Articles | Volume 25, issue 18
https://doi.org/10.5194/acp-25-10747-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-25-10747-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
18 Sep 2025
Research article |
| 18 Sep 2025
Modeling support for an extensive Δ14CO2 flask sample monitoring campaign over Europe to constrain fossil CO2 emissions
Carlos Gómez-Ortiz
CORRESPONDING AUTHOR
Department of Physical Geography and Ecosystem Science, Lund University, Lund, Sweden
Guillaume Monteil
Department of Physical Geography and Ecosystem Science, Lund University, Lund, Sweden
Barcelona Supercomputing Centre (BSC), Barcelona, Spain
Ute Karstens
ICOS ERIC – Carbon Portal, Department of Physical Geography and Ecosystem Science, Lund University, Lund, Sweden
Marko Scholze
Department of Physical Geography and Ecosystem Science, Lund University, Lund, Sweden
Related authors
Carlos Gómez-Ortiz, Guillaume Monteil, Sourish Basu, and Marko Scholze
Atmos. Chem. Phys., 25, 397–424, https://doi.org/10.5194/acp-25-397-2025, https://doi.org/10.5194/acp-25-397-2025, 2025
Short summary
Short summary
In this paper, we test new implementations of our inverse modeling tool to estimate the weekly and regional CO2 emissions from fossil fuels in Europe. We use synthetic atmospheric observations of CO2 and radiocarbon (14CO2) to trace emissions to their sources, while separating the natural and fossil CO2. Our tool accurately estimates fossil CO2 emissions in densely monitored regions like western/central Europe. This approach aids in developing strategies for reducing CO2 emissions.
Jalisha Theanutti Kallingal, Marko Scholze, Paul Anthony Miller, Johan Lindström, Janne Rinne, Mika Aurela, Patrik Vestin, and Per Weslien
Biogeosciences, 22, 4061–4086, https://doi.org/10.5194/bg-22-4061-2025, https://doi.org/10.5194/bg-22-4061-2025, 2025
Short summary
Short summary
We explored the possibilities of a Bayesian-based data assimilation algorithm to improve the wetland CH4 flux estimates by a dynamic vegetation model. By assimilating CH4 observations from 14 wetland sites, we calibrated model parameters and estimated large-scale annual emissions from northern wetlands. Our findings indicate that this approach leads to more reliable estimates of CH4 dynamics, which will improve our understanding of the climate change feedback from wetland CH4 emissions.
August Thomasson, Pontus Roldin, Nick Schutgens, Babitha George, Hugo Denier van der Gon, Guillaume Monteil, and Marko Scholze
EGUsphere, https://doi.org/10.5194/egusphere-2025-1568, https://doi.org/10.5194/egusphere-2025-1568, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
We present top-down black carbon emissions estimates in Europe based on surface observations of concentrations at 24 rural sites from 2021. The annual emissions are 411 ± 10 Gg, overall 18 % higher compared to a traditional bottom-up estimate. Emissions are higher in for instance eastern Europe and the Iberian peninsula but lower in Poland and Italy. Validation with independent observations show overall better match and the uncertainties are reduced.
Eleftherios Ioannidis, Antoon Meesters, Michael Steiner, Dominik Brunner, Friedemann Reum, Isabelle Pison, Antoine Berchet, Rona Thompson, Espen Sollum, Frank-Thomas Koch, Christoph Gerbig, Fenjuan Wang, Shamil Maksyutov, Aki Tsuruta, Maria Tenkanen, Tuula Aalto, Guillaume Monteil, Hong Lin, Ge Ren, Marko Scholze, and Sander Houweling
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-235, https://doi.org/10.5194/essd-2025-235, 2025
Preprint under review for ESSD
Short summary
Short summary
This paper describes a detailed study on CH4 European emissions, using different methodologies (9 total inverse models). The study spans over 15 years and provides detailed information on European CH4 emission trends and seasonality, using in-situ data, including ICOS network. Our results highlight the importance of improving details in the inversion setup, such as the treatment of lateral boundary conditions to narrow the uncertainty ranges further.
Ida Storm, Ute Karstens, Claudio D’Onofrio, Alex Vermeulen, Samuel Hammer, Ingrid Super, Theo Glauch, and Wouter Peters
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-63, https://doi.org/10.5194/essd-2025-63, 2025
Preprint under review for ESSD
Short summary
Short summary
Many cities are committed to ambitious CO2 emission reduction targets, supported by climate action plans. Atmospheric measurements are essential to verify that these efforts lead to the expected reductions. Here, we characterize and compare 96 European cities across 18 metrics, linking them to four major challenges in CO2 emissions monitoring. Our framework includes a tool with additional cities and metrics, as well as "mapbooks" for the 96 cities.
