Articles | Volume 15, issue 2
https://doi.org/10.5194/essd-15-579-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-15-579-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
06 Feb 2023
Data description paper |
| 06 Feb 2023
| 06 Feb 2023
Near-real-time CO2 fluxes from CarbonTracker Europe for high-resolution atmospheric modeling
Auke M. van der Woude
CORRESPONDING AUTHOR
Centre for Isotope Research, Energy and Sustainability Research Institute Groningen, University of Groningen, Nijenborgh 4, 9747 AG Groningen, the Netherlands
Meteorology and Air Quality Group, Wageningen University, P.O. Box 47, 6700 AA Wageningen, the Netherlands
Remco de Kok
Meteorology and Air Quality Group, Wageningen University, P.O. Box 47, 6700 AA Wageningen, the Netherlands
ICOS ERIC Carbon Portal, Geocentrum II, Sölvegatan 12, 22362 Lund, Sweden
Naomi Smith
Meteorology and Air Quality Group, Wageningen University, P.O. Box 47, 6700 AA Wageningen, the Netherlands
Ingrid T. Luijkx
Meteorology and Air Quality Group, Wageningen University, P.O. Box 47, 6700 AA Wageningen, the Netherlands
Santiago Botía
Max Planck Institute for Biogeochemistry, Hans-Knoell-Straße 10, 07745 Jena, Germany
Ute Karstens
ICOS ERIC Carbon Portal, Physical Geography and Ecosystem Science, Lund University, Lund, P.O. Box 117, 221 00, Lund, Sweden
Linda M. J. Kooijmans
Meteorology and Air Quality Group, Wageningen University, P.O. Box 47, 6700 AA Wageningen, the Netherlands
Gerbrand Koren
Copernicus Institute of Sustainable Development, Utrecht University, Utrecht, the Netherlands
Meteorology and Air Quality Group, Wageningen University, P.O. Box 47, 6700 AA Wageningen, the Netherlands
Harro A. J. Meijer
Centre for Isotope Research, Energy and Sustainability Research Institute Groningen, University of Groningen, Nijenborgh 4, 9747 AG Groningen, the Netherlands
Gert-Jan Steeneveld
Meteorology and Air Quality Group, Wageningen University, P.O. Box 47, 6700 AA Wageningen, the Netherlands
Ida Storm
ICOS ERIC Carbon Portal, Physical Geography and Ecosystem Science, Lund University, Lund, P.O. Box 117, 221 00, Lund, Sweden
Meteorology and Air Quality Group, Wageningen University, P.O. Box 47, 6700 AA Wageningen, the Netherlands
Ingrid Super
Department of Climate, Air and Sustainability, TNO, P.O. Box 80015, 3508 TA Utrecht, the Netherlands
Hubertus A. Scheeren
Centre for Isotope Research, Energy and Sustainability Research Institute Groningen, University of Groningen, Nijenborgh 4, 9747 AG Groningen, the Netherlands
Alex Vermeulen
ICOS ERIC Carbon Portal, Geocentrum II, Sölvegatan 12, 22362 Lund, Sweden
ICOS ERIC Carbon Portal, Physical Geography and Ecosystem Science, Lund University, Lund, P.O. Box 117, 221 00, Lund, Sweden
Wouter Peters
Meteorology and Air Quality Group, Wageningen University, P.O. Box 47, 6700 AA Wageningen, the Netherlands
Centre for Isotope Research, Energy and Sustainability Research Institute Groningen, University of Groningen, Nijenborgh 4, 9747 AG Groningen, the Netherlands
Related authors
Anne-Wil van den Berg, Joram J. D. Hooghiem, Auke M. van der Woude, Pieter Rijsdijk, Roland Vernooij, Santiago Botia, Guido R. van der Werf, John B. Miller, Ingrid T. Luijkx, Maarten C. Krol, and Wouter Peters
EGUsphere, https://doi.org/10.5194/egusphere-2025-6213, https://doi.org/10.5194/egusphere-2025-6213, 2026
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
We estimate 2019 Brazilian fire carbon monoxide (CO) emissions using CO retrievals from different satellite instruments in a new top-down inversion framework. The retrievals strongly constrain fire emissions and complement existing inventories. National-scale posterior emissions align well with the new GFED5.1 inventory, supporting progress in fire emission modelling. Yet, posterior emissions in the Cerrado and Caatinga are systematically higher than inventories, we discuss potential drivers.
