Articles | Volume 15, issue 22
https://doi.org/10.5194/amt-15-6605-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-15-6605-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
17 Nov 2022
Research article |
| 17 Nov 2022
| 17 Nov 2022
Comparison of OCO-2 target observations to MUCCnet – is it possible to capture urban XCO2 gradients from space?
Maximilian Rißmann
Environmental Sensing and Modeling, Technical University of Munich (TUM), Munich, Germany
Environmental Sensing and Modeling, Technical University of Munich (TUM), Munich, Germany
Gregory Osterman
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
Xinxu Zhao
Environmental Sensing and Modeling, Technical University of Munich (TUM), Munich, Germany
Florian Dietrich
Environmental Sensing and Modeling, Technical University of Munich (TUM), Munich, Germany
Moritz Makowski
Environmental Sensing and Modeling, Technical University of Munich (TUM), Munich, Germany
Frank Hase
Institute of Meteorology and Climate Research (IMK-ASF), Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
Matthäus Kiel
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
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Ethan Manninen, Apisada Chulakadabba, Maryann Sargent, Zhan Zhang, Harshil Kamdar, Jack Warren, Sébastien Roche, Christopher Chan Miller, Ethan Kyzivat, Joshua Benmergui, Jasna Pittman, Eleanor Walker, Jacob Bushey, Jenna Samra, Jacob Hawthorne, Bingkun Luo, Maya Nasr, Kang Sun, Jonathan Franklin, Xiong Liu, Jia Chen, and Steven Wofsy
Atmos. Chem. Phys., 26, 15915–15929, https://doi.org/10.5194/acp-26-15915-2026, https://doi.org/10.5194/acp-26-15915-2026, 2026
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In this work, my coauthors and I interpret methane emissions observed by remote sensing systems as plumes, or point sources. We model the probability that a general imaging spectrometer will detect a plume, and apply this framework to multiple remote sensing systems. We show how two recent systems- MethanAIR and MethaneSAT- provide enough sensitivity to facility scale point sources to effectively characterize most plume emissions in the Permian Basin.
Daniel Kühbacher, Jia Chen, Patrick Aigner, Adrian Wenzel, Pascal Rubli, Dominik Brunner, Lukas Emmenegger, and Stuart K. Grange
EGUsphere, https://doi.org/10.5194/egusphere-2026-6001, https://doi.org/10.5194/egusphere-2026-6001, 2026
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
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SCOUT is a network of 100 battery-powered sensor nodes deployed at street level in Munich (Germany). We developed novel methods to improve the measurement accuracy and correct for a gradually drifting sensor signal, achieving a median RMSE of 9.95 ppm for hourly CO2 measurements. The sensors capture the diurnal characteristics of urban CO2 across different sites well, and the measured enhancements correlate strongly with the local emissions from the city inventory at the corresponding sites.
Jacob B. H. Bushey, Michael Bertolacci, Joshua Benmergui, Julian Kostinek, Maryann Sargent, Marvin Knapp, Ethan Kyzivat, Sasha Ayvazov, Marcus Russi, Zhan Zhang, Apisada Chulakadabba, Jia Chen, Christopher Chan Miller, Sébastien Roche, Lucas A. Estrada, James D. East, Luna Yin, James P. Williams, Anthony Himmelberger, Ritesh Gautam, Mark Omara, and Steven C. Wofsy
EGUsphere, https://doi.org/10.5194/egusphere-2026-4693, https://doi.org/10.5194/egusphere-2026-4693, 2026
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
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MethaneSAT was a designed to measure the concentration of methane in the atmosphere over oil and gas producing regions. Our modeling framework uses observations from MethaneSAT to estimate emissions from the Permian Basin. We show that the model accurately captures spatial patterns in emissions and compares well to other models that rely on different atmospheric transport. This data set is valuable for emissions monitoring and mitigation at high spatial resolution and with high precision.
Tobias Grasberger, Jia Chen, Benjamin Zanger, Alessandro Lupoli, Moritz Oliveira Makowski, Josef Stauber, and Felix Krahmer
EGUsphere, https://doi.org/10.5194/egusphere-2026-3161, https://doi.org/10.5194/egusphere-2026-3161, 2026
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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As climate change makes reliable city-scale greenhouse gas monitoring more urgent, we developed a new mathematical method to better trace back emissions in cities. We combine approaches that detect point sources with methods that estimate widespread emissions for inferring urban emissions from air measurements. The result is a more accurate emission field reconstruction than traditional methods, adapted to the heterogeneous urban greenhouse gas emissions and supporting targeted climate action.
Robert J. Parker, Michael P. Cartwright, Dan Orr, Lakshmi N. Bharathan, Neil Humpage, Alex J. Webb, Peter Somkuti, Hartmut Boesch, Antonio Di Noia, Hiroshi Suto, Matthias Buschmann, Nicholas M. Deutscher, David W. T. Griffith, Frank Hase, Rigel Kivi, Erin McGee, Isamu Morino, Hirofumi Ohyama, Christof Petri, John Robinson, Coleen M. Roehl, Mahesh Kumar Sha, Kei Shiomi, Kimberly Strong, Ralf Sussmann, Yao Té, Voltaire A. Velazco, Mihalis Vrekoussis, Wei Wang, Thorsten Warneke, Damien Weidmann, Debra Wunch, and Minqiang Zhou
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2026-625, https://doi.org/10.5194/essd-2026-625, 2026
Preprint under review for ESSD
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Methane is a powerful greenhouse gas and its concentration in the atmosphere is rising rapidly. We present a new record of atmospheric methane measured from space by the Japanese GOSAT-2 satellite, covering 2019 to 2025. The measurements are processed identically to those from its predecessor GOSAT and checked against ground-based instruments around the world. Together the two satellites provide a continuous 17-year record that helps track where methane comes from and how quickly it is changing.
Hui Li, Philippe Ciais, Frédéric Chevallier, Bo Zheng, Paul I. Palmer, Frank Hase, Morgan Lopez, Elsa M. Ordway, Shushi Peng, Danielle Monteverde, Michel Ramonet, Jason M. St. Clair, Le Bienfaiteur Sagang, and Benjamin Poulter
Atmos. Chem. Phys., 26, 11893–11908, https://doi.org/10.5194/acp-26-11893-2026, https://doi.org/10.5194/acp-26-11893-2026, 2026
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We studied how to best place methane monitoring instruments across Africa to better understand where emissions come from. Because observations can overlap in what they detect, adding more sites does not always improve results equally. Using a statistical approach, we identified both the ideal number and locations of sites (ten new sites can reduce emission uncertainty by over 65 % for total African CH4). Our results help guide cost-effective monitoring strategies in regions with limited data.
