Articles | Volume 15, issue 22
https://doi.org/10.5194/gmd-15-8295-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/gmd-15-8295-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model evaluation paper
| 
18 Nov 2022
Model evaluation paper |
| 18 Nov 2022
| 18 Nov 2022
A comprehensive evaluation of the use of Lagrangian particle dispersion models for inverse modeling of greenhouse gas emissions
Department of Meteorology and Geophysics, University of Vienna, Vienna, Austria
Andreas Plach
Department of Meteorology and Geophysics, University of Vienna, Vienna, Austria
Physics Institute, Climate and Environmental Physics, University of Bern, Bern, Switzerland
Rona L. Thompson
Norwegian Institute for Air Research NILU, Kjeller, Norway
Andreas Stohl
Department of Meteorology and Geophysics, University of Vienna, Vienna, Austria
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Our manuscript presents a six-year, high-resolution inversion of European methane emissions using the Community Inversion Framework and FLEXPART. Leveraging an expanded in situ network, we reconcile inventories with observations, reveal regional biases, refine European methane budgets, and highlight the dominance of agricultural emissions. Results provide policy-relevant insights for mitigation and inventory verification.
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Microplastics are transported over large distances in the atmosphere, but the shape-dependence of their atmospheric transport lacks investigation. We conducted laboratory experiments and atmospheric transport simulations to study the settling of commercially sold microplastics. We found that films settle up to 74 % slower and travel up to ~ 4x further than volume-equivalent spheres. Our work emphasizes the role of the atmosphere as a transport medium for commercial microplastics such as glitter.
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Zhu Deng, Philippe Ciais, Liting Hu, Adrien Martinez, Marielle Saunois, Rona L. Thompson, Kushal Tibrewal, Wouter Peters, Brendan Byrne, Giacomo Grassi, Paul I. Palmer, Ingrid T. Luijkx, Zhu Liu, Junjie Liu, Xuekun Fang, Tengjiao Wang, Hanqin Tian, Katsumasa Tanaka, Ana Bastos, Stephen Sitch, Benjamin Poulter, Clément Albergel, Aki Tsuruta, Shamil Maksyutov, Rajesh Janardanan, Yosuke Niwa, Bo Zheng, Joël Thanwerdas, Dmitry Belikov, Arjo Segers, and Frédéric Chevallier
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This study reconciles national greenhouse gas (GHG) inventories with updated atmospheric inversion results to evaluate discrepancies for three principal GHG fluxes at the national level. Compared to our previous study, new satellite-based CO2 inversions were included and an updated mask of managed lands was used, improving agreement for Brazil and Canada. The proposed methodology can be regularly applied as a check to assess the gap between top-down inversions and bottom-up inventories.
Michel Legrand, Mstislav Vorobyev, Daria Bokuchava, Stanislav Kutuzov, Andreas Plach, Andreas Stohl, Alexandra Khairedinova, Vladimir Mikhalenko, Maria Vinogradova, Sabine Eckhardt, and Susanne Preunkert
Atmos. Chem. Phys., 25, 1385–1399, https://doi.org/10.5194/acp-25-1385-2025, https://doi.org/10.5194/acp-25-1385-2025, 2025
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Past atmospheric NH3 pollution in south-eastern Europe was reconstructed by analysing ammonium in an ice core drilled at the Mount Elbrus (Caucasus, Russia). The observed 3.5-fold increase in ice concentrations between 1750 and 1990 CE is in good agreement with estimated past dominant ammonia emissions from agriculture, mainly from south European Russia and Türkiye. In contrast to present-day conditions, the ammonium level observed in 1750 CE indicates significant natural emissions at that time.
Matthew Boyer, Diego Aliaga, Lauriane L. J. Quéléver, Silvia Bucci, Hélène Angot, Lubna Dada, Benjamin Heutte, Lisa Beck, Marina Duetsch, Andreas Stohl, Ivo Beck, Tiia Laurila, Nina Sarnela, Roseline C. Thakur, Branka Miljevic, Markku Kulmala, Tuukka Petäjä, Mikko Sipilä, Julia Schmale, and Tuija Jokinen
Atmos. Chem. Phys., 24, 12595–12621, https://doi.org/10.5194/acp-24-12595-2024, https://doi.org/10.5194/acp-24-12595-2024, 2024
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We analyze the seasonal cycle and sources of gases that are relevant for the formation of aerosol particles in the central Arctic. Since theses gases can form new particles, they can influence Arctic climate. We show that the sources of these gases are associated with changes in the Arctic environment during the year, especially with respect to sea ice. Therefore, the concentration of these gases will likely change in the future as the Arctic continues to warm.