William J. M. Seviour, Justin Finkel, Philip Rupp, Regan Mudhar, Amy H. Butler, Chaim I. Garfinkel, Peter Hitchcock, Blanca Ayarzagüena, Dong-Chan Hong, Yu-Kyung Hyun, Hera Kim, Eun-Pa Lim, Daniel De Maeseneire, Gabriele Messori, Gerbrand Koren, Michael Sigmond, Isla R. Simpson, and Seok-Woo Son
EGUsphere, https://doi.org/10.5194/egusphere-2026-230, https://doi.org/10.5194/egusphere-2026-230, 2026
This preprint is open for discussion and under review for Weather and Climate Dynamics (WCD).
Short summary
Short summary
Variability of the stratospheric polar vortex is thought to play a role in driving weather extremes, but quantifying this role for a given event has proved challenging. Using a new set of perturbed subseasonal forecast experiments from 7 modelling centres we determine the stratospheric contribution to the risk and severity of three recent extreme weather events. The forecast-based methodology that we develop is applicable to understanding a range of other drivers of weather extremes.
Anne-Wil van den Berg, Joram J. D. Hooghiem, Auke M. van der Woude, Pieter Rijsdijk, Roland Vernooij, Santiago Botia, Guido R. van der Werf, John B. Miller, Ingrid T. Luijkx, Maarten C. Krol, and Wouter Peters
EGUsphere, https://doi.org/10.5194/egusphere-2025-6213, https://doi.org/10.5194/egusphere-2025-6213, 2026
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
We estimate 2019 Brazilian fire carbon monoxide (CO) emissions using CO retrievals from different satellite instruments in a new top-down inversion framework. The retrievals strongly constrain fire emissions and complement existing inventories. National-scale posterior emissions align well with the new GFED5.1 inventory, supporting progress in fire emission modelling. Yet, posterior emissions in the Cerrado and Caatinga are systematically higher than inventories, we discuss potential drivers.
Carla Souza, Anne C. S. Mendonça, Hella Van Asperen, Flávio A. D’Oliveira, Santiago Botía, Luís G. N. Martins, Denisi H. Hall, Raoni A. Santana, Gilberto Fisch, Leonardo R. Oliveira, Jailson R. Mata, Ranyelli Figueiredo, Bruno T. T. Portela, Carlos A. Quesada, and Cléo Q. Dias-Júnior
EGUsphere, https://doi.org/10.5194/egusphere-2025-6531, https://doi.org/10.5194/egusphere-2025-6531, 2026
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
We investigated how the height of the nocturnal air layer (hn) above the Amazon forest changes over the year and how this influences gas measurements. Using two years of tower observations, we found that this layer is higher during wetter periods and much lower during dry periods linked to large climate events. hn can controls how gases accumulate or disperse at night, which affects how we interpret observations and improve weather and climate predictions.
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
Short summary
Short summary
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.
Ida Storm, Ute Karstens, Claudio D'Onofrio, Alex Vermeulen, Samuel Hammer, Ingrid Super, Theo Glauch, and Wouter Peters
Earth Syst. Sci. Data, 17, 6681–6701, https://doi.org/10.5194/essd-17-6681-2025, https://doi.org/10.5194/essd-17-6681-2025, 2025
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 characterise 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.
Dieu Anh Tran, Jordi Vilà-Guerau de Arellano, Ingrid T. Luijkx, Christoph Gerbig, Michał Gałkowski, Santiago Botía, Kim Faassen, and Sönke Zaehle
Atmos. Chem. Phys., 25, 16553–16588, https://doi.org/10.5194/acp-25-16553-2025, https://doi.org/10.5194/acp-25-16553-2025, 2025
Short summary
Short summary
Analysis of CH4 data (2010–2021) from ZOtino Tall Tower Observatory in Central Siberia shows an increase in the late summer diurnal amplitude, driven by nighttime emissions. These trends correlate with rising soil temperature and moisture during the late summer and snow depth of the preceding spring. Peaks in 2012 and 2019 emission link to wildfires activity. Findings suggest wetlands as key CH4 sources and underscore the need for ongoing high-resolution monitoring in this region.