Wolfgang Knorr, Matthew Williams, Tea Thum, Thomas Kaminski, Michael Voßbeck, Marko Scholze, Tristan Quaife, T. Luke Smallman, Susan C. Steele-Dunne, Mariette Vreugdenhil, Tim Green, Sönke Zaehle, Mika Aurela, Alexandre Bouvet, Emanuel Bueechi, Wouter Dorigo, Tarek S. El-Madany, Mirco Migliavacca, Marika Honkanen, Yann H. Kerr, Anna Kontu, Juha Lemmetyinen, Hannakaisa Lindqvist, Arnaud Mialon, Tuuli Miinalainen, Gaétan Pique, Amanda Ojasalo, Shaun Quegan, Peter J. Rayner, Pablo Reyes-Muñoz, Nemesio Rodríguez-Fernández, Mike Schwank, Jochem Verrelst, Songyan Zhu, Dirk Schüttemeyer, and Matthias Drusch
Geosci. Model Dev., 18, 2137–2159, https://doi.org/10.5194/gmd-18-2137-2025, https://doi.org/10.5194/gmd-18-2137-2025, 2025
Short summary
Short summary
When it comes to climate change, the land surface is where the vast majority of impacts happen. The task of monitoring those impacts across the globe is formidable and must necessarily rely on satellites – at a significant cost: the measurements are only indirect and require comprehensive physical understanding. We have created a comprehensive modelling system that we offer to the research community to explore how satellite data can be better exploited to help us capture the changes that happen on our lands.
Maksym Gachkivskyi, Ute Karstens, Bernd Fischer, Dagmar Kubistin, Jennifer Müller-Williams, Matthias Lindauer, and Ingeborg Levin
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-551, https://doi.org/10.5194/essd-2024-551, 2025
Revised manuscript accepted for ESSD
Short summary
Short summary
222Radon (Rn) can be used to distinguish marine and continental air masses or to validate transport models. The Heidelberg Radon Monitor (HRM) measures 214Polonium (Po), a progeny of Rn. This study presents Po-based Rn activity concentrations measured with the HRM at 8 stations in Germany with guidelines for estimating Rn from Po measurements. Comparison between modeled and measured activity concentrations show that at high relative humidity Po measurements cannot be interpreted as Rn.
Fabian Maier, Eva Falge, Maksym Gachkivskyi, Stephan Henne, Ute Karstens, Dafina Kikaj, Ingeborg Levin, Alistair Manning, Christian Rödenbeck, and Christoph Gerbig
EGUsphere, https://doi.org/10.5194/egusphere-2025-477, https://doi.org/10.5194/egusphere-2025-477, 2025
Short summary
Short summary
The radioactive noble gas radon (222Rn) is a suitable natural tracer for atmospheric transport and mixing processes that can be used to validate and calibrate atmospheric transport models. However, this requires accurate estimates of the 222Rn flux from the soil into the atmosphere. In our study, we evaluate the reliability of process-based 222Rn flux maps for Europe using a 222Rn inversion. Our inversion results can give some indications on how to improve the process-based 222Rn flux maps.
Carlos Gómez-Ortiz, Guillaume Monteil, Sourish Basu, and Marko Scholze
Atmos. Chem. Phys., 25, 397–424, https://doi.org/10.5194/acp-25-397-2025, https://doi.org/10.5194/acp-25-397-2025, 2025
Short summary
Short summary
In this paper, we test new implementations of our inverse modeling tool to estimate the weekly and regional CO2 emissions from fossil fuels in Europe. We use synthetic atmospheric observations of CO2 and radiocarbon (14CO2) to trace emissions to their sources, while separating the natural and fossil CO2. Our tool accurately estimates fossil CO2 emissions in densely monitored regions like western/central Europe. This approach aids in developing strategies for reducing CO2 emissions.
Guillaume Monteil, Jalisha Theanutti Kallingal, and Marko Scholze
EGUsphere, https://doi.org/10.5194/egusphere-2024-3122, https://doi.org/10.5194/egusphere-2024-3122, 2024
Short summary
Short summary
Methane is a potent greenhouse gas, emitted both from natural and anthropogenic processes. Large uncertainties remain on its emission budget. Our study compares and combines two approaches to estimate European methane emissions, with a focus on wetlands, based on observed atmospheric CH4 concentrations and in-situ flux measurements. We find a good agreement and complementarity between the approaches, and identify obstacles towards a more integrated data-informed emission estimation system.
Camille Yver-Kwok, Michel Ramonet, Léonard Rivier, Jinghui Lian, Claudia Grossi, Roger Curcoll, Dafina Kikaj, Edward Chung, and Ute Karstens
EGUsphere, https://doi.org/10.5194/egusphere-2024-3107, https://doi.org/10.5194/egusphere-2024-3107, 2024
Short summary
Short summary
Here, we use greenhouse gas and radon data from a tall tower in France to estimate their fluxes within the station footprint from January 2017 to December 2022 using the Radon Tracer Method. Using the latest radon exhalation maps and standardized radon measurements, we found the greenhouse gas fluxes to be in agreement with the literature. Compared to inventories, there is a general agreement except for carbon dioxide where we show that the biogenic fluxes are not well represented in the model.
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
Short summary
Short summary
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.
Jalisha T. Kallingal, Johan Lindström, Paul A. Miller, Janne Rinne, Maarit Raivonen, and Marko Scholze
Geosci. Model Dev., 17, 2299–2324, https://doi.org/10.5194/gmd-17-2299-2024, https://doi.org/10.5194/gmd-17-2299-2024, 2024
Short summary
Short summary
By unlocking the mysteries of CH4 emissions from wetlands, our work improved the accuracy of the LPJ-GUESS vegetation model using Bayesian statistics. Via assimilation of long-term real data from a wetland, we significantly enhanced CH4 emission predictions. This advancement helps us better understand wetland contributions to atmospheric CH4, which are crucial for addressing climate change. Our method offers a promising tool for refining global climate models and guiding conservation efforts
Jalisha Theanutti Kallingal, Marko Scholze, Paul Anthony Miller, Johan Lindström, Janne Rinne, Mika Aurela, Patrik Vestin, and Per Weslien
EGUsphere, https://doi.org/10.5194/egusphere-2024-373, https://doi.org/10.5194/egusphere-2024-373, 2024
Preprint archived
Short summary
Short summary
Our study employs an Adaptive MCMC algorithm (GRaB-AM) to constrain process parameters in the wetlands emission module of the LPJ-GUESS model, using CH4 EC flux observations from 14 diverse wetlands. We aim to derive a single set of parameters capable of representing the diversity of northern wetlands. By reducing uncertainties in model parameters and improving simulation accuracy, our research contributes to more reliable projections of future wetland CH4 emissions and their climate impact.