Martin Vojta, Andreas Plach, Saurabh Annadate, Sunyoung Park, Gawon Lee, Pallav Purohit, Florian Lindl, Xin Lan, Jens Mühle, Rona L. Thompson, and Andreas Stohl
Atmos. Chem. Phys., 24, 12465–12493, https://doi.org/10.5194/acp-24-12465-2024, https://doi.org/10.5194/acp-24-12465-2024, 2024
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We constrain the global emissions of the very potent greenhouse gas sulfur hexafluoride (SF6) between 2005 and 2021. We show that SF6 emissions are decreasing in the USA and in the EU, while they are substantially growing in China, leading overall to an increasing global emission trend. The national reports for the USA, EU, and China all underestimated their SF6 emissions. However, stringent mitigation measures can successfully reduce SF6 emissions, as can be seen in the EU emission trend.
Lucie Bakels, Daria Tatsii, Anne Tipka, Rona Thompson, Marina Dütsch, Michael Blaschek, Petra Seibert, Katharina Baier, Silvia Bucci, Massimo Cassiani, Sabine Eckhardt, Christine Groot Zwaaftink, Stephan Henne, Pirmin Kaufmann, Vincent Lechner, Christian Maurer, Marie D. Mulder, Ignacio Pisso, Andreas Plach, Rakesh Subramanian, Martin Vojta, and Andreas Stohl
Geosci. Model Dev., 17, 7595–7627, https://doi.org/10.5194/gmd-17-7595-2024, https://doi.org/10.5194/gmd-17-7595-2024, 2024
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Computer models are essential for improving our understanding of how gases and particles move in the atmosphere. We present an update of the atmospheric transport model FLEXPART. FLEXPART 11 is more accurate due to a reduced number of interpolations and a new scheme for wet deposition. It can simulate non-spherical aerosols and includes linear chemical reactions. It is parallelised using OpenMP and includes new user options. A new user manual details how to use FLEXPART 11.
Katharina Baier, Lucie Bakels, and Andreas Stohl
EGUsphere, https://doi.org/10.5194/egusphere-2024-2801, https://doi.org/10.5194/egusphere-2024-2801, 2024
Preprint withdrawn
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As extremely dry and warm conditions over the Amazon basin can cause huge damages, we study the role of atmospheric transport into the western Amazon for such events. We show that the physical processes depend on the climate variability El Niño Southern Oscillation (ENSO). While warm and dry air from the Atlantic Ocean is transported to the western Amazon for extreme events during the warm ENSO phase, we expect continental regions to have a stronger impact for the other extreme events we found.
Ana Maria Roxana Petrescu, Glen P. Peters, Richard Engelen, Sander Houweling, Dominik Brunner, Aki Tsuruta, Bradley Matthews, Prabir K. Patra, Dmitry Belikov, Rona L. Thompson, Lena Höglund-Isaksson, Wenxin Zhang, Arjo J. Segers, Giuseppe Etiope, Giancarlo Ciotoli, Philippe Peylin, Frédéric Chevallier, Tuula Aalto, Robbie M. Andrew, David Bastviken, Antoine Berchet, Grégoire Broquet, Giulia Conchedda, Stijn N. C. Dellaert, Hugo Denier van der Gon, Johannes Gütschow, Jean-Matthieu Haussaire, Ronny Lauerwald, Tiina Markkanen, Jacob C. A. van Peet, Isabelle Pison, Pierre Regnier, Espen Solum, Marko Scholze, Maria Tenkanen, Francesco N. Tubiello, Guido R. van der Werf, and John R. Worden
Earth Syst. Sci. Data, 16, 4325–4350, https://doi.org/10.5194/essd-16-4325-2024, https://doi.org/10.5194/essd-16-4325-2024, 2024
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This study provides an overview of data availability from observation- and inventory-based CH4 emission estimates. It systematically compares them and provides recommendations for robust comparisons, aiming to steadily engage more parties in using observational methods to complement their UNFCCC submissions. Anticipating improvements in atmospheric modelling and observations, future developments need to resolve knowledge gaps in both approaches and to better quantify remaining uncertainty.
Haklim Choi, Alison L. Redington, Hyeri Park, Jooil Kim, Rona L. Thompson, Jens Mühle, Peter K. Salameh, Christina M. Harth, Ray F. Weiss, Alistair J. Manning, and Sunyoung Park
Atmos. Chem. Phys., 24, 7309–7330, https://doi.org/10.5194/acp-24-7309-2024, https://doi.org/10.5194/acp-24-7309-2024, 2024
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We analyzed with an inversion model the atmospheric abundance of hydrofluorocarbons (HFCs), potent greenhouse gases, from 2008 to 2020 at Gosan station in South Korea and revealed a significant increase in emissions, especially from eastern China and Japan. This increase contradicts reported data, underscoring the need for accurate monitoring and reporting. Our findings are crucial for understanding and managing global HFCs emissions, highlighting the importance of efforts to reduce HFCs.