Sebastian H. M. Hickman, Makoto M. Kelp, Paul T. Griffiths, Kelsey Doerksen, Kazuyuki Miyazaki, Elyse A. Pennington, Gerbrand Koren, Fernando Iglesias-Suarez, Martin G. Schultz, Kai-Lan Chang, Owen R. Cooper, Alex Archibald, Roberto Sommariva, David Carlson, Hantao Wang, J. Jason West, and Zhenze Liu
Geosci. Model Dev., 18, 8777–8800, https://doi.org/10.5194/gmd-18-8777-2025, https://doi.org/10.5194/gmd-18-8777-2025, 2025
Short summary
Short summary
Machine learning is being more widely used across environmental and climate science. This work reviews the use of machine learning in tropospheric ozone research, focusing on three main application areas in which significant progress has been made. Common challenges in using machine learning across the three areas are highlighted, and future directions for the field are indicated.
Camille Yver-Kwok, Michel Ramonet, Leonard Rivier, Jinghui Lian, Claudia Grossi, Roger Curcoll, Dafina Kikaj, Edward Chung, and Ute Karstens
Atmos. Chem. Phys., 25, 16085–16106, https://doi.org/10.5194/acp-25-16085-2025, https://doi.org/10.5194/acp-25-16085-2025, 2025
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 October 2024 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.
Maksym Gachkivskyi, Ute Karstens, Bernd Fischer, Dagmar Kubistin, Jennifer Müller-Williams, Matthias Lindauer, and Ingeborg Levin
Earth Syst. Sci. Data, 17, 6173–6197, https://doi.org/10.5194/essd-17-6173-2025, https://doi.org/10.5194/essd-17-6173-2025, 2025
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 eight stations in Germany with guidelines for estimating Rn from Po measurements. Comparison between modeled and measured activity concentrations shows that at high relative humidity Po measurements cannot be interpreted as Rn.
Marco M. Lehmann, Josie Geris, Ilja van Meerveld, Daniele Penna, Youri Rothfuss, Matteo Verdone, Pertti Ala-Aho, Matyas Arvai, Alise Babre, Philippe Balandier, Fabian Bernhard, Lukrecija Butorac, Simon D. Carrière, Natalie C. Ceperley, Zuosinan Chen, Alicia Correa, Haoyu Diao, David Dubbert, Maren Dubbert, Fabio Ercoli, Marius G. Floriancic, Alligin Ghazoul, Teresa E. Gimeno, Damien Gounelle, Frank Hagedorn, Christophe Hissler, Frédéric Huneau, Alberto Iraheta, Tamara Jakovljević, Nerantzis Kazakis, Zoltan Kern, Laura Kinzinger, Karl Knaebel, Johannes Kobler, Jiri Kocum, Charlotte Koeber, Gerbrand Koren, Angelika Kübert, Dawid Kupka, Samuel Le Gall, Aleksi Lehtonen, Thomas Leydier, Philippe Malagoli, Francesca Sofia Manca di Villahermosa, Chiara Marchina, Núria Martínez-Carreras, Nicolas Martin-StPaul, Hannu Marttila, Aline Meyer Oliveira, Gael Monvoisin, Natalie Orlowski, Kadi Palmik-Das, Aurel Persoiu, Andrei Popa, Egor Prikaziuk, Cécile Quantin, Katja T. Rinne-Garmston, Clara Rohde, Martin Sanda, Matthias Saurer, Daniel Schulz, Michael P. Stockinger, Christine Stumpp, Jean-Stéphane Vénisse, Lukas Vlcek, Stylianos Voudouris, Björn Weeser, Mark E. Wilkinson, Giulia Zuecco, and Katrin Meusburger
Earth Syst. Sci. Data, 17, 6129–6147, https://doi.org/10.5194/essd-17-6129-2025, https://doi.org/10.5194/essd-17-6129-2025, 2025
Short summary
Short summary
This study describes a unique large-scale isotope dataset to study water dynamics in European forests. Researchers collected data from 40 beech and spruce forest sites in spring and summer 2023, using a standardized method to ensure consistency. The results show that water sources for trees change between seasons and vary by tree species. This large dataset offers valuable information for understanding plant water use, improving ecohydrological models, and mapping water cycles across Europe.