Zhendong Wu, Alex Vermeulen, Yousuke Sawa, Ute Karstens, Wouter Peters, Remco de Kok, Xin Lan, Yasuyuki Nagai, Akinori Ogi, and Oksana Tarasova
Atmos. Chem. Phys., 24, 1249–1264, https://doi.org/10.5194/acp-24-1249-2024, https://doi.org/10.5194/acp-24-1249-2024, 2024
Short summary
Short summary
This study focuses on exploring the differences in calculating global surface CO2 and its growth rate, considering the impact of analysis methodologies and site selection. Our study reveals that the current global CO2 network has a good capacity to represent global surface CO2 and its growth rate, as well as trends in atmospheric CO2 mass changes. However, small differences exist in different analyses due to the impact of methodology and site selection.
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
Short summary
Short summary
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.
Alessandro Zanchetta, Linda M. J. Kooijmans, Steven van Heuven, Andrea Scifo, Hubertus A. Scheeren, Ivan Mammarella, Ute Karstens, Jin Ma, Maarten Krol, and Huilin Chen
Biogeosciences, 20, 3539–3553, https://doi.org/10.5194/bg-20-3539-2023, https://doi.org/10.5194/bg-20-3539-2023, 2023
Short summary
Short summary
Carbonyl sulfide (COS) has been suggested as a tool to estimate carbon dioxide (CO2) uptake by plants during photosynthesis. However, understanding its sources and sinks is critical to preventing biases in this estimate. Combining observations and models, this study proves that regional sources occasionally influence the measurements at the 60 m tall Lutjewad tower (1 m a.s.l.; 53°24′ N, 6°21′ E) in the Netherlands. Moreover, it estimates nighttime COS fluxes to be −3.0 ± 2.6 pmol m−2 s−1.
Ida Storm, Ute Karstens, Claudio D'Onofrio, Alex Vermeulen, and Wouter Peters
Atmos. Chem. Phys., 23, 4993–5008, https://doi.org/10.5194/acp-23-4993-2023, https://doi.org/10.5194/acp-23-4993-2023, 2023
Short summary
Short summary
In this study, we evaluate what is in the influence regions of the ICOS atmospheric measurement stations to gain insight into what land cover types and land-cover-associated fluxes the network represents. Subsequently, insights about strengths, weaknesses, and potential gaps can assist in future network expansion decisions. The network is concentrated in central Europe, which leads to a general overrepresentation of coniferous forest and cropland and underrepresentation of grass and shrubland.
Saqr Munassar, Guillaume Monteil, Marko Scholze, Ute Karstens, Christian Rödenbeck, Frank-Thomas Koch, Kai U. Totsche, and Christoph Gerbig
Atmos. Chem. Phys., 23, 2813–2828, https://doi.org/10.5194/acp-23-2813-2023, https://doi.org/10.5194/acp-23-2813-2023, 2023
Short summary
Short summary
Using different transport models results in large errors in optimized fluxes in the atmospheric inversions. Boundary conditions and inversion system configurations lead to a smaller but non-negligible impact. The findings highlight the importance to validate transport models for further developments but also to properly account for such errors in inverse modelling. This will help narrow the convergence of gas estimates reported in the scientific literature from different inversion frameworks.
Auke M. van der Woude, Remco de Kok, Naomi Smith, Ingrid T. Luijkx, Santiago Botía, Ute Karstens, Linda M. J. Kooijmans, Gerbrand Koren, Harro A. J. Meijer, Gert-Jan Steeneveld, Ida Storm, Ingrid Super, Hubertus A. Scheeren, Alex Vermeulen, and Wouter Peters
Earth Syst. Sci. Data, 15, 579–605, https://doi.org/10.5194/essd-15-579-2023, https://doi.org/10.5194/essd-15-579-2023, 2023
Short summary
Short summary
To monitor the progress towards the CO2 emission goals set out in the Paris Agreement, the European Union requires an independent validation of emitted CO2. For this validation, atmospheric measurements of CO2 can be used, together with first-guess estimates of CO2 emissions and uptake. To quickly inform end users, it is imperative that this happens in near real-time. To aid these efforts, we create estimates of European CO2 exchange at high resolution in near real time.
Simone M. Pieber, Béla Tuzson, Stephan Henne, Ute Karstens, Christoph Gerbig, Frank-Thomas Koch, Dominik Brunner, Martin Steinbacher, and Lukas Emmenegger
Atmos. Chem. Phys., 22, 10721–10749, https://doi.org/10.5194/acp-22-10721-2022, https://doi.org/10.5194/acp-22-10721-2022, 2022
Short summary
Short summary
Understanding regional greenhouse gas emissions into the atmosphere is a prerequisite to mitigate climate change. In this study, we investigated the regional contributions of carbon dioxide (CO2) at the location of the high Alpine observatory Jungfraujoch (JFJ, Switzerland, 3580 m a.s.l.). To this purpose, we combined receptor-oriented atmospheric transport simulations for CO2 concentration in the period 2009–2017 with stable carbon isotope (δ13C–CO2) information.