Zhan Zhang, Maryann Sargent, Ethan Manninen, Jack D. Warren, Apisada Chulakadabba, Marcus Russi, Sasha Ayvazov, Joshua Benmergui, Marvin Knapp, Ethan Kyzivat, Christopher C. Miller, Sébastien Roche, Bingkun Luo, David J. Miller, Maya Nasr, Manuel Perez-Carrasco, Kang Sun, James P. Williams, Katlyn MacKay, Mark Omara, Jia Chen, Luis Guanter, Ritesh Gautam, Jonathan Franklin, Xiong Liu, and Steven C. Wofsy
Atmos. Meas. Tech., 19, 4637–4651, https://doi.org/10.5194/amt-19-4637-2026, https://doi.org/10.5194/amt-19-4637-2026, 2026
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Methane released into the atmosphere is often difficult to detect in satellite imagery because the signals can be weak and hidden by background noise. We developed an automated method that improves the visibility of methane plumes while reducing false detections, decreasing the need for time-consuming manual inspection. The method identifies more small emission sources across different instruments, helping build a more complete understanding of methane emissions and their impacts.
Yanxia Li, Hengheng Zhang, Xuefeng Shi, Yaowei Li, Sophie Abou-Rizk, Jessica B. Smith, Zhaojin An, Adrian Wenzel, Junwei Song, Thomas Leisner, Frank Keutsch, Jia Chen, and Harald Saathoff
EGUsphere, https://doi.org/10.5194/egusphere-2026-2195, https://doi.org/10.5194/egusphere-2026-2195, 2026
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Urban ultrafine particles (<100 nm) sources and growth mechanisms remain poorly constrained. Measurements in a Munich street canyon reveal that UFP number concentrations peak at night due to traffic and cooking emissions trapped under a shallow boundary layer. Particle growth is instead driven by condensation of organic vapours with strong seasonal shifts: biogenic and barbeque charcoal biomass-burning compounds dominate in summer, while combustion-related organics control winter growth.
Jacoline van Es, Juan Bettinelli, Jia Chen, Carina van der Veen, Stephan Henne, and Thomas Röckmann
EGUsphere, https://doi.org/10.5194/egusphere-2026-1813, https://doi.org/10.5194/egusphere-2026-1813, 2026
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The increase in atmospheric methane needs to be reversed to mitigate ongoing global warming. To design effective mitigation strategies at the local/regional level, we need to know what the main sources in different regions. We show that in Hamburg, Germany, biogenic sources are the main contributor to local emissions, with additional contributions from waste and fossil CH4 sources. An unexpected source is the Elbe River, with spiking emissions at low tide when the river banks are exposed.
Yanxia Li, Hengheng Zhang, Xuefeng Shi, Yaowei Li, Sophie Abou-Rizk, Jessica B. Smith, Zhaojin An, Adrian Wenzel, Junwei Song, Thomas Leisner, Frank Keutsch, Jia Chen, and Harald Saathoff
Atmos. Chem. Phys., 26, 5813–5837, https://doi.org/10.5194/acp-26-5813-2026, https://doi.org/10.5194/acp-26-5813-2026, 2026
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We analyzed Munich air samples across seasons to identify pollution sources. Traffic contributes less to particles than expected, while biomass burning dominates year-round. Summer barbecuing and winter heating release significant pollution. Monoterpene emissions from plants produce particles at night. Effective air quality improvement requires year-round strategies targeting biomass burning, not just vehicles. Understanding each city's pollution patterns is essential for public health.
Vincent Enders, Astrid Müller, Matthias Max Frey, Frank Hase, Ralph Kleinschek, Marvin Knapp, Benedikt Löw, Isamu Morino, Shin-Ichiro Nakaoka, Hideki Nara, Hiroshi Tanimoto, Sanam N. Vardag, Karolin Voss, and André Butz
Atmos. Meas. Tech., 19, 2633–2655, https://doi.org/10.5194/amt-19-2633-2026, https://doi.org/10.5194/amt-19-2633-2026, 2026
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We have deployed two spectrometers on a ship traveling along the coast of Japan. By that, we were able to repeatedly measure the greenhouse gas and air pollutant emissions of power plants, large industrial facilities, and cities. Using the ratios between the different gases, we are able to identify sources based on their unique signature. In addition, we are able to show that spectrometers can be operated on a ship, while still fulfilling the high standards of land-based observation networks.
Ann-Kristin Kunz, Samuel Hammer, Patrick Aigner, Laura Bignotti, Lars Borchardt, Jia Chen, Julian Della Coletta, Lukas Emmenegger, Markus Eritt, Xochilt Gutiérrez, Josh Hashemi, Rainer Hilland, Christopher Holst, Armin Jordan, Natascha Kljun, Richard Kneißl, Changxing Lan, Virgile Legendre, Ingeborg Levin, Benjamin Loubet, Matthias Mauder, Betty Molinier, Susanne Preunkert, Michel Ramonet, Stavros Stagakis, and Andreas Christen
Atmos. Chem. Phys., 26, 4967–5003, https://doi.org/10.5194/acp-26-4967-2026, https://doi.org/10.5194/acp-26-4967-2026, 2026
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We present radiocarbon (14C)-based fossil fuel CO2 fluxes from relaxed eddy accumulation measurements on tall towers in the cities of Zurich, Paris, and Munich. By separating net CO2 fluxes into fossil and non-fossil components, these data reveal significant and variable contributions from human, plant, and soil respiration, as well as point-source emissions. These unique insights into CO2 flux composition offer crucial information for observation-based validation of urban emission estimates.
