Articles | Volume 15, issue 12
https://doi.org/10.5194/acp-15-7049-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/acp-15-7049-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
30 Jun 2015
Research article |
| 30 Jun 2015
Estimating global and North American methane emissions with high spatial resolution using GOSAT satellite data
School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, USA
D. J. Jacob
School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, USA
Department of Earth and Planetary Sciences, Harvard University, Cambridge, Massachusetts, USA
K. J. Wecht
Department of Earth and Planetary Sciences, Harvard University, Cambridge, Massachusetts, USA
J. D. Maasakkers
School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, USA
E. Lundgren
School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, USA
A. E. Andrews
NOAA Earth System Research Laboratory, Boulder, Colorado, USA
S. C. Biraud
Lawrence Berkeley National Laboratory, Berkeley, California, USA
H. Boesch
Earth Observation Science Group, Department of Physics and Astronomy, University of Leicester, Leicester, UK
National Centre for Earth Observation, University of Leicester, Leicester, UK
K. W. Bowman
Jet Propulsion Laboratory/California Institute of Technology, Pasadena, California, USA
N. M. Deutscher
Centre for Atmospheric Chemistry, University of Wollongong, NSW, Australia
Institute of Environmental Physics, University of Bremen, Bremen, Germany
M. K. Dubey
Los Alamos National Laboratory, Los Alamos, New Mexico, USA
D. W. T. Griffith
Centre for Atmospheric Chemistry, University of Wollongong, NSW, Australia
F. Hase
Karlsruhe Institute of Technology, IMK-ASF, Karlsruhe, Germany
Japan Aerospace Exploration Agency, Tsukuba, Ibaraki, Japan
J. Notholt
Institute of Environmental Physics, University of Bremen, Bremen, Germany
H. Ohyama
Japan Aerospace Exploration Agency, Tsukuba, Ibaraki, Japan
Solar-Terrestrial Environment Laboratory, Nagoya University, Nagoya, Aichi, Japan
R. Parker
Earth Observation Science Group, Department of Physics and Astronomy, University of Leicester, Leicester, UK
National Centre for Earth Observation, University of Leicester, Leicester, UK
V. H. Payne
Jet Propulsion Laboratory/California Institute of Technology, Pasadena, California, USA
R. Sussmann
Karlsruhe Institute of Technology, IMK-IFU, Garmisch-Partenkirchen, Germany
C. Sweeney
NOAA Earth System Research Laboratory, Boulder, Colorado, USA
Cooperative Institute for Research in Environmental Sciences, University of Colorado at Boulder, Boulder, Colorado, USA
V. A. Velazco
Centre for Atmospheric Chemistry, University of Wollongong, NSW, Australia
T. Warneke
Institute of Environmental Physics, University of Bremen, Bremen, Germany
P. O. Wennberg
California Institute of Technology, Pasadena, California, USA
California Institute of Technology, Pasadena, California, USA
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We used a ground-based Fourier Transform Spectrometer to measure columnar greenhouse gas mixing ratios and validate methane observations from the GOSAT satellite and carbon dioxide observations from GOSAT and OCO-2 over India. Both satellites provide high precision and accuracy, making them suitable for emission flux estimates. Simulations using a Lagrangian dispersion model showed that background mixing ratio variations play a larger role than local source changes.
Sven Krautwurst, Christian Fruck, Sebastian Wolff, Jakob Borchardt, Oke Huhs, Konstantin Gerilowski, Michał Gałkowski, Christoph Kiemle, Mathieu Quatrevalet, Martin Wirth, Christian Mallaun, John P. Burrows, Christoph Gerbig, Andreas Fix, Hartmut Bösch, and Heinrich Bovensmann
EGUsphere, https://doi.org/10.5194/egusphere-2024-3182, https://doi.org/10.5194/egusphere-2024-3182, 2024
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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Anomalously high CH4 emissions from landfills in Madrid, Spain, have been observed by satellite measurements in recent years. Our investigations of these waste facilities using passive and active airborne remote sensing measurements confirm these high emission rates with values of up to 13 th-1 during the overflight and show excellent agreement between the two techniques. A large fraction of the emissions is attributed to active landfill sites.
Noémie Taquet, Wolfgang Stremme, María Eugenia González del Castillo, Victor Almanza, Alejandro Bezanilla, Olivier Laurent, Carlos Alberti, Frank Hase, Michel Ramonet, Thomas Lauvaux, Ke Che, and Michel Grutter
Atmos. Chem. Phys., 24, 11823–11848, https://doi.org/10.5194/acp-24-11823-2024, https://doi.org/10.5194/acp-24-11823-2024, 2024
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We characterize the variability in CO and CO2 emissions over Mexico City from long-term time-resolved Fourier transform infrared spectroscopy solar absorption and surface measurements from 2013 to 2021. Using the average intraday CO growth rate from total columns, the average CO / CO2 ratio and TROPOMI data, we estimate the interannual variability in the CO and CO2 anthropogenic emissions of Mexico City, highlighting the effect of an unprecedented drop in activity due to the COVID-19 lockdown.
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
EGUsphere, https://doi.org/10.5194/egusphere-2024-2700, https://doi.org/10.5194/egusphere-2024-2700, 2024
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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Reducing methane emissions, 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 regional to global scales and allow continuous emissions monitoring.
Mohit L. Dubey, Andre Santos, Andrew B. Moyes, Ken Reichl, James E. Lee, Manvendra K. Dubey, Corentin LeYhuelic, Evan Variano, Emily Follansbee, Fotini K. Chow, and Sébastien C. Biraud
EGUsphere, https://doi.org/10.5194/egusphere-2024-3040, https://doi.org/10.5194/egusphere-2024-3040, 2024
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Orphaned wells, meaning wells lacking responsible owners, pose a significant and poorly understood environmental challenge. We propose, develop, and test a novel method for estimating emissions from orphaned wells using a Forced Advection Sampling Technique (FAST) that can overcome many of the limitations in current methods (cost, accuracy, safety). Our results suggest that the FAST method can provide a low-cost alternative to existing methods over a range of leak rates.
Kavitha Mottungan, Chayan Roychoudhury, Vanessa Brocchi, Benjamin Gaubert, Wenfu Tang, Mohammad Amin Mirrezaei, John McKinnon, Yafang Guo, David W. T. Griffith, Dietrich G. Feist, Isamu Morino, Mahesh K. Sha, Manvendra K. Dubey, Martine De Mazière, Nicholas M. Deutscher, Paul O. Wennberg, Ralf Sussmann, Rigel Kivi, Tae-Young Goo, Voltaire A. Velazco, Wei Wang, and Avelino F. Arellano Jr.
Atmos. Meas. Tech., 17, 5861–5885, https://doi.org/10.5194/amt-17-5861-2024, https://doi.org/10.5194/amt-17-5861-2024, 2024
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A combination of data analysis techniques is introduced to separate local and regional influences on observed levels of carbon dioxide, carbon monoxide, and methane from an established ground-based remote sensing network. We take advantage of the covariations in these trace gases to identify the dominant type of sources driving these levels. Applying these methods in conjunction with existing approaches to other datasets can better address uncertainties in identifying sources and sinks.
Edward Malina, Jure Brence, Jennifer Adams, Jovan Tanevski, Sašo Džeroski, Valentin Kantchev, and Kevin W. Bowman
EGUsphere, https://doi.org/10.5194/egusphere-2024-2392, https://doi.org/10.5194/egusphere-2024-2392, 2024
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The large fleet of Earth Observation satellites in orbit currently generate huge volumes of data, requiring significant computational resources to process in a timely manner. We present a method for predicting poor quality measurements using machine learning. We find that machine learning methods can accurately predict poor quality measurements, and remove them from the processing change, saving time and computational resources.
Frank Hase, Paolo Castracane, Angelika Dehn, Omaira Elena García, David W. T. Griffith, Lukas Heizmann, Nicholas B. Jones, Tomi Karppinen, Rigel Kivi, Martine de Mazière, Justus Notholt, and Mahesh Kumar Sha
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-140, https://doi.org/10.5194/amt-2024-140, 2024
Revised manuscript accepted for AMT
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The primary measurement result delivered by a Fourier Transform spectrometer is an interferogram, and the spectrum required for further analysis needs to be calculated from the interferogram by a Fourier analysis. The paper deals with technical aspects of this process and shows how the reconstruction of the spectrum can be optimized.
Neil Humpage, Hartmut Boesch, William Okello, Jia Chen, Florian Dietrich, Mark F. Lunt, Liang Feng, Paul I. Palmer, and Frank Hase
Atmos. Meas. Tech., 17, 5679–5707, https://doi.org/10.5194/amt-17-5679-2024, https://doi.org/10.5194/amt-17-5679-2024, 2024
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We used a Bruker EM27/SUN spectrometer within an automated weatherproof enclosure to measure greenhouse gas column concentrations over a 3-month period in Jinja, Uganda. The portability of the EM27/SUN allows us to evaluate satellite and model data in locations not covered by traditional validation networks. This is of particular value in tropical Africa, where extensive terrestrial ecosystems are a significant store of carbon and play a key role in the atmospheric budgets of CO2 and CH4.
Nikhil Dadheech, Tai-Long He, and Alexander J. Turner
EGUsphere, https://doi.org/10.5194/egusphere-2024-2918, https://doi.org/10.5194/egusphere-2024-2918, 2024
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We developed an efficient GHG flux inversion framework using a machine learning emulator (FootNet) as a surrogate for an atmospheric transport model, resulting in a 650× speedup. Paradoxically, the flux inversion using the ML-model outperforms the full-physics model in our case study. We attribute this to the ML model mitigating transport errors in the GHG flux inversion.
Edward Malina, Kevin W. Bowman, Valentin Kantchev, Le Kuai, Thomas P. Kurosu, Kazuyuki Miyazaki, Vijay Natraj, Gregory B. Osterman, Fabiano Oyafuso, and Matthew D. Thill
Atmos. Meas. Tech., 17, 5341–5371, https://doi.org/10.5194/amt-17-5341-2024, https://doi.org/10.5194/amt-17-5341-2024, 2024
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Characterizing the distribution of ozone in the atmosphere is a challenging problem, with current Earth observation satellites using either thermal infrared (TIR) or ultraviolet (UV) instruments, sensitive to different portions of the atmosphere, making it difficult to gain a full picture. In this work, we combine measurements from the TIR and UV instruments Suomi NPP CrIS and Sentinel-5P/TROPOMI to improve sensitivity through the whole atmosphere and improve knowledge of ozone distribution.
Pinchas Nürnberg, Sarah A. Strode, and Ralf Sussmann
Atmos. Chem. Phys., 24, 10001–10012, https://doi.org/10.5194/acp-24-10001-2024, https://doi.org/10.5194/acp-24-10001-2024, 2024
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We created a set of scaling factors describing the diurnal increase in stratospheric nitrogen oxides above Zugspitze, Germany. We used these factors to validate recently published model simulation data. On the one hand, this validation enables the use of the validated data to better understand the stratospheric photochemistry. On the other hand, it can improve satellite validation, which has implications for the understanding of urban smog events and other pollution events in the troposphere.
Matthias Schneider, Kinya Toride, Farahnaz Khosrawi, Frank Hase, Benjamin Ertl, Christopher J. Diekmann, and Kei Yoshimura
Atmos. Meas. Tech., 17, 5243–5259, https://doi.org/10.5194/amt-17-5243-2024, https://doi.org/10.5194/amt-17-5243-2024, 2024
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Despite its importance for extreme weather and climate feedbacks, atmospheric convection is not well constrained. This study assesses the potential of novel tropospheric water vapour isotopologue satellite observations for improving the analyses of convective events. We find that the impact of the isotopologues is small for stable atmospheric conditions but significant for unstable conditions, which have the strongest societal impacts (e.g. storms and flooding).
Yujin J. Oak, Daniel J. Jacob, Nicholas Balasus, Laura H. Yang, Heesung Chong, Junsung Park, Hanlim Lee, Gitaek T. Lee, Eunjo S. Ha, Rokjin J. Park, Hyeong-Ahn Kwon, and Jhoon Kim
Atmos. Meas. Tech., 17, 5147–5159, https://doi.org/10.5194/amt-17-5147-2024, https://doi.org/10.5194/amt-17-5147-2024, 2024
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We present an improved NO2 product from GEMS by calibrating it to TROPOMI using machine learning and by reprocessing both satellite products to adopt common NO2 profiles. Our corrected GEMS product combines the high data density of GEMS with the accuracy of TROPOMI, supporting the combined use for analyses of East Asia air quality including emissions and chemistry. This method can be extended to other species and geostationary satellites including TEMPO and Sentinel-4.
Jonathan F. Dooley, Kenneth Minschwaner, Manvendra K. Dubey, Sahar H. El Abbadi, Evan D. Sherwin, Aaron G. Meyer, Emily Follansbee, and James E. Lee
Atmos. Meas. Tech., 17, 5091–5111, https://doi.org/10.5194/amt-17-5091-2024, https://doi.org/10.5194/amt-17-5091-2024, 2024
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Methane is a powerful greenhouse gas originating from both natural and human activities. We describe a new uncrewed aerial system (UAS) designed to measure methane emission rates over a wide range of scales. This system has been used for direct quantification of point sources and distributed emitters over scales of up to 1 km. The system uses simultaneous measurements of methane and ethane to distinguish between different kinds of natural and human-related emission sources.
Henk Eskes, Athanasios Tsikerdekis, Melanie Ades, Mihai Alexe, Anna Carlin Benedictow, Yasmine Bennouna, Lewis Blake, Idir Bouarar, Simon Chabrillat, Richard Engelen, Quentin Errera, Johannes Flemming, Sebastien Garrigues, Jan Griesfeller, Vincent Huijnen, Luka Ilić, Antje Inness, John Kapsomenakis, Zak Kipling, Bavo Langerock, Augustin Mortier, Mark Parrington, Isabelle Pison, Mikko Pitkänen, Samuel Remy, Andreas Richter, Anja Schoenhardt, Michael Schulz, Valerie Thouret, Thorsten Warneke, Christos Zerefos, and Vincent-Henri Peuch
Atmos. Chem. Phys., 24, 9475–9514, https://doi.org/10.5194/acp-24-9475-2024, https://doi.org/10.5194/acp-24-9475-2024, 2024
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The Copernicus Atmosphere Monitoring Service (CAMS) provides global analyses and forecasts of aerosols and trace gases in the atmosphere. On 27 June 2023 a major upgrade, Cy48R1, became operational. Comparisons with in situ, surface remote sensing, aircraft, and balloon and satellite observations show that the new CAMS system is a significant improvement. The results quantify the skill of CAMS to forecast impactful events, such as wildfires, dust storms and air pollution peaks.
Christopher Johannes Diekmann, Matthias Schneider, Peter Knippertz, Tim Trent, Hartmut Boesch, Amelie Ninja Roehling, John Worden, Benjamin Ertl, Farahnaz Khosrawi, and Frank Hase
EGUsphere, https://doi.org/10.5194/egusphere-2024-1613, https://doi.org/10.5194/egusphere-2024-1613, 2024
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The West African Monsoon is the main source of rainfall over West Africa, and understanding the development of the monsoon remains challenging due to complex interactions of atmospheric processes. We make use of new satellite datasets of isotopes in tropospheric water vapour to bring new insights into processes controlling the monsoon convection. We find that comparing different water vapour isotopes reveals effects of rain-vapour interactions and air mass transport.
Matthew S. Johnson, Sofia D. Hamilton, Seongeun Jeong, Yuyan Cui, Dien Wu, Alex Turner, and Marc Fischer
EGUsphere, https://doi.org/10.5194/egusphere-2024-2152, https://doi.org/10.5194/egusphere-2024-2152, 2024
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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Satellites, such as NASA’s Orbiting Carbon Observatory-2 and -3 (OCO-2/3), retrieve carbon dioxide (CO2) concentrations which provide vital information for estimating surface CO2 emissions. Here we investigate the ability of OCO-2/3 retrievals to constrain CO2 emissions for the state of California for the major emission sectors (i.e., fossil fuels, net ecosystem exchange, wildfire).
Haipeng Lin, Louisa K. Emmons, Elizabeth W. Lundgren, Laura Hyesung Yang, Xu Feng, Ruijun Dang, Shixian Zhai, Yunxiao Tang, Makoto M. Kelp, Nadia K. Colombi, Sebastian D. Eastham, Thibaud M. Fritz, and Daniel J. Jacob
Atmos. Chem. Phys., 24, 8607–8624, https://doi.org/10.5194/acp-24-8607-2024, https://doi.org/10.5194/acp-24-8607-2024, 2024
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Tropospheric ozone is a major air pollutant, a greenhouse gas, and a major indicator of model skill. Global atmospheric chemistry models show large differences in simulations of tropospheric ozone, but isolating sources of differences is complicated by different model environments. By implementing the GEOS-Chem model side by side to CAM-chem within a common Earth system model, we identify and evaluate specific differences between the two models and their impacts on key chemical species.
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
EGUsphere, https://doi.org/10.5194/egusphere-2024-2260, https://doi.org/10.5194/egusphere-2024-2260, 2024
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The hydroxyl radical (OH), destroys many air pollutants, including methane. Global mean OH cannot be directly measured, so 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 instead. We find shortwave infrared observations can characterize yearly OH and its seasonality, but not the latitudinal distribution. Thermal infrared observations add little information.