Stefan Röttger, Annette Röttger, Claudia Grossi, Arturo Vargas, Ute Karstens, Giorgia Cinelli, Edward Chung, Dafina Kikaj, Chris Rennick, Florian Mertes, and Ileana Radulescu
Adv. Geosci., 57, 37–47, https://doi.org/10.5194/adgeo-57-37-2022, https://doi.org/10.5194/adgeo-57-37-2022, 2022
Short summary
Short summary
Radon gas is the largest source of public exposure to naturally occurring radioactivity. Radon can also be used, as a tracer to improve indirectly the estimates of greenhouse gases important for supporting successful GHG mitigation strategies.
Both climate and radiation protection research communities need improved traceable low-level atmospheric radon measurements. The EMPIR project 19ENV01 traceRadon started to provide the necessary measurement infrastructure and transfer standards.
Ingeborg Levin, Ute Karstens, Samuel Hammer, Julian DellaColetta, Fabian Maier, and Maksym Gachkivskyi
Atmos. Chem. Phys., 21, 17907–17926, https://doi.org/10.5194/acp-21-17907-2021, https://doi.org/10.5194/acp-21-17907-2021, 2021
Short summary
Short summary
The radon tracer method is applied to atmospheric methane and radon observations from the upper Rhine valley to independently estimate methane emissions from the region. Comparison of our top-down results with bottom-up inventory data requires high-resolution footprint modelling and representative radon flux data. In agreement with inventories, observed emissions decreased, but only until 2005. A limitation of this method is that point-source emissions are not captured or not fully captured.
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
Short summary
Short summary
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.
Guillaume Monteil and Marko Scholze
Geosci. Model Dev., 14, 3383–3406, https://doi.org/10.5194/gmd-14-3383-2021, https://doi.org/10.5194/gmd-14-3383-2021, 2021
Short summary
Short summary
LUMIA is a Python library for atmospheric inversions, originally developed at Lund University to perform regional atmospheric CO2 inversions. The inversions rely on coupling the regional transport model FLEXPART and the global transport model TM5. The paper presents the modeling setup and some first results, and it introduces the LUMIA Python package as a toolbox for inversions beyond the use case presented in the paper.
Ana Maria Roxana Petrescu, Matthew J. McGrath, Robbie M. Andrew, Philippe Peylin, Glen P. Peters, Philippe Ciais, Gregoire Broquet, Francesco N. Tubiello, Christoph Gerbig, Julia Pongratz, Greet Janssens-Maenhout, Giacomo Grassi, Gert-Jan Nabuurs, Pierre Regnier, Ronny Lauerwald, Matthias Kuhnert, Juraj Balkovič, Mart-Jan Schelhaas, Hugo A. C. Denier van der
Gon, Efisio Solazzo, Chunjing Qiu, Roberto Pilli, Igor B. Konovalov, Richard A. Houghton, Dirk Günther, Lucia Perugini, Monica Crippa, Raphael Ganzenmüller, Ingrid T. Luijkx, Pete Smith, Saqr Munassar, Rona L. Thompson, Giulia Conchedda, Guillaume Monteil, Marko Scholze, Ute Karstens, Patrick Brockmann, and Albertus Johannes Dolman
Earth Syst. Sci. Data, 13, 2363–2406, https://doi.org/10.5194/essd-13-2363-2021, https://doi.org/10.5194/essd-13-2363-2021, 2021
Short summary
Short summary
This study is topical and provides a state-of-the-art scientific overview of data availability from bottom-up and top-down CO2 fossil emissions and CO2 land fluxes in the EU27+UK. The data integrate recent emission inventories with ecosystem data, land carbon models and regional/global inversions for the European domain, aiming at reconciling CO2 estimates with official country-level UNFCCC national GHG inventories in support to policy and facilitating real-time verification procedures.
Guillaume Monteil, Grégoire Broquet, Marko Scholze, Matthew Lang, Ute Karstens, Christoph Gerbig, Frank-Thomas Koch, Naomi E. Smith, Rona L. Thompson, Ingrid T. Luijkx, Emily White, Antoon Meesters, Philippe Ciais, Anita L. Ganesan, Alistair Manning, Michael Mischurow, Wouter Peters, Philippe Peylin, Jerôme Tarniewicz, Matt Rigby, Christian Rödenbeck, Alex Vermeulen, and Evie M. Walton
Atmos. Chem. Phys., 20, 12063–12091, https://doi.org/10.5194/acp-20-12063-2020, https://doi.org/10.5194/acp-20-12063-2020, 2020
Short summary
Short summary
The paper presents the first results from the EUROCOM project, a regional atmospheric inversion intercomparison exercise involving six European research groups. It aims to produce an estimate of the net carbon flux between the European terrestrial ecosystems and the atmosphere for the period 2006–2015, based on constraints provided by observed CO2 concentrations and using inverse modelling techniques. The use of six different models enables us to investigate the robustness of the results.