Hanqin Tian, Naiqing Pan, Rona L. Thompson, Josep G. Canadell, Parvadha Suntharalingam, Pierre Regnier, Eric A. Davidson, Michael Prather, Philippe Ciais, Marilena Muntean, Shufen Pan, Wilfried Winiwarter, Sönke Zaehle, Feng Zhou, Robert B. Jackson, Hermann W. Bange, Sarah Berthet, Zihao Bian, Daniele Bianchi, Alexander F. Bouwman, Erik T. Buitenhuis, Geoffrey Dutton, Minpeng Hu, Akihiko Ito, Atul K. Jain, Aurich Jeltsch-Thömmes, Fortunat Joos, Sian Kou-Giesbrecht, Paul B. Krummel, Xin Lan, Angela Landolfi, Ronny Lauerwald, Ya Li, Chaoqun Lu, Taylor Maavara, Manfredi Manizza, Dylan B. Millet, Jens Mühle, Prabir K. Patra, Glen P. Peters, Xiaoyu Qin, Peter Raymond, Laure Resplandy, Judith A. Rosentreter, Hao Shi, Qing Sun, Daniele Tonina, Francesco N. Tubiello, Guido R. van der Werf, Nicolas Vuichard, Junjie Wang, Kelley C. Wells, Luke M. Western, Chris Wilson, Jia Yang, Yuanzhi Yao, Yongfa You, and Qing Zhu
Earth Syst. Sci. Data, 16, 2543–2604, https://doi.org/10.5194/essd-16-2543-2024, https://doi.org/10.5194/essd-16-2543-2024, 2024
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Atmospheric concentrations of nitrous oxide (N2O), a greenhouse gas 273 times more potent than carbon dioxide, have increased by 25 % since the preindustrial period, with the highest observed growth rate in 2020 and 2021. This rapid growth rate has primarily been due to a 40 % increase in anthropogenic emissions since 1980. Observed atmospheric N2O concentrations in recent years have exceeded the worst-case climate scenario, underscoring the importance of reducing anthropogenic N2O emissions.
Rona L. Thompson, Stephen A. Montzka, Martin K. Vollmer, Jgor Arduini, Molly Crotwell, Paul B. Krummel, Chris Lunder, Jens Mühle, Simon O'Doherty, Ronald G. Prinn, Stefan Reimann, Isaac Vimont, Hsiang Wang, Ray F. Weiss, and Dickon Young
Atmos. Chem. Phys., 24, 1415–1427, https://doi.org/10.5194/acp-24-1415-2024, https://doi.org/10.5194/acp-24-1415-2024, 2024
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The hydroxyl radical determines the atmospheric lifetimes of numerous species including methane. Since OH is very short-lived, it is not possible to directly measure its concentration on scales relevant for understanding its effect on other species. Here, OH is inferred by looking at changes in hydrofluorocarbons (HFCs). We find that OH levels have been fairly stable over our study period (2004 to 2021), suggesting that OH is not the main driver of the recent increase in atmospheric methane.
Matthew J. McGrath, Ana Maria Roxana Petrescu, Philippe Peylin, Robbie M. Andrew, Bradley Matthews, Frank Dentener, Juraj Balkovič, Vladislav Bastrikov, Meike Becker, Gregoire Broquet, Philippe Ciais, Audrey Fortems-Cheiney, Raphael Ganzenmüller, Giacomo Grassi, Ian Harris, Matthew Jones, Jürgen Knauer, Matthias Kuhnert, Guillaume Monteil, Saqr Munassar, Paul I. Palmer, Glen P. Peters, Chunjing Qiu, Mart-Jan Schelhaas, Oksana Tarasova, Matteo Vizzarri, Karina Winkler, Gianpaolo Balsamo, Antoine Berchet, Peter Briggs, Patrick Brockmann, Frédéric Chevallier, Giulia Conchedda, Monica Crippa, Stijn N. C. Dellaert, Hugo A. C. Denier van der Gon, Sara Filipek, Pierre Friedlingstein, Richard Fuchs, Michael Gauss, Christoph Gerbig, Diego Guizzardi, Dirk Günther, Richard A. Houghton, Greet Janssens-Maenhout, Ronny Lauerwald, Bas Lerink, Ingrid T. Luijkx, Géraud Moulas, Marilena Muntean, Gert-Jan Nabuurs, Aurélie Paquirissamy, Lucia Perugini, Wouter Peters, Roberto Pilli, Julia Pongratz, Pierre Regnier, Marko Scholze, Yusuf Serengil, Pete Smith, Efisio Solazzo, Rona L. Thompson, Francesco N. Tubiello, Timo Vesala, and Sophia Walther
Earth Syst. Sci. Data, 15, 4295–4370, https://doi.org/10.5194/essd-15-4295-2023, https://doi.org/10.5194/essd-15-4295-2023, 2023
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Accurate estimation of fluxes of carbon dioxide from the land surface is essential for understanding future impacts of greenhouse gas emissions on the climate system. A wide variety of methods currently exist to estimate these sources and sinks. We are continuing work to develop annual comparisons of these diverse methods in order to clarify what they all actually calculate and to resolve apparent disagreement, in addition to highlighting opportunities for increased understanding.