Hella van Asperen, Thorsten Warneke, Alessandro Carioca de Araújo, Bruce Forsberg, Sávio José Filgueiras Ferreira, Thomas Röckmann, Carina van der Veen, Sipko Bulthuis, Leonardo Ramos de Oliveira, Thiago de Lima Xavier, Jailson da Mata, Marta de Oliveira Sá, Paulo Ricardo Teixeira, Julie Andrews de França e Silva, Susan Trumbore, and Justus Notholt
Biogeosciences, 21, 3183–3199, https://doi.org/10.5194/bg-21-3183-2024, https://doi.org/10.5194/bg-21-3183-2024, 2024
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Carbon monoxide (CO) is regarded as an important indirect greenhouse gas. Soils can emit and take up CO, but, until now, uncertainty remains as to which process dominates in tropical rainforests. We present the first soil CO flux measurements from a tropical rainforest. Based on our observations, we report that tropical rainforest soils are a net source of CO. In addition, we show that valley streams and inundated areas are likely additional hot spots of CO in the ecosystem.
Oliver Schneising, Michael Buchwitz, Maximilian Reuter, Michael Weimer, Heinrich Bovensmann, John P. Burrows, and Hartmut Bösch
Atmos. Chem. Phys., 24, 7609–7621, https://doi.org/10.5194/acp-24-7609-2024, https://doi.org/10.5194/acp-24-7609-2024, 2024
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Large quantities of CO and CO2 are emitted during conventional steel production. As satellite-based estimates of CO2 emissions at the facility level are challenging, co-emitted CO can indicate the carbon footprint of steel plants. We estimate CO emissions for German steelworks and use CO2 emissions from emissions trading data to derive a sector-specific CO/CO2 emission ratio for the steel industry; it is a prerequisite to use CO as a proxy for CO2 emissions from similar steel production sites.
Zihan Zhu, Javier González-Rocha, Yifan Ding, Isis Frausto-Vicencio, Sajjan Heerah, Akula Venkatram, Manvendra Dubey, Don Collins, and Francesca M. Hopkins
Atmos. Meas. Tech., 17, 3883–3895, https://doi.org/10.5194/amt-17-3883-2024, https://doi.org/10.5194/amt-17-3883-2024, 2024
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Increases in agriculture, oil and gas, and waste management activities have contributed to the increase in atmospheric methane levels and resultant climate warming. In this paper, we explore the use of small uncrewed aircraft systems (sUASs) and AirCore technology to detect and quantify methane emissions. Results from field experiments demonstrate that sUASs and AirCore technology can be effective for detecting and quantifying methane emissions in near real time.
Tai-Long He, Nikhil Dadheech, Tammy M. Thompson, and Alexander J. Turner
EGUsphere, https://doi.org/10.31223/X5197G, https://doi.org/10.31223/X5197G, 2024
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It is computationally expensive to infer greenhouse gas (GHG) emissions using atmospheric observations. This is partly due to the detailed model used to represent atmospheric transport. We demonstrate how a machine learning (ML) model can be used to simulate high-resolution atmospheric transport. This type of ML model will help estimate GHG emissions using dense observations, which are becoming increasingly common with the proliferation of urban monitoring networks and geostationary satellites.
Laura Hyesung Yang, Daniel J. Jacob, Ruijun Dang, Yujin J. Oak, Haipeng Lin, Jhoon Kim, Shixian Zhai, Nadia K. Colombi, Drew C. Pendergrass, Ellie Beaudry, Viral Shah, Xu Feng, Robert M. Yantosca, Heesung Chong, Junsung Park, Hanlim Lee, Won-Jin Lee, Soontae Kim, Eunhye Kim, Katherine R. Travis, James H. Crawford, and Hong Liao
Atmos. Chem. Phys., 24, 7027–7039, https://doi.org/10.5194/acp-24-7027-2024, https://doi.org/10.5194/acp-24-7027-2024, 2024
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The Geostationary Environment Monitoring Spectrometer (GEMS) provides hourly measurements of NO2. We use the chemical transport model to find how emissions, chemistry, and transport drive the changes in NO2 observed by GEMS at different times of the day. In winter, the chemistry plays a minor role, and high daytime emissions dominate the diurnal variation in NO2, balanced by transport. In summer, emissions, chemistry, and transport play an important role in shaping the diurnal variation in NO2.
Kelley Wells, Dylan Millet, Jared Brewer, Vivienne Payne, Karen Cady-Pereira, Rick Pernak, Susan Kulawik, Corinne Vigouroux, Nicholas Jones, Emmanuel Mahieu, Maria Makarova, Tomoo Nagahama, Ivan Ortega, Mathias Palm, Kimberly Strong, Matthias Schneider, Dan Smale, Ralf Sussmann, and Minqiang Zhou
EGUsphere, https://doi.org/10.5194/egusphere-2024-1551, https://doi.org/10.5194/egusphere-2024-1551, 2024
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Atmospheric volatile organic compounds affect both air quality and climate. Satellite measurements can help us to assess and predict their global impacts. We present new long-term (2012–2023) measurements of four key VOCs: methanol, ethene, ethyne, and hydrogen cyanide (HCN) from the Cross-track Infrared Sounder. The measurements reflect emissions from major forests, wildfires, and industry, and provide new information to advance understanding of these sources and their changes over time.
Brian Nathan, Joannes D. Maasakkers, Stijn Naus, Ritesh Gautam, Mark Omara, Daniel J. Varon, Melissa P. Sulprizio, Lucas A. Estrada, Alba Lorente, Tobias Borsdorff, Robert J. Parker, and Ilse Aben
Atmos. Chem. Phys., 24, 6845–6863, https://doi.org/10.5194/acp-24-6845-2024, https://doi.org/10.5194/acp-24-6845-2024, 2024
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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.
Marielle Saunois, Adrien Martinez, Benjamin Poulter, Zhen Zhang, Peter Raymond, Pierre Regnier, Joseph 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, Akihito Ito, Atul K. Jain, Rajesh Janardanan, Matthew S. Johnson, Thomas Kleinen, Paul 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, Joel Thanwerdas, Hanquin Tian, Aki Tsuruta, Francesco N. Tubiello, Thomas S. Weber, Guido van der Werf, Doug E. Worthy, Yi Xi, Yukio Yoshida, Wenxin Zhang, Bo Zheng, Qing Zhu, Qiuan Zhu, and Qianlai Zhuang
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-115, https://doi.org/10.5194/essd-2024-115, 2024
Revised manuscript under review for ESSD
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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 synthesize and update the budget of the sources and sinks of CH4. This edition benefits from important progresses 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.
Benedikt Herkommer, Carlos Alberti, Paolo Castracane, Jia Chen, Angelika Dehn, Florian Dietrich, Nicholas M. Deutscher, Matthias Max Frey, Jochen Groß, Lawson Gillespie, Frank Hase, Isamu Morino, Nasrin Mostafavi Pak, Brittany Walker, and Debra Wunch
Atmos. Meas. Tech., 17, 3467–3494, https://doi.org/10.5194/amt-17-3467-2024, https://doi.org/10.5194/amt-17-3467-2024, 2024
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The Total Carbon Column Observing Network is a network of ground-based Fourier transform infrared (FTIR) spectrometers used mainly for satellite validation. To ensure the highest-quality validation data, the network needs to be highly consistent. This is a major challenge, which so far is solved by site comparisons with airborne in situ measurements. In this work, we describe the use of a portable FTIR spectrometer as a travel standard for evaluating the consistency of TCCON sites.
Drew C. Pendergrass, Daniel J. Jacob, Yujin J. Oak, Jeewoo Lee, Minseok Kim, Jhoon Kim, Seoyoung Lee, Shixian Zhai, Hitoshi Irie, and Hong Liao
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-172, https://doi.org/10.5194/essd-2024-172, 2024
Preprint withdrawn
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Fine particles suspended in the atmosphere are a major form of air pollution and an important public health burden. However, measurements of particulate matter are sparse in space and in places like East Asia monitors are established after regulatory policies to improve pollution have changed. In this paper, we use machine learning to fill in the gaps. We train an algorithm to predict pollution at the surface from the atmosphere’s opacity, then produce high resolution maps of data without gaps.
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.
Joshua L. Laughner, Geoffrey C. Toon, Joseph Mendonca, Christof Petri, Sébastien Roche, Debra Wunch, Jean-Francois Blavier, David W. T. Griffith, Pauli Heikkinen, Ralph F. Keeling, Matthäus Kiel, Rigel Kivi, Coleen M. Roehl, Britton B. Stephens, Bianca C. Baier, Huilin Chen, Yonghoon Choi, Nicholas M. Deutscher, Joshua P. DiGangi, Jochen Gross, Benedikt Herkommer, Pascal Jeseck, Thomas Laemmel, Xin Lan, Erin McGee, Kathryn McKain, John Miller, Isamu Morino, Justus Notholt, Hirofumi Ohyama, David F. Pollard, Markus Rettinger, Haris Riris, Constantina Rousogenous, Mahesh Kumar Sha, Kei Shiomi, Kimberly Strong, Ralf Sussmann, Yao Té, Voltaire A. Velazco, Steven C. Wofsy, Minqiang Zhou, and Paul O. Wennberg
Earth Syst. Sci. Data, 16, 2197–2260, https://doi.org/10.5194/essd-16-2197-2024, https://doi.org/10.5194/essd-16-2197-2024, 2024
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This paper describes a new version, called GGG2020, of a data set containing column-integrated observations of greenhouse and related gases (including CO2, CH4, CO, and N2O) made by ground stations located around the world. Compared to the previous version (GGG2014), improvements have been made toward site-to-site consistency. This data set plays a key role in validating space-based greenhouse gas observations and in understanding the carbon cycle.
Amanda R. Fay, David R. Munro, Galen A. McKinley, Denis Pierrot, Stewart C. Sutherland, Colm Sweeney, and Rik Wanninkhof
Earth Syst. Sci. Data, 16, 2123–2139, https://doi.org/10.5194/essd-16-2123-2024, https://doi.org/10.5194/essd-16-2123-2024, 2024
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Presented here is a near-global monthly climatological estimate of the difference between atmosphere and ocean carbon dioxide concentrations. The ocean's ability to take up carbon, both now and in the future, is defined by this difference in concentrations. With over 30 million measurements of surface ocean carbon over the last 40 years and utilization of an extrapolation technique, a mean estimate of surface ocean ΔfCO2 is presented.
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.
Qiansi Tu, Frank Hase, Kai Qin, Jason Blake Cohen, Farahnaz Khosrawi, Xinrui Zou, Matthias Schneider, and Fan Lu
Atmos. Chem. Phys., 24, 4875–4894, https://doi.org/10.5194/acp-24-4875-2024, https://doi.org/10.5194/acp-24-4875-2024, 2024
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Four-year satellite observations of XCH4 are used to derive CH4 emissions in three regions of China’s coal-rich Shanxi province. The wind-assigned anomalies for two opposite wind directions are calculated, and the estimated emission rates are comparable to the current bottom-up inventory but lower than the CAMS and EDGAR inventories. This research enhances the understanding of emissions in Shanxi and supports climate mitigation strategies by validating emission inventories.
Stefan Noël, Michael Buchwitz, Michael Hilker, Maximilian Reuter, Michael Weimer, Heinrich Bovensmann, John P. Burrows, Hartmut Bösch, and Ruediger Lang
Atmos. Meas. Tech., 17, 2317–2334, https://doi.org/10.5194/amt-17-2317-2024, https://doi.org/10.5194/amt-17-2317-2024, 2024
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FOCAL-CO2M is one of the three operational retrieval algorithms which will be used to derive XCO2 and XCH4 from measurements of the forthcoming European CO2M mission. We present results of applications of FOCAL-CO2M to simulated spectra, from which confidence is gained that the algorithm is able to fulfil the challenging requirements on systematic errors for the CO2M mission (spatio-temporal bias ≤ 0.5 ppm for XCO2 and ≤ 5 ppb for XCH4).
Karl Voglmeier, Voltaire A. Velazco, Luca Egli, Julian Gröbner, Alberto Redondas, and Wolfgang Steinbrecht
Atmos. Meas. Tech., 17, 2277–2294, https://doi.org/10.5194/amt-17-2277-2024, https://doi.org/10.5194/amt-17-2277-2024, 2024
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Comparison between total ozone column (TOC) measurements from ground-based Dobson and Brewer spectrophotometers generally reveals seasonally varying differences of a few percent. This study recommends a new TOC retrieval approach, which effectively eliminates these seasonally varying differences by applying new ozone absorption cross sections, appropriate slit functions for the Dobson instrument, and climatological values for the effective ozone temperature.
Alexandra Klemme, Thorsten Warneke, Heinrich Bovensmann, Matthias Weigelt, Jürgen Müller, Tim Rixen, Justus Notholt, and Claus Lämmerzahl
Hydrol. Earth Syst. Sci., 28, 1527–1538, https://doi.org/10.5194/hess-28-1527-2024, https://doi.org/10.5194/hess-28-1527-2024, 2024
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Satellite data help estimate groundwater depletion, but earlier assessments missed mass loss from river sediment. In the Ganges–Brahmaputra–Meghna (GBM) river system, sediment accounts for 4 % of the depletion. Correcting for sediment in the GBM mountains reduces estimated depletion by 14 %. It's important to note that the Himalayas' uplift may offset some sediment-induced mass loss. This understanding is vital for accurate water storage trend assessments and sustainable groundwater management.
Ryan N. Farley, James E. Lee, Laura-Hélèna Rivellini, Alex K. Y. Lee, Rachael Dal Porto, Christopher D. Cappa, Kyle Gorkowski, Abu Sayeed Md Shawon, Katherine B. Benedict, Allison C. Aiken, Manvendra K. Dubey, and Qi Zhang
Atmos. Chem. Phys., 24, 3953–3971, https://doi.org/10.5194/acp-24-3953-2024, https://doi.org/10.5194/acp-24-3953-2024, 2024
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The black carbon aerosol composition and mixing state were characterized using a soot particle aerosol mass spectrometer. Single-particle measurements revealed the major role of atmospheric processing in modulating the black carbon mixing state. A significant fraction of soot particles were internally mixed with oxidized organic aerosol and sulfate, with implications for activation as cloud nuclei.
Pinchas Nürnberg, Markus Rettinger, and Ralf Sussmann
Atmos. Chem. Phys., 24, 3743–3757, https://doi.org/10.5194/acp-24-3743-2024, https://doi.org/10.5194/acp-24-3743-2024, 2024
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For a better understanding of stratospheric photochemistry, we analyzed long-term data from spectroscopic measurements at Zugspitze and Garmisch, Germany. We provide information about the seasonal cycle of diurnal nitrogen oxide variation in the stratosphere. For the first time we create an experimental data set to validate stratospheric model simulation that can improve satellite validation to gain further insights into ozone depletion and smog prevention.
James M. Roberts, Siyuan Wang, Patrick R. Veres, J. Andrew Neuman, Michael A. Robinson, Ilann Bourgeois, Jeff Peischl, Thomas B. Ryerson, Chelsea R. Thompson, Hannah M. Allen, John D. Crounse, Paul O. Wennberg, Samuel R. Hall, Kirk Ullmann, Simone Meinardi, Isobel J. Simpson, and Donald Blake
Atmos. Chem. Phys., 24, 3421–3443, https://doi.org/10.5194/acp-24-3421-2024, https://doi.org/10.5194/acp-24-3421-2024, 2024
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We measured cyanogen bromide (BrCN) in the troposphere for the first time. BrCN is a product of the same active bromine chemistry that destroys ozone and removes mercury in polar surface environments and is a previously unrecognized sink for active Br compounds. BrCN has an apparent lifetime against heterogeneous loss in the range 1–10 d, so it serves as a cumulative marker of Br-radical chemistry. Accounting for BrCN chemistry is an important part of understanding polar Br cycling.
Nicole Jacobs, Christopher W. O'Dell, Thomas E. Taylor, Thomas L. Logan, Brendan Byrne, Matthäus Kiel, Rigel Kivi, Pauli Heikkinen, Aronne Merrelli, Vivienne H. Payne, and Abhishek Chatterjee
Atmos. Meas. Tech., 17, 1375–1401, https://doi.org/10.5194/amt-17-1375-2024, https://doi.org/10.5194/amt-17-1375-2024, 2024
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The accuracy of trace gas retrievals from spaceborne observations, like those from the Orbiting Carbon Observatory 2 (OCO-2), are sensitive to the referenced digital elevation model (DEM). Therefore, we evaluate several global DEMs, used in versions 10 and 11 of the OCO-2 retrieval along with the Copernicus DEM. We explore the impacts of changing the DEM on biases in OCO-2-retrieved XCO2 and inferred CO2 fluxes. Our findings led to an update to OCO-2 v11.1 using the Copernicus DEM globally.
Sebastian D. Eastham, Guillaume P. Chossière, Raymond L. Speth, Daniel J. Jacob, and Steven R. H. Barrett
Atmos. Chem. Phys., 24, 2687–2703, https://doi.org/10.5194/acp-24-2687-2024, https://doi.org/10.5194/acp-24-2687-2024, 2024
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Emissions from aircraft are known to cause air quality impacts worldwide, but the scale and mechanisms of this impact are not well understood. This work uses high-resolution computational modeling of the atmosphere to show that air pollution changes from aviation are mostly the result of emissions during cruise (high-altitude) operations, that these impacts are related to how much non-aviation pollution is present, and that prior regional assessments have underestimated these impacts.