Ingeborg Levin, Ute Karstens, Markus Eritt, Fabian Maier, Sabrina Arnold, Daniel Rzesanke, Samuel Hammer, Michel Ramonet, Gabriela Vítková, Sebastien Conil, Michal Heliasz, Dagmar Kubistin, and Matthias Lindauer
Atmos. Chem. Phys., 20, 11161–11180, https://doi.org/10.5194/acp-20-11161-2020, https://doi.org/10.5194/acp-20-11161-2020, 2020
Short summary
Short summary
Based on observations and Stochastic Time-Inverted Lagrangian Transport (STILT) footprint modelling, a sampling strategy has been developed for tall tower stations of the Integrated Carbon Observation System (ICOS) research infrastructure atmospheric station network. This strategy allows independent quality control of in situ measurements, provides representative coverage of the influence area of the sites, and is capable of automated targeted sampling of fossil fuel CO2 emission hotspots.
Cited articles
Akata, N., Abe, K., Kakiuchi, H., Iyogi, T., Shima, N., and Hisamatsu, S.: Radiocarbon Concentrations in Environmental Samples Collected Near the Spent Nuclear Fuel Reprocessing Plant at Rokkasho, Aomori, Japan, During Test Operation Using Spent Nuclear Fuel, Health Physics, 105, 236–244, https://doi.org/10.1097/HP.0b013e318292b9fc, 2013. a, b
Basu, S., Miller, J. B., and Lehman, S.: Separation of biospheric and fossil fuel fluxes of CO2 by atmospheric inversion of CO2 and 14CO2 measurements: Observation System Simulations, Atmos. Chem. Phys., 16, 5665–5683, https://doi.org/10.5194/acp-16-5665-2016, 2016. a, b, c
Basu, S., Lehman, S. J., Miller, J. B., Andrews, A. E., Sweeney, C., Gurney, K. R., Xu, X., Southon, J., and Tans, P. P.: Estimating US fossil fuel CO2 emissions from measurements of 14C in atmospheric CO2, P. Natl. Acad. Sci. USA, 117, 13300–13307, https://doi.org/10.1073/pnas.1919032117, 2020. a, b, c, d, e
Bozhinova, D., van der Molen, M. K., van der Velde, I. R., Krol, M. C., van der Laan, S., Meijer, H. A. J., and Peters, W.: Simulating the integrated summertime Δ14CO2 signature from anthropogenic emissions over Western Europe, Atmos. Chem. Phys., 14, 7273–7290, https://doi.org/10.5194/acp-14-7273-2014, 2014. a, b
Chawner, H., Saboya, E., Adcock, K. E., Arnold, T., Artioli, Y., Dylag, C., Forster, G. L., Ganesan, A., Graven, H., Lessin, G., Levy, P., Luijkx, I. T., Manning, A., Pickers, P. A., Rennick, C., Rödenbeck, C., and Rigby, M.: Atmospheric oxygen as a tracer for fossil fuel carbon dioxide: a sensitivity study in the UK, Atmos. Chem. Phys., 24, 4231–4252, https://doi.org/10.5194/acp-24-4231-2024, 2024. a
Chen, H. W., Zhang, F., Lauvaux, T., Scholze, M., Davis, K. J., and Alley, R. B.: Regional CO2 Inversion Through Ensemble-Based Simultaneous State and Parameter Estimation: TRACE Framework and Controlled Experiments, J. Adv. Model. Earth Sy., 15, e2022MS003208, https://doi.org/10.1029/2022MS003208, 2023. a
Denier van der Gon, H., Hendriks, C., Kuenen, J., Segers, A., and Visschedijk, A.: Description of current temporal emission patterns and sensitivity of predicted AQ for temporal emission patterns, Tech. rep., TNO, Utrecht, https://atmosphere.copernicus.eu/sites/default/files/2019-07/MACC_TNO_del_1_3_v2.pdf (last access: September 2025), 2011. a
Fischer, M. L., Parazoo, N., Brophy, K., Cui, X., Jeong, S., Liu, J., Keeling, R., Taylor, T. E., Gurney, K., Oda, T., and Graven, H.: Simulating estimation of California fossil fuel and biosphere carbon dioxide exchanges combining in situ tower and satellite column observations, J. Geophys. Res.-Atmos., 122, 3653–3671, https://doi.org/10.1002/2016JD025617, 2017. a
Gerbig, C. and Koch, F.-T.: Biosphere-atmosphere exchange fluxes for CO2 from the Vegetation Photosynthesis and Respiration Model VPRM for 2006–2022, ICOS RI [data set], https://doi.org/10.18160/VX78-HVA1, 2021. a
Gómez-Ortiz, C.: Modeling support for an extensive D14CO2 flask sample monitoring campaign over Europe to constrain fossil CO2 emissions: Postprocessed model outputs and figures, Zenodo [data set] [code], https://doi.org/10.5281/zenodo.13842604, 2025. a
Graven, H. D., Guilderson, T. P., and Keeling, R. F.: Observations of radiocarbon in CO2 at seven global sampling sites in the Scripps flask network: Analysis of spatial gradients and seasonal cycles, J. Geophys. Res.-Atmos., 117, https://doi.org/10.1029/2011JD016535, 2012. a, b