Hyeri Park, Jooil Kim, Haklim Choi, Sohyeon Geum, Yeaseul Kim, Rona L. Thompson, Jens Mühle, Peter K. Salameh, Christina M. Harth, Kieran M. Stanley, Simon O'Doherty, Paul J. Fraser, Peter G. Simmonds, Paul B. Krummel, Ray F. Weiss, Ronald G. Prinn, and Sunyoung Park
Atmos. Chem. Phys., 23, 9401–9411, https://doi.org/10.5194/acp-23-9401-2023, https://doi.org/10.5194/acp-23-9401-2023, 2023
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Based on atmospheric HFC-23 observations, the first estimate of post-CDM HFC-23 emissions in eastern Asia for 2008–2019 shows that these emissions contribute significantly to the global emissions rise. The observation-derived emissions were much larger than the bottom-up estimates expected to approach zero after 2015 due to national abatement activities. These discrepancies could be attributed to unsuccessful factory-level HFC-23 abatement and inaccurate quantification of emission reductions.
Sophie Wittig, Antoine Berchet, Isabelle Pison, Marielle Saunois, Joël Thanwerdas, Adrien Martinez, Jean-Daniel Paris, Toshinobu Machida, Motoki Sasakawa, Douglas E. J. Worthy, Xin Lan, Rona L. Thompson, Espen Sollum, and Mikhail Arshinov
Atmos. Chem. Phys., 23, 6457–6485, https://doi.org/10.5194/acp-23-6457-2023, https://doi.org/10.5194/acp-23-6457-2023, 2023
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Here, an inverse modelling approach is applied to estimate CH4 sources and sinks in the Arctic from 2008 to 2019. We study the magnitude, seasonal patterns and trends from different sources during recent years. We also assess how the current observation network helps to constrain fluxes. We find that constraints are only significant for North America and, to a lesser extent, West Siberia, where the observation network is relatively dense. We find no clear trend over the period of inversion.
Anja Eichler, Michel Legrand, Theo M. Jenk, Susanne Preunkert, Camilla Andersson, Sabine Eckhardt, Magnuz Engardt, Andreas Plach, and Margit Schwikowski
The Cryosphere, 17, 2119–2137, https://doi.org/10.5194/tc-17-2119-2023, https://doi.org/10.5194/tc-17-2119-2023, 2023
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We investigate how a 250-year history of the emission of air pollutants (major inorganic aerosol constituents, black carbon, and trace species) is preserved in ice cores from four sites in the European Alps. The observed uniform timing in species-dependent longer-term concentration changes reveals that the different ice-core records provide a consistent, spatially representative signal of the pollution history from western European countries.
Rüdiger Brecht, Lucie Bakels, Alex Bihlo, and Andreas Stohl
Geosci. Model Dev., 16, 2181–2192, https://doi.org/10.5194/gmd-16-2181-2023, https://doi.org/10.5194/gmd-16-2181-2023, 2023
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We use neural-network-based single-image super-resolution to improve the upscaling of meteorological wind fields to be used for particle dispersion models. This deep-learning-based methodology improves the standard linear interpolation typically used in particle dispersion models. The improvement of wind fields leads to substantial improvement in the computed trajectories of the particles.
Ana Maria Roxana Petrescu, Chunjing Qiu, Matthew J. McGrath, Philippe Peylin, Glen P. Peters, Philippe Ciais, Rona L. Thompson, Aki Tsuruta, Dominik Brunner, Matthias Kuhnert, Bradley Matthews, Paul I. Palmer, Oksana Tarasova, Pierre Regnier, Ronny Lauerwald, David Bastviken, Lena Höglund-Isaksson, Wilfried Winiwarter, Giuseppe Etiope, Tuula Aalto, Gianpaolo Balsamo, Vladislav Bastrikov, Antoine Berchet, Patrick Brockmann, Giancarlo Ciotoli, Giulia Conchedda, Monica Crippa, Frank Dentener, Christine D. Groot Zwaaftink, Diego Guizzardi, Dirk Günther, Jean-Matthieu Haussaire, Sander Houweling, Greet Janssens-Maenhout, Massaer Kouyate, Adrian Leip, Antti Leppänen, Emanuele Lugato, Manon Maisonnier, Alistair J. Manning, Tiina Markkanen, Joe McNorton, Marilena Muntean, Gabriel D. Oreggioni, Prabir K. Patra, Lucia Perugini, Isabelle Pison, Maarit T. Raivonen, Marielle Saunois, Arjo J. Segers, Pete Smith, Efisio Solazzo, Hanqin Tian, Francesco N. Tubiello, Timo Vesala, Guido R. van der Werf, Chris Wilson, and Sönke Zaehle
Earth Syst. Sci. Data, 15, 1197–1268, https://doi.org/10.5194/essd-15-1197-2023, https://doi.org/10.5194/essd-15-1197-2023, 2023
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This study updates the state-of-the-art scientific overview of CH4 and N2O emissions in the EU27 and UK in Petrescu et al. (2021a). Yearly updates are needed to improve the different respective approaches and to inform on the development of formal verification systems. It integrates the most recent emission inventories, process-based model and regional/global inversions, comparing them with UNFCCC national GHG inventories, in support to policy to facilitate real-time verification procedures.