Oliver Schneising, Heinrich Bovensmann, Michael Buchwitz, Matthias Buschmann, Nicholas M. Deutscher, David W. T. Griffith, Jonas Hachmeister, Frank Hase, Laura T. Iraci, Rigel Kivi, Isamu Morino, Hirofumi Ohyama, Christof Petri, Maximilian Reuter, John Robinson, Coleen Roehl, Mahesh Kumar Sha, Kei Shiomi, Kimberly Strong, Ralf Sussmann, Yao Té, Voltaire A. Velazco, Mihalis Vrekoussis, Wei Wang, Thorsten Warneke, Damien Weidmann, Debra Wunch, Minqiang Zhou, and Hartmut Bösch
Atmos. Meas. Tech., 19, 2407–2435, https://doi.org/10.5194/amt-19-2407-2026, https://doi.org/10.5194/amt-19-2407-2026, 2026
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We present an improved version of the TROPOMI/WFMD (TROPOspheric Monitoring Instrument/Weighting Function Modified Differential) algorithm for the simultaneous retrieval of atmospheric methane and carbon monoxide from satellite observations. The updated data product combines higher data yield with better precision and accuracy, expanding its suitability for a wider range of scientific applications. These substantial advances are mainly due to refined quality filtering, enabling more reliable identification of cloudy scenes and mitigating specific aerosol-related issues.
Kanwal Shahzadi, Matthias Schneider, Nga Ying Lo, Frank Hase, Jörg Meyer, Ugur Cayoglu, Tobias Borsdorff, and Mari C. Martinez-Velarte
Earth Syst. Sci. Data, 18, 2153–2177, https://doi.org/10.5194/essd-18-2153-2026, https://doi.org/10.5194/essd-18-2153-2026, 2026
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We merge TROPOMI and IASI L2 methane data from January 2018 to June 2021 on a global scale. The data merging yields total column-averaged and upper tropospheric/stratospheric partial column-averaged mole fractions (already provided by the individual data sets). In addition, it outputs tropospheric partial column-averaged mole fractions (not provided by any of the two individual data sets). We briefly document their increased potential for quantifying near-surface methane emissions.
Patrick Aigner, Jia Chen, Felix Böhm, Mali Chariot, Lukas Emmenegger, Lars Frölich, Stuart Grange, Daniel Kühbacher, Klaus Kürzinger, Olivier Laurent, Moritz Makowski, Pascal Rubli, Adrian Schmitt, and Adrian Wenzel
Atmos. Meas. Tech., 19, 745–773, https://doi.org/10.5194/amt-19-745-2026, https://doi.org/10.5194/amt-19-745-2026, 2026
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Dense urban CO2 monitoring is challenging due to cost and operational constraints. We developed a mid-cost sensor network for Munich, deployed on 17 rooftops. Temperature-stabilized enclosures and automated 2-point calibration ensured reliable performance, assessed by side-by-side comparison with a Picarro reference. In 1.5 years, the network collected 90 million measurements and resolved urban-rural gradients and seasonal diurnal patterns, capturing spatial CO2 variability at city scale.
Friedrich Klappenbach, Jia Chen, Moritz Makowski, Andreas Luther, Ronald C. Cohen, Jonathan E. Franklin, Steven Wofsy, and Taylor Jones
EGUsphere, https://doi.org/10.5194/egusphere-2026-204, https://doi.org/10.5194/egusphere-2026-204, 2026
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This work presents a method to infer the upwind distance of emission sources from observed peak enhancements in atmospheric trace gas measurements. Using meteorological model output, the expected dilution of emissions from candidate source locations is quantified and compared with the observed concentration signals. The method enables the identification of plausible source locations and provides quantitative estimates of their emission strengths.
Daniel Kühbacher, Jia Chen, Patrick Aigner, Mario Ilic, Ingrid Super, and Hugo Denier van der Gon
Geosci. Model Dev., 18, 9967–9990, https://doi.org/10.5194/gmd-18-9967-2025, https://doi.org/10.5194/gmd-18-9967-2025, 2025
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We present DRIVE v1.0, a data-driven framework to estimate road transport emissions, their temporal profiles, and the associated uncertainties. The method was applied to the city of Munich, where we present bottom-up emission estimates for the years 2019 to 2022. The estimates are compared against official municipal reports as well as national and European downscaled inventories.
Qiansi Tu, Frank Hase, Ying Zhang, Jiaxin Fang, Yanwu Jiang, Xiaofan Li, Matthias Schneider, Zhuolin Yang, Xin Zhang, and Zhengqiang Li
Atmos. Chem. Phys., 25, 17779–17796, https://doi.org/10.5194/acp-25-17779-2025, https://doi.org/10.5194/acp-25-17779-2025, 2025
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Understanding greenhouse gas and air pollutant concentrations and emissions characteristics in the Qinghai-Tibetan Plateau cities remains limited. We present the first CO2, CH4 and CO abundances using a portal Fourier-transform infrared (FTIR) spectrometer in Xining. Ground-based data exceeded satellite/model estimates, indicating higher local emissions. Strong CO discrepancies and ∆XCO–∆XCO2 correlation under easterly winds highlight the value of portable FTIR for urban emission studies.
Sina Voshtani, Dylan B. A. Jones, Debra Wunch, Drew C. Pendergrass, Paul O. Wennberg, David F. Pollard, Isamu Morino, Hirofumi Ohyama, Nicholas M. Deutscher, Frank Hase, Ralf Sussmann, Damien Weidmann, Rigel Kivi, Omaira García, Yao Té, Jack Chen, Kerry Anderson, Robin Stevens, Shobha Kondragunta, Aihua Zhu, Douglas Worthy, Senen Racki, Kathryn McKain, Maria V. Makarova, Nicholas Jones, Emmanuel Mahieu, Andrea Cadena-Caicedo, Paolo Cristofanelli, Casper Labuschagne, Elena Kozlova, Thomas Seitz, Martin Steinbacher, Reza Mahdi, and Isao Murata
Atmos. Chem. Phys., 25, 15527–15565, https://doi.org/10.5194/acp-25-15527-2025, https://doi.org/10.5194/acp-25-15527-2025, 2025
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We assess the complementarity of the greater temporal coverage provided by ground-based remote sensing data with the spatial coverage of satellite observations when these data are used together to quantify CO emissions from extreme wildfires in 2023. Our results reveal that the commonly used biomass burning emission inventories significantly underestimate the fire emissions and emphasize the importance of the ground-based remote sensing data in reducing uncertainties in the estimated emissions.