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Dorothee C. E. Bakker, Judith Hauck, Peter Landschützer, Corinne Le Quéré, Hongmei Li, Ingrid T. Luijkx, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Kjetil Aas, Simone R. Alin, Peter Anthoni, Leticia Barbero, Nicholas R. Bates, Nicolas Bellouin, Alice Benoit-Cattin, Carla F. Berghoff, Raffaele Bernardello, Laurent Bopp, Ida B. M. Brasika, Matthew A. Chamberlain, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Nathan O. Collier, Thomas H. Colligan, Margot Cronin, Laique Djeutchouang, Xinyu Dou, Matt P. Enright, Kazutaka Enyo, Michael Erb, Wiley Evans, Richard A. Feely, Liang Feng, Daniel J. Ford, Adrianna Foster, Filippa Fransner, Thomas Gasser, Marion Gehlen, Thanos Gkritzalis, Jefferson Goncalves De Souza, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Bertrand Guenet, Özgür Gürses, Kirsty Harrington, Ian Harris, Jens Heinke, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Akihiko Ito, Andrew R. Jacobson, Atul K. Jain, Tereza Jarníková, Annika Jersild, Fei Jiang, Steve D. Jones, Etsushi Kato, Ralph F. Keeling, Kees Klein Goldewijk, Jürgen Knauer, Yawen Kong, Jan Ivar Korsbakken, Charles Koven, Taro Kunimitsu, Xin Lan, Junjie Liu, Zhiqiang Liu, Zhu Liu, Claire Lo Monaco, Lei Ma, Gregg Marland, Patrick C. McGuire, Galen A. McKinley, Joe Melton, Natalie Monacci, Erwan Monier, Eric J. Morgan, David R. Munro, Jens D. Müller, Shin-Ichiro Nakaoka, Lorna R. Nayagam, Yosuke Niwa, Tobias Nutzel, Are Olsen, Abdirahman M. Omar, Naiqing Pan, Sudhanshu Pandey, Denis Pierrot, Zhangcai Qin, Pierre A. G. Regnier, Gregor Rehder, Laure Resplandy, Alizée Roobaert, Thais M. Rosan, Christian Rödenbeck, Jörg Schwinger, Ingunn Skjelvan, T. Luke Smallman, Victoria Spada, Mohanan G. Sreeush, Qing Sun, Adrienne J. Sutton, Colm Sweeney, Didier Swingedouw, Roland Séférian, Shintaro Takao, Hiroaki Tatebe, Hanqin Tian, Xiangjun Tian, Bronte Tilbrook, Hiroyuki Tsujino, Francesco Tubiello, Erik van Ooijen, Guido van der Werf, Sebastiaan J. van de Velde, Anthony Walker, Rik Wanninkhof, Xiaojuan Yang, Wenping Yuan, Xu Yue, and Jiye Zeng
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-659, https://doi.org/10.5194/essd-2025-659, 2025
Preprint under review for ESSD
Short summary
Short summary
The Global Carbon Budget 2025 describes the methodology, main results, and datasets used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, land ecosystems, and the ocean over the historical period (1750–2025). These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Scott D. Chambers, Ute Karstens, Alan D. Griffiths, Stefan Röttger, Arnoud Frumau, Christopher T. Roulston, Peter Sperlich, Felix Vogel, Agnieszka Podstawczyńska, Dafina Kikaj, Maksym Gachkivskyi, Michel Ramonet, Blagoj Mitrevski, Janja Vaupotič, Xuemeng Chen, and Annette Röttger
EGUsphere, https://doi.org/10.5194/egusphere-2025-5042, https://doi.org/10.5194/egusphere-2025-5042, 2025
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
Short summary
Short summary
The Radon Tracer Method (RTM) is a top-down approach to estimate greenhouse gas emissions. While simple in principle, incorrect use can complicate interpretation of results. Based on observations from a range of contrasting sites, this article reviews the underlying assumptions and key considerations for applying the RTM. It also introduces the concept of coupling RTM analyses with nocturnal stability classification, to reduce uncertainty of fetch estimates and improve interpretation of results.
Indy van Grinsven, Meiert Willem Grootes, Remko Uijlenhoet, and Gert-Jan Steeneveld
EGUsphere, https://doi.org/10.5194/egusphere-2025-2634, https://doi.org/10.5194/egusphere-2025-2634, 2025
Short summary
Short summary
This study explores the use the signal attenuation of cellular communication networks, combined with machine learning approaches, to observe fog events. We use the McFly software package that selects the most appropriate machine leaning technique (out of ~20 available techniques) based on small samples of the input datasets. This approach is developed for a microwave link over Wageningen in The Netherlands, while in a second part of the paper the approach is upscaled to the whole country.