Rona L. Thompson and Ignacio Pisso
Atmos. Meas. Tech., 16, 235–246, https://doi.org/10.5194/amt-16-235-2023, https://doi.org/10.5194/amt-16-235-2023, 2023
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Atmospheric networks are used for monitoring air quality and greenhouse gases and can provide essential information about the sources and sinks. The design of the network, specifically where to place the observations, is a critical question in order to maximize the information provided while minimizing the cost. Here, a novel method of designing atmospheric networks is presented with two examples, one on monitoring sources of methane and the second on monitoring fossil fuel emissions of CO2.
Matthew Boyer, Diego Aliaga, Jakob Boyd Pernov, Hélène Angot, Lauriane L. J. Quéléver, Lubna Dada, Benjamin Heutte, Manuel Dall'Osto, David C. S. Beddows, Zoé Brasseur, Ivo Beck, Silvia Bucci, Marina Duetsch, Andreas Stohl, Tiia Laurila, Eija Asmi, Andreas Massling, Daniel Charles Thomas, Jakob Klenø Nøjgaard, Tak Chan, Sangeeta Sharma, Peter Tunved, Radovan Krejci, Hans Christen Hansson, Federico Bianchi, Katrianne Lehtipalo, Alfred Wiedensohler, Kay Weinhold, Markku Kulmala, Tuukka Petäjä, Mikko Sipilä, Julia Schmale, and Tuija Jokinen
Atmos. Chem. Phys., 23, 389–415, https://doi.org/10.5194/acp-23-389-2023, https://doi.org/10.5194/acp-23-389-2023, 2023
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The Arctic is a unique environment that is warming faster than other locations on Earth. We evaluate measurements of aerosol particles, which can influence climate, over the central Arctic Ocean for a full year and compare the data to land-based measurement stations across the Arctic. Our measurements show that the central Arctic has similarities to but also distinct differences from the stations further south. We note that this may change as the Arctic warms and sea ice continues to decline.
Andreas Plach, Rolf Rüfenacht, Simone Kotthaus, and Markus Leuenberger
EGUsphere, https://doi.org/10.5194/egusphere-2022-1019, https://doi.org/10.5194/egusphere-2022-1019, 2022
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Greenhouse gases emissions are contributing to global warming and it is essential to better understand where they originate from and how they are transported. In this study we analyze greenhouse gas observations at a Swiss tall tower where measurements are taken more than 200 m above ground and investigate their origin by looking at the condition of the atmosphere at the time of the observations. We find that most pollution at this site is caused from emissions transported from further away.
Zhu Deng, Philippe Ciais, Zitely A. Tzompa-Sosa, Marielle Saunois, Chunjing Qiu, Chang Tan, Taochun Sun, Piyu Ke, Yanan Cui, Katsumasa Tanaka, Xin Lin, Rona L. Thompson, Hanqin Tian, Yuanzhi Yao, Yuanyuan Huang, Ronny Lauerwald, Atul K. Jain, Xiaoming Xu, Ana Bastos, Stephen Sitch, Paul I. Palmer, Thomas Lauvaux, Alexandre d'Aspremont, Clément Giron, Antoine Benoit, Benjamin Poulter, Jinfeng Chang, Ana Maria Roxana Petrescu, Steven J. Davis, Zhu Liu, Giacomo Grassi, Clément Albergel, Francesco N. Tubiello, Lucia Perugini, Wouter Peters, and Frédéric Chevallier
Earth Syst. Sci. Data, 14, 1639–1675, https://doi.org/10.5194/essd-14-1639-2022, https://doi.org/10.5194/essd-14-1639-2022, 2022
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In support of the global stocktake of the Paris Agreement on climate change, we proposed a method for reconciling the results of global atmospheric inversions with data from UNFCCC national greenhouse gas inventories (NGHGIs). Here, based on a new global harmonized database that we compiled from the UNFCCC NGHGIs and a comprehensive framework presented in this study to process the results of inversions, we compared their results of carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O).
Hanna K. Lappalainen, Tuukka Petäjä, Timo Vihma, Jouni Räisänen, Alexander Baklanov, Sergey Chalov, Igor Esau, Ekaterina Ezhova, Matti Leppäranta, Dmitry Pozdnyakov, Jukka Pumpanen, Meinrat O. Andreae, Mikhail Arshinov, Eija Asmi, Jianhui Bai, Igor Bashmachnikov, Boris Belan, Federico Bianchi, Boris Biskaborn, Michael Boy, Jaana Bäck, Bin Cheng, Natalia Chubarova, Jonathan Duplissy, Egor Dyukarev, Konstantinos Eleftheriadis, Martin Forsius, Martin Heimann, Sirkku Juhola, Vladimir Konovalov, Igor Konovalov, Pavel Konstantinov, Kajar Köster, Elena Lapshina, Anna Lintunen, Alexander Mahura, Risto Makkonen, Svetlana Malkhazova, Ivan Mammarella, Stefano Mammola, Stephany Buenrostro Mazon, Outi Meinander, Eugene Mikhailov, Victoria Miles, Stanislav Myslenkov, Dmitry Orlov, Jean-Daniel Paris, Roberta Pirazzini, Olga Popovicheva, Jouni Pulliainen, Kimmo Rautiainen, Torsten Sachs, Vladimir Shevchenko, Andrey Skorokhod, Andreas Stohl, Elli Suhonen, Erik S. Thomson, Marina Tsidilina, Veli-Pekka Tynkkynen, Petteri Uotila, Aki Virkkula, Nadezhda Voropay, Tobias Wolf, Sayaka Yasunaka, Jiahua Zhang, Yubao Qiu, Aijun Ding, Huadong Guo, Valery Bondur, Nikolay Kasimov, Sergej Zilitinkevich, Veli-Matti Kerminen, and Markku Kulmala
Atmos. Chem. Phys., 22, 4413–4469, https://doi.org/10.5194/acp-22-4413-2022, https://doi.org/10.5194/acp-22-4413-2022, 2022
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We summarize results during the last 5 years in the northern Eurasian region, especially from Russia, and introduce recent observations of the air quality in the urban environments in China. Although the scientific knowledge in these regions has increased, there are still gaps in our understanding of large-scale climate–Earth surface interactions and feedbacks. This arises from limitations in research infrastructures and integrative data analyses, hindering a comprehensive system analysis.