Jean-François Müller, Trissevgeni Stavrakou, Glenn-Michael Oomen, Beata Opacka, Isabelle De Smedt, Alex Guenther, Corinne Vigouroux, Bavo Langerock, Carlos Augusto Bauer Aquino, Michel Grutter, James Hannigan, Frank Hase, Rigel Kivi, Erik Lutsch, Emmanuel Mahieu, Maria Makarova, Jean-Marc Metzger, Isamu Morino, Isao Murata, Tomoo Nagahama, Justus Notholt, Ivan Ortega, Mathias Palm, Amelie Röhling, Wolfgang Stremme, Kimberly Strong, Ralf Sussmann, Yao Té, and Alan Fried
Atmos. Chem. Phys., 24, 2207–2237, https://doi.org/10.5194/acp-24-2207-2024, https://doi.org/10.5194/acp-24-2207-2024, 2024
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Formaldehyde observations from satellites can be used to constrain the emissions of volatile organic compounds, but those observations have biases. Using an atmospheric model, aircraft and ground-based remote sensing data, we quantify these biases, propose a correction to the data, and assess the consequence of this correction for the evaluation of emissions.
Min Huang, Gregory R. Carmichael, James H. Crawford, Kevin W. Bowman, Isabelle De Smedt, Andreas Colliander, Michael H. Cosh, Sujay V. Kumar, Alex B. Guenther, Scott J. Janz, Ryan M. Stauffer, Anne M. Thompson, Niko M. Fedkin, Robert J. Swap, John D. Bolten, and Alicia T. Joseph
EGUsphere, https://doi.org/10.5194/egusphere-2024-484, https://doi.org/10.5194/egusphere-2024-484, 2024
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This study uses model simulations along with multiplatform, multidisciplinary observations and a range of analysis methods to estimate and understand the distributions, temporal changes, and impacts of reactive nitrogen and ozone over the most populous US region that has undergone significant environmental changes. Deposition, biogenic emissions, and extra-regional sources have been playing increasingly important roles in controlling pollutants’ budgets in this area as local emissions go down.
Kelvin H. Bates, Mathew J. Evans, Barron H. Henderson, and Daniel J. Jacob
Geosci. Model Dev., 17, 1511–1524, https://doi.org/10.5194/gmd-17-1511-2024, https://doi.org/10.5194/gmd-17-1511-2024, 2024
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Accurate representation of rates and products of chemical reactions in atmospheric models is crucial for simulating concentrations of pollutants and climate forcers. We update the widely used GEOS-Chem atmospheric chemistry model with reaction parameters from recent compilations of experimental data and demonstrate the implications for key atmospheric chemical species. The updates decrease tropospheric CO mixing ratios and increase stratospheric nitrogen oxide mixing ratios, among other changes.
Blanca Fuentes Andrade, Michael Buchwitz, Maximilian Reuter, Heinrich Bovensmann, Andreas Richter, Hartmut Boesch, and John P. Burrows
Atmos. Meas. Tech., 17, 1145–1173, https://doi.org/10.5194/amt-17-1145-2024, https://doi.org/10.5194/amt-17-1145-2024, 2024
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We developed a method to estimate CO2 emissions from localized sources, such as power plants, using satellite data and applied it to estimate CO2 emissions from the Bełchatów Power Station (Poland). As the detection of CO2 emission plumes from satellite data is difficult, we used observations of co-emitted NO2 to constrain the emission plume region. Our results agree with CO2 emission estimations based on the power-plant-generated power and emission factors.
Georgios I. Gkatzelis, Matthew M. Coggon, Chelsea E. Stockwell, Rebecca S. Hornbrook, Hannah Allen, Eric C. Apel, Megan M. Bela, Donald R. Blake, Ilann Bourgeois, Steven S. Brown, Pedro Campuzano-Jost, Jason M. St. Clair, James H. Crawford, John D. Crounse, Douglas A. Day, Joshua P. DiGangi, Glenn S. Diskin, Alan Fried, Jessica B. Gilman, Hongyu Guo, Johnathan W. Hair, Hannah S. Halliday, Thomas F. Hanisco, Reem Hannun, Alan Hills, L. Gregory Huey, Jose L. Jimenez, Joseph M. Katich, Aaron Lamplugh, Young Ro Lee, Jin Liao, Jakob Lindaas, Stuart A. McKeen, Tomas Mikoviny, Benjamin A. Nault, J. Andrew Neuman, John B. Nowak, Demetrios Pagonis, Jeff Peischl, Anne E. Perring, Felix Piel, Pamela S. Rickly, Michael A. Robinson, Andrew W. Rollins, Thomas B. Ryerson, Melinda K. Schueneman, Rebecca H. Schwantes, Joshua P. Schwarz, Kanako Sekimoto, Vanessa Selimovic, Taylor Shingler, David J. Tanner, Laura Tomsche, Krystal T. Vasquez, Patrick R. Veres, Rebecca Washenfelder, Petter Weibring, Paul O. Wennberg, Armin Wisthaler, Glenn M. Wolfe, Caroline C. Womack, Lu Xu, Katherine Ball, Robert J. Yokelson, and Carsten Warneke
Atmos. Chem. Phys., 24, 929–956, https://doi.org/10.5194/acp-24-929-2024, https://doi.org/10.5194/acp-24-929-2024, 2024
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This study reports emissions of gases and particles from wildfires. These emissions are related to chemical proxies that can be measured by satellite and incorporated into models to improve predictions of wildfire impacts on air quality and climate.
Karen E. Cady-Pereira, Xuehui Guo, Rui Wang, April B. Leytem, Chase Calkins, Elizabeth Berry, Kang Sun, Markus Müller, Armin Wisthaler, Vivienne H. Payne, Mark W. Shephard, Mark A. Zondlo, and Valentin Kantchev
Atmos. Meas. Tech., 17, 15–36, https://doi.org/10.5194/amt-17-15-2024, https://doi.org/10.5194/amt-17-15-2024, 2024
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Ammonia is a significant precursor of PM2.5 particles and thus contributes to poor air quality in many regions. Furthermore, ammonia concentrations are rising due to the increase of large-scale, intensive agricultural activities. Here we evaluate satellite measurements of ammonia against aircraft and surface network data, and show that there are differences in magnitude, but the satellite data are spatially and temporally well correlated with the in situ data.
Lisa Azzarello, Rebecca A. Washenfelder, Michael A. Robinson, Alessandro Franchin, Caroline C. Womack, Christopher D. Holmes, Steven S. Brown, Ann Middlebrook, Tim Newberger, Colm Sweeney, and Cora J. Young
Atmos. Chem. Phys., 23, 15643–15654, https://doi.org/10.5194/acp-23-15643-2023, https://doi.org/10.5194/acp-23-15643-2023, 2023
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We present a molecular size-resolved offline analysis of water-soluble brown carbon collected on an aircraft during FIREX-AQ. The smoke plumes were aged 0 to 5 h, where absorption was dominated by small molecular weight molecules, brown carbon absorption downwind did not consistently decrease, and the measurements differed from online absorption measurements of the same samples. We show how differences between online and offline absorption could be related to different measurement conditions.
Tobias D. Schmitt, Jonas Kuhn, Ralph Kleinschek, Benedikt A. Löw, Stefan Schmitt, William Cranton, Martina Schmidt, Sanam N. Vardag, Frank Hase, David W. T. Griffith, and André Butz
Atmos. Meas. Tech., 16, 6097–6110, https://doi.org/10.5194/amt-16-6097-2023, https://doi.org/10.5194/amt-16-6097-2023, 2023
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Our new observatory measures greenhouse gas concentrations of carbon dioxide (CO2) and methane (CH4) along a 1.55 km long light path over the city of Heidelberg, Germany. We compared our measurements with measurements that were taken at a single point at one end of our path. The two mostly agreed but show a significant difference for CO2 with certain wind directions. This is important when using greenhouse gas concentration measurements to observe greenhouse gas emissions of cities.
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.
Ariana L. Tribby and Paul O. Wennberg
EGUsphere, https://doi.org/10.5194/egusphere-2023-2227, https://doi.org/10.5194/egusphere-2023-2227, 2023
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The simulation of in-situ atmospheric trace gases via chemical transport modeling is key towards improving knowledge of fundamental chemical processes and validating emissions but are associated with significant time and monetary constraints. We show the advantages of using potential temperature as a dynamical coordinate to efficiently compare in-situ observations to global chemical transport simulations even as the spatial resolution is increased 100-fold.
Hirofumi Ohyama, Matthias M. Frey, Isamu Morino, Kei Shiomi, Masahide Nishihashi, Tatsuya Miyauchi, Hiroko Yamada, Makoto Saito, Masanobu Wakasa, Thomas Blumenstock, and Frank Hase
Atmos. Chem. Phys., 23, 15097–15119, https://doi.org/10.5194/acp-23-15097-2023, https://doi.org/10.5194/acp-23-15097-2023, 2023
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We conducted a field campaign for CO2 column measurements in the Tokyo metropolitan area with three ground-based Fourier transform spectrometers. The model simulations using prior CO2 fluxes were generally in good agreement with the observations. We developed an urban-scale inversion system in which spatially resolved CO2 fluxes and a scaling factor of large point source emissions were estimated. The posterior total CO2 emissions agreed with emission inventories within the posterior uncertainty.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Dorothee C. E. Bakker, Judith Hauck, Peter Landschützer, Corinne Le Quéré, Ingrid T. Luijkx, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Peter Anthoni, Leticia Barbero, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Bertrand Decharme, Laurent Bopp, Ida Bagus Mandhara Brasika, Patricia Cadule, Matthew A. Chamberlain, Naveen Chandra, Thi-Tuyet-Trang Chau, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Xinyu Dou, Kazutaka Enyo, Wiley Evans, Stefanie Falk, Richard A. Feely, Liang Feng, Daniel J. Ford, Thomas Gasser, Josefine Ghattas, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Jens Heinke, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Andrew R. Jacobson, Atul Jain, Tereza Jarníková, Annika Jersild, Fei Jiang, Zhe Jin, Fortunat Joos, Etsushi Kato, Ralph F. Keeling, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Arne Körtzinger, Xin Lan, Nathalie Lefèvre, Hongmei Li, Junjie Liu, Zhiqiang Liu, Lei Ma, Greg Marland, Nicolas Mayot, Patrick C. McGuire, Galen A. McKinley, Gesa Meyer, Eric J. Morgan, David R. Munro, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin M. O'Brien, Are Olsen, Abdirahman M. Omar, Tsuneo Ono, Melf Paulsen, Denis Pierrot, Katie Pocock, Benjamin Poulter, Carter M. Powis, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Thais M. Rosan, Jörg Schwinger, Roland Séférian, T. Luke Smallman, Stephen M. Smith, Reinel Sospedra-Alfonso, Qing Sun, Adrienne J. Sutton, Colm Sweeney, Shintaro Takao, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Hiroyuki Tsujino, Francesco Tubiello, Guido R. van der Werf, Erik van Ooijen, Rik Wanninkhof, Michio Watanabe, Cathy Wimart-Rousseau, Dongxu Yang, Xiaojuan Yang, Wenping Yuan, Xu Yue, Sönke Zaehle, Jiye Zeng, and Bo Zheng
Earth Syst. Sci. Data, 15, 5301–5369, https://doi.org/10.5194/essd-15-5301-2023, https://doi.org/10.5194/essd-15-5301-2023, 2023
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The Global Carbon Budget 2023 describes the methodology, main results, and data sets used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, land ecosystems, and the ocean over the historical period (1750–2023). These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Reina S. Buenconsejo, Sophia M. Charan, John H. Seinfeld, and Paul O. Wennberg
EGUsphere, https://doi.org/10.5194/egusphere-2023-2483, https://doi.org/10.5194/egusphere-2023-2483, 2023
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We look at the atmospheric chemistry of a volatile chemical product (VCP), benzyl alcohol. Benzyl alcohol and other VCPs may play a significant role in the formation of urban smog. By better understanding the chemistry of VCPs like benzyl alcohol, we may better understand observed data and how VCPs affect air quality. We identify products formed from benzyl alcohol chemistry and use this chemistry to understand how benzyl alcohol forms a key component of smog, secondary organic aerosol.
Benedikt A. Löw, Ralph Kleinschek, Vincent Enders, Stanley P. Sander, Thomas J. Pongetti, Tobias D. Schmitt, Frank Hase, Julian Kostinek, and André Butz
Atmos. Meas. Tech., 16, 5125–5144, https://doi.org/10.5194/amt-16-5125-2023, https://doi.org/10.5194/amt-16-5125-2023, 2023
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We developed a portable spectrometer (EM27/SCA) that remotely measures greenhouse gases in the lower atmosphere above a target region. The measurements can deliver insights into local emission patterns. To evaluate its performance, we set up the EM27/SCA above the Los Angeles Basin side by side with a similar non-portable instrument (CLARS-FTS). The precision is promising and the measurements are consistent with CLARS-FTS. In the future, we need to account for light scattering.
Dien Wu, Joshua L. Laughner, Junjie Liu, Paul I. Palmer, John C. Lin, and Paul O. Wennberg
Geosci. Model Dev., 16, 6161–6185, https://doi.org/10.5194/gmd-16-6161-2023, https://doi.org/10.5194/gmd-16-6161-2023, 2023
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To balance computational expenses and chemical complexity in extracting emission signals from tropospheric NO2 columns, we propose a simplified non-linear Lagrangian chemistry transport model and assess its performance against TROPOMI v2 over power plants and cities. Using this model, we then discuss how NOx chemistry affects the relationship between NOx and CO2 emissions and how studying NO2 columns helps quantify modeled biases in wind directions and prior emissions.
Óscar Alvárez, África Barreto, Omaira E. García, Frank Hase, Rosa D. García, Julian Gröbner, Sergio F. León-Luis, Eliezer Sepúlveda, Virgilio Carreño, Antonio Alcántara, Ramón Ramos, A. Fernando Almansa, Stelios Kazadzis, Noémie Taquet, Carlos Toledano, and Emilio Cuevas
Atmos. Meas. Tech., 16, 4861–4884, https://doi.org/10.5194/amt-16-4861-2023, https://doi.org/10.5194/amt-16-4861-2023, 2023
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In this work, we have extended the capabilities of a portable Fourier transform infrared (FTIR) instrument, which was originally designed to provide high-quality greenhouse gas monitoring within COCCON (COllaborative Carbon Column Observing Network). The extension allows the spectrometer to now also provide coincidentally column-integrated aerosol information. This addition of a reference instrument to a global network will be utilised to enhance our understanding of atmospheric chemistry.
Lawson David Gillespie, Sébastien Ars, James Phillip Williams, Louise Klotz, Tianjie Feng, Stephanie Gu, Mishaal Kandapath, Amy Mann, Michael Raczkowski, Mary Kang, Felix Vogel, and Debra Wunch
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-193, https://doi.org/10.5194/amt-2023-193, 2023
Preprint withdrawn
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We investigate techniques for calculating emissions from mobile in situ gas concentrations recorded during downwind plume transects. We find that using the enhancement area to estimate emissions is the most consistent method when comparing different setups and instruments. Observations from a multi year urban methane survey and controlled release experiment are analyzed, and emissions rates for combined sewage overflow basins and a large wastewater treatment plant in Toronto are calculated.
Rafaella Chiarella, Matthias Buschmann, Joshua Laughner, Isamu Morino, Justus Notholt, Christof Petri, Geoffrey Toon, Voltaire A. Velazco, and Thorsten Warneke
Atmos. Meas. Tech., 16, 3987–4007, https://doi.org/10.5194/amt-16-3987-2023, https://doi.org/10.5194/amt-16-3987-2023, 2023
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The goal is to establish a window and strategy for xCO2 retrieval from ground-based Fourier transform spectrometers for NDACC. In the study we describe the spectroscopy of the region, the locations and instruments used, and the methods of calculating the retrieved xCO2. We performed tests to assess the sensitivity to diverse factors and sources of errors while comparing the retrieval to a well-established xCO2 retrieval from TCCON.
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.
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.
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.
Thomas E. Taylor, Christopher W. O'Dell, David Baker, Carol Bruegge, Albert Chang, Lars Chapsky, Abhishek Chatterjee, Cecilia Cheng, Frédéric Chevallier, David Crisp, Lan Dang, Brian Drouin, Annmarie Eldering, Liang Feng, Brendan Fisher, Dejian Fu, Michael Gunson, Vance Haemmerle, Graziela R. Keller, Matthäus Kiel, Le Kuai, Thomas Kurosu, Alyn Lambert, Joshua Laughner, Richard Lee, Junjie Liu, Lucas Mandrake, Yuliya Marchetti, Gregory McGarragh, Aronne Merrelli, Robert R. Nelson, Greg Osterman, Fabiano Oyafuso, Paul I. Palmer, Vivienne H. Payne, Robert Rosenberg, Peter Somkuti, Gary Spiers, Cathy To, Brad Weir, Paul O. Wennberg, Shanshan Yu, and Jia Zong
Atmos. Meas. Tech., 16, 3173–3209, https://doi.org/10.5194/amt-16-3173-2023, https://doi.org/10.5194/amt-16-3173-2023, 2023
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NASA's Orbiting Carbon Observatory 2 and 3 (OCO-2 and OCO-3, respectively) provide complementary spatiotemporal coverage from a sun-synchronous and precession orbit, respectively. Estimates of total column carbon dioxide (XCO2) derived from the two sensors using the same retrieval algorithm show broad consistency over a 2.5-year overlapping time record. This suggests that data from the two satellites may be used together for scientific analysis.
Jianghanyang Li, Bianca C. Baier, Fred Moore, Tim Newberger, Sonja Wolter, Jack Higgs, Geoff Dutton, Eric Hintsa, Bradley Hall, and Colm Sweeney
Atmos. Meas. Tech., 16, 2851–2863, https://doi.org/10.5194/amt-16-2851-2023, https://doi.org/10.5194/amt-16-2851-2023, 2023
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Monitoring a suite of trace gases in the stratosphere will help us better understand the stratospheric circulation and its impact on the earth's radiation balance. However, such measurements are rare and usually expensive. We developed an instrument that can measure stratospheric trace gases using a low-cost sampling platform (AirCore). The results showed expected agreement with aircraft measurements, demonstrating this technique provides a low-cost and robust way to observe the stratosphere.