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J. N.: The ERA5 global reanalysis, Q. J. Roy. Meteor. Soc., 146, 1999–2049, https://doi.org/10.1002/QJ.3803, 2020. a
Huijnen, V., Williams, J., van Weele, M., van Noije, T., Krol, M., Dentener, F., Segers, A., Houweling, S., Peters, W., de Laat, J., Boersma, F., Bergamaschi, P., van Velthoven, P., Le Sager, P., Eskes, H., Alkemade, F., Scheele, R., Nédélec, P., and Pätz, H.-W.: The global chemistry transport model TM5: description and evaluation of the tropospheric chemistry version 3.0, Geosci. Model Dev., 3, 445–473, https://doi.org/10.5194/gmd-3-445-2010, 2010. a
ICOS RI, Apadula, F., Arnold, S., Bergamaschi, P., Biermann, T., Chen, H., Colomb, A., Conil, S., Couret, C., Cristofanelli, P., De Mazière, M., Delmotte, M., Di Iorio enea, T., Emmenegger, L., Forster, G., Frumau, A., Haszpra, L., Hatakka, J., Heliasz, M., Heltai, D., Hensen, A., Hermansen, O., Hoheisel, A., Kneuer, T., Komínková, K., Kubistin, D., Larmanou, E., Laurent, O., Laurila, T., Lehner, I., Lehtinen, K., Leskinen, A., Leuenberger, M., Levula, J., Lindauer, M., Lopez, M., Lund Myhre, C., Lunder, C., Mammarella, I., Manca, G., Manning, A., Marek, M. V., Marklund, P., Meinhardt, F., Molnár, M., Mölder, M., Müller-Williams, J., O'Doherty, S., Ottosson-Löfvenius, M., Piacentino, S., Pichon, J.-M., Pitt, J., Platt, S. M., Plaß-Dülmer, C., Ramonet, M., Rivas-Soriano, P., Roulet, Y.-A., Scheeren, B., Schmidt, M., Schumacher, M., Sferlazzo, D., Sha, M. K., Smith, P., Stanley, K., Steinbacher, M., Sørensen, L. L., Trisolino, P., Vítková, G., Yver-Kwok, C., Zazzeri, G., di Sarra, A., ICOS ATC-Laboratoires des Sciences du Climat et de L'Environnement (LSCE) France, ICOS Central Radiocarbon Laboratory (CRL) Germany, and ICOS Flask And Calibration Laboratory (FCL) Germany: ICOS Atmosphere Release 2024-1 of Level 2 Greenhouse Gas Mole Fractions of CO2, CH4, N2O, CO, meteorology and 14CO2, and flask samples analysed for CO2, CH4, N2O, CO, H2, SF6 and 14C, ICOS RI [data set], https://doi.org/10.18160/0F1E-DKXT, 2024. a, b, c
Janssens-Maenhout, G., Crippa, M., Guizzardi, D., Muntean, M., Schaaf, E., Dentener, F., Bergamaschi, P., Pagliari, V., Olivier, J. G. J., Peters, J. A. H. W., van Aardenne, J. A., Monni, S., Doering, U., Petrescu, A. M. R., Solazzo, E., and Oreggioni, G. D.: EDGAR v4.3.2 Global Atlas of the three major greenhouse gas emissions for the period 1970–2012, Earth Syst. Sci. Data, 11, 959–1002, https://doi.org/10.5194/essd-11-959-2019, 2019. a
Koch, F.-T. and Gerbig, C.: European anthropogenic CO2 emissions based on EDGARv4.3 and BP statistics 2023 for 2005–2022, ICOS RI [data set], https://doi.org/10.18160/RFJD-QV8J, 2023. a
Kuderer, M., Hammer, S., and Levin, I.: The influence of 14CO2 releases from regional nuclear facilities at the Heidelberg 14CO2 sampling site (1986–2014), Atmos. Chem. Phys., 18, 7951–7959, https://doi.org/10.5194/acp-18-7951-2018, 2018. a, b
Kutschera, W.: THE VERSATILE USES OF THE 14C BOMB PEAK, Radiocarbon, 64, 1295–1308, https://doi.org/10.1017/RDC.2022.13, 2022. a
Lehmuskoski, J., Vasama, H., Hämäläinen, J., Hokkinen, J., Kärkelä, T., Heiskanen, K., Reinikainen, M., Rautio, S., Hirvelä, M., and Genoud, G.: On-Line Monitoring of Radiocarbon Emissions in a Nuclear Facility with Cavity Ring-Down Spectroscopy, Anal. Chem., 93, 16096–16104, https://doi.org/10.1021/acs.analchem.1c03814, 2021. a
Levin, I. and Kromer, B.: The Tropospheric 14CO2 Level in Mid-Latitudes of the Northern Hemisphere (1959–2003), Radiocarbon, 46, 1261–1272, https://doi.org/10.1017/S0033822200033130, 2004. a
Levin, I., Kromer, B., Schmidt, M., and Sartorius, H.: A novel approach for independent budgeting of fossil fuel CO2 over Europe by 14CO2 observations, Geophys. Res. Lett., 30, 2194, https://doi.org/10.1029/2003GL018477, 2003. a
Levin, I., Karstens, U., Eritt, M., Maier, F., Arnold, S., Rzesanke, D., Hammer, S., Ramonet, M., Vítková, G., Conil, S., Heliasz, M., Kubistin, D., and Lindauer, M.: A dedicated flask sampling strategy developed for Integrated Carbon Observation System (ICOS) stations based on CO2 and CO measurements and Stochastic Time-Inverted Lagrangian Transport (STILT) footprint modelling, Atmos. Chem. Phys., 20, 11161–11180, https://doi.org/10.5194/acp-20-11161-2020, 2020. a, b, c, d, e, f, g, h, i, j