Stephen M. Platt, Øystein Hov, Torunn Berg, Knut Breivik, Sabine Eckhardt, Konstantinos Eleftheriadis, Nikolaos Evangeliou, Markus Fiebig, Rebecca Fisher, Georg Hansen, Hans-Christen Hansson, Jost Heintzenberg, Ove Hermansen, Dominic Heslin-Rees, Kim Holmén, Stephen Hudson, Roland Kallenborn, Radovan Krejci, Terje Krognes, Steinar Larssen, David Lowry, Cathrine Lund Myhre, Chris Lunder, Euan Nisbet, Pernilla B. Nizzetto, Ki-Tae Park, Christina A. Pedersen, Katrine Aspmo Pfaffhuber, Thomas Röckmann, Norbert Schmidbauer, Sverre Solberg, Andreas Stohl, Johan Ström, Tove Svendby, Peter Tunved, Kjersti Tørnkvist, Carina van der Veen, Stergios Vratolis, Young Jun Yoon, Karl Espen Yttri, Paul Zieger, Wenche Aas, and Kjetil Tørseth
Atmos. Chem. Phys., 22, 3321–3369, https://doi.org/10.5194/acp-22-3321-2022, https://doi.org/10.5194/acp-22-3321-2022, 2022
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Here we detail the history of the Zeppelin Observatory, a unique global background site and one of only a few in the high Arctic. We present long-term time series of up to 30 years of atmospheric components and atmospheric transport phenomena. Many of these time series are important to our understanding of Arctic and global atmospheric composition change. Finally, we discuss the future of the Zeppelin Observatory and emerging areas of future research on the Arctic atmosphere.
Antoine Berchet, Espen Sollum, Rona L. Thompson, Isabelle Pison, Joël Thanwerdas, Grégoire Broquet, Frédéric Chevallier, Tuula Aalto, Adrien Berchet, Peter Bergamaschi, Dominik Brunner, Richard Engelen, Audrey Fortems-Cheiney, Christoph Gerbig, Christine D. Groot Zwaaftink, Jean-Matthieu Haussaire, Stephan Henne, Sander Houweling, Ute Karstens, Werner L. Kutsch, Ingrid T. Luijkx, Guillaume Monteil, Paul I. Palmer, Jacob C. A. van Peet, Wouter Peters, Philippe Peylin, Elise Potier, Christian Rödenbeck, Marielle Saunois, Marko Scholze, Aki Tsuruta, and Yuanhong Zhao
Geosci. Model Dev., 14, 5331–5354, https://doi.org/10.5194/gmd-14-5331-2021, https://doi.org/10.5194/gmd-14-5331-2021, 2021
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We present here the Community Inversion Framework (CIF) to help rationalize development efforts and leverage the strengths of individual inversion systems into a comprehensive framework. The CIF is a programming protocol to allow various inversion bricks to be exchanged among researchers.
The ensemble of bricks makes a flexible, transparent and open-source Python-based tool. We describe the main structure and functionalities and demonstrate it in a simple academic case.
Cited articles
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Berchet, A., Sollum, E., Thompson, R. L., Pison, I., Thanwerdas, J., Broquet, G., Chevallier, F., Aalto, T., Berchet, A., Bergamaschi, P., Brunner, D., Engelen, R., Fortems-Cheiney, A., Gerbig, C., Groot Zwaaftink, C. D., Haussaire, J.-M., Henne, S., Houweling, S., Karstens, U., Kutsch, W. L., Luijkx, I. T., Monteil, G., Palmer, P. I., van Peet, J. C. A., Peters, W., Peylin, P., Potier, E., Rödenbeck, C., Saunois, M., Scholze, M., Tsuruta, A., and Zhao, Y.: The Community Inversion Framework v1.0: a unified system for atmospheric inversion studies, Geosci. Model Dev., 14, 5331–5354, https://doi.org/10.5194/gmd-14-5331-2021, 2021. a
Brunner, D., Arnold, T., Henne, S., Manning, A., Thompson, R. L., Maione, M., O'Doherty, S., and Reimann, S.: Comparison of four inverse modelling systems applied to the estimation of HFC-125, HFC-134a, and SF6 emissions over Europe, Atmos. Chem. Phys., 17, 10651–10674, https://doi.org/10.5194/acp-17-10651-2017, 2017. a, b, c
CIESIN: Center for International Earth Science Information Network, Columbia University, Gridded Population of the World, Version 4 (GPWv4): Population Density, Revision 11, NASA Socioeconomic Data and Applications Center (SEDAC), Palisades, NY, https://doi.org/10.7927/H49C6VHW (last access: 27 April 2022), 2018. a
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Fang, X., Thompson, R. L., Saito, T., Yokouchi, Y., Kim, J., Li, S., Kim, K. R., Park, S., Graziosi, F., and Stohl, A.: Sulfur hexafluoride (SF6) emissions in East Asia determined by inverse modeling, Atmos. Chem. Phys., 14, 4779–4791, https://doi.org/10.5194/acp-14-4779-2014, 2014. a, b, c
Fang, X., Stohl, A., Yokouchi, Y., Kim, J., Li, S., Saito, T., Park, S., and Hu, J.: Multiannual Top-Down Estimate of HFC-23 Emissions in East Asia, Environ. Sci. Technol., 49, 4345–4353, https://doi.org/10.1021/es505669j, 2015. a
Fang, X., Yao, B., Vollmer, M. K., Reimann, S., Liu, L., Chen, L., Prinn, R. G., and Hu, J.: Changes in HCFC Emissions in China During 2011–2017, Geophys. Res. Lett., 46, 10034–10042, https://doi.org/10.1029/2019GL083169, 2019. a
FLEXPART developer team: FLEXPART v10.4, FLEXPART [code], https://www.flexpart.eu/downloads/66, last access: 27 April 2022. a
Ganesan, A. L., Rigby, M., Zammit-Mangion, A., Manning, A. J., Prinn, R. G., Fraser, P. J., Harth, C. M., Kim, K.-R., Krummel, P. B., Li, S., Mühle, J., O'Doherty, S. J., Park, S., Salameh, P. K., Steele, L. P., and Weiss, R. F.: Characterization of uncertainties in atmospheric trace gas inversions using hierarchical Bayesian methods, Atmos. Chem. Phys., 14, 3855–3864, https://doi.org/10.5194/acp-14-3855-2014, 2014. a
Ganshin, A., Oda, T., Saito, M., Maksyutov, S., Valsala, V., Andres, R. J., Fisher, R. E., Lowry, D., Lukyanov, A., Matsueda, H., Nisbet, E. G., Rigby, M., Sawa, Y., Toumi, R., Tsuboi, K., Varlagin, A., and Zhuravlev, R.: A global coupled Eulerian-Lagrangian model and 1×1 km CO2 surface flux dataset for high-resolution atmospheric CO2 transport simulations, Geosci. Model Dev., 5, 231–243, https://doi.org/10.5194/gmd-5-231-2012, 2012. a
Groot Zwaaftink, C. D., Henne, S., Thompson, R. L., Dlugokencky, E. J., Machida, T., Paris, J.-D., Sasakawa, M., Segers, A., Sweeney, C., and Stohl, A.: Three-dimensional methane distribution simulated with FLEXPART 8-CTM-1.1 constrained with observation data, Geosci. Model Dev., 11, 4469–4487, https://doi.org/10.5194/gmd-11-4469-2018, 2018. a, b, c
Guillevic, M., Vollmer, M. K., Wyss, S. A., Leuenberger, D., Ackermann, A., Pascale, C., Niederhauser, B., and Reimann, S.: Dynamic–gravimetric preparation of metrologically traceable primary calibration standards for halogenated greenhouse gases, Atmos. Meas. Tech., 11, 3351–3372, https://doi.org/10.5194/amt-11-3351-2018, 2018. a
Henne, S., Brunner, D., Oney, B., Leuenberger, M., Eugster, W., Bamberger, I., Meinhardt, F., Steinbacher, M., and Emmenegger, L.: Validation of the Swiss methane emission inventory by atmospheric observations and inverse modelling, Atmos. Chem. Phys., 16, 3683–3710, https://doi.org/10.5194/acp-16-3683-2016, 2016. a, b, c
Henne, S., Brunner, D., Groot Zwaaftink, C., and Stohl, A.: FLEXPART 8-CTM-1.1: Atmospheric Lagrangian Particle Dispersion Model for global tracer transport (8-CTM-1.1), Zenodo [code], https://doi.org/10.5281/zenodo.1249190, 2018. a, b, c
Hersbach, H., de Rosnay, P., Bell, B., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Alonso-Balmaseda, M., Balsamo, G., Bechtold, P., Berrisford, P., Bidlot, J.-R., de Boisséson, E., Bonavita, M., Browne, P., Buizza, R., Dahlgren, P., Dee, D., Dragani, R., Diamantakis, M., Flemming, J., Forbes, R., Geer, A., Haiden, T., Hólm, E., Haimberger, L., Hogan, R., Horányi, A., Janiskova, M., Laloyaux, P., Lopez, P., Munoz-Sabater, J., Peubey, C., Radu, R., Richardson, D., Thépaut, J.-N., Vitart, F., Yang, X., Zsótér, E., and Zuo, H.: Operational global reanalysis: progress, future directions and synergies with NWP, ERA Report, https://doi.org/10.21957/tkic6g3wm, 2018. a
Hu, L., Andrews, A. E., Thoning, K. W., Sweeney, C., Miller, J. B., Michalak, A. M., Dlugokencky, E., Tans, P. P., Shiga, Y. P., Mountain, M., Nehrkorn, T., Montzka, S. A., McKain, K., Kofler, J., Trudeau, M., Michel, S. E., Biraud, S. C., Fischer, M. L., Worthy, D. E. J., Vaughn, B. H., White, J. W. C., Yadav, V., Basu, S., and van der Velde, I. R.: Enhanced North American carbon uptake associated with El Niño, Science Advances, 5, eaaw0076, https://doi.org/10.1126/sciadv.aaw0076, 2019. a
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Keller, C. A., Hill, M., Vollmer, M. K., Henne, S., Brunner, D., Reimann, S., O'Doherty, S., Arduini, J., Maione, M., Ferenczi, Z., Haszpra, L., Manning, A. J., and Peter, T.: European emissions of halogenated greenhouse gases inferred from atmospheric measurements, Environ. Sci. Technol., 46, 217–225, https://doi.org/10.1021/es202453j, 2012. a
Koyama, Y., Maksyutov, S., Mukai, H., Thoning, K., and Tans, P.: Simulation of variability in atmospheric carbon dioxide using a global coupled Eulerian – Lagrangian transport model, Geosci. Model Dev., 4, 317–324, https://doi.org/10.5194/gmd-4-317-2011, 2011. a, b
Leip, A., Skiba, U., Vermeulen, A., and Thompson, R. L.: A complete rethink is needed on how greenhouse gas emissions are quantified for national reporting, Atmos. Environ., 174, 237–240, https://doi.org/10.1016/j.atmosenv.2017.12.006, 2017. a
Lunt, M. F., Rigby, M., Ganesan, A. L., and Manning, A. J.: Estimation of trace gas fluxes with objectively determined basis functions using reversible-jump Markov chain Monte Carlo, Geosci. Model Dev., 9, 3213–3229, https://doi.org/10.5194/gmd-9-3213-2016, 2016. a, b
Maione, M., Graziosi, F., Arduini, J., Furlani, F., Giostra, U., Blake, D. R., Bonasoni, P., Fang, X., Montzka, S. A., O'Doherty, S. J., Reimann, S., Stohl, A., and Vollmer, M. K.: Estimates of European emissions of methyl chloroform using a Bayesian inversion method, Atmos. Chem. Phys., 14, 9755–9770, https://doi.org/10.5194/acp-14-9755-2014, 2014. a
Manning, A. J., Redington, A. L., Say, D., O'Doherty, S., Young, D., Simmonds, P. G., Vollmer, M. K., Mühle, J., Arduini, J., Spain, G., Wisher, A., Maione, M., Schuck, T. J., Stanley, K., Reimann, S., Engel, A., Krummel, P. B., Fraser, P. J., Harth, C. M., Salameh, P. K., Weiss, R. F., Gluckman, R., Brown, P. N., Watterson, J. D., and Arnold, T.: Evidence of a recent decline in UK emissions of hydrofluorocarbons determined by the InTEM inverse model and atmospheric measurements, Atmos. Chem. Phys., 21, 12739–12755, https://doi.org/10.5194/acp-21-12739-2021, 2021. a, b
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Monteil, G. and Scholze, M.: Regional CO2 inversions with LUMIA, the Lund University Modular Inversion Algorithm, v1.0, Geosci. Model Dev., 14, 3383–3406, https://doi.org/10.5194/gmd-14-3383-2021, 2021. a
Myhre, G., Shindell, D., Bréon, F.-M., Collins, W., Fuglestvedt, J., Huang, J., Koch, D., Lamarque, J.-F., Lee, D., Mendoza, B., Nakajima, T., Robock, A., Stephens, G., Takemura, T., and Zhang, H.: Anthropogenic and natural radiative forcing, Cambridge University Press, Cambridge, UK, 659–740, https://doi.org/10.1017/CBO9781107415324.018, 2013. a
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Short summary
In light of recent global warming, we aim to improve methods for modeling greenhouse gas emissions in order to support the successful implementation of the Paris Agreement. In this study, we investigate certain aspects of a Bayesian inversion method that uses computer simulations and atmospheric observations to improve estimates of greenhouse gas emissions. We explore method limitations, discuss problems, and suggest improvements.
In light of recent global warming, we aim to improve methods for modeling greenhouse gas...
Special issue