Noémie Taquet, Thomas Boulesteix, Omaira García, Robin Campion, Wolfgang Stremme, Sergio Rodríguez, Jessica López-Darias, Carlos Marrero, Diego González-García, Andreas Klügel, Frank Hase, M. Isabel García, Ramón Ramos, Pedro Rivas-Soriano, Sergio Léon-Luis, Virgilio Carreño, Antonio Alcántara, Eliezer Sépulveda, Celia Milford, Pablo González-Sicilia, and Carlos Torres
Atmos. Chem. Phys., 25, 14591–14628, https://doi.org/10.5194/acp-25-14591-2025, https://doi.org/10.5194/acp-25-14591-2025, 2025
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Volcanic gas emissions were quantified during the 2021 La Palma eruption using ground-based direct-sun Fourier transform infrared spectroscopy and differential optical absorption spectroscopy up to 140 km from the vent. New petrological estimations are consistent with our emission budgets. These findings highlight the feasibility of using existing atmospheric monitoring networks to study the atmospheric impact of volcanic degassing and support monitoring during eruptive crises.
Andrew Gerald Barr, Jochen Landgraf, Mari Martinez-Velarte, Mihalis Vrekoussis, Ralf Sussmann, Isamu Morino, Kimberly Strong, Minqiang Zhou, Voltaire A. Velazco, Hirofumi Ohyama, Thorsten Warneke, Frank Hase, and Tobias Borsdorff
Atmos. Meas. Tech., 18, 6093–6123, https://doi.org/10.5194/amt-18-6093-2025, https://doi.org/10.5194/amt-18-6093-2025, 2025
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The Greenhouse Gases Observing Satellite-2 (GOSAT-2) is a satellite dedicated to measuring concentrations of greenhouse gases from space. Since its launch, the increase of CH4 and CO2 concentrations in the atmosphere is clear. The datasets obtained from GOSAT-2 are used in the Copernicus atmospheric services to monitor the climate, in light of the Paris Agreement. Here we present robust datasets of these gases from GOSAT-2, including a novel machine learning approach to data quality filtering.
Dominik Brunner, Ivo Suter, Leonie Bernet, Lionel Constantin, Stuart K. Grange, Pascal Rubli, Junwei Li, Jia Chen, Alessandro Bigi, and Lukas Emmenegger
Atmos. Chem. Phys., 25, 14387–14410, https://doi.org/10.5194/acp-25-14387-2025, https://doi.org/10.5194/acp-25-14387-2025, 2025
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To support the city of Zurich in tracking its path to net-zero greenhouse gas emissions planned to be reached by 2040, a CO2 emission monitoring system was established. The system combines a dense network of CO2 sensors with a high-resolution atmospheric transport model GRAMM/GRAL. This study presents the setup of the model together with its numerous inputs and evaluates its performance in comparison with observations from the CO2 sensor network.
Harish Shivraj Gadhavi, Akanksha Arora, Chaithanya Jain, Mahesh Kumar Sha, Frank Hase, Matthias Max Frey, Srikanthan Ramachandran, and Achuthan Jayaraman
Atmos. Meas. Tech., 18, 4497–4514, https://doi.org/10.5194/amt-18-4497-2025, https://doi.org/10.5194/amt-18-4497-2025, 2025
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We measured carbon dioxide (CO₂) and methane (CH₄) over South India using a ground-based spectrometer and compared the results with satellite data from GOSAT (Greenhouse gases Observing SATellite; Japan) and OCO-2 (Orbiting Carbon Observatory-2; NASA, USA). The satellite data have good accuracy and precision for estimating emissions. A computer model showed that changes in methane levels are influenced more by background levels than by local sources.
Elyse A. Pennington, Gregory B. Osterman, Vivienne H. Payne, Kazuyuki Miyazaki, Kevin W. Bowman, and Jessica L. Neu
Atmos. Chem. Phys., 25, 8533–8552, https://doi.org/10.5194/acp-25-8533-2025, https://doi.org/10.5194/acp-25-8533-2025, 2025
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Tropospheric ozone is a harmful pollutant and powerful greenhouse gas. For satellite products to accurately quantify trends in tropospheric ozone, they must have a low bias compared to a reliable source of data. This study compares three NASA satellite products to ozonesonde data. They have low global measurement bias and thus can be used to detect global tropospheric ozone trends, but the measurement bias should be considered in certain regions and time periods.
Aki Tsuruta, Akihiko Kuze, Kei Shiomi, Fumie Kataoka, Nobuhiro Kikuchi, Tuula Aalto, Leif Backman, Ella Kivimäki, Maria K. Tenkanen, Kathryn McKain, Omaira E. García, Frank Hase, Rigel Kivi, Isamu Morino, Hirofumi Ohyama, David F. Pollard, Mahesh K. Sha, Kimberly Strong, Ralf Sussmann, Yao Te, Voltaire A. Velazco, Mihalis Vrekoussis, Thorsten Warneke, Minqiang Zhou, and Hiroshi Suto
Atmos. Chem. Phys., 25, 7829–7862, https://doi.org/10.5194/acp-25-7829-2025, https://doi.org/10.5194/acp-25-7829-2025, 2025
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Satellite data bring invaluable information about greenhouse gas emissions globally. We found that a new type of data from the Greenhouse Gas Observing Satellite (GOSAT), which contains information about methane in the lowest layer of Earth's atmosphere, could provide reliable estimates of recent methane emissions when combined with atmospheric modelling. Therefore, the use of such data is encouraged to improve emission quantification methods and advance our understanding of methane cycles.
Christopher Johannes Diekmann, Matthias Schneider, Peter Knippertz, Tim Trent, Hartmut Boesch, Amelie Ninja Roehling, John Worden, Benjamin Ertl, Farahnaz Khosrawi, and Frank Hase
Atmos. Chem. Phys., 25, 5409–5431, https://doi.org/10.5194/acp-25-5409-2025, https://doi.org/10.5194/acp-25-5409-2025, 2025
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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 characterize processes controlling the monsoon convection. We find that comparing different water vapour isotopes reveals effects of rain–vapour interactions and air mass transport.
Stavros Stagakis, Dominik Brunner, Junwei Li, Leif Backman, Anni Karvonen, Lionel Constantin, Leena Järvi, Minttu Havu, Jia Chen, Sophie Emberger, and Liisa Kulmala
Biogeosciences, 22, 2133–2161, https://doi.org/10.5194/bg-22-2133-2025, https://doi.org/10.5194/bg-22-2133-2025, 2025
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The balance between CO2 uptake and emissions from urban green areas is still not well understood. This study evaluated for the first time the urban park CO2 exchange simulations with four different types of biosphere model by comparing them with observations. Even though some advantages and disadvantages of the different model types were identified, there was no strong evidence that more complex models performed better than simple ones.