Lingenfelter, R. E.: Production of carbon 14 by cosmic-ray neutrons, Rev. Geophys., 1, 35–55, https://doi.org/10.1029/RG001I001P00035, 1963. a
Mahadevan, P., Wofsy, S. C., Matross, D. M., Xiao, X., Dunn, A. L., Lin, J. C., Gerbig, C., Munger, J. W., Chow, V. Y., and Gottlieb, E. W.: A satellite-based biosphere parameterization for net ecosystem CO2 exchange: Vegetation Photosynthesis and Respiration Model (VPRM), Global Biogeochem. Cycles, 22, https://doi.org/10.1029/2006GB002735, 2008. a
Maier, F., Gerbig, C., Levin, I., Super, I., Marshall, J., and Hammer, S.: Effects of point source emission heights in WRF–STILT: a step towards exploiting nocturnal observations in models, Geosci. Model Dev., 15, 5391–5406, https://doi.org/10.5194/gmd-15-5391-2022, 2022. a, b
Monteil, G., Broquet, G., Scholze, M., Lang, M., Karstens, U., Gerbig, C., Koch, F.-T., Smith, N. E., Thompson, R. L., Luijkx, I. T., White, E., Meesters, A., Ciais, P., Ganesan, A. L., Manning, A., Mischurow, M., Peters, W., Peylin, P., Tarniewicz, J., Rigby, M., Rödenbeck, C., Vermeulen, A., and Walton, E. M.: The regional European atmospheric transport inversion comparison, EUROCOM: first results on European-wide terrestrial carbon fluxes for the period 2006–2015, Atmos. Chem. Phys., 20, 12063–12091, https://doi.org/10.5194/acp-20-12063-2020, 2020. a
Monteil, G., Gómez-Ortiz, C., Meier, A., and Villalobos, Y.: Lund University Modular Inversion Algorithm, Zenodo [code], https://doi.org/10.5281/zenodo.8426217, 2023. a
Munassar, S., Monteil, G., Scholze, M., Karstens, U., Rödenbeck, C., Koch, F.-T., Totsche, K. U., and Gerbig, C.: Why do inverse models disagree? A case study with two European CO2 inversions, Atmos. Chem. Phys., 23, 2813–2828, https://doi.org/10.5194/acp-23-2813-2023, 2023. a
Oda, T. and Maksyutov, S.: ODIAC Fossil Fuel CO2 Emissions Dataset (Version name: ODIAC2020b), National Institute for Environmental Studies [data set], https://doi.org/10.17595/20170411.001, 2020. a
Oda, T., Maksyutov, S., and Andres, R. J.: The Open-source Data Inventory for Anthropogenic CO2, version 2016 (ODIAC2016): a global monthly fossil fuel CO2 gridded emissions data product for tracer transport simulations and surface flux inversions, Earth Syst. Sci. Data, 10, 87–107, https://doi.org/10.5194/essd-10-87-2018, 2018. a
Pisso, I., Sollum, E., Grythe, H., Kristiansen, N. I., Cassiani, M., Eckhardt, S., Arnold, D., Morton, D., Thompson, R. L., Groot Zwaaftink, C. D., Evangeliou, N., Sodemann, H., Haimberger, L., Henne, S., Brunner, D., Burkhart, J. F., Fouilloux, A., Brioude, J., Philipp, A., Seibert, P., and Stohl, A.: The Lagrangian particle dispersion model FLEXPART version 10.4, Geosci. Model Dev., 12, 4955–4997, https://doi.org/10.5194/gmd-12-4955-2019, 2019. a, b
Rayner, P. J., Michalak, A. M., and Chevallier, F.: Fundamentals of data assimilation applied to biogeochemistry, Atmos. Chem. Phys., 19, 13911–13932, https://doi.org/10.5194/acp-19-13911-2019, 2019. a
Rödenbeck, C., Gerbig, C., Trusilova, K., and Heimann, M.: A two-step scheme for high-resolution regional atmospheric trace gas inversions based on independent models, Atmos. Chem. Phys., 9, 5331–5342, https://doi.org/10.5194/acp-9-5331-2009, 2009. a, b, c
Rödenbeck, C., Keeling, R. F., Bakker, D. C. E., Metzl, N., Olsen, A., Sabine, C., and Heimann, M.: Global surface-ocean pCO2 and sea–air CO2 flux variability from an observation-driven ocean mixed-layer scheme, Ocean Sci., 9, 193–216, https://doi.org/10.5194/os-9-193-2013, 2013. a
Rödenbeck, C., DeVries, T., Hauck, J., Le Quéré, C., and Keeling, R. F.: Data-based estimates of interannual sea–air CO2 flux variations 1957–2020 and their relation to environmental drivers, Biogeosciences, 19, 2627–2652, https://doi.org/10.5194/bg-19-2627-2022, 2022. a
Smith, B., Wårlind, D., Arneth, A., Hickler, T., Leadley, P., Siltberg, J., and Zaehle, S.: Implications of incorporating N cycling and N limitations on primary production in an individual-based dynamic vegetation model, Biogeosciences, 11, 2027–2054, https://doi.org/10.5194/bg-11-2027-2014, 2014. a