Carlos A. Sierra, Ingrid Chanca, Meinrat O. Andreae, Alessandro Carioca de Araújo, Hella van Asperen, Lars Borchardt, Santiago Botía, Luiz Antonio Candido, Caio S. C. Correa, Cléo Quaresma Dias-Junior, Markus Eritt, Annica Fröhlich, Luciana V. Gatti, Marcus Guderle, Samuel Hammer, Martin Heimann, Viviana Horna, Armin Jordan, Steffen Knabe, Richard Kneißl, Jost Valentin Lavric, Ingeborg Levin, Kita Macario, Juliana Menger, Heiko Moossen, Carlos Alberto Quesada, Michael Rothe, Christian Rödenbeck, Yago Santos, Axel Steinhof, Bruno Takeshi, Susan Trumbore, and Sönke Zaehle
Earth Syst. Sci. Data, 17, 5871–5884, https://doi.org/10.5194/essd-17-5871-2025, https://doi.org/10.5194/essd-17-5871-2025, 2025
Short summary
Short summary
We present here a unique dataset of atmospheric observations of greenhouse gases and isotopes that provide key information on land-atmosphere interactions for the Amazon forests of central Brazil. The data show a relatively large level of variability, but also important trends in greenhouse gases, and signals from fires as well as seasonal biological activity.
Jordi Vilà-Guerau de Arellano, Roderick Dewar, Kim A. P. Faassen, Teemu Hölttä, Remco de Kok, Ingrid T. Luijkx, and Timo Vesala
Biogeosciences, 22, 6327–6341, https://doi.org/10.5194/bg-22-6327-2025, https://doi.org/10.5194/bg-22-6327-2025, 2025
Short summary
Short summary
This study explores how oxygen moves through tiny pores in leaves, especially when water vapor is also flowing out. We show that under common conditions, oxygen can move from the leaf to the air even when its concentration is higher outside – a surprising effect. Our findings help explain oxygen exchange in still air and support better models of plant–atmosphere interactions.
Sophie L. Baartman, Steven M. Driever, Maarten L. J. Wassenaar, Linda M. J. Kooijmans, Nerea Ubierna, Leon Mossink, Maria E. Popa, Ara Cho, Lisa Wingate, Thomas Röckmann, Steven M. A. C. van Heuven, and Maarten C. Krol
Biogeosciences, 22, 5683–5703, https://doi.org/10.5194/bg-22-5683-2025, https://doi.org/10.5194/bg-22-5683-2025, 2025
Short summary
Short summary
Carbonyl sulfide (COS) is a proposed tracer for gross primary production. For the first time, COS and carbon dioxide (CO2) uptake fluxes and isotope discrimination were jointly measured in sunflower and papyrus plants, using a flow-through plant chamber approach and varying light availability. COS isotope discrimination did not differ significantly between the species, nor with changes in light. CO2 fluxes and isotope values provided additional valuable information for data interpretation.
Fabian Maier, Eva Falge, Maksym Gachkivskyi, Stephan Henne, Ute Karstens, Dafina Kikaj, Ingeborg Levin, Alistair Manning, Christian Rödenbeck, and Christoph Gerbig
Atmos. Chem. Phys., 25, 12779–12809, https://doi.org/10.5194/acp-25-12779-2025, https://doi.org/10.5194/acp-25-12779-2025, 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.
Tamara Emmerichs, Abdulla Al Mamun, Lisa Emberson, Huiting Mao, Leiming Zhang, Limei Ran, Clara Betancourt, Anthony Wong, Gerbrand Koren, Giacomo Gerosa, Min Huang, and Pierluigi Guaita
Biogeosciences, 22, 4823–4849, https://doi.org/10.5194/bg-22-4823-2025, https://doi.org/10.5194/bg-22-4823-2025, 2025
Short summary
Short summary
The risk of ozone pollution to plants is estimated based on the flux through the plant pores which still has uncertainties. In this study, we estimate this quantity with nine models at different land types worldwide, driven by measurement data. The models mostly estimated reasonable summertime ozone flux to plants. The model results varied by land cover, mainly related to the a lack of moisture in the soil. This work is an important step for assessing the ozone impact on vegetation.
Carlos Gómez-Ortiz, Guillaume Monteil, Ute Karstens, and Marko Scholze
Atmos. Chem. Phys., 25, 10747–10771, https://doi.org/10.5194/acp-25-10747-2025, https://doi.org/10.5194/acp-25-10747-2025, 2025
Short summary
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.