Lena Feld, Pablo Schmid, Marios Mermigkas, Dimitrios Balis, Jochen Gross, Darko Dubravica, Carlos Alberti, Benedikt Herkommer, Stefan Versick, Roland Ruhnke, Frank Hase, and Peter Braesicke
EGUsphere, https://doi.org/10.5194/egusphere-2025-639, https://doi.org/10.5194/egusphere-2025-639, 2025
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Our goal is to measure CO2 emissions from cities, to verify and improve our knowledge of reported anthropogenic emissions. We use atmospheric measurements and simulations of CO2 transport to find an independent estimate. This study investigates the CO2 emissions of the city of Thessaloniki, where the reported emissions differ. The data we collected indicates that the emissions are larger than stated by the ODIAC inventory, which we used for our simulations.
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., 18, 1257–1267, https://doi.org/10.5194/amt-18-1257-2025, https://doi.org/10.5194/amt-18-1257-2025, 2025
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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 Fourier analysis. The paper deals with technical aspects of this process and shows how the reconstruction of the spectrum can be optimized.
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.
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.
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.
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).
Ayah Abu-Hani, Jia Chen, Vigneshkumar Balamurugan, Adrian Wenzel, and Alessandro Bigi
Atmos. Meas. Tech., 17, 3917–3931, https://doi.org/10.5194/amt-17-3917-2024, https://doi.org/10.5194/amt-17-3917-2024, 2024
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This study examined the transferability of machine learning calibration models among low-cost sensor units targeting NO2 and NO. The global models were evaluated under similar and different emission conditions. To counter cross-sensitivity, the study proposed integrating O3 measurements from nearby reference stations, in Switzerland. The models show substantial improvement when O3 measurements are incorporated, which is more pronounced when in regions with elevated O3 concentrations.
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.
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.
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.
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.
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.
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.
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.
Xinxu Zhao, Jia Chen, Julia Marshall, Michal Gałkowski, Stephan Hachinger, Florian Dietrich, Ankit Shekhar, Johannes Gensheimer, Adrian Wenzel, and Christoph Gerbig
Atmos. Chem. Phys., 23, 14325–14347, https://doi.org/10.5194/acp-23-14325-2023, https://doi.org/10.5194/acp-23-14325-2023, 2023
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We develop a modeling framework using the Weather Research and Forecasting model at a high spatial resolution (up to 400 m) to simulate atmospheric transport of greenhouse gases and interpret column observations. Output is validated against weather stations and column measurements in August 2018. The differential column method is applied, aided by air-mass transport tracing with the Stochastic Time-Inverted Lagrangian Transport (STILT) model, also for an exploratory measurement interpretation.
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.
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.
Vigneshkumar Balamurugan, Jia Chen, Adrian Wenzel, and Frank N. Keutsch
Atmos. Chem. Phys., 23, 10267–10285, https://doi.org/10.5194/acp-23-10267-2023, https://doi.org/10.5194/acp-23-10267-2023, 2023
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In this study, machine learning models are employed to model NO2 and O3 concentrations. We employed a wide range of sources of data, including meteorological and column satellite measurements, to model NO2 and O3 concentrations. The spatial and temporal variability, and their drivers, were investigated. Notably, the machine learning model established the relationship between NOx and O3. Despite the fact that metropolitan regions are NO2 hotspots, rural areas have high O3 concentrations.
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.
Andreas Forstmaier, Jia Chen, Florian Dietrich, Juan Bettinelli, Hossein Maazallahi, Carsten Schneider, Dominik Winkler, Xinxu Zhao, Taylor Jones, Carina van der Veen, Norman Wildmann, Moritz Makowski, Aydin Uzun, Friedrich Klappenbach, Hugo Denier van der Gon, Stefan Schwietzke, and Thomas Röckmann
Atmos. Chem. Phys., 23, 6897–6922, https://doi.org/10.5194/acp-23-6897-2023, https://doi.org/10.5194/acp-23-6897-2023, 2023
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Large cities emit greenhouse gases which contribute to global warming. In this study, we measured the release of one important green house gas, methane, in Hamburg. Multiple sources that contribute to methane emissions were located and quantified. Methane sources were found to be mainly caused by human activity (e.g., by release from oil and gas refineries). Moreover, potential natural sources have been located, such as the Elbe River and lakes.
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.
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.
Emily Bell, Christopher W. O'Dell, Thomas E. Taylor, Aronne Merrelli, Robert R. Nelson, Matthäus Kiel, Annmarie Eldering, Robert Rosenberg, and Brendan Fisher
Atmos. Meas. Tech., 16, 109–133, https://doi.org/10.5194/amt-16-109-2023, https://doi.org/10.5194/amt-16-109-2023, 2023
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A small percentage of data from the Orbiting Carbon Observatory-3 (OCO-3) instrument has been shown to have a geometry-related bias in the earliest public data release. This work shows that the bias is due to a complex interplay of aerosols and viewing geometry and is largely mitigated in the latest data version through improved bias correction and quality filtering.
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.
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.
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.
Benjamin Zanger, Jia Chen, Man Sun, and Florian Dietrich
Geosci. Model Dev., 15, 7533–7556, https://doi.org/10.5194/gmd-15-7533-2022, https://doi.org/10.5194/gmd-15-7533-2022, 2022
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Gaussian priors (GPs) used in least squares inversion do not reflect the true distributions of greenhouse gas emissions well. A method that does not rely on GPs is sparse reconstruction (SR). We show that necessary conditions for SR are satisfied for cities and that the application of a wavelet transform can further enhance sparsity. We apply the theory of compressed sensing to SR. Our results show that SR needs fewer measurements and is superior for assessing unknown emitters compared to GPs.
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.
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.