Steinbach, J., Gerbig, C., Rödenbeck, C., Karstens, U., Minejima, C., and Mukai, H.: The CO2 release and Oxygen uptake from Fossil Fuel Emission Estimate (COFFEE) dataset: effects from varying oxidative ratios, Atmos. Chem. Phys., 11, 6855–6870, https://doi.org/10.5194/acp-11-6855-2011, 2011. a
Storm, I., Maier, F., Levin, I., Preunkert, S., and Karstens, U.: Annual emission totals of 14CO2 from nuclear facilities, ICOS RI [data set], https://hdl.handle.net/11676/Qa5PvLgEeiXW3IRAfTU5d_Oo (last access: September 2025), 2024. a
Sweeney, C., Gloor, E., Jacobson, A. R., Key, R. M., McKinley, G., Sarmiento, J. L., and Wanninkhof, R.: Constraining global air-sea gas exchange for CO2 with recent bomb 14C measurements, Global Biogeochem. Cycles, 21, https://doi.org/10.1029/2006GB002784, 2007. a
Thompson, R. L., Broquet, G., Gerbig, C., Koch, T., Lang, M., Monteil, G., Munassar, S., Nickless, A., Scholze, M., Ramonet, M., Karstens, U., van Schaik, E., Wu, Z., and Rödenbeck, C.: Changes in net ecosystem exchange over Europe during the 2018 drought based on atmospheric observations, Philos. T. Roy. Soc. B, 375, 20190512, https://doi.org/10.1098/rstb.2019.0512, 2020. a, b, c
Turnbull, J., Rayner, P., Miller, J., Naegler, T., Ciais, P., and Cozic, A.: On the use of 14CO2 as a tracer for fossil fuel CO2: Quantifying uncertainties using an atmospheric transport model, J. Geophys. Res.-Atmos., 114, https://doi.org/10.1029/2009JD012308, 2009. a, b
Turnbull, J. C., Karion, A., Fischer, M. L., Faloona, I., Guilderson, T., Lehman, S. J., Miller, B. R., Miller, J. B., Montzka, S., Sherwood, T., Saripalli, S., Sweeney, C., and Tans, P. P.: Assessment of fossil fuel carbon dioxide and other anthropogenic trace gas emissions from airborne measurements over Sacramento, California in spring 2009, Atmos. Chem. Phys., 11, 705–721, https://doi.org/10.5194/acp-11-705-2011, 2011. a
van der Woude, A., de Kok, R., Luijkx, I., Peters, W., and Smith, N.: High-resolution, near-real-time fluxes over Europe from CTE-HR: ocean fluxes 2020-04, 2020-04-01–2020-04-30, ICOS RI [data set], https://hdl.handle.net/11676/VcS2nlfN06qH22RgmCWbPMUA (last access: September 2025), 2022. a
Varga, T., Orsovszki, G., Major, I., Veres, M., Bujtás, T., Végh, G., Manga, L., Jull, A. J. T., Palcsu, L., and Molnár, M.: Advanced atmospheric 14C monitoring around the Paks Nuclear Power Plant, Hungary, Journal of Environmental Radioactivity, 213, 106138, https://doi.org/10.1016/j.jenvrad.2019.106138, 2020. a, b
Vogel, F. R., Levin, I., and Worthy, D. E. J.: Implications for Deriving Regional Fossil Fuel CO2 Estimates from Atmospheric Observations in a Hot Spot of Nuclear Power Plant 14CO2 Emissions, Radiocarbon, 55, 1556–1572, https://doi.org/10.1017/S0033822200048487, 2013. a, b, c, d
Wang, J. S., Oda, T., Kawa, S. R., Strode, S. A., Baker, D. F., Ott, L. E., and Pawson, S.: The impacts of fossil fuel emission uncertainties and accounting for 3-D chemical CO2 production on inverse natural carbon flux estimates from satellite and in situ data, Environ. Res. Lett., 15, 085002, https://doi.org/10.1088/1748-9326/AB9795, 2020. a
Wang, Y., Broquet, G., Ciais, P., Chevallier, F., Vogel, F., Wu, L., Yin, Y., Wang, R., and Tao, S.: Potential of European 14CO2 observation network to estimate the fossil fuel CO2 emissions via atmospheric inversions, Atmos. Chem. Phys., 18, 4229–4250, https://doi.org/10.5194/acp-18-4229-2018, 2018. a
Wu, Z.: European hourly NEE, GPP and total respiration for 2010–2022 based on LPJ-GUESS (generated in 2023), ICOS RI [data set], https://doi.org/10.18160/p52c-1qjm, 2023. a
Zazzeri, G., Acuña Yeomans, E., and Graven, H. D.: Global and Regional Emissions of Radiocarbon from Nuclear Power Plants from 1972 to 2016, Radiocarbon, 60, 1067–1081, https://doi.org/10.1017/RDC.2018.42, 2018. a, b
Short summary
In 2024, an intensive sampling campaign was conducted to improve fossil CO2 emission estimates in Europe using 14C measurements. By testing different strategies for selecting air samples, this study shows that increasing sample frequency and carefully choosing samples based on their fossil fuel and nuclear content leads to more accurate results, reducing the uncertainty and bias of the estimates.
In 2024, an intensive sampling campaign was conducted to improve fossil CO2 emission estimates...
Altmetrics
Final-revised paper
Preprint