Ruijun Dang, Daniel J. Jacob, Viral Shah, Sebastian D. Eastham, Thibaud M. Fritz, Loretta J. Mickley, Tianjia Liu, Yi Wang, and Jun Wang
Atmos. Chem. Phys., 23, 6271–6284, https://doi.org/10.5194/acp-23-6271-2023, https://doi.org/10.5194/acp-23-6271-2023, 2023
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We use the GEOS-Chem model to better understand the magnitude and trend in free tropospheric NO2 over the contiguous US. Model underestimate of background NO2 is largely corrected by considering aerosol nitrate photolysis. Increase in aircraft emissions affects satellite retrievals by altering the NO2 shape factor, and this effect is expected to increase in future. We show the importance of properly accounting for the free tropospheric background in interpreting NO2 observations from space.
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.
Peter Joyce, Cristina Ruiz Villena, Yahui Huang, Alex Webb, Manuel Gloor, Fabien H. Wagner, Martyn P. Chipperfield, Rocío Barrio Guilló, Chris Wilson, and Hartmut Boesch
Atmos. Meas. Tech., 16, 2627–2640, https://doi.org/10.5194/amt-16-2627-2023, https://doi.org/10.5194/amt-16-2627-2023, 2023
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Methane emissions are responsible for a lot of the warming caused by the greenhouse effect, much of which comes from a small number of point sources. We can identify methane point sources by analysing satellite data, but it requires a lot of time invested by experts and is prone to very high errors. Here, we produce a neural network that can automatically identify methane point sources and estimate the mass of methane that is being released per hour and are able to do so with far smaller errors.
Harrison A. Parker, Joshua L. Laughner, Geoffrey C. Toon, Debra Wunch, Coleen M. Roehl, Laura T. Iraci, James R. Podolske, Kathryn McKain, Bianca C. Baier, and Paul O. Wennberg
Atmos. Meas. Tech., 16, 2601–2625, https://doi.org/10.5194/amt-16-2601-2023, https://doi.org/10.5194/amt-16-2601-2023, 2023
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We describe a retrieval algorithm for determining limited information about the vertical distribution of carbon monoxide (CO) and carbon dioxide (CO2) from total column observations from ground-based observations. Our retrieved partial column values compare well with integrated in situ data. The average error for our retrieval is 1.51 ppb (~ 2 %) for CO and 5.09 ppm (~ 1.25 %) for CO2. We anticipate that this approach will find broad application for use in carbon cycle science.
Claudio Belotti, Flavio Barbara, Marco Barucci, Giovanni Bianchini, Francesco D'Amato, Samuele Del Bianco, Gianluca Di Natale, Marco Gai, Alessio Montori, Filippo Pratesi, Markus Rettinger, Christian Rolf, Ralf Sussmann, Thomas Trickl, Silvia Viciani, Hannes Vogelmann, and Luca Palchetti
Atmos. Meas. Tech., 16, 2511–2529, https://doi.org/10.5194/amt-16-2511-2023, https://doi.org/10.5194/amt-16-2511-2023, 2023
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FIRMOS (Far-Infrared Radiation Mobile Observation System) is a spectroradiometer measuring in the far-infrared, developed to support the preparation of the FORUM (Far-infrared Outgoing Radiation Understanding and Monitoring) satellite mission. In this paper, we describe the instrument, its data products, and the results of the comparison with a suite of observations made from a high-altitude site during a field campaign, in winter 2018–2019.
Yifan Guan, Gretchen Keppel-Aleks, Scott C. Doney, Christof Petri, Dave Pollard, Debra Wunch, Frank Hase, Hirofumi Ohyama, Isamu Morino, Justus Notholt, Kei Shiomi, Kim Strong, Rigel Kivi, Matthias Buschmann, Nicholas Deutscher, Paul Wennberg, Ralf Sussmann, Voltaire A. Velazco, and Yao Té
Atmos. Chem. Phys., 23, 5355–5372, https://doi.org/10.5194/acp-23-5355-2023, https://doi.org/10.5194/acp-23-5355-2023, 2023
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We characterize spatial–temporal patterns of interannual variability (IAV) in atmospheric CO2 based on NASA’s Orbiting Carbon Observatory-2 (OCO-2). CO2 variation is strongly impacted by climate events, with higher anomalies during El Nino years. We show high correlation in IAV between space-based and ground-based CO2 from long-term sites. Because OCO-2 has near-global coverage, our paper provides a roadmap to study IAV where in situ observation is sparse, such as open oceans and remote lands.
Qiansi Tu, Frank Hase, Zihan Chen, Matthias Schneider, Omaira García, Farahnaz Khosrawi, Shuo Chen, Thomas Blumenstock, Fang Liu, Kai Qin, Jason Cohen, Qin He, Song Lin, Hongyan Jiang, and Dianjun Fang
Atmos. Meas. Tech., 16, 2237–2262, https://doi.org/10.5194/amt-16-2237-2023, https://doi.org/10.5194/amt-16-2237-2023, 2023
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Four-year TROPOMI observations are used to derive tropospheric NO2 emissions in two mega(cities) with high anthropogenic activity. Wind-assigned anomalies are calculated, and the emission rates and spatial patterns are estimated based on a machine learning algorithm. The results are in reasonable agreement with previous studies and the inventory. Our method is quite robust and can be used as a simple method to estimate the emissions of NO2 as well as other gases in other regions.
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.
Isis Frausto-Vicencio, Sajjan Heerah, Aaron G. Meyer, Harrison A. Parker, Manvendra Dubey, and Francesca M. Hopkins
Atmos. Chem. Phys., 23, 4521–4543, https://doi.org/10.5194/acp-23-4521-2023, https://doi.org/10.5194/acp-23-4521-2023, 2023
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Wildfires are increasing in the western USA, making it critical to understand the impacts of greenhouse gases and air pollutants on the atmosphere. We used a ground-based remote sensing technique to measure the greenhouse gases and aerosol in the atmosphere. We isolate a large smoke plume from a nearby wildfire and calculate variables to understand the fuel properties and combustion phases. We find that a significant amount of methane is emitted from the 2020 California wildfire season.
Shixian Zhai, Daniel J. Jacob, Drew C. Pendergrass, Nadia K. Colombi, Viral Shah, Laura Hyesung Yang, Qiang Zhang, Shuxiao Wang, Hwajin Kim, Yele Sun, Jin-Soo Choi, Jin-Soo Park, Gan Luo, Fangqun Yu, Jung-Hun Woo, Younha Kim, Jack E. Dibb, Taehyoung Lee, Jin-Seok Han, Bruce E. Anderson, Ke Li, and Hong Liao
Atmos. Chem. Phys., 23, 4271–4281, https://doi.org/10.5194/acp-23-4271-2023, https://doi.org/10.5194/acp-23-4271-2023, 2023
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Anthropogenic fugitive dust in East Asia not only causes severe coarse particulate matter air pollution problems, but also affects fine particulate nitrate. Due to emission control efforts, coarse PM decreased steadily. We find that the decrease of coarse PM is a major driver for a lack of decrease of fine particulate nitrate, as it allows more nitric acid to form fine particulate nitrate. The continuing decrease of coarse PM requires more stringent ammonia and nitrogen oxides emission controls.
Nadia K. Colombi, Daniel J. Jacob, Laura Hyesung Yang, Shixian Zhai, Viral Shah, Stuart K. Grange, Robert M. Yantosca, Soontae Kim, and Hong Liao
Atmos. Chem. Phys., 23, 4031–4044, https://doi.org/10.5194/acp-23-4031-2023, https://doi.org/10.5194/acp-23-4031-2023, 2023
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Surface ozone, detrimental to human and ecosystem health, is very high and increasing in South Korea. Using a global model of the atmosphere, we found that emissions from South Korea and China contribute equally to the high ozone observed. We found that in the absence of all anthropogenic emissions over East Asia, ozone is still very high, implying that the air quality standard in South Korea is not practically achievable unless this background external to East Asia can be decreased.
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.
Yu Someya, Yukio Yoshida, Hirofumi Ohyama, Shohei Nomura, Akihide Kamei, Isamu Morino, Hitoshi Mukai, Tsuneo Matsunaga, Joshua L. Laughner, Voltaire A. Velazco, Benedikt Herkommer, Yao Té, Mahesh Kumar Sha, Rigel Kivi, Minqiang Zhou, Young Suk Oh, Nicholas M. Deutscher, and David W. T. Griffith
Atmos. Meas. Tech., 16, 1477–1501, https://doi.org/10.5194/amt-16-1477-2023, https://doi.org/10.5194/amt-16-1477-2023, 2023
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The updated retrieval algorithm for the Greenhouse gases Observing SATellite level 2 product is presented. The main changes in the algorithm from the previous one are the treatment of cirrus clouds, the degradation model of the sensor, solar irradiance, and gas absorption coefficient tables. The retrieval results showed improvements in fitting accuracy and an increase in the data amount over land. On the other hand, there are still large biases of XCO2 which should be corrected over the ocean.
Cameron G. MacDonald, Jon-Paul Mastrogiacomo, Joshua L. Laughner, Jacob K. Hedelius, Ray Nassar, and Debra Wunch
Atmos. Chem. Phys., 23, 3493–3516, https://doi.org/10.5194/acp-23-3493-2023, https://doi.org/10.5194/acp-23-3493-2023, 2023
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We use three satellites measuring carbon dioxide (CO2), carbon monoxide (CO) and nitrogen dioxide (NO2) to calculate atmospheric enhancements of these gases from 27 urban areas. We calculate enhancement ratios between the species and compare those to ratios derived from four globally gridded anthropogenic emission inventories. We find that the global inventories generally underestimate CO emissions in many North American and European cities relative to our observed enhancement ratios.
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.
Nasrin Mostafavi Pak, Jacob K. Hedelius, Sébastien Roche, Liz Cunningham, Bianca Baier, Colm Sweeney, Coleen Roehl, Joshua Laughner, Geoffrey Toon, Paul Wennberg, Harrison Parker, Colin Arrowsmith, Joseph Mendonca, Pierre Fogal, Tyler Wizenberg, Beatriz Herrera, Kimberly Strong, Kaley A. Walker, Felix Vogel, and Debra Wunch
Atmos. Meas. Tech., 16, 1239–1261, https://doi.org/10.5194/amt-16-1239-2023, https://doi.org/10.5194/amt-16-1239-2023, 2023
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Ground-based remote sensing instruments in the Total Carbon Column Observing Network (TCCON) measure greenhouse gases in the atmosphere. Consistency between TCCON measurements is crucial to accurately infer changes in atmospheric composition. We use portable remote sensing instruments (EM27/SUN) to evaluate biases between TCCON stations in North America. We also improve the retrievals of EM27/SUN instruments and evaluate the previous (GGG2014) and newest (GGG2020) retrieval algorithms.
Brendan Byrne, David F. Baker, Sourish Basu, Michael Bertolacci, Kevin W. Bowman, Dustin Carroll, Abhishek Chatterjee, Frédéric Chevallier, Philippe Ciais, Noel Cressie, David Crisp, Sean Crowell, Feng Deng, Zhu Deng, Nicholas M. Deutscher, Manvendra K. Dubey, Sha Feng, Omaira E. García, David W. T. Griffith, Benedikt Herkommer, Lei Hu, Andrew R. Jacobson, Rajesh Janardanan, Sujong Jeong, Matthew S. Johnson, Dylan B. A. Jones, Rigel Kivi, Junjie Liu, Zhiqiang Liu, Shamil Maksyutov, John B. Miller, Scot M. Miller, Isamu Morino, Justus Notholt, Tomohiro Oda, Christopher W. O'Dell, Young-Suk Oh, Hirofumi Ohyama, Prabir K. Patra, Hélène Peiro, Christof Petri, Sajeev Philip, David F. Pollard, Benjamin Poulter, Marine Remaud, Andrew Schuh, Mahesh K. Sha, Kei Shiomi, Kimberly Strong, Colm Sweeney, Yao Té, Hanqin Tian, Voltaire A. Velazco, Mihalis Vrekoussis, Thorsten Warneke, John R. Worden, Debra Wunch, Yuanzhi Yao, Jeongmin Yun, Andrew Zammit-Mangion, and Ning Zeng
Earth Syst. Sci. Data, 15, 963–1004, https://doi.org/10.5194/essd-15-963-2023, https://doi.org/10.5194/essd-15-963-2023, 2023
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Changes in the carbon stocks of terrestrial ecosystems result in emissions and removals of CO2. These can be driven by anthropogenic activities (e.g., deforestation), natural processes (e.g., fires) or in response to rising CO2 (e.g., CO2 fertilization). This paper describes a dataset of CO2 emissions and removals derived from atmospheric CO2 observations. This pilot dataset informs current capabilities and future developments towards top-down monitoring and verification systems.
Joshua L. Laughner, Sébastien Roche, Matthäus Kiel, Geoffrey C. Toon, Debra Wunch, Bianca C. Baier, Sébastien Biraud, Huilin Chen, Rigel Kivi, Thomas Laemmel, Kathryn McKain, Pierre-Yves Quéhé, Constantina Rousogenous, Britton B. Stephens, Kaley Walker, and Paul O. Wennberg
Atmos. Meas. Tech., 16, 1121–1146, https://doi.org/10.5194/amt-16-1121-2023, https://doi.org/10.5194/amt-16-1121-2023, 2023
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Observations using sunlight to measure surface-to-space total column of greenhouse gases in the atmosphere need an initial guess of the vertical distribution of those gases to start from. We have developed an approach to provide those initial guess profiles that uses readily available meteorological data as input. This lets us make these guesses without simulating them with a global model. The profiles generated this way match independent observations well.
Madison J. Shogrin, Vivienne H. Payne, Susan S. Kulawik, Kazuyuki Miyazaki, and Emily V. Fischer
Atmos. Chem. Phys., 23, 2667–2682, https://doi.org/10.5194/acp-23-2667-2023, https://doi.org/10.5194/acp-23-2667-2023, 2023
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We evaluate the spatiotemporal variability of peroxy acyl nitrates (PANs), important photochemical pollutants, over Mexico City using satellite observations. PANs exhibit a seasonal cycle that maximizes in spring. Wildfires contribute to observed interannual variability, and the satellite indicates several areas of frequent outflow. Recent changes in NOx emissions are not accompanied by changes in PANs. This work demonstrates analysis approaches that can be applied to other megacities.
Laura Hyesung Yang, Daniel J. Jacob, Nadia K. Colombi, Shixian Zhai, Kelvin H. Bates, Viral Shah, Ellie Beaudry, Robert M. Yantosca, Haipeng Lin, Jared F. Brewer, Heesung Chong, Katherine R. Travis, James H. Crawford, Lok N. Lamsal, Ja-Ho Koo, and Jhoon Kim
Atmos. Chem. Phys., 23, 2465–2481, https://doi.org/10.5194/acp-23-2465-2023, https://doi.org/10.5194/acp-23-2465-2023, 2023
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A geostationary satellite can now provide hourly NO2 vertical columns, and obtaining the NO2 vertical columns from space relies on NO2 vertical distribution from the chemical transport model (CTM). In this work, we update the CTM to better represent the chemistry environment so that the CTM can accurately provide NO2 vertical distribution. We also find that the changes in NO2 vertical distribution driven by a change in mixing depth play an important role in the NO2 column's diurnal variation.
Lei Hu, Deborah Ottinger, Stephanie Bogle, Stephen A. Montzka, Philip L. DeCola, Ed Dlugokencky, Arlyn Andrews, Kirk Thoning, Colm Sweeney, Geoff Dutton, Lauren Aepli, and Andrew Crotwell
Atmos. Chem. Phys., 23, 1437–1448, https://doi.org/10.5194/acp-23-1437-2023, https://doi.org/10.5194/acp-23-1437-2023, 2023
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Effective mitigation of greenhouse gas (GHG) emissions relies on an accurate understanding of emissions. Here we demonstrate the added value of using inventory- and atmosphere-based approaches for estimating US emissions of SF6, the most potent GHG known. The results suggest a large decline in US SF6 emissions, shed light on the possible processes causing the differences between the independent estimates, and identify opportunities for substantial additional emission reductions.
Viral Shah, Daniel J. Jacob, Ruijun Dang, Lok N. Lamsal, Sarah A. Strode, Stephen D. Steenrod, K. Folkert Boersma, Sebastian D. Eastham, Thibaud M. Fritz, Chelsea Thompson, Jeff Peischl, Ilann Bourgeois, Ilana B. Pollack, Benjamin A. Nault, Ronald C. Cohen, Pedro Campuzano-Jost, Jose L. Jimenez, Simone T. Andersen, Lucy J. Carpenter, Tomás Sherwen, and Mat J. Evans
Atmos. Chem. Phys., 23, 1227–1257, https://doi.org/10.5194/acp-23-1227-2023, https://doi.org/10.5194/acp-23-1227-2023, 2023
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NOx in the free troposphere (above 2 km) affects global tropospheric chemistry and the retrieval and interpretation of satellite NO2 measurements. We evaluate free tropospheric NOx in global atmospheric chemistry models and find that recycling NOx from its reservoirs over the oceans is faster than that simulated in the models, resulting in increases in simulated tropospheric ozone and OH. Over the U.S., free tropospheric NO2 contributes the majority of the tropospheric NO2 column in summer.
Lu Xu, Matthew M. Coggon, Chelsea E. Stockwell, Jessica B. Gilman, Michael A. Robinson, Martin Breitenlechner, Aaron Lamplugh, John D. Crounse, Paul O. Wennberg, J. Andrew Neuman, Gordon A. Novak, Patrick R. Veres, Steven S. Brown, and Carsten Warneke
Atmos. Meas. Tech., 15, 7353–7373, https://doi.org/10.5194/amt-15-7353-2022, https://doi.org/10.5194/amt-15-7353-2022, 2022
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We describe the development and operation of a chemical ionization mass spectrometer using an ammonium–water cluster (NH4+·H2O) as a reagent ion. NH4+·H2O is a highly versatile reagent ion for measurements of a wide range of oxygenated organic compounds. The major product ion is the cluster with NH4+ produced via ligand-switching reactions. The instrumental sensitivities of analytes depend on the binding energy of the analyte–NH4+ cluster; sensitivities can be estimated using voltage scanning.
Luke D. Schiferl, Jennifer D. Watts, Erik J. L. Larson, Kyle A. Arndt, Sébastien C. Biraud, Eugénie S. Euskirchen, Jordan P. Goodrich, John M. Henderson, Aram Kalhori, Kathryn McKain, Marikate E. Mountain, J. William Munger, Walter C. Oechel, Colm Sweeney, Yonghong Yi, Donatella Zona, and Róisín Commane
Biogeosciences, 19, 5953–5972, https://doi.org/10.5194/bg-19-5953-2022, https://doi.org/10.5194/bg-19-5953-2022, 2022
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As the Arctic rapidly warms, vast stores of thawing permafrost could release carbon dioxide (CO2) into the atmosphere. We combined observations of atmospheric CO2 concentrations from aircraft and a tower with observed CO2 fluxes from tundra ecosystems and found that the Alaskan North Slope in not a consistent source nor sink of CO2. Our study shows the importance of using both site-level and atmospheric measurements to constrain regional net CO2 fluxes and improve biogenic processes in models.
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.
Farahnaz Khosrawi, Kinya Toride, Kei Yoshimura, Christopher Diekmann, Benjamin Ertl, Frank Hase, and Matthias Schneider
EGUsphere, https://doi.org/10.5194/egusphere-2022-1408, https://doi.org/10.5194/egusphere-2022-1408, 2022
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We assess with an Observation System Simulation Experiment the potential of mid-tropospheric water isotopologue data for constraining uncertainties in meteorological analysis fields in the tropics. Our assimilation experiments indicate that isotopologue observations have the potential to reduce the uncertainties of diabatic heating rates and precipitation in the tropics and in consequence offer potential for improving meteorological analysis in the tropical regions.
David F. Pollard, Frank Hase, Mahesh Kumar Sha, Darko Dubravica, Carlos Alberti, and Dan Smale
Earth Syst. Sci. Data, 14, 5427–5437, https://doi.org/10.5194/essd-14-5427-2022, https://doi.org/10.5194/essd-14-5427-2022, 2022
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We describe measurements made in Antarctica using an EM27/SUN, a near-infrared, portable, low-resolution spectrometer from which we can retrieve the average atmospheric concentration of several greenhouse gases. We show that these measurements are reliable and comparable to other, similar ground-based measurements. Comparisons to the ESA's Sentinel-5 precursor (S5P) satellite demonstrate the usefulness of these data for satellite validation.
Pamela S. Rickly, Hongyu Guo, Pedro Campuzano-Jost, Jose L. Jimenez, Glenn M. Wolfe, Ryan Bennett, Ilann Bourgeois, John D. Crounse, Jack E. Dibb, Joshua P. DiGangi, Glenn S. Diskin, Maximilian Dollner, Emily M. Gargulinski, Samuel R. Hall, Hannah S. Halliday, Thomas F. Hanisco, Reem A. Hannun, Jin Liao, Richard Moore, Benjamin A. Nault, John B. Nowak, Jeff Peischl, Claire E. Robinson, Thomas Ryerson, Kevin J. Sanchez, Manuel Schöberl, Amber J. Soja, Jason M. St. Clair, Kenneth L. Thornhill, Kirk Ullmann, Paul O. Wennberg, Bernadett Weinzierl, Elizabeth B. Wiggins, Edward L. Winstead, and Andrew W. Rollins
Atmos. Chem. Phys., 22, 15603–15620, https://doi.org/10.5194/acp-22-15603-2022, https://doi.org/10.5194/acp-22-15603-2022, 2022
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Biomass burning sulfur dioxide (SO2) emission factors range from 0.27–1.1 g kg-1 C. Biomass burning SO2 can quickly form sulfate and organosulfur, but these pathways are dependent on liquid water content and pH. Hydroxymethanesulfonate (HMS) appears to be directly emitted from some fire sources but is not the sole contributor to the organosulfur signal. It is shown that HMS and organosulfur chemistry may be an important S(IV) reservoir with the fate dependent on the surrounding conditions.
Joël Thanwerdas, Marielle Saunois, Isabelle Pison, Didier Hauglustaine, Antoine Berchet, Bianca Baier, Colm Sweeney, and Philippe Bousquet
Atmos. Chem. Phys., 22, 15489–15508, https://doi.org/10.5194/acp-22-15489-2022, https://doi.org/10.5194/acp-22-15489-2022, 2022
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Atmospheric methane (CH4) concentrations have been rising since 2007, resulting from an imbalance between CH4 sources and sinks. The CH4 budget is generally estimated through top-down approaches using CH4 and δ13C(CH4) observations as constraints. The oxidation by chlorine (Cl) contributes little to the total oxidation of CH4 but strongly influences δ13C(CH4). Here, we compare multiple recent Cl fields and quantify the influence of Cl concentrations on CH4, δ13C(CH4), and CH4 budget estimates.
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.
Thibaud M. Fritz, Sebastian D. Eastham, Louisa K. Emmons, Haipeng Lin, Elizabeth W. Lundgren, Steve Goldhaber, Steven R. H. Barrett, and Daniel J. Jacob
Geosci. Model Dev., 15, 8669–8704, https://doi.org/10.5194/gmd-15-8669-2022, https://doi.org/10.5194/gmd-15-8669-2022, 2022
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We bring the state-of-the-science chemistry module GEOS-Chem into the Community Earth System Model (CESM). We show that some known differences between results from GEOS-Chem and CESM's CAM-chem chemistry module may be due to the configuration of model meteorology rather than inherent differences in the model chemistry. This is a significant step towards a truly modular Earth system model and allows two strong but currently separate research communities to benefit from each other's advances.
Ali Jalali, Kaley A. Walker, Kimberly Strong, Rebecca R. Buchholz, Merritt N. Deeter, Debra Wunch, Sébastien Roche, Tyler Wizenberg, Erik Lutsch, Erin McGee, Helen M. Worden, Pierre Fogal, and James R. Drummond
Atmos. Meas. Tech., 15, 6837–6863, https://doi.org/10.5194/amt-15-6837-2022, https://doi.org/10.5194/amt-15-6837-2022, 2022
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This study validates MOPITT version 8 carbon monoxide measurements over the Canadian high Arctic for the period 2006 to 2019. The MOPITT products from different detector pixels and channels are compared with ground-based measurements from the Polar Environment Atmospheric Research Laboratory (PEARL) in Eureka, Nunavut, Canada. These results show good consistency between the satellite and ground-based measurements and provide guidance on the usage of these MOPITT data at high latitudes.
Maximilian Rißmann, Jia Chen, Gregory Osterman, Xinxu Zhao, Florian Dietrich, Moritz Makowski, Frank Hase, and Matthäus Kiel
Atmos. Meas. Tech., 15, 6605–6623, https://doi.org/10.5194/amt-15-6605-2022, https://doi.org/10.5194/amt-15-6605-2022, 2022
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The Orbiting Carbon Observatory 2 (OCO-2) measures atmospheric concentrations of the most potent greenhouse gas, CO2, globally. By comparing its measurements to a ground-based monitoring network in Munich (MUCCnet), we find that the satellite is able to reliably detect urban CO2 concentrations. Furthermore, spatial CO2 differences captured by OCO-2 and MUCCnet are strongly correlated, which indicates that OCO-2 could be helpful in determining urban CO2 emissions from space.
Dien Wu, Junjie Liu, Paul O. Wennberg, Paul I. Palmer, Robert R. Nelson, Matthäus Kiel, and Annmarie Eldering
Atmos. Chem. Phys., 22, 14547–14570, https://doi.org/10.5194/acp-22-14547-2022, https://doi.org/10.5194/acp-22-14547-2022, 2022
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Prior studies have derived the combustion efficiency for a region/city using observed CO2 and CO. We further zoomed into the urban domain and accounted for factors affecting the calculation of spatially resolved combustion efficiency from two satellites. The intra-city variability in combustion efficiency was linked to heavy industry within Shanghai and LA without relying on emission inventories. Such an approach can be applied when analyzing data from future geostationary satellites.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Luke Gregor, Judith Hauck, Corinne Le Quéré, Ingrid T. Luijkx, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Ramdane Alkama, Almut Arneth, Vivek K. Arora, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Henry C. Bittig, Laurent Bopp, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Wiley Evans, Stefanie Falk, Richard A. Feely, Thomas Gasser, Marion Gehlen, Thanos Gkritzalis, Lucas Gloege, Giacomo Grassi, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Atul K. Jain, Annika Jersild, Koji Kadono, Etsushi Kato, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Peter Landschützer, Nathalie Lefèvre, Keith Lindsay, Junjie Liu, Zhu Liu, Gregg Marland, Nicolas Mayot, Matthew J. McGrath, Nicolas Metzl, Natalie M. Monacci, David R. Munro, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin O'Brien, Tsuneo Ono, Paul I. Palmer, Naiqing Pan, Denis Pierrot, Katie Pocock, Benjamin Poulter, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Carmen Rodriguez, Thais M. Rosan, Jörg Schwinger, Roland Séférian, Jamie D. Shutler, Ingunn Skjelvan, Tobias Steinhoff, Qing Sun, Adrienne J. Sutton, Colm Sweeney, Shintaro Takao, Toste Tanhua, Pieter P. Tans, Xiangjun Tian, Hanqin Tian, Bronte Tilbrook, Hiroyuki Tsujino, Francesco Tubiello, Guido R. van der Werf, Anthony P. Walker, Rik Wanninkhof, Chris Whitehead, Anna Willstrand Wranne, Rebecca Wright, Wenping Yuan, Chao Yue, Xu Yue, Sönke Zaehle, Jiye Zeng, and Bo Zheng
Earth Syst. Sci. Data, 14, 4811–4900, https://doi.org/10.5194/essd-14-4811-2022, https://doi.org/10.5194/essd-14-4811-2022, 2022
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The Global Carbon Budget 2022 describes the datasets and methodology used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, the land ecosystems, and the ocean. These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Beatriz Herrera, Alejandro Bezanilla, Thomas Blumenstock, Enrico Dammers, Frank Hase, Lieven Clarisse, Adolfo Magaldi, Claudia Rivera, Wolfgang Stremme, Kimberly Strong, Camille Viatte, Martin Van Damme, and Michel Grutter
Atmos. Chem. Phys., 22, 14119–14132, https://doi.org/10.5194/acp-22-14119-2022, https://doi.org/10.5194/acp-22-14119-2022, 2022
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This work investigates atmospheric ammonia (NH3), a key trace gas with consequences for the environment and human health, in Mexico City. The results from the ground-based and satellite instruments show the variability and spatial distribution of NH3 over this region. NH3 in Mexico City has been increasing for the past 10 years and most of its sources are urban. This work contributes to a better understanding of NH3 sources and variability in urban and remote areas.
Tai-Long He, Dylan B. A. Jones, Kazuyuki Miyazaki, Kevin W. Bowman, Zhe Jiang, Xiaokang Chen, Rui Li, Yuxiang Zhang, and Kunna Li
Atmos. Chem. Phys., 22, 14059–14074, https://doi.org/10.5194/acp-22-14059-2022, https://doi.org/10.5194/acp-22-14059-2022, 2022
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We use a deep-learning (DL) model to estimate Chinese NOx emissions by combining satellite analysis and in situ measurements. Our results are consistent with conventional analyses of Chinese NOx emissions. Comparison with mobility data shows that the DL model has a better capability to capture changes in NOx. We analyse Chinese NOx emissions during the COVID-19 pandemic lockdown period. Our results illustrate the potential use of DL as a complementary tool for conventional air quality studies.
Haolin Wang, Xiao Lu, Daniel J. Jacob, Owen R. Cooper, Kai-Lan Chang, Ke Li, Meng Gao, Yiming Liu, Bosi Sheng, Kai Wu, Tongwen Wu, Jie Zhang, Bastien Sauvage, Philippe Nédélec, Romain Blot, and Shaojia Fan
Atmos. Chem. Phys., 22, 13753–13782, https://doi.org/10.5194/acp-22-13753-2022, https://doi.org/10.5194/acp-22-13753-2022, 2022
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We report significant global tropospheric ozone increases in 1995–2017 based on extensive aircraft and ozonesonde observations. Using GEOS-Chem (Goddard Earth Observing System chemistry model) multi-decadal global simulations, we find that changes in global anthropogenic emissions, in particular the rapid increases in aircraft emissions, contribute significantly to the increases in tropospheric ozone and resulting radiative impact.
Brendan Byrne, Junjie Liu, Yonghong Yi, Abhishek Chatterjee, Sourish Basu, Rui Cheng, Russell Doughty, Frédéric Chevallier, Kevin W. Bowman, Nicholas C. Parazoo, David Crisp, Xing Li, Jingfeng Xiao, Stephen Sitch, Bertrand Guenet, Feng Deng, Matthew S. Johnson, Sajeev Philip, Patrick C. McGuire, and Charles E. Miller
Biogeosciences, 19, 4779–4799, https://doi.org/10.5194/bg-19-4779-2022, https://doi.org/10.5194/bg-19-4779-2022, 2022
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Plants draw CO2 from the atmosphere during the growing season, while respiration releases CO2 to the atmosphere throughout the year, driving seasonal variations in atmospheric CO2 that can be observed by satellites, such as the Orbiting Carbon Observatory 2 (OCO-2). Using OCO-2 XCO2 data and space-based constraints on plant growth, we show that permafrost-rich northeast Eurasia has a strong seasonal release of CO2 during the autumn, hinting at an unexpectedly large respiration signal from soils.
Helen M. Worden, Gene L. Francis, Susan S. Kulawik, Kevin W. Bowman, Karen Cady-Pereira, Dejian Fu, Jennifer D. Hegarty, Valentin Kantchev, Ming Luo, Vivienne H. Payne, John R. Worden, Róisín Commane, and Kathryn McKain
Atmos. Meas. Tech., 15, 5383–5398, https://doi.org/10.5194/amt-15-5383-2022, https://doi.org/10.5194/amt-15-5383-2022, 2022
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Satellite observations of global carbon monoxide (CO) are essential for understanding atmospheric chemistry and pollution sources. This paper describes a new data product using radiance measurements from the Cross-track Infrared Sounder (CrIS) instrument on the Suomi National Polar-orbiting Partnership (SNPP) satellite that provides vertical profiles of CO from single-field-of-view observations. We show how these satellite CO profiles compare to aircraft observations and evaluate their biases.
Hiroshi Suto, Fumie Kataoka, Robert O. Knuteson, Kei Shiomi, Nobuhiro Kikuchi, and Akihiko Kuze
Atmos. Meas. Tech., 15, 5399–5413, https://doi.org/10.5194/amt-15-5399-2022, https://doi.org/10.5194/amt-15-5399-2022, 2022
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TANSO-FTS-2 onboard GOSAT-2 has operated nominally since February 2019, and the atmospheric radiance spectra it has acquired have been released to the public. This paper describes an updated model for spectral radiance calibration of TIR and its validation. The multi-satellite sensor and multi-angle comparison results suggest that the spectral radiance for TANSO-FTS-2 TIR, version v210210, is superior to that of the previous version in its consistency of multi-satellite sensor data.
Sophie Godin-Beekmann, Niramson Azouz, Viktoria F. Sofieva, Daan Hubert, Irina Petropavlovskikh, Peter Effertz, Gérard Ancellet, Doug A. Degenstein, Daniel Zawada, Lucien Froidevaux, Stacey Frith, Jeannette Wild, Sean Davis, Wolfgang Steinbrecht, Thierry Leblanc, Richard Querel, Kleareti Tourpali, Robert Damadeo, Eliane Maillard Barras, René Stübi, Corinne Vigouroux, Carlo Arosio, Gerald Nedoluha, Ian Boyd, Roeland Van Malderen, Emmanuel Mahieu, Dan Smale, and Ralf Sussmann
Atmos. Chem. Phys., 22, 11657–11673, https://doi.org/10.5194/acp-22-11657-2022, https://doi.org/10.5194/acp-22-11657-2022, 2022
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An updated evaluation up to 2020 of stratospheric ozone profile long-term trends at extrapolar latitudes based on satellite and ground-based records is presented. Ozone increase in the upper stratosphere is confirmed, with significant trends at most latitudes. In this altitude region, a very good agreement is found with trends derived from chemistry–climate model simulations. Observed and modelled trends diverge in the lower stratosphere, but the differences are non-significant.
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.
Asher P. Mouat, Clare Paton-Walsh, Jack B. Simmons, Jhonathan Ramirez-Gamboa, David W. T. Griffith, and Jennifer Kaiser
Atmos. Chem. Phys., 22, 11033–11047, https://doi.org/10.5194/acp-22-11033-2022, https://doi.org/10.5194/acp-22-11033-2022, 2022
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We examine emissions of volatile organic compounds from 2020 wildfires in forested regions of Australia (AU). We find that biomass burning in temperate regions of the US and AU emit similar species in similar proportion, both in natural and lab settings. This suggests studies of wildfires in one region may be used to help improve air quality models in other parts of the world. We observe time series of ozone and nitrogen dioxide. Last, we look at which compounds contribute most to OH reactivity.
Ilann Bourgeois, Jeff Peischl, J. Andrew Neuman, Steven S. Brown, Hannah M. Allen, Pedro Campuzano-Jost, Matthew M. Coggon, Joshua P. DiGangi, Glenn S. Diskin, Jessica B. Gilman, Georgios I. Gkatzelis, Hongyu Guo, Hannah A. Halliday, Thomas F. Hanisco, Christopher D. Holmes, L. Gregory Huey, Jose L. Jimenez, Aaron D. Lamplugh, Young Ro Lee, Jakob Lindaas, Richard H. Moore, Benjamin A. Nault, John B. Nowak, Demetrios Pagonis, Pamela S. Rickly, Michael A. Robinson, Andrew W. Rollins, Vanessa Selimovic, Jason M. St. Clair, David Tanner, Krystal T. Vasquez, Patrick R. Veres, Carsten Warneke, Paul O. Wennberg, Rebecca A. Washenfelder, Elizabeth B. Wiggins, Caroline C. Womack, Lu Xu, Kyle J. Zarzana, and Thomas B. Ryerson
Atmos. Meas. Tech., 15, 4901–4930, https://doi.org/10.5194/amt-15-4901-2022, https://doi.org/10.5194/amt-15-4901-2022, 2022
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Understanding fire emission impacts on the atmosphere is key to effective air quality management and requires accurate measurements. We present a comparison of airborne measurements of key atmospheric species in ambient air and in fire smoke. We show that most instruments performed within instrument uncertainties. In some cases, further work is needed to fully characterize instrument performance. Comparing independent measurements using different techniques is important to assess their accuracy.
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 %).
Joshin Kumar, Theo Paik, Nishit J. Shetty, Patrick Sheridan, Allison C. Aiken, Manvendra K. Dubey, and Rajan K. Chakrabarty
Atmos. Meas. Tech., 15, 4569–4583, https://doi.org/10.5194/amt-15-4569-2022, https://doi.org/10.5194/amt-15-4569-2022, 2022
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Accurate long-term measurement of aerosol light absorption is vital for assessing direct aerosol radiative forcing. Light absorption by aerosols at the US Department of Energy long-term climate monitoring SGP site is measured using the Particle Soot Absorption Photometer (PSAP), which suffers from artifacts and biases difficult to quantify. Machine learning offers a promising path forward to correct for biases in the long-term absorption dataset at the SGP site and similar Class-I areas.
Omaira E. García, Esther Sanromá, Frank Hase, Matthias Schneider, Sergio Fabián León-Luis, Thomas Blumenstock, Eliezer Sepúlveda, Carlos Torres, Natalia Prats, Alberto Redondas, and Virgilio Carreño
Atmos. Meas. Tech., 15, 4547–4567, https://doi.org/10.5194/amt-15-4547-2022, https://doi.org/10.5194/amt-15-4547-2022, 2022
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Retrieving high-precision concentrations of atmospheric trace gases from FTIR (Fourier transform infrared) spectrometry requires a precise knowledge of the instrumental performance. In this context, this paper examines the impact on the ozone (O3) retrievals of several approaches used to characterise the instrumental line shape (ILS) function of ground-based FTIR spectrometers within NDACC (Network for the Detection of Atmospheric Composition Change).
Qiansi Tu, Matthias Schneider, Frank Hase, Farahnaz Khosrawi, Benjamin Ertl, Jaroslaw Necki, Darko Dubravica, Christopher J. Diekmann, Thomas Blumenstock, and Dianjun Fang
Atmos. Chem. Phys., 22, 9747–9765, https://doi.org/10.5194/acp-22-9747-2022, https://doi.org/10.5194/acp-22-9747-2022, 2022
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Three-year satellite observations and high-resolution model forecast of XCH4 are used to derive CH4 emissions in the USCB region, Poland – a region of intense coal mining activities. The wind-assigned anomalies for two opposite wind directions are calculated and the estimated emission rates are very close to the inventories and in reasonable agreement with the previous studies. Our method is quite robust and can serve as a simple method to estimate CH4 or CO2 emissions for other regions.
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. 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.
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.
Yohanna Villalobos, Peter J. Rayner, Jeremy D. Silver, Steven Thomas, Vanessa Haverd, Jürgen Knauer, Zoë M. Loh, Nicholas M. Deutscher, David W. T. Griffith, and David F. Pollard
Atmos. Chem. Phys., 22, 8897–8934, https://doi.org/10.5194/acp-22-8897-2022, https://doi.org/10.5194/acp-22-8897-2022, 2022
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We study the interannual variability in Australian carbon fluxes for 2015–2019 derived from OCO-2 satellite data. Our results suggest that Australia's semi-arid ecosystems are highly responsive to variations in climate drivers such as rainfall and temperature. We found that high rainfall and low temperatures recorded in 2016 led to an anomalous carbon sink over savanna and sparsely vegetated regions, while unprecedented dry and hot weather in 2019 led to anomalous carbon release.
Mei Bai, Zoe Loh, David W. T. Griffith, Debra Turner, Richard Eckard, Robert Edis, Owen T. Denmead, Glenn W. Bryant, Clare Paton-Walsh, Matthew Tonini, Sean M. McGinn, and Deli Chen
Atmos. Meas. Tech., 15, 3593–3610, https://doi.org/10.5194/amt-15-3593-2022, https://doi.org/10.5194/amt-15-3593-2022, 2022
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The open-path laser (OPL) and open-path Fourier transform infrared (OP-FTIR) are used in agricultural research, but their error in emissions research has not been the focus of studies. We conducted trace gas release trials and herd and paddock emission studies to compare their applicability and performance. The OP-FTIR has better stability in stable conditions than OPL. The CH4 OPL accurately detects the low background level of CH4, but the NH3 OPL only detects background values >10 ppbv.
Alexandra Klemme, Tim Rixen, Denise Müller-Dum, Moritz Müller, Justus Notholt, and Thorsten Warneke
Biogeosciences, 19, 2855–2880, https://doi.org/10.5194/bg-19-2855-2022, https://doi.org/10.5194/bg-19-2855-2022, 2022
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Tropical peat-draining rivers contain high amounts of carbon. Surprisingly, measured carbon dioxide (CO2) emissions from those rivers are comparatively moderate. We compiled data from 10 Southeast Asian rivers and found that CO2 production within these rivers is hampered by low water pH, providing a natural threshold for CO2 emissions. Furthermore, we find that enhanced carbonate input, e.g. caused by human activities, suspends this natural threshold and causes increased CO2 emissions.
Vivienne H. Payne, Susan S. Kulawik, Emily V. Fischer, Jared F. Brewer, L. Gregory Huey, Kazuyuki Miyazaki, John R. Worden, Kevin W. Bowman, Eric J. Hintsa, Fred Moore, James W. Elkins, and Julieta Juncosa Calahorrano
Atmos. Meas. Tech., 15, 3497–3511, https://doi.org/10.5194/amt-15-3497-2022, https://doi.org/10.5194/amt-15-3497-2022, 2022
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We compare new satellite measurements of peroxyacetyl nitrate (PAN) with reference aircraft measurements from two different instruments flown on the same platform. While there is a systematic difference between the two aircraft datasets, both show the same large-scale distribution of PAN and the discrepancy between aircraft datasets is small compared to the satellite uncertainties. The satellite measurements show skill in capturing large-scale variations in PAN.
Min Huang, James H. Crawford, Gregory R. Carmichael, Kevin W. Bowman, Sujay V. Kumar, and Colm Sweeney
Atmos. Chem. Phys., 22, 7461–7487, https://doi.org/10.5194/acp-22-7461-2022, https://doi.org/10.5194/acp-22-7461-2022, 2022
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This study demonstrates that ozone dry-deposition modeling can be improved by revising the model's dry-deposition parameterizations to better represent the effects of environmental conditions including the soil moisture fields. Applying satellite soil moisture data assimilation is shown to also have added value. Such advancements in coupled modeling and data assimilation can benefit the assessments of ozone impacts on human and vegetation health.
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.
Colm Sweeney, Abhishek Chatterjee, Sonja Wolter, Kathryn McKain, Robert Bogue, Stephen Conley, Tim Newberger, Lei Hu, Lesley Ott, Benjamin Poulter, Luke Schiferl, Brad Weir, Zhen Zhang, and Charles E. Miller
Atmos. Chem. Phys., 22, 6347–6364, https://doi.org/10.5194/acp-22-6347-2022, https://doi.org/10.5194/acp-22-6347-2022, 2022
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The Arctic Carbon Atmospheric Profiles (Arctic-CAP) project demonstrates the utility of aircraft profiles for independent evaluation of model-derived emissions and uptake of atmospheric CO2, CH4, and CO from land and ocean. Comparison with the Goddard Earth Observing System (GEOS) modeling system suggests that fluxes of CO2 are very consistent with observations, while those of CH4 have some regional and seasonal biases, and that CO comparison is complicated by transport errors.
Andreas Luther, Julian Kostinek, Ralph Kleinschek, Sara Defratyka, Mila Stanisavljević, Andreas Forstmaier, Alexandru Dandocsi, Leon Scheidweiler, Darko Dubravica, Norman Wildmann, Frank Hase, Matthias M. Frey, Jia Chen, Florian Dietrich, Jarosław Nȩcki, Justyna Swolkień, Christoph Knote, Sanam N. Vardag, Anke Roiger, and André Butz
Atmos. Chem. Phys., 22, 5859–5876, https://doi.org/10.5194/acp-22-5859-2022, https://doi.org/10.5194/acp-22-5859-2022, 2022
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Coal mining is an extensive source of anthropogenic methane emissions. In order to reduce and mitigate methane emissions, it is important to know how much and where the methane is emitted. We estimated coal mining methane emissions in Poland based on atmospheric methane measurements and particle dispersion modeling. In general, our emission estimates suggest higher emissions than expected by previous annual emission reports.
Omaira Elena García, Esther Sanromá, Matthias Schneider, Frank Hase, Sergio Fabián León-Luis, Thomas Blumenstock, Eliezer Sepúlveda, Alberto Redondas, Virgilio Carreño, Carlos Torres, and Natalia Prats
Atmos. Meas. Tech., 15, 2557–2577, https://doi.org/10.5194/amt-15-2557-2022, https://doi.org/10.5194/amt-15-2557-2022, 2022
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Accurate observations of atmospheric ozone (O3) are essential to monitor in detail its key role in atmospheric chemistry. In this context, this paper has assessed the effect of using different retrieval strategies on the quality of O3 products from ground-based NDACC FTIR (Fourier transform infrared) spectrometry, with the aim of providing an improved O3 retrieval that could be applied at any NDACC FTIR station.
Pierre Friedlingstein, Matthew W. Jones, Michael O'Sullivan, Robbie M. Andrew, Dorothee C. E. Bakker, Judith Hauck, Corinne Le Quéré, Glen P. Peters, Wouter Peters, Julia Pongratz, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Rob B. Jackson, Simone R. Alin, Peter Anthoni, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Laurent Bopp, Thi Tuyet Trang Chau, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Kim I. Currie, Bertrand Decharme, Laique M. Djeutchouang, Xinyu Dou, Wiley Evans, Richard A. Feely, Liang Feng, Thomas Gasser, Dennis Gilfillan, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Ingrid T. Luijkx, Atul Jain, Steve D. Jones, Etsushi Kato, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Arne Körtzinger, Peter Landschützer, Siv K. Lauvset, Nathalie Lefèvre, Sebastian Lienert, Junjie Liu, Gregg Marland, Patrick C. McGuire, Joe R. Melton, David R. Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Yosuke Niwa, Tsuneo Ono, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Thais M. Rosan, Jörg Schwinger, Clemens Schwingshackl, Roland Séférian, Adrienne J. Sutton, Colm Sweeney, Toste Tanhua, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Francesco Tubiello, Guido R. van der Werf, Nicolas Vuichard, Chisato Wada, Rik Wanninkhof, Andrew J. Watson, David Willis, Andrew J. Wiltshire, Wenping Yuan, Chao Yue, Xu Yue, Sönke Zaehle, and Jiye Zeng
Earth Syst. Sci. Data, 14, 1917–2005, https://doi.org/10.5194/essd-14-1917-2022, https://doi.org/10.5194/essd-14-1917-2022, 2022
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The Global Carbon Budget 2021 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Carlos Alberti, Frank Hase, Matthias Frey, Darko Dubravica, Thomas Blumenstock, Angelika Dehn, Paolo Castracane, Gregor Surawicz, Roland Harig, Bianca C. Baier, Caroline Bès, Jianrong Bi, Hartmut Boesch, André Butz, Zhaonan Cai, Jia Chen, Sean M. Crowell, Nicholas M. Deutscher, Dragos Ene, Jonathan E. Franklin, Omaira García, David Griffith, Bruno Grouiez, Michel Grutter, Abdelhamid Hamdouni, Sander Houweling, Neil Humpage, Nicole Jacobs, Sujong Jeong, Lilian Joly, Nicholas B. Jones, Denis Jouglet, Rigel Kivi, Ralph Kleinschek, Morgan Lopez, Diogo J. Medeiros, Isamu Morino, Nasrin Mostafavipak, Astrid Müller, Hirofumi Ohyama, Paul I. Palmer, Mahesh Pathakoti, David F. Pollard, Uwe Raffalski, Michel Ramonet, Robbie Ramsay, Mahesh Kumar Sha, Kei Shiomi, William Simpson, Wolfgang Stremme, Youwen Sun, Hiroshi Tanimoto, Yao Té, Gizaw Mengistu Tsidu, Voltaire A. Velazco, Felix Vogel, Masataka Watanabe, Chong Wei, Debra Wunch, Marcia Yamasoe, Lu Zhang, and Johannes Orphal
Atmos. Meas. Tech., 15, 2433–2463, https://doi.org/10.5194/amt-15-2433-2022, https://doi.org/10.5194/amt-15-2433-2022, 2022
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Space-borne greenhouse gas missions require ground-based validation networks capable of providing fiducial reference measurements. Here, considerable refinements of the calibration procedures for the COllaborative Carbon Column Observing Network (COCCON) are presented. Laboratory and solar side-by-side procedures for the characterization of the spectrometers have been refined and extended. Revised calibration factors for XCO2, XCO and XCH4 are provided, incorporating 47 new spectrometers.
Edward Malina, Ben Veihelmann, Matthias Buschmann, Nicholas M. Deutscher, Dietrich G. Feist, and Isamu Morino
Atmos. Meas. Tech., 15, 2377–2406, https://doi.org/10.5194/amt-15-2377-2022, https://doi.org/10.5194/amt-15-2377-2022, 2022
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Methane retrievals from remote sensing instruments are fundamentally based on spectroscopic parameters, which indicate spectral-line positions, and their characteristics. These parameters are stored in several databases that vary in their make-up. Here we assess how concentrations of methane isotopologues measured from the same Total Carbon Column Observing Network (TCCON) instruments vary across a range of spectral windows using different spectroscopic databases and comment on the implications.
Carlos Alberti, Qiansi Tu, Frank Hase, Maria V. Makarova, Konstantin Gribanov, Stefani C. Foka, Vyacheslav Zakharov, Thomas Blumenstock, Michael Buchwitz, Christopher Diekmann, Benjamin Ertl, Matthias M. Frey, Hamud Kh. Imhasin, Dmitry V. Ionov, Farahnaz Khosrawi, Sergey I. Osipov, Maximilian Reuter, Matthias Schneider, and Thorsten Warneke
Atmos. Meas. Tech., 15, 2199–2229, https://doi.org/10.5194/amt-15-2199-2022, https://doi.org/10.5194/amt-15-2199-2022, 2022
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Satellite and ground-based observations at high latitudes are much sparser than at low or mid latitudes, which makes direct coincident comparisons between remote-sensing observations more difficult. Therefore, a method of scaling continuous CAMS model data to the ground-based observations is developed and used for creating virtual COCCON observations. These adjusted CAMS data are then used for satellite inter-comparison, showing good agreement in both Peterhof and Yekaterinburg cities.
Glenn M. Wolfe, Thomas F. Hanisco, Heather L. Arkinson, Donald R. Blake, Armin Wisthaler, Tomas Mikoviny, Thomas B. Ryerson, Ilana Pollack, Jeff Peischl, Paul O. Wennberg, John D. Crounse, Jason M. St. Clair, Alex Teng, L. Gregory Huey, Xiaoxi Liu, Alan Fried, Petter Weibring, Dirk Richter, James Walega, Samuel R. Hall, Kirk Ullmann, Jose L. Jimenez, Pedro Campuzano-Jost, T. Paul Bui, Glenn Diskin, James R. Podolske, Glen Sachse, and Ronald C. Cohen
Atmos. Chem. Phys., 22, 4253–4275, https://doi.org/10.5194/acp-22-4253-2022, https://doi.org/10.5194/acp-22-4253-2022, 2022
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Smoke plumes are chemically complex. This work combines airborne observations of smoke plume composition with a photochemical model to probe the production of ozone and the fate of reactive gases in the outflow of a large wildfire. Model–measurement comparisons illustrate how uncertain emissions and chemical processes propagate into simulated chemical evolution. Results provide insight into how this system responds to perturbations, which can help guide future observation and modeling efforts.
Johannes Gensheimer, Alexander J. Turner, Philipp Köhler, Christian Frankenberg, and Jia Chen
Biogeosciences, 19, 1777–1793, https://doi.org/10.5194/bg-19-1777-2022, https://doi.org/10.5194/bg-19-1777-2022, 2022
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We develop a convolutional neural network, named SIFnet, that increases the spatial resolution of SIF from TROPOMI by a factor of 10 to a spatial resolution of 0.005°. SIFnet utilizes coarse SIF observations, together with a broad range of high-resolution auxiliary data. The insights gained from interpretable machine learning techniques allow us to make quantitative claims about the relationships between SIF and other common parameters related to photosynthesis.
Helen L. Fitzmaurice, Alexander J. Turner, Jinsol Kim, Katherine Chan, Erin R. Delaria, Catherine Newman, Paul Wooldridge, and Ronald C. Cohen
Atmos. Chem. Phys., 22, 3891–3900, https://doi.org/10.5194/acp-22-3891-2022, https://doi.org/10.5194/acp-22-3891-2022, 2022
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On-road emissions are thought to vary widely from existing predictions, as the effects of the age of the vehicle fleet, the performance of emission control systems, and variations in speed are difficult to assess under ambient driving conditions. We present an observational approach to characterize on-road emissions and show that the method is consistent with other approaches to within ~ 3 %.
Vijay Natraj, Ming Luo, Jean-Francois Blavier, Vivienne H. Payne, Derek J. Posselt, Stanley P. Sander, Zhao-Cheng Zeng, Jessica L. Neu, Denis Tremblay, Longtao Wu, Jacola A. Roman, Yen-Hung Wu, and Leonard I. Dorsky
Atmos. Meas. Tech., 15, 1251–1267, https://doi.org/10.5194/amt-15-1251-2022, https://doi.org/10.5194/amt-15-1251-2022, 2022
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High-fidelity monitoring and forecast of air quality and the hydrological cycle require understanding the vertical distribution of temperature, humidity, and trace gases at high spatiotemporal resolution. We describe a new instrument concept, called the JPL GEO-IR Sounder, that would provide this information for the first time from a single instrument platform. Simulations demonstrate the benefits of combining measurements from multiple wavelengths for this purpose from geostationary orbit.
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.
Thomas von Clarmann, Steven Compernolle, and Frank Hase
Atmos. Meas. Tech., 15, 1145–1157, https://doi.org/10.5194/amt-15-1145-2022, https://doi.org/10.5194/amt-15-1145-2022, 2022
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Contrary to the claims put forward in
Evaluation of measurement data – Guide to the expression of uncertainty in measurementissued by the JCGM, the error concept and the uncertainty concept are the same. Arguments in favor of the contrary were found not to be compelling. Neither was any evidence presented that
errorsand
uncertaintiesdefine a different relation between the measured and true values, nor is a Bayesian concept beyond the mere subjective probability referred to.
Drew C. Pendergrass, Shixian Zhai, Jhoon Kim, Ja-Ho Koo, Seoyoung Lee, Minah Bae, Soontae Kim, Hong Liao, and Daniel J. Jacob
Atmos. Meas. Tech., 15, 1075–1091, https://doi.org/10.5194/amt-15-1075-2022, https://doi.org/10.5194/amt-15-1075-2022, 2022
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This paper uses a machine learning algorithm to infer high-resolution maps of particulate air quality in eastern China, Japan, and the Korean peninsula, using data from a geostationary satellite along with meteorology. We then perform an extensive evaluation of this inferred air quality and use it to diagnose trends in the region. We hope this paper and the associated data will be valuable to other scientists interested in epidemiology, air quality, remote sensing, and machine learning.
Lei Hu, Stephen A. Montzka, Fred Moore, Eric Hintsa, Geoff Dutton, M. Carolina Siso, Kirk Thoning, Robert W. Portmann, Kathryn McKain, Colm Sweeney, Isaac Vimont, David Nance, Bradley Hall, and Steven Wofsy
Atmos. Chem. Phys., 22, 2891–2907, https://doi.org/10.5194/acp-22-2891-2022, https://doi.org/10.5194/acp-22-2891-2022, 2022
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The unexpected increase in CFC-11 emissions between 2012 and 2017 resulted in concerns about delaying the stratospheric ozone recovery. Although the subsequent decline of CFC-11 emissions indicated a mitigation in part to this problem, the regions fully responsible for these large emission changes were unclear. Here, our new estimate, based on atmospheric measurements from two global campaigns and from NOAA, suggests Asia primarily contributed to the global CFC-11 emission rise during 2012–2017.
Lu Shen, Daniel J. Jacob, Mauricio Santillana, Kelvin Bates, Jiawei Zhuang, and Wei Chen
Geosci. Model Dev., 15, 1677–1687, https://doi.org/10.5194/gmd-15-1677-2022, https://doi.org/10.5194/gmd-15-1677-2022, 2022
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The high computational cost of chemical integration is a long-standing limitation in global atmospheric chemistry models. Here we present an adaptive and efficient algorithm that can reduce the computational time of atmospheric chemistry by 50 % and maintain the error below 2 % for important species, inspired by machine learning clustering techniques and traditional asymptotic analysis ideas.
Matthias Schneider, Benjamin Ertl, Christopher J. Diekmann, Farahnaz Khosrawi, Andreas Weber, Frank Hase, Michael Höpfner, Omaira E. García, Eliezer Sepúlveda, and Douglas Kinnison
Earth Syst. Sci. Data, 14, 709–742, https://doi.org/10.5194/essd-14-709-2022, https://doi.org/10.5194/essd-14-709-2022, 2022
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We present atmospheric H2O, HDO / H2O ratio, N2O, CH4, and HNO3 data generated by the MUSICA IASI processor using thermal nadir spectra measured by the IASI satellite instrument. The data have global daily coverage and are available for the period between October 2014 and June 2021. Multiple possibilities of data reuse are offered by providing each individual data product together with information about retrieval settings and the products' uncertainty and vertical representativeness.
Thomas E. Taylor, Christopher W. O'Dell, David Crisp, Akhiko Kuze, Hannakaisa Lindqvist, Paul O. Wennberg, Abhishek Chatterjee, Michael Gunson, Annmarie Eldering, Brendan Fisher, Matthäus Kiel, Robert R. Nelson, Aronne Merrelli, Greg Osterman, Frédéric Chevallier, Paul I. Palmer, Liang Feng, Nicholas M. Deutscher, Manvendra K. Dubey, Dietrich G. Feist, Omaira E. García, David W. T. Griffith, Frank Hase, Laura T. Iraci, Rigel Kivi, Cheng Liu, Martine De Mazière, Isamu Morino, Justus Notholt, Young-Suk Oh, Hirofumi Ohyama, David F. Pollard, Markus Rettinger, Matthias Schneider, Coleen M. Roehl, Mahesh Kumar Sha, Kei Shiomi, Kimberly Strong, Ralf Sussmann, Yao Té, Voltaire A. Velazco, Mihalis Vrekoussis, Thorsten Warneke, and Debra Wunch
Earth Syst. Sci. Data, 14, 325–360, https://doi.org/10.5194/essd-14-325-2022, https://doi.org/10.5194/essd-14-325-2022, 2022
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We provide an analysis of an 11-year record of atmospheric carbon dioxide (CO2) concentrations derived using an optimal estimation retrieval algorithm on measurements made by the GOSAT satellite. The new product (version 9) shows improvement over the previous version (v7.3) as evaluated against independent estimates of CO2 from ground-based sensors and atmospheric inversion systems. We also compare the new GOSAT CO2 values to collocated estimates from NASA's Orbiting Carbon Observatory-2.
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.
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.
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.
Alexander J. Turner, Philipp Köhler, Troy S. Magney, Christian Frankenberg, Inez Fung, and Ronald C. Cohen
Biogeosciences, 18, 6579–6588, https://doi.org/10.5194/bg-18-6579-2021, https://doi.org/10.5194/bg-18-6579-2021, 2021
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This work builds a high-resolution estimate (500 m) of gross primary productivity (GPP) over the US using satellite measurements of solar-induced chlorophyll fluorescence (SIF) from the TROPOspheric Monitoring Instrument (TROPOMI) between 2018 and 2020. We identify ecosystem-specific scaling factors for estimating gross primary productivity (GPP) from TROPOMI SIF. Extreme precipitation events drive four regional GPP anomalies that account for 28 % of year-to-year GPP differences across the US.
Kelvin H. Bates, Daniel J. Jacob, Ke Li, Peter D. Ivatt, Mat J. Evans, Yingying Yan, and Jintai Lin
Atmos. Chem. Phys., 21, 18351–18374, https://doi.org/10.5194/acp-21-18351-2021, https://doi.org/10.5194/acp-21-18351-2021, 2021
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Simple aromatic compounds (benzene, toluene, xylene) have complex gas-phase chemistry that is inconsistently represented in atmospheric models. We compile recent experimental and theoretical insights to develop a new mechanism for gas-phase aromatic oxidation that is sufficiently compact for use in multiscale models. We compare our new mechanism to chamber experiments and other mechanisms, and implement it in a global model to quantify the impacts of aromatic oxidation on tropospheric chemistry.
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.
Joseph Mendonca, Ray Nassar, Christopher W. O'Dell, Rigel Kivi, Isamu Morino, Justus Notholt, Christof Petri, Kimberly Strong, and Debra Wunch
Atmos. Meas. Tech., 14, 7511–7524, https://doi.org/10.5194/amt-14-7511-2021, https://doi.org/10.5194/amt-14-7511-2021, 2021
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Machine learning has become an important tool for pattern recognition in many applications. In this study, we used a neural network to improve the data quality of OCO-2 measurements made at northern high latitudes. The neural network was trained and used as a binary classifier to filter out bad OCO-2 measurements in order to increase the accuracy and precision of OCO-2 XCO2 measurements in the Boreal and Arctic regions.
Yohanna Villalobos, Peter J. Rayner, Jeremy D. Silver, Steven Thomas, Vanessa Haverd, Jürgen Knauer, Zoë M. Loh, Nicholas M. Deutscher, David W. T. Griffith, and David F. Pollard
Atmos. Chem. Phys., 21, 17453–17494, https://doi.org/10.5194/acp-21-17453-2021, https://doi.org/10.5194/acp-21-17453-2021, 2021
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Semi-arid ecosystems such as those in Australia are evolving and might play an essential role in the future of climate change. We use carbon dioxide concentrations derived from the OCO-2 satellite instrument and a regional transport model to understand if Australia was a carbon sink or source of CO2 in 2015. Our research's main findings suggest that Australia acted as a carbon sink of about −0.41 ± 0.08 petagrams of carbon in 2015, driven primarily by savanna and sparsely vegetated ecosystems.
Shixian Zhai, Daniel J. Jacob, Jared F. Brewer, Ke Li, Jonathan M. Moch, Jhoon Kim, Seoyoung Lee, Hyunkwang Lim, Hyun Chul Lee, Su Keun Kuk, Rokjin J. Park, Jaein I. Jeong, Xuan Wang, Pengfei Liu, Gan Luo, Fangqun Yu, Jun Meng, Randall V. Martin, Katherine R. Travis, Johnathan W. Hair, Bruce E. Anderson, Jack E. Dibb, Jose L. Jimenez, Pedro Campuzano-Jost, Benjamin A. Nault, Jung-Hun Woo, Younha Kim, Qiang Zhang, and Hong Liao
Atmos. Chem. Phys., 21, 16775–16791, https://doi.org/10.5194/acp-21-16775-2021, https://doi.org/10.5194/acp-21-16775-2021, 2021
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Geostationary satellite aerosol optical depth (AOD) has tremendous potential for monitoring surface fine particulate matter (PM2.5). Our study explored the physical relationship between AOD and PM2.5 by integrating data from surface networks, aircraft, and satellites with the GEOS-Chem chemical transport model. We quantitatively showed that accurate simulation of aerosol size distributions, boundary layer depths, relative humidity, coarse particles, and diurnal variations in PM2.5 are essential.
Nicole Jacobs, William R. Simpson, Kelly A. Graham, Christopher Holmes, Frank Hase, Thomas Blumenstock, Qiansi Tu, Matthias Frey, Manvendra K. Dubey, Harrison A. Parker, Debra Wunch, Rigel Kivi, Pauli Heikkinen, Justus Notholt, Christof Petri, and Thorsten Warneke
Atmos. Chem. Phys., 21, 16661–16687, https://doi.org/10.5194/acp-21-16661-2021, https://doi.org/10.5194/acp-21-16661-2021, 2021
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Spatial patterns of carbon dioxide seasonal cycle amplitude and summer drawdown timing derived from the OCO-2 satellite over northern high latitudes agree well with corresponding estimates from two models. The Asian boreal forest is anomalous with the largest amplitude and earliest seasonal drawdown. Modeled land contact tracers suggest that accumulated CO2 exchanges during atmospheric transport play a major role in shaping carbon dioxide seasonality in northern high-latitude regions.
Christopher J. Diekmann, Matthias Schneider, Benjamin Ertl, Frank Hase, Omaira García, Farahnaz Khosrawi, Eliezer Sepúlveda, Peter Knippertz, and Peter Braesicke
Earth Syst. Sci. Data, 13, 5273–5292, https://doi.org/10.5194/essd-13-5273-2021, https://doi.org/10.5194/essd-13-5273-2021, 2021
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The joint analysis of different stable water isotopes in water vapour is a powerful tool for investigating atmospheric moisture pathways. This paper presents a novel global and multi-annual dataset of H2O and HDO in mid-tropospheric water vapour by using data from the satellite sensor Metop/IASI. Due to its unique combination of coverage and resolution in space and time, this dataset is highly promising for studying the hydrological cycle and its representation in weather and climate models.
Mark F. Lunt, Alistair J. Manning, Grant Allen, Tim Arnold, Stéphane J.-B. Bauguitte, Hartmut Boesch, Anita L. Ganesan, Aoife Grant, Carole Helfter, Eiko Nemitz, Simon J. O'Doherty, Paul I. Palmer, Joseph R. Pitt, Chris Rennick, Daniel Say, Kieran M. Stanley, Ann R. Stavert, Dickon Young, and Matt Rigby
Atmos. Chem. Phys., 21, 16257–16276, https://doi.org/10.5194/acp-21-16257-2021, https://doi.org/10.5194/acp-21-16257-2021, 2021
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We present an evaluation of the UK's methane emissions between 2013 and 2020 using a network of tall tower measurement sites. We find emissions that are consistent in both magnitude and trend with the UK's reported emissions, with a declining trend driven by a decrease in emissions from England. The impact of various components of the modelling set-up on these findings are explored through a number of sensitivity studies.
Dandan Wei, Hariprasad D. Alwe, Dylan B. Millet, Brandon Bottorff, Michelle Lew, Philip S. Stevens, Joshua D. Shutter, Joshua L. Cox, Frank N. Keutsch, Qianwen Shi, Sarah C. Kavassalis, Jennifer G. Murphy, Krystal T. Vasquez, Hannah M. Allen, Eric Praske, John D. Crounse, Paul O. Wennberg, Paul B. Shepson, Alexander A. T. Bui, Henry W. Wallace, Robert J. Griffin, Nathaniel W. May, Megan Connor, Jonathan H. Slade, Kerri A. Pratt, Ezra C. Wood, Mathew Rollings, Benjamin L. Deming, Daniel C. Anderson, and Allison L. Steiner
Geosci. Model Dev., 14, 6309–6329, https://doi.org/10.5194/gmd-14-6309-2021, https://doi.org/10.5194/gmd-14-6309-2021, 2021
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Over the past decade, understanding of isoprene oxidation has improved, and proper representation of isoprene oxidation and isoprene-derived SOA (iSOA) formation in canopy–chemistry models is now recognized to be important for an accurate understanding of forest–atmosphere exchange. The updated FORCAsT version 2.0 improves the estimation of some isoprene oxidation products and is one of the few canopy models currently capable of simulating SOA formation from monoterpenes and isoprene.
Gianluca Di Natale, Marco Barucci, Claudio Belotti, Giovanni Bianchini, Francesco D'Amato, Samuele Del Bianco, Marco Gai, Alessio Montori, Ralf Sussmann, Silvia Viciani, Hannes Vogelmann, and Luca Palchetti
Atmos. Meas. Tech., 14, 6749–6758, https://doi.org/10.5194/amt-14-6749-2021, https://doi.org/10.5194/amt-14-6749-2021, 2021
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The importance of cirrus and mixed-phase clouds in the Earth radiation budget has been proven by many studies. In this paper the properties that characterize these clouds are retrieved from lidar and far-infrared spectral measurements performed in winter 2018/19 on the Zugspitze (Germany). The synergy of lidar and spectrometer measurements allowed us to assess the exponent k of the power-law relationship between the backscattering and the extinction coefficients.
Omaira E. García, Matthias Schneider, Eliezer Sepúlveda, Frank Hase, Thomas Blumenstock, Emilio Cuevas, Ramón Ramos, Jochen Gross, Sabine Barthlott, Amelie N. Röhling, Esther Sanromá, Yenny González, Ángel J. Gómez-Peláez, Mónica Navarro-Comas, Olga Puentedura, Margarita Yela, Alberto Redondas, Virgilio Carreño, Sergio F. León-Luis, Enrique Reyes, Rosa D. García, Pedro P. Rivas, Pedro M. Romero-Campos, Carlos Torres, Natalia Prats, Miguel Hernández, and César López
Atmos. Chem. Phys., 21, 15519–15554, https://doi.org/10.5194/acp-21-15519-2021, https://doi.org/10.5194/acp-21-15519-2021, 2021
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This paper analyses the potential of ground-based Fourier transform infrared (FTIR) solar observations to monitor atmospheric gaseous composition and investigate multiple climate processes. To this end, this work reviews the FTIR programme of one of most relevant ground-based FTIR stations at a global scale, the subtropical Izaña Observatory (IZO, Spain), going over its history during its first 20 years of operation (1999–2018) and exploring its great value for long-term climate research.