Yuming Jin, Britton B. Stephens, Matthew C. Long, Naveen Chandra, Frédéric Chevallier, Joram J. D. Hooghiem, Ingrid T. Luijkx, Shamil Maksyutov, Eric J. Morgan, Yosuke Niwa, Prabir K. Patra, Christian Rödenbeck, and Jesse Vance
Geosci. Model Dev., 18, 5937–5969, https://doi.org/10.5194/gmd-18-5937-2025, https://doi.org/10.5194/gmd-18-5937-2025, 2025
Short summary
Short summary
We carry out a comprehensive atmospheric transport model (ATM) intercomparison project. This project aims to evaluate errors in ATMs and three air-sea O2 flux products by comparing model simulations with observations collected from surface stations, ships, and aircraft. We also present a model evaluation framework to independently quantify transport-related and flux-related biases that contribute to model-observation discrepancies in atmospheric tracer distributions.
Elias C. Massoud, Nathan Collier, Yaoping Wang, Jiafu Mao, Adrian Harpold, Steven A. Kannenberg, Gerbrand Koren, Mukesh Kumar, Pushpendra Raghav, Pallav Ray, Mingjie Shi, Jing Tao, Sreedevi P. Vasu, Huiqi Wang, Qing Zhu, and Forrest M. Hoffman
EGUsphere, https://doi.org/10.5194/egusphere-2025-3517, https://doi.org/10.5194/egusphere-2025-3517, 2025
Short summary
Short summary
We studied how well Earth System Models simulate soil moisture and its connection to plant growth and water use. Using a model evaluation tool and real-world data, we found that models generally perform well at the surface but struggle deeper in the soil. These issues vary by region, especially in colder regions. Our results can help improve future model development and support better predictions of how ecosystems respond to a changing environment.
Yunqian Zhu, Hideharu Akiyoshi, Valentina Aquila, Elizabeth Asher, Ewa M. Bednarz, Slimane Bekki, Christoph Brühl, Amy H. Butler, Parker Case, Simon Chabrillat, Gabriel Chiodo, Margot Clyne, Peter R. Colarco, Sandip Dhomse, Lola Falletti, Eric Fleming, Ben Johnson, Andrin Jörimann, Mahesh Kovilakam, Gerbrand Koren, Ales Kuchar, Nicolas Lebas, Qing Liang, Cheng-Cheng Liu, Graham Mann, Michael Manyin, Marion Marchand, Olaf Morgenstern, Paul Newman, Luke D. Oman, Freja F. Østerstrøm, Yifeng Peng, David Plummer, Ilaria Quaglia, William Randel, Samuel Rémy, Takashi Sekiya, Stephen Steenrod, Timofei Sukhodolov, Simone Tilmes, Kostas Tsigaridis, Rei Ueyama, Daniele Visioni, Xinyue Wang, Shingo Watanabe, Yousuke Yamashita, Pengfei Yu, Wandi Yu, Jun Zhang, and Zhihong Zhuo
Geosci. Model Dev., 18, 5487–5512, https://doi.org/10.5194/gmd-18-5487-2025, https://doi.org/10.5194/gmd-18-5487-2025, 2025
Short summary
Short summary
To understand the climate impact of the 2022 Hunga volcanic eruption, we developed a climate model–observation comparison project. The paper describes the protocols and models that participate in the experiments. We designed several experiments to achieve our goals of this activity: (1) to evaluate the climate model performance and (2) to understand the Earth system responses to this eruption.
Hong Zhao, Han Dolman, Jan Elbers, Wilma Jans, Bart Kruijt, Eddy Moors, Henk Snellen, Jordi Vila-Guerau de Arellano, Wouter Peters, Maarten Krol, Ronald Hutjes, and Michiel van der Molen
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-372, https://doi.org/10.5194/essd-2025-372, 2025
Revised manuscript under review for ESSD
Short summary
Short summary
Under the Kyoto Protocol the carbon dioxide (CO2) balance for forest ecosystems was required to be measured. Consequently, CO2 flux measurements have been conducted in Loobos site in the Netherlands since 1996, becoming one of the 17 first FLUXNET sites globally. This paper provides a comprehensive overview of the instrumentation, data processing and the resulting data archive, enabling its further use in data analysis, model development and validation of satellite data retrievals.