Vigneshkumar Balamurugan, Jia Chen, Zhen Qu, Xiao Bi, and Frank N. Keutsch
Atmos. Chem. Phys., 22, 7105–7129, https://doi.org/10.5194/acp-22-7105-2022, https://doi.org/10.5194/acp-22-7105-2022, 2022
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In this study, we investigated the response of secondary pollutants to changes in precursor emissions, focusing on the formation of secondary PM, during the COVID-19 lockdown period. We show that, due to the decrease in primary NOx emissions, atmospheric oxidizing capacity is increased. The nighttime increase in ozone, caused by less NO titration, results in higher NO3 radicals, which contribute significantly to the formation of PM nitrates. O3 should be limited in order to control PM pollution.
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.
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.
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.
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.
Gerrit Kuhlmann, Ka Lok Chan, Sebastian Donner, Ying Zhu, Marc Schwaerzel, Steffen Dörner, Jia Chen, Andreas Hueni, Duc Hai Nguyen, Alexander Damm, Annette Schütt, Florian Dietrich, Dominik Brunner, Cheng Liu, Brigitte Buchmann, Thomas Wagner, and Mark Wenig
Atmos. Meas. Tech., 15, 1609–1629, https://doi.org/10.5194/amt-15-1609-2022, https://doi.org/10.5194/amt-15-1609-2022, 2022
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Nitrogen dioxide (NO2) is an air pollutant whose concentration often exceeds air quality guideline values, especially in urban areas. To map the spatial distribution of NO2 in Munich, we conducted the Munich NO2 Imaging Campaign (MuNIC), where NO2 was measured with stationary, mobile, and airborne in situ and remote sensing instruments. The campaign provides a unique dataset that has been used to compare the different instruments and to study the spatial variability of NO2 and its sources.
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.
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.
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.
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.
Cited articles
Alberti, C., Hase, F., Frey, M., Dubravica, D., Blumenstock, T., Dehn, A., Castracane, P., Surawicz, G., Harig, R., Baier, B. C., Bès, C., Bi, J., Boesch, H., Butz, A., Cai, Z., Chen, J., Crowell, S. M., Deutscher, N. M., Ene, D., Franklin, J. E., García, O., Griffith, D., Grouiez, B., Grutter, M., Hamdouni, A., Houweling, S., Humpage, N., Jacobs, N., Jeong, S., Joly, L., Jones, N. B., Jouglet, D., Kivi, R., Kleinschek, R., Lopez, M., Medeiros, D. J., Morino, I., Mostafavipak, N., Müller, A., Ohyama, H., Palmer, P. I., Pathakoti, M., Pollard, D. F., Raffalski, U., Ramonet, M., Ramsay, R., Sha, M. K., Shiomi, K., Simpson, W., Stremme, W., Sun, Y., Tanimoto, H., Té, Y., Tsidu, G. M., Velazco, V. A., Vogel, F., Watanabe, M., Wei, C., Wunch, D., Yamasoe, M., Zhang, L., and Orphal, J.:
Improved calibration procedures for the EM27/SUN spectrometers of the COllaborative Carbon Column Observing Network (COCCON), Atmos. Meas. Tech., 15, 2433–2463, https://doi.org/10.5194/amt-15-2433-2022, 2022. a, b, c
Beck, V., Koch, T., Kretschmer, R., Marshall, J., Ahmadov, R., Gerbig, C., Pillai, D., and Heimann, M.:
The WRF Greenhouse Gas Model (WRF-GHG) Technical Report, Max Planck Institute for Biogeochemistry, Jena, Germany, https://www.bgc-jena.mpg.de/bgc-systems/pmwiki2/uploads/Download/Wrf-ghg/WRF-GHG_Techn_Report.pdf (last access: 31 January 2022), 2011. a
Chen, J., Viatte, C., Hedelius, J. K., Jones, T., Franklin, J. E., Parker, H., Gottlieb, E. W., Wennberg, P. O., Dubey, M. K., and Wofsy, S. C.:
Differential column measurements using compact solar-tracking spectrometers, Atmos. Chem. Phys., 16, 8479–8498, https://doi.org/10.5194/acp-16-8479-2016, 2016. a, b, c
Chen, J., Dietrich, F., Forstmaier, A., Bettinelli, J., Maazallahi, H., Schneider, C., Röckmann, T., Winkler, D., Zhao, X., Makowski, M., Klappenbach, F., van der Veen, C., Wildmann, N., Jones, T., Ament, F., Lange, I., Denier van der Gon, H., and Schwietzke, S.: Multi-scale measurements combined with inverse modeling for assessing methane emissions of Hamburg, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11548, https://doi.org/10.5194/egusphere-egu22-11548, 2022. a
Crisp, D.:
Measuring atmospheric carbon dioxide from space: The GOSAT and OCO-2 missions, Optics InfoBase Conference Papers, 2, jet Propulsion Laboratory/California Institute of Technology, https://doi.org/10.1364/e2.2011.ewc6, 2011. a, b
Frey, M., Hase, F., Blumenstock, T., Groß, J., Kiel, M., Mengistu Tsidu, G., Schäfer, K., Sha, M. K., and Orphal, J.:
Calibration and instrumental line shape characterization of a set of portable FTIR spectrometers for detecting greenhouse gas emissions, Atmos. Meas. Tech., 8, 3047–3057, https://doi.org/10.5194/amt-8-3047-2015, 2015. a, b
Frey, M., Sha, M. K., Hase, F., Kiel, M., Blumenstock, T., Harig, R., Surawicz, G., Deutscher, N. M., Shiomi, K., Franklin, J. E., Bösch, H., Chen, J., Grutter, M., Ohyama, H., Sun, Y., Butz, A., Mengistu Tsidu, G., Ene, D., Wunch, D., Cao, Z., Garcia, O., Ramonet, M., Vogel, F., and Orphal, J.:
Building the COllaborative Carbon Column Observing Network (COCCON): long-term stability and ensemble performance of the EM27/SUN Fourier transform spectrometer, Atmos. Meas. Tech., 12, 1513–1530, https://doi.org/10.5194/amt-12-1513-2019, 2019. a, b, c, d, e
Gisi, M., Hase, F., Dohe, S., Blumenstock, T., Simon, A., and Keens, A.:
XCO2−measurements with a tabletop FTS using solar absorption spectroscopy, Atmos. Meas. Tech., 5, 2969–2980, https://doi.org/10.5194/amt-5-2969-2012, 2012. a
Gurney, K. R., Romero-Lankao, P., Seto, K. C., Hutyra, L. R., Duren, R., Kennedy, C., Grimm, N. B., Ehleringer, J. R., Marcotullio, P., Hughes, S., Pincetl, S., Chester, M. V., Runfola, D. M., Feddema, J. J., and Sperling, J.:
Climate change: Track urban emissions on a human scale, Nature, 525, 179–181, https://doi.org/10.1038/525179a, 2015. a
Hase, F., Hannigan, J., Coffey, M., Goldman, A., Höpfner, M., Jones, N., Rinsland, C., and Wood, S.:
Intercomparison of retrieval codes used for the analysis of high-resolution, ground-based FTIR measurements, J. Quant. Spectrosc. Ra., 87, 25–52, https://doi.org/10.1016/j.jqsrt.2003.12.008, 2004. a
Hase, F., Frey, M., Blumenstock, T., Groß, J., Kiel, M., Kohlhepp, R., Mengistu Tsidu, G., Schäfer, K., Sha, M. K., and Orphal, J.:
Application of portable FTIR spectrometers for detecting greenhouse gas emissions of the major city Berlin, Atmos. Meas. Tech., 8, 3059–3068, https://doi.org/10.5194/amt-8-3059-2015, 2015. a
Hedelius, J. K., Viatte, C., Wunch, D., Roehl, C. M., Toon, G. C., Chen, J., Jones, T., Wofsy, S. C., Franklin, J. E., Parker, H., Dubey, M. K., and Wennberg, P. O.: Assessment of errors and biases in retrievals of X
Heinle, L. and Chen, J.:
Automated enclosure and protection system for compact solar-tracking spectrometers, Atmos. Meas. Tech., 11, 2173–2185, https://doi.org/10.5194/amt-11-2173-2018, 2018. a
Jacobs, N., Simpson, W. R., Wunch, D., O'Dell, C. W., Osterman, G. B., Hase, F., Blumenstock, T., Tu, Q., Frey, M., Dubey, M. K., Parker, H. A., Kivi, R., and Heikkinen, P.:
Quality controls, bias, and seasonality of CO2 columns in the boreal forest with Orbiting Carbon Observatory-2, Total Carbon Column Observing Network, and EM27/SUN measurements, Atmos. Meas. Tech., 13, 5033–5063, https://doi.org/10.5194/amt-13-5033-2020, 2020. a
Jones, T. S., Franklin, J. E., Chen, J., Dietrich, F., Hajny, K. D., Paetzold, J. C., Wenzel, A., Gately, C., Gottlieb, E., Parker, H., Dubey, M., Hase, F., Shepson, P. B., Mielke, L. H., and Wofsy, S. C.:
Assessing urban methane emissions using column-observing portable Fourier transform infrared (FTIR) spectrometers and a novel Bayesian inversion framework, Atmos. Chem. Phys., 21, 13131–13147, https://doi.org/10.5194/acp-21-13131-2021, 2021. a
Kiel, M.: OCO-2 Science Team Telecon: A six year record of OCO-2 XCO2 measurements, NASA JPL, https://trs.jpl.nasa.gov/bitstream/handle/2014/54929/CL%2321-2020.pdf?sequence=1 (last access: 23 October 2022), 2021. a
Kiel, M., O'Dell, C. W., Fisher, B., Eldering, A., Nassar, R., MacDonald, C. G., and Wennberg, P. O.:
How bias correction goes wrong: measurement of
Kiel, M., Eldering, A., Roten, D. D., Lin, J. C., Feng, S., Lei, R., Lauvaux, T., Oda, T., Roehl, C. M., Blavier, J. F., and Iraci, L. T.:
Urban-focused satellite CO2 observations from the Orbiting Carbon Observatory-3: A first look at the Los Angeles megacity, Remote Sens. Environ., 258, https://doi.org/10.1016/j.rse.2021.112314, 2021. a, b, c
Klappenbach, F., Chen, J., Wenzel, A., Forstmaier, A., Dietrich, F., Zhao, X., Jones, T., Franklin, J., Wofsy, S., Frey, M., Hase, F., Hedelius, J., Wennberg, P., Cohen, R., and Fischer, M.: Methane emission estimate using ground based remote sensing in complex terrain, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15406, https://doi.org/10.5194/egusphere-egu21-15406, 2021. a
Luther, A., Kleinschek, R., Scheidweiler, L., Defratyka, S., Stanisavljevic, M., Forstmaier, A., Dandocsi, A., Wolff, S., Dubravica, D., Wildmann, N., Kostinek, J., Jöckel, P., Nickl, A.-L., Klausner, T., Hase, F., Frey, M., Chen, J., Dietrich, F., Nȩcki, J., Swolkień, J., Fix, A., Roiger, A., and Butz, A.:
Quantifying CH4 emissions from hard coal mines using mobile sun-viewing Fourier transform spectrometry, Atmos. Meas. Tech., 12, 5217–5230, https://doi.org/10.5194/amt-12-5217-2019, 2019. a
Luther, A., Kostinek, J., Kleinschek, R., Defratyka, S., Stanisavljević, M., Forstmaier, A., Dandocsi, A., Scheidweiler, L., Dubravica, D., Wildmann, N., Hase, F., Frey, M. M., Chen, J., Dietrich, F., Nȩcki, J., Swolkień, J., Knote , C., Vardag, S. N., Roiger, A., and Butz, A.:
Observational constraints on methane emissions from Polish coal mines using a ground-based remote sensing network, Atmos. Chem. Phys., 22, 5859–5876, https://doi.org/10.5194/acp-22-5859-2022, 2022. a
Makarova, M. V., Alberti, C., Ionov, D. V., Hase, F., Foka, S. C., Blumenstock, T., Warneke, T., Virolainen, Y. A., Kostsov, V. S., Frey, M., Poberovskii, A. V., Timofeyev, Y. M., Paramonova, N. N., Volkova, K. A., Zaitsev, N. A., Biryukov, E. Y., Osipov, S. I., Makarov, B. K., Polyakov, A. V., Ivakhov, V. M., Imhasin, H. Kh., and Mikhailov, E. F.:
Emission Monitoring Mobile Experiment (EMME): an overview and first results of the St. Petersburg megacity campaign 2019, Atmos. Meas. Tech., 14, 1047–1073, https://doi.org/10.5194/amt-14-1047-2021, 2021. a
Montzka, S.: The NOAA Annual Greenhous Gas Index (AGGI), NOAA (National Oceanic and Atmospheric Administration), https://gml.noaa.gov/aggi/aggi.html (last access: 31 January 2022), 2021. a
Nguyen, H., Osterman, G., Wunch, D., O'Dell, C., Mandrake, L., Wennberg, P., Fisher, B., and Castano, R.:
A method for colocating satellite
OCO-2 Science Team/Michael Gunson, Annmarie Eldering: OCO-2 Level 2 bias-corrected XCO2 and other select fields from the full-physics retrieval aggregated as daily files, Retrospective processing V10r, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set], Greenbelt, MD, USA, https://doi.org/10.5067/E4E140XDMPO2, 2020. a, b
O'Dell, C. W., Connor, B., Bösch, H., O'Brien, D., Frankenberg, C., Castano, R., Christi, M., Eldering, D., Fisher, B., Gunson, M., McDuffie, J., Miller, C. E., Natraj, V., Oyafuso, F., Polonsky, I., Smyth, M., Taylor, T., Toon, G. C., Wennberg, P. O., and Wunch, D.:
The ACOS CO2 retrieval algorithm – Part 1: Description and validation against synthetic observations, Atmos. Meas. Tech., 5, 99–121, https://doi.org/10.5194/amt-5-99-2012, 2012. a
O'Dell, C. W., Eldering, A., Wennberg, P. O., Crisp, D., Gunson, M. R., Fisher, B., Frankenberg, C., Kiel, M., Lindqvist, H., Mandrake, L., Merrelli, A., Natraj, V., Nelson, R. R., Osterman, G. B., Payne, V. H., Taylor, T. E., Wunch, D., Drouin, B. J., Oyafuso, F., Chang, A., McDuffie, J., Smyth, M., Baker, D. F., Basu, S., Chevallier, F., Crowell, S. M. R., Feng, L., Palmer, P. I., Dubey, M., García, O. E., Griffith, D. W. T., Hase, F., Iraci, L. T., Kivi, R., Morino, I., Notholt, J., Ohyama, H., Petri, C., Roehl, C. M., Sha, M. K., Strong, K., Sussmann, R., Te, Y., Uchino, O., and Velazco, V. A.:
Improved retrievals of carbon dioxide from Orbiting Carbon Observatory-2 with the version 8 ACOS algorithm, Atmos. Meas. Tech., 11, 6539–6576, https://doi.org/10.5194/amt-11-6539-2018, 2018. a
Osterman, G., ODell, C., Eldering, A., Fisher, B., Crisp, D., Cheng, C., Frankenberg, C., Lambert, A., Gunson, M. R., Mandrake, L., and Wunch, D.:
Orbiting Carbon Observatory-2 and 3 (OCO-2 and OCO-3): Data Product Users Guide, Operational Level 2 Data Versions 10 and Lite File Version 10 and VEarly, 3, NASA JPL, https://docserver.gesdisc.eosdis.nasa.gov/public/project/OCO/OCO2_OCO3_B10_DUG.pdf (last access: 23 October 2022), 2020. a, b, c, d
Osterman, G. B., Eldering, A., Mandrake, L., O'Dell, C., Wunch, D., Wennberg, P. O., Fisher, B., and Marchetti, Y.:
OCO-2 XCO2 V8r Lite Products, Warn Levels, and Bias Correction, 2, NASA JPL, https://docserver.gesdisc.eosdis.nasa.gov/public/project/OCO/OCO2_XCO2_Lite_Files_and_Bias_Correction.pdf (last access: 30 September 2021), 2017. a
Park, C., Jeong, S., Park, H., Yun, J., and Liu, J.:
Evaluation of the Potential Use of Satellite-Derived XCO2 in Detecting CO2 Enhancement in Megacities with Limited Ground Observations: A Case Study in Seoul Using Orbiting Carbon Observatory-2, Asia-Pac. J. Atmos. Sci., 57, 289–299, https://doi.org/10.1007/s13143-020-00202-5, 2021. a
Sha, M. K., De Mazière, M., Notholt, J., Blumenstock, T., Chen, H., Dehn, A., Griffith, D. W. T., Hase, F., Heikkinen, P., Hermans, C., Hoffmann, A., Huebner, M., Jones, N., Kivi, R., Langerock, B., Petri, C., Scolas, F., Tu, Q., and Weidmann, D.:
Intercomparison of low- and high-resolution infrared spectrometers for ground-based solar remote sensing measurements of total column concentrations of CO2, CH4, and CO, Atmos. Meas. Tech., 13, 4791–4839, https://doi.org/10.5194/amt-13-4791-2020, 2020. a
Shekhar, A., Chen, J., Paetzold, J. C., Dietrich, F., Zhao, X., Bhattacharjee, S., Ruisinger, V., and Wofsy, S. C.:
Anthropogenic CO2 emissions assessment of Nile Delta using XCO2 and SIF data from OCO-2 satellite, Environ. Res. Lett., 15, 095010, https://doi.org/10.1088/1748-9326/ab9cfe, 2020. a
IPCC: Climate Change and Land: an IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems, edited by:
Shukla, P. R., Skea, J., Calvo Buendia, E., Masson-Delmotte, V., Pörtner, H.-O., Roberts, D. C., Zhai, P., Slade, R., Connors, S., van Diemen, R., Ferrat, M., Haughey, E., Luz, S., Neogi, S., Pathak, M., Petzold, J. Portugal Pereira, J., Vyas, P., Huntley, E., Kissick, K., Belkacemi, M., and Malley, J., IPCC, https://www.ipcc.ch/site/assets/uploads/2019/11/SRCCL-Full-Report-Compiled-191128.pdf (last access: 23 October 2022), 2019. a
Super, I., Dellaert, S. N. C., Visschedijk, A. J. H., and Denier van der Gon, H. A. C.:
Uncertainty analysis of a European high-resolution emission inventory of CO2 and CO to support inverse modelling and network design, Atmos. Chem. Phys., 20, 1795–1816, https://doi.org/10.5194/acp-20-1795-2020, 2020. a
Wu, C. and Yu, J. Z.:
Evaluation of linear regression techniques for atmospheric applications: the importance of appropriate weighting, Atmos. Meas. Tech., 11, 1233–1250, https://doi.org/10.5194/amt-11-1233-2018, 2018.
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Short summary
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.
The Orbiting Carbon Observatory 2 (OCO-2) measures atmospheric concentrations of the most potent...
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