Liam Bindle, Randall V. Martin, Matthew J. Cooper, Elizabeth W. Lundgren, Sebastian D. Eastham, Benjamin M. Auer, Thomas L. Clune, Hongjian Weng, Jintai Lin, Lee T. Murray, Jun Meng, Christoph A. Keller, William M. Putman, Steven Pawson, and Daniel J. Jacob
Geosci. Model Dev., 14, 5977–5997, https://doi.org/10.5194/gmd-14-5977-2021, https://doi.org/10.5194/gmd-14-5977-2021, 2021
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Atmospheric chemistry models like GEOS-Chem are versatile tools widely used in air pollution and climate studies. The simulations used in such studies can be very computationally demanding, and thus it is useful if the model can simulate a specific geographic region at a higher resolution than the rest of the globe. Here, we implement, test, and demonstrate a new variable-resolution capability in GEOS-Chem that is suitable for simulations conducted on supercomputers.
Mahesh Kumar Sha, Bavo Langerock, Jean-François L. Blavier, Thomas Blumenstock, Tobias Borsdorff, Matthias Buschmann, Angelika Dehn, Martine De Mazière, Nicholas M. Deutscher, Dietrich G. Feist, Omaira E. García, David W. T. Griffith, Michel Grutter, James W. Hannigan, Frank Hase, Pauli Heikkinen, Christian Hermans, Laura T. Iraci, Pascal Jeseck, Nicholas Jones, Rigel Kivi, Nicolas Kumps, Jochen Landgraf, Alba Lorente, Emmanuel Mahieu, Maria V. Makarova, Johan Mellqvist, Jean-Marc Metzger, Isamu Morino, Tomoo Nagahama, Justus Notholt, Hirofumi Ohyama, Ivan Ortega, Mathias Palm, Christof Petri, David F. Pollard, Markus Rettinger, John Robinson, Sébastien Roche, Coleen M. Roehl, Amelie N. Röhling, Constantina Rousogenous, Matthias Schneider, Kei Shiomi, Dan Smale, Wolfgang Stremme, Kimberly Strong, Ralf Sussmann, Yao Té, Osamu Uchino, Voltaire A. Velazco, Corinne Vigouroux, Mihalis Vrekoussis, Pucai Wang, Thorsten Warneke, Tyler Wizenberg, Debra Wunch, Shoma Yamanouchi, Yang Yang, and Minqiang Zhou
Atmos. Meas. Tech., 14, 6249–6304, https://doi.org/10.5194/amt-14-6249-2021, https://doi.org/10.5194/amt-14-6249-2021, 2021
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This paper presents, for the first time, Sentinel-5 Precursor methane and carbon monoxide validation results covering a period from November 2017 to September 2020. For this study, we used global TCCON and NDACC-IRWG network data covering a wide range of atmospheric and surface conditions across different terrains. We also show the influence of a priori alignment, smoothing uncertainties and the sensitivity of the validation results towards the application of advanced co-location criteria.
Bharat Rastogi, John B. Miller, Micheal Trudeau, Arlyn E. Andrews, Lei Hu, Marikate Mountain, Thomas Nehrkorn, Bianca Baier, Kathryn McKain, John Mund, Kaiyu Guan, and Caroline B. Alden
Atmos. Chem. Phys., 21, 14385–14401, https://doi.org/10.5194/acp-21-14385-2021, https://doi.org/10.5194/acp-21-14385-2021, 2021
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Predicting Earth's climate is difficult, partly due to uncertainty in forecasting how much CO2 can be removed by oceans and plants, because we cannot measure these exchanges directly on large scales. Satellites such as NASA's OCO-2 can provide part of the needed information, but data need to be highly precise and accurate. We evaluate these data and find small biases in certain months that are similar to the signals of interest. We argue that continued improvement of these data is necessary.
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.
Xuan Wang, Daniel J. Jacob, William Downs, Shuting Zhai, Lei Zhu, Viral Shah, Christopher D. Holmes, Tomás Sherwen, Becky Alexander, Mathew J. Evans, Sebastian D. Eastham, J. Andrew Neuman, Patrick R. Veres, Theodore K. Koenig, Rainer Volkamer, L. Gregory Huey, Thomas J. Bannan, Carl J. Percival, Ben H. Lee, and Joel A. Thornton
Atmos. Chem. Phys., 21, 13973–13996, https://doi.org/10.5194/acp-21-13973-2021, https://doi.org/10.5194/acp-21-13973-2021, 2021
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Halogen radicals have a broad range of implications for tropospheric chemistry, air quality, and climate. We present a new mechanistic description and comprehensive simulation of tropospheric halogens in a global 3-D model and compare the model results with surface and aircraft measurements. We find that halogen chemistry decreases the global tropospheric burden of ozone by 11 %, NOx by 6 %, and OH by 4 %.
Taylor S. Jones, Jonathan E. Franklin, Jia Chen, Florian Dietrich, Kristian D. Hajny, Johannes C. Paetzold, Adrian Wenzel, Conor Gately, Elaine Gottlieb, Harrison Parker, Manvendra Dubey, Frank Hase, Paul B. Shepson, Levi H. Mielke, and Steven C. Wofsy
Atmos. Chem. Phys., 21, 13131–13147, https://doi.org/10.5194/acp-21-13131-2021, https://doi.org/10.5194/acp-21-13131-2021, 2021
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Methane emissions from leaks in natural gas pipes are often a large source in urban areas, but they are difficult to measure on a city-wide scale. Here we use an array of innovative methane sensors distributed around the city of Indianapolis and a new method of combining their data with an atmospheric model to accurately determine the magnitude of these emissions, which are about 70 % larger than predicted. This method can serve as a framework for cities trying to account for their emissions.
Haipeng Lin, Daniel J. Jacob, Elizabeth W. Lundgren, Melissa P. Sulprizio, Christoph A. Keller, Thibaud M. Fritz, Sebastian D. Eastham, Louisa K. Emmons, Patrick C. Campbell, Barry Baker, Rick D. Saylor, and Raffaele Montuoro
Geosci. Model Dev., 14, 5487–5506, https://doi.org/10.5194/gmd-14-5487-2021, https://doi.org/10.5194/gmd-14-5487-2021, 2021
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Emissions are a central component of atmospheric chemistry models. The Harmonized Emissions Component (HEMCO) is a software component for computing emissions from a user-selected ensemble of emission inventories and algorithms. It allows users to select, add, and scale emissions from different sources through a configuration file with no change to the model source code. We demonstrate the implementation of HEMCO in several models, all sharing the same HEMCO core code and database library.
Luca Palchetti, Marco Barucci, Claudio Belotti, Giovanni Bianchini, Bertrand Cluzet, Francesco D'Amato, Samuele Del Bianco, Gianluca Di Natale, Marco Gai, Dina Khordakova, Alessio Montori, Hilke Oetjen, Markus Rettinger, Christian Rolf, Dirk Schuettemeyer, Ralf Sussmann, Silvia Viciani, Hannes Vogelmann, and Frank Gunther Wienhold
Earth Syst. Sci. Data, 13, 4303–4312, https://doi.org/10.5194/essd-13-4303-2021, https://doi.org/10.5194/essd-13-4303-2021, 2021
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The FIRMOS far-infrared (IR) prototype, developed for the preparation of the ESA FORUM mission, was deployed for the first time at Mt. Zugspitze at 3000 m altitude to measure the far-IR spectrum of atmospheric emissions. The measurements, including co-located radiometers, lidars, radio soundings, weather, and surface properties, provide a unique dataset to study radiative properties of water vapour, cirrus clouds, and snow emissivity over the IR emissions, including the under-explored far-IR.
Matthias M. Frey, Frank Hase, Thomas Blumenstock, Darko Dubravica, Jochen Groß, Frank Göttsche, Martin Handjaba, Petrus Amadhila, Roland Mushi, Isamu Morino, Kei Shiomi, Mahesh Kumar Sha, Martine de Mazière, and David F. Pollard
Atmos. Meas. Tech., 14, 5887–5911, https://doi.org/10.5194/amt-14-5887-2021, https://doi.org/10.5194/amt-14-5887-2021, 2021
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In this study, we present measurements of carbon dioxide, methane and carbon monoxide from a recently established site in Gobabeb, Namibia. Gobabeb is the first site observing these gases on the African mainland and improves the global coverage of measurement sites. Gobabeb is a hyperarid desert site, offering unique characteristics. Measurements started 2015 as part of the COllaborative Carbon Column Observing Network. We compare our results with other datasets and find a good agreement.
Yi Yin, Frederic Chevallier, Philippe Ciais, Philippe Bousquet, Marielle Saunois, Bo Zheng, John Worden, A. Anthony Bloom, Robert J. Parker, Daniel J. Jacob, Edward J. Dlugokencky, and Christian Frankenberg
Atmos. Chem. Phys., 21, 12631–12647, https://doi.org/10.5194/acp-21-12631-2021, https://doi.org/10.5194/acp-21-12631-2021, 2021
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The growth of methane, the second-most important anthropogenic greenhouse gas after carbon dioxide, has been accelerating in recent years. Using an ensemble of multi-tracer atmospheric inversions constrained by surface or satellite observations, we show that global methane emissions increased by nearly 1 % per year from 2010–2017, with leading contributions from the tropics and East Asia.
Rebecca D. Kutzner, Juan Cuesta, Pascale Chelin, Jean-Eudes Petit, Mokhtar Ray, Xavier Landsheere, Benoît Tournadre, Jean-Charles Dupont, Amandine Rosso, Frank Hase, Johannes Orphal, and Matthias Beekmann
Atmos. Chem. Phys., 21, 12091–12111, https://doi.org/10.5194/acp-21-12091-2021, https://doi.org/10.5194/acp-21-12091-2021, 2021
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Our work investigates the diurnal evolution of atmospheric ammonia concentrations during a major pollution event. It analyses it in regard of both chemical (gas–particle conversion) and physical (vertical mixing, meteorology) processes in the atmosphere. These mechanisms are key for understanding the evolution of the physicochemical state of the atmosphere; therefore, it clearly fits into the scope of Atmospheric Chemistry and Physics.
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.
Farahnaz Khosrawi, Kinya Toride, Kei Yoshimura, Christopher J. Diekmann, Benjamin Ertl, Frank Hase, and Matthias Schneider
Weather Clim. Dynam. Discuss., https://doi.org/10.5194/wcd-2021-49, https://doi.org/10.5194/wcd-2021-49, 2021
Revised manuscript not accepted
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We assess with an Observation System Simulation Experiment the potential of mid-tropospheric water isotopologue data for constraining uncertainties in meteorological analysis fields in the tropics. Our assimilation experiments indicate that isotopologue observations have the potential to reduce the uncertainties of diabatic heating rates and meteorological variables in the tropics and in consequence offer potential for improving meteorological analysis in the tropical regions.
Xiaoling Liu, August L. Weinbren, He Chang, Jovan M. Tadić, Marikate E. Mountain, Michael E. Trudeau, Arlyn E. Andrews, Zichong Chen, and Scot M. Miller
Geosci. Model Dev., 14, 4683–4696, https://doi.org/10.5194/gmd-14-4683-2021, https://doi.org/10.5194/gmd-14-4683-2021, 2021
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Observations of greenhouse gases have become far more numerous in recent years due to new satellite observations. The sheer size of these datasets makes it challenging to incorporate these data into statistical models and use these data to estimate greenhouse gas sources and sinks. In this paper, we develop an approach to reduce the size of these datasets while preserving the most information possible. We subsequently test this approach using satellite observations of carbon dioxide.
Yenny Gonzalez, Róisín Commane, Ethan Manninen, Bruce C. Daube, Luke D. Schiferl, J. Barry McManus, Kathryn McKain, Eric J. Hintsa, James W. Elkins, Stephen A. Montzka, Colm Sweeney, Fred Moore, Jose L. Jimenez, Pedro Campuzano Jost, Thomas B. Ryerson, Ilann Bourgeois, Jeff Peischl, Chelsea R. Thompson, Eric Ray, Paul O. Wennberg, John Crounse, Michelle Kim, Hannah M. Allen, Paul A. Newman, Britton B. Stephens, Eric C. Apel, Rebecca S. Hornbrook, Benjamin A. Nault, Eric Morgan, and Steven C. Wofsy
Atmos. Chem. Phys., 21, 11113–11132, https://doi.org/10.5194/acp-21-11113-2021, https://doi.org/10.5194/acp-21-11113-2021, 2021
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Vertical profiles of N2O and a variety of chemical species and aerosols were collected nearly from pole to pole over the oceans during the NASA Atmospheric Tomography mission. We observed that tropospheric N2O variability is strongly driven by the influence of stratospheric air depleted in N2O, especially at middle and high latitudes. We also traced the origins of biomass burning and industrial emissions and investigated their impact on the variability of tropospheric N2O.
Min Huang, James H. Crawford, Joshua P. DiGangi, Gregory R. Carmichael, Kevin W. Bowman, Sujay V. Kumar, and Xiwu Zhan
Atmos. Chem. Phys., 21, 11013–11040, https://doi.org/10.5194/acp-21-11013-2021, https://doi.org/10.5194/acp-21-11013-2021, 2021
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This study evaluates the impact of satellite soil moisture data assimilation on modeled weather and ozone fields at various altitudes above the southeastern US during the summer. It emphasizes the importance of soil moisture in the understanding of surface ozone pollution and upper tropospheric chemistry, as well as air pollutants’ source–receptor relationships between the US and its downwind areas.
Dmitry V. Ionov, Maria V. Makarova, Frank Hase, Stefani C. Foka, Vladimir S. Kostsov, Carlos Alberti, Thomas Blumenstock, Thorsten Warneke, and Yana A. Virolainen
Atmos. Chem. Phys., 21, 10939–10963, https://doi.org/10.5194/acp-21-10939-2021, https://doi.org/10.5194/acp-21-10939-2021, 2021
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Megacities are a significant source of emissions of various substances in the atmosphere, including carbon dioxide, which is the most important anthropogenic greenhouse gas. In 2019–2020, the Emission Monitoring Mobile Experiment was carried out in St Petersburg, which is the second-largest industrial city in Russia. The results of this experiment, coupled with numerical modelling, helped to estimate the amount of CO2 emitted by the city. This value was twice as high as predicted.
Beata Bukosa, Jenny Fisher, Nicholas Deutscher, and Dylan Jones
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2021-173, https://doi.org/10.5194/gmd-2021-173, 2021
Revised manuscript not accepted
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Human activities led to rising levels of greenhouse gases (carbon dioxide (CO2), methane (CH4), carbon monoxide (CO)) in the atmosphere, threatening our future. We use models and measurements to predict and understand the climatological impact of these gases. Here, we describe a new simulation in the GEOS-Chem model that uses a more accurate method to simulate CO2, CH4 and CO, through their chemical dependence. Relative to the original simulations our results agree better with measurements.
Chris Wilson, Martyn P. Chipperfield, Manuel Gloor, Robert J. Parker, Hartmut Boesch, Joey McNorton, Luciana V. Gatti, John B. Miller, Luana S. Basso, and Sarah A. Monks
Atmos. Chem. Phys., 21, 10643–10669, https://doi.org/10.5194/acp-21-10643-2021, https://doi.org/10.5194/acp-21-10643-2021, 2021
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Methane (CH4) is an important greenhouse gas emitted from wetlands like those found in the basin of the Amazon River. Using an atmospheric model and observations from GOSAT, we quantified CH4 emissions from Amazonia during the previous decade. We found that the largest emissions came from a region in the eastern basin and that emissions there were rising faster than in other areas of South America. This finding was supported by CH4 observations made on aircraft within the basin.
Ilya Stanevich, Dylan B. A. Jones, Kimberly Strong, Martin Keller, Daven K. Henze, Robert J. Parker, Hartmut Boesch, Debra Wunch, Justus Notholt, Christof Petri, Thorsten Warneke, Ralf Sussmann, Matthias Schneider, Frank Hase, Rigel Kivi, Nicholas M. Deutscher, Voltaire A. Velazco, Kaley A. Walker, and Feng Deng
Atmos. Chem. Phys., 21, 9545–9572, https://doi.org/10.5194/acp-21-9545-2021, https://doi.org/10.5194/acp-21-9545-2021, 2021
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We explore the utility of a weak-constraint (WC) four-dimensional variational (4D-Var) data assimilation scheme for mitigating systematic errors in methane simulation in the GEOS-Chem model. We use data from the Greenhouse Gases Observing Satellite (GOSAT) and show that, compared to the traditional 4D-Var approach, the WC scheme improves the agreement between the model and independent observations. We find that the WC corrections to the model provide insight into the source of the errors.
Matthieu Dogniaux, Cyril Crevoisier, Raymond Armante, Virginie Capelle, Thibault Delahaye, Vincent Cassé, Martine De Mazière, Nicholas M. Deutscher, Dietrich G. Feist, Omaira E. Garcia, David W. T. Griffith, Frank Hase, Laura T. Iraci, Rigel Kivi, Isamu Morino, Justus Notholt, David F. Pollard, Coleen M. Roehl, Kei Shiomi, Kimberly Strong, Yao Té, Voltai