Blanca Ayarzagüena, Amy H. Butler, Peter Hitchcock, Chaim I. Garfinkel, Zac D. Lawrence, Wuhan Ning, Philip Rupp, Zheng Wu, Hilla Afargan-Gerstman, Natalia Calvo, Álvaro de la Cámara, Martin Jucker, Gerbrand Koren, Daniel De Maeseneire, Gloria L. Manney, Marisol Osman, Masakazu Taguchi, Cory Barton, Dong-Chang Hong, Yu-Kyung Hyun, Hera Kim, Jeff Knight, Piero Malguzzi, Daniele Mastrangelo, Jiyoung Oh, Inna Polichtchouk, Jadwiga H. Richter, Isla R. Simpson, Seok-Woo Son, Damien Specq, and Tim Stockdale
EGUsphere, https://doi.org/10.5194/egusphere-2025-3611, https://doi.org/10.5194/egusphere-2025-3611, 2025
Short summary
Short summary
Sudden Stratospheric Warmings (SSWs) are known to follow a sustained wave dissipation in the stratosphere, which depends on both the tropospheric and stratospheric states. However, the relative role of each state is still unclear. Using a new set of subseasonal to seasonal forecasts, we show that the stratospheric state does not drastically affect the precursors of three recent SSWs, but modulates the stratospheric wave activity, with impacts depending on SSW features.
Theo Glauch, Julia Marshall, Christoph Gerbig, Santiago Botía, Michał Gałkowski, Sanam N. Vardag, and André Butz
Geosci. Model Dev., 18, 4713–4742, https://doi.org/10.5194/gmd-18-4713-2025, https://doi.org/10.5194/gmd-18-4713-2025, 2025
Short summary
Short summary
The Vegetation Photosynthesis and Respiration Model (VPRM) estimates carbon exchange between the atmosphere and biosphere by modeling gross primary production and respiration using satellite data and weather variables. Our new version, pyVPRM, supports diverse satellite products like Sentinel-2, MODIS, VIIRS, and new land cover maps, enabling high spatial and temporal resolution. This improves flux estimates, especially in complex landscapes, and ensures continuity as MODIS nears decommissioning.
Theertha Kariyathan, Ana Bastos, Markus Reichstein, Wouter Peters, and Julia Marshall
Atmos. Chem. Phys., 25, 7863–7878, https://doi.org/10.5194/acp-25-7863-2025, https://doi.org/10.5194/acp-25-7863-2025, 2025
Short summary
Short summary
The carbon uptake period (CUP) is the time period when land absorbs more CO2 than it emits. While atmospheric CO2 mole fraction measurements can be used to assess CUP changes, atmospheric transport and asynchronous timing across regions reduce the accuracy of the estimates. Forward model experiments show that only ~ 50 % of prescribed shifts in CUP timing applied to surface fluxes (ΔCUPNEE) are captured in simulated CO2 mole fraction data at monitoring sites like the Barrow Atmospheric Baseline Observatory.
Amauri C. Prudente Junior, Luiz A. T. Machado, Felipe S. Silva, Tercio Ambrizzi, Paulo Artaxo, Santiago Botia, Luan P. Cordeiro, Cleo Q. Dias Junior, Edmilson Freitas, Demerval S. Moreira, Christopher Pöhlker, Ivan M. C. Toro, Xiyan Xu, and Luciana V. Rizzo
EGUsphere, https://doi.org/10.5194/egusphere-2025-2869, https://doi.org/10.5194/egusphere-2025-2869, 2025
Short summary
Short summary
This study propoes a new method of spatialization to estimate carbon fluxes in the Brazilian Amazon biome. To do so, was used a land surface model (JULES) and two vegetation properties. The results of this spatialization resulted in a carbon fluxes of -1.34 Pg C during the year of 2021 in the entire Brazilian Amazon biome being the states of Amapa and Acre main relevant regions of carbon source.
Santiago Botía, Saqr Munassar, Thomas Koch, Danilo Custodio, Luana S. Basso, Shujiro Komiya, Jost V. Lavric, David Walter, Manuel Gloor, Giordane Martins, Stijn Naus, Gerbrand Koren, Ingrid T. Luijkx, Stijn Hantson, John B. Miller, Wouter Peters, Christian Rödenbeck, and Christoph Gerbig
Atmos. Chem. Phys., 25, 6219–6255, https://doi.org/10.5194/acp-25-6219-2025, https://doi.org/10.5194/acp-25-6219-2025, 2025
Short summary
Short summary
This study uses dry CO2 mole fractions from the Amazon Tall Tower Observatory together with airborne profiles to estimate net carbon exchange in tropical South America. We found that the biogeographic Amazon is a net carbon sink, while the Cerrado and Caatinga biomes are net carbon sources, resulting in an overall neutral balance. Finally, to further reduce the uncertainty in our estimates we call for an expansion of the monitoring capacity, especially in the Amazon–Andes foothills.
Getachew Agmuas Adnew, Gerbrand Koren, Neha Mehendale, Sergey Gromov, Maarten Krol, and Thomas Röckmann
Atmos. Meas. Tech., 18, 2701–2719, https://doi.org/10.5194/amt-18-2701-2025, https://doi.org/10.5194/amt-18-2701-2025, 2025
Short summary
Short summary
This study presents high-precision measurements of ∆′17O(CO2). Key findings include the extension of the N2O–∆′17O correlation to the upper troposphere and the identification of significant differences in the N2O–∆′17O slope in StratoClim samples. Additionally, the ∆′17O measurements are used to estimate global stratospheric production and surface removal of ∆′17O, providing an independent estimate of global vegetation CO2 exchange.
Cynthia H. Whaley, Tim Butler, Jose A. Adame, Rupal Ambulkar, Steve R. Arnold, Rebecca R. Buchholz, Benjamin Gaubert, Douglas S. Hamilton, Min Huang, Hayley Hung, Johannes W. Kaiser, Jacek W. Kaminski, Christoph Knote, Gerbrand Koren, Jean-Luc Kouassi, Meiyun Lin, Tianjia Liu, Jianmin Ma, Kasemsan Manomaiphiboon, Elisa Bergas Masso, Jessica L. McCarty, Mariano Mertens, Mark Parrington, Helene Peiro, Pallavi Saxena, Saurabh Sonwani, Vanisa Surapipith, Damaris Y. T. Tan, Wenfu Tang, Veerachai Tanpipat, Kostas Tsigaridis, Christine Wiedinmyer, Oliver Wild, Yuanyu Xie, and Paquita Zuidema
Geosci. Model Dev., 18, 3265–3309, https://doi.org/10.5194/gmd-18-3265-2025, https://doi.org/10.5194/gmd-18-3265-2025, 2025
Short summary
Short summary
The multi-model experiment design of the HTAP3 Fires project takes a multi-pollutant approach to improving our understanding of transboundary transport of wildland fire and agricultural burning emissions and their impacts. The experiments are designed with the goal of answering science policy questions related to fires. The options for the multi-model approach, including inputs, outputs, and model setup, are discussed, and the official recommendations for the project are presented.
Samuel Upton, Markus Reichstein, Wouter Peters, Santiago Botía, Jacob A. Nelson, Sophia Walther, Martin Jung, Fabian Gans, László Haszpra, and Ana Bastos
EGUsphere, https://doi.org/10.5194/egusphere-2025-2097, https://doi.org/10.5194/egusphere-2025-2097, 2025
Short summary
Short summary
We create a hybrid ecosystem-level carbon flux model using both eddy-covariance observations and observations of the atmospheric mole fraction of CO2 at three tall-tower observatories. Our study uses an atmospheric transport model (STILT) to connect the atmospheric signal to the ecosystem-level model. We show that this inclusion of atmospheric information meaningfully improves the model's representation of the interannual variability of the global net flux of CO2.
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
Earth Syst. Sci. Data, 17, 1121–1152, https://doi.org/10.5194/essd-17-1121-2025, https://doi.org/10.5194/essd-17-1121-2025, 2025
Short summary
Short summary
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.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Judith Hauck, Peter Landschützer, Corinne Le Quéré, Hongmei Li, Ingrid T. Luijkx, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Almut Arneth, Vivek Arora, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Carla F. Berghoff, Henry C. Bittig, Laurent Bopp, Patricia Cadule, Katie Campbell, Matthew A. Chamberlain, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Thomas Colligan, Jeanne Decayeux, Laique M. Djeutchouang, Xinyu Dou, Carolina Duran Rojas, Kazutaka Enyo, Wiley Evans, Amanda R. Fay, Richard A. Feely, Daniel J. Ford, Adrianna Foster, Thomas Gasser, Marion Gehlen, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Jens Heinke, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Andrew R. Jacobson, Atul K. Jain, Tereza Jarníková, Annika Jersild, Fei Jiