, 2022
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We assimilate MOPITT CO satellite data in the TM5-4D-Var inverse modelling framework to estimate Amazon fire CO emissions for 2003–2018. We show that fire emissions have decreased over the analysis period, coincident with a decrease in deforestation rates. However, interannual variations in fire emissions are large, and they correlate strongly with soil moisture. Our results reveal an important role for robust, top-down fire CO emissions in quantifying and attributing Amazon fire intensity.
Alba Lorente, Tobias Borsdorff, Mari C. Martinez-Velarte, Andre Butz, Otto P. Hasekamp, Lianghai Wu, and Jochen Landgraf
Atmos. Meas. Tech., 15, 6585–6603, https://doi.org/10.5194/amt-15-6585-2022, https://doi.org/10.5194/amt-15-6585-2022, 2022
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The TROPOspheric Monitoring Instrument (TROPOMI) performs observations over ocean in every orbit, enhancing the monitoring capabilities of methane from space. In the sun glint geometry the mirror-like reflection at the water surface provides a signal that is high enough to retrieve methane with high accuracy and precision. We present 4 years of methane concentrations over the ocean, and we assess its quality. We also show the importance of ocean observations to quantify total CH4 emissions.
Antje Inness, Ilse Aben, Melanie Ades, Tobias Borsdorff, Johannes Flemming, Luke Jones, Jochen Landgraf, Bavo Langerock, Philippe Nedelec, Mark Parrington, and Roberto Ribas
Atmos. Chem. Phys., 22, 14355–14376, https://doi.org/10.5194/acp-22-14355-2022, https://doi.org/10.5194/acp-22-14355-2022, 2022
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The Copernicus Atmosphere Monitoring Service (CAMS) provides daily global air quality forecasts to users worldwide. One of the species of interest is carbon monoxide (CO), an important trace gas in the atmosphere with anthropogenic and natural sources, produced by incomplete combustion, for example, by wildfires. This paper looks at how well CAMS can model CO in the atmosphere and shows that the fields can be improved when blending CO data from the TROPOMI instrument with the CAMS model.
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.
Zichong Chen, Daniel J. Jacob, Hannah Nesser, Melissa P. Sulprizio, Alba Lorente, Daniel J. Varon, Xiao Lu, Lu Shen, Zhen Qu, Elise Penn, and Xueying Yu
Atmos. Chem. Phys., 22, 10809–10826, https://doi.org/10.5194/acp-22-10809-2022, https://doi.org/10.5194/acp-22-10809-2022, 2022
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We quantify methane emissions in China and contributions from different sectors by inverse analysis of 2019 TROPOMI satellite observations of atmospheric methane. We find that anthropogenic methane emissions for China are underestimated in the national inventory. Our estimate of emissions indicates a small life-cycle loss rate, implying net climate benefits from the current
coal-to-gasenergy transition in China. However, this small loss rate can be misleading given China's high gas imports.
Sara Martínez-Alonso, Merritt N. Deeter, Bianca C. Baier, Kathryn McKain, Helen Worden, Tobias Borsdorff, Colm Sweeney, and Ilse Aben
Atmos. Meas. Tech., 15, 4751–4765, https://doi.org/10.5194/amt-15-4751-2022, https://doi.org/10.5194/amt-15-4751-2022, 2022
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AirCore is a novel balloon sampling system that can measure, among others, vertical profiles of carbon monoxide (CO) from 25–30 km of altitude to near the surface. Our analyses of AirCore and satellite CO data show that AirCore profiles are suited for satellite data validation, the use of shorter aircraft vertical profiles in satellite validation results in small errors (1–3 percent points) mostly at 300 hPa and above, and the error introduced by clouds in TROPOMI land data is small (1–2 %).
Pieternel F. Levelt, Deborah C. Stein Zweers, Ilse Aben, Maite Bauwens, Tobias Borsdorff, Isabelle De Smedt, Henk J. Eskes, Christophe Lerot, Diego G. Loyola, Fabian Romahn, Trissevgeni Stavrakou, Nicolas Theys, Michel Van Roozendael, J. Pepijn Veefkind, and Tijl Verhoelst
Atmos. Chem. Phys., 22, 10319–10351, https://doi.org/10.5194/acp-22-10319-2022, https://doi.org/10.5194/acp-22-10319-2022, 2022
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Using the COVID-19 lockdown periods as an example, we show how Sentinel-5P/TROPOMI trace gas data (NO2, SO2, CO, HCHO and CHOCHO) can be used to understand impacts on air quality for regions and cities around the globe. We also provide information for both experienced and inexperienced users about how we created the data using state-of-the-art algorithms, where to get the data, methods taking meteorological and seasonal variability into consideration, and insights for future studies.
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.
Matthias Schneider, Benjamin Ertl, Qiansi Tu, Christopher J. Diekmann, Farahnaz Khosrawi, Amelie N. Röhling, Frank Hase, Darko Dubravica, Omaira E. García, Eliezer Sepúlveda, Tobias Borsdorff, Jochen Landgraf, Alba Lorente, André Butz, Huilin Chen, Rigel Kivi, Thomas Laemmel, Michel Ramonet, Cyril Crevoisier, Jérome Pernin, Martin Steinbacher, Frank Meinhardt, Kimberly Strong, Debra Wunch, Thorsten Warneke, Coleen Roehl, Paul O. Wennberg, Isamu Morino, Laura T. Iraci, Kei Shiomi, Nicholas M. Deutscher, David W. T. Griffith, Voltaire A. Velazco, and David F. Pollard
Atmos. Meas. Tech., 15, 4339–4371, https://doi.org/10.5194/amt-15-4339-2022, https://doi.org/10.5194/amt-15-4339-2022, 2022
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We present a computationally very efficient method for the synergetic use of level 2 remote-sensing data products. We apply the method to IASI vertical profile and TROPOMI total column space-borne methane observations and thus gain sensitivity for the tropospheric methane partial columns, which is not achievable by the individual use of TROPOMI and IASI. These synergetic effects are evaluated theoretically and empirically by inter-comparisons to independent references of TCCON, AirCore, and GAW.
Daniel J. Varon, Daniel J. Jacob, Melissa Sulprizio, Lucas A. Estrada, William B. Downs, Lu Shen, Sarah E. Hancock, Hannah Nesser, Zhen Qu, Elise Penn, Zichong Chen, Xiao Lu, Alba Lorente, Ashutosh Tewari, and Cynthia A. Randles
Geosci. Model Dev., 15, 5787–5805, https://doi.org/10.5194/gmd-15-5787-2022, https://doi.org/10.5194/gmd-15-5787-2022, 2022
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Reducing atmospheric methane emissions is critical to slow near-term climate change. Globally surveying satellite instruments like the TROPOspheric Monitoring Instrument (TROPOMI) have unique capabilities for monitoring atmospheric methane around the world. Here we present a user-friendly cloud-computing tool that enables researchers and stakeholders to quantify methane emissions across user-selected regions of interest using TROPOMI satellite observations.
Jonas Hachmeister, Oliver Schneising, Michael Buchwitz, Alba Lorente, Tobias Borsdorff, John P. Burrows, Justus Notholt, and Matthias Buschmann
Atmos. Meas. Tech., 15, 4063–4074, https://doi.org/10.5194/amt-15-4063-2022, https://doi.org/10.5194/amt-15-4063-2022, 2022
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Sentinel-5P trace gas retrievals rely on elevation data in their calculations. Outdated or inaccurate data can lead to significant errors in e.g. dry-air mole fractions of methane (XCH4). We show that the use of inadequate elevation data leads to strong XCH4 anomalies in Greenland. Similar problems can be expected for other regions with inaccurate elevation data. However, we expect these to be more localized. We show that updating elevation data used in the retrieval solves this issue.
Stefan Noël, Maximilian Reuter, Michael Buchwitz, Jakob Borchardt, Michael Hilker, Oliver Schneising, Heinrich Bovensmann, John P. Burrows, Antonio Di Noia, Robert J. Parker, Hiroshi Suto, Yukio Yoshida, Matthias Buschmann, Nicholas M. Deutscher, Dietrich G. Feist, David W. T. Griffith, Frank Hase, Rigel Kivi, Cheng Liu, Isamu Morino, Justus Notholt, Young-Suk Oh, Hirofumi Ohyama, Christof Petri, David F. Pollard, Markus Rettinger, Coleen Roehl, Constantina Rousogenous, Mahesh Kumar Sha, Kei Shiomi, Kimberly Strong, Ralf Sussmann, Yao Té, Voltaire A. Velazco, Mihalis Vrekoussis, and Thorsten Warneke
Atmos. Meas. Tech., 15, 3401–3437, https://doi.org/10.5194/amt-15-3401-2022, https://doi.org/10.5194/amt-15-3401-2022, 2022
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We present a new version (v3) of the GOSAT and GOSAT-2 FOCAL products.
In addition to an increased number of XCO2 data, v3 also includes products for XCH4 (full-physics and proxy), XH2O and the relative ratio of HDO to H2O (δD). For GOSAT-2, we also present first XCO and XN2O results. All FOCAL data products show reasonable spatial distribution and temporal variations and agree well with TCCON. Global XN2O maps show a gradient from the tropics to higher latitudes on the order of 15 ppb.
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.
Andreas Schneider, Tobias Borsdorff, Joost aan de Brugh, Alba Lorente, Franziska Aemisegger, David Noone, Dean Henze, Rigel Kivi, and Jochen Landgraf
Atmos. Meas. Tech., 15, 2251–2275, https://doi.org/10.5194/amt-15-2251-2022, https://doi.org/10.5194/amt-15-2251-2022, 2022
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This paper presents an extended H₂O/HDO total column dataset from short-wave infrared measurements by TROPOMI including cloudy and clear-sky scenes. Coverage is tremendously increased compared to previous TROPOMI HDO datasets. The new dataset is validated against recent ground-based FTIR measurements from TCCON and against aircraft measurements over the ocean. The use of the new dataset is demonstrated with a case study of a cold air outbreak in January 2020.
Elena Sánchez-García, Javier Gorroño, Itziar Irakulis-Loitxate, Daniel J. Varon, and Luis Guanter
Atmos. Meas. Tech., 15, 1657–1674, https://doi.org/10.5194/amt-15-1657-2022, https://doi.org/10.5194/amt-15-1657-2022, 2022
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This study seeks to present the as-yet-unknown potential use of WorldView-3 for the mapping of methane point source emissions. The proposed retrieval methodology is based on the idea that the spectral channels not affected by methane can be used to predict the methane-affected band through regression analysis. The results show the precise location of 26 independent point emissions over different methane hotspot regions worldwide, which prove the game-changing potential that this mission entails.
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.
Haiyue Tan, Lin Zhang, Xiao Lu, Yuanhong Zhao, Bo Yao, Robert J. Parker, and Hartmut Boesch
Atmos. Chem. Phys., 22, 1229–1249, https://doi.org/10.5194/acp-22-1229-2022, https://doi.org/10.5194/acp-22-1229-2022, 2022
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Methane is the second most important anthropogenic greenhouse gas. Understanding methane emissions and concentration growth over China in the past decade is important to support its mitigation. This study analyzes the contributions of methane emissions from different regions and sources over the globe to methane changes over China in 2007–2018. Our results show strong international transport influences and emphasize the need of intensive methane measurements covering eastern China.
Tobias Küchler, Stefan Noël, Heinrich Bovensmann, John Philip Burrows, Thomas Wagner, Christian Borger, Tobias Borsdorff, and Andreas Schneider
Atmos. Meas. Tech., 15, 297–320, https://doi.org/10.5194/amt-15-297-2022, https://doi.org/10.5194/amt-15-297-2022, 2022
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We applied the air-mass-corrected differential optical absorption spectroscopy (AMC-DOAS) method to derive total column water vapour (TCWV) from Sentinel-5P measurements and compared it to independent data sets. The correlation coefficients of typically more than 0.9 and the small deviations up to 2.5 kg m−2 reveal good agreement between our data product and other TCWV data sets. In particular for the different Sentinel-5P water vapour products, the deviations are around 1 kg m−2.
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.
Qiansi Tu, Frank Hase, Matthias Schneider, Omaira García, Thomas Blumenstock, Tobias Borsdorff, Matthias Frey, Farahnaz Khosrawi, Alba Lorente, Carlos Alberti, Juan J. Bustos, André Butz, Virgilio Carreño, Emilio Cuevas, Roger Curcoll, Christopher J. Diekmann, Darko Dubravica, Benjamin Ertl, Carme Estruch, Sergio Fabián León-Luis, Carlos Marrero, Josep-Anton Morgui, Ramón Ramos, Christian Scharun, Carsten Schneider, Eliezer Sepúlveda, Carlos Toledano, and Carlos Torres
Atmos. Chem. Phys., 22, 295–317, https://doi.org/10.5194/acp-22-295-2022, https://doi.org/10.5194/acp-22-295-2022, 2022
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We use different methane ground- and space-based remote sensing data sets for investigating the emission strength of three waste disposal sites close to Madrid. We present a method that uses wind-assigned anomalies for deriving emission strengths from satellite data and estimate their uncertainty to 9–14 %. The emission strengths estimated from the remote sensing data sets are significantly larger than the values published in the official register.
Sabour Baray, Daniel J. Jacob, Joannes D. Maasakkers, Jian-Xiong Sheng, Melissa P. Sulprizio, Dylan B. A. Jones, A. Anthony Bloom, and Robert McLaren
Atmos. Chem. Phys., 21, 18101–18121, https://doi.org/10.5194/acp-21-18101-2021, https://doi.org/10.5194/acp-21-18101-2021, 2021
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We use 2010–2015 surface and satellite observations to disentangle methane from anthropogenic and natural sources in Canada. Using a chemical transport model (GEOS-Chem), the mismatch between modelled and observed methane concentrations can be used to infer emissions according to Bayesian statistics. Compared to prior knowledge, we show higher anthropogenic emissions attributed to energy and/or agriculture in Western Canada and lower natural emissions from Boreal wetlands.
Tyler Wizenberg, Kimberly Strong, Kaley Walker, Erik Lutsch, Tobias Borsdorff, and Jochen Landgraf
Atmos. Meas. Tech., 14, 7707–7728, https://doi.org/10.5194/amt-14-7707-2021, https://doi.org/10.5194/amt-14-7707-2021, 2021
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CO is an important atmospheric gas that influences both air quality and the climate. Here, we compare CO measurements from TROPOMI with those from ACE-FTS and an Arctic ground-based FTS at Eureka, Nunavut, to further characterize the accuracy of TROPOMI measurements. CO columns from the instruments agree well but show larger differences at high latitudes. Despite this, the results fall within the TROPOMI accuracy target, indicating good data quality at high latitudes.
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
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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.
Cited articles
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Short summary
Venezuela's Lake Maracaibo region is notoriously hard to observe from space and features intensive oil exploitation, although production has strongly decreased in recent years. We estimate methane emissions using 2018–2020 TROPOMI satellite observations with national and regional transport models. Despite the production decrease, we find relatively constant emissions from Lake Maracaibo between 2018 and 2020, indicating that there could be large emissions from abandoned infrastructure.
Venezuela's Lake Maracaibo region is notoriously hard to observe from space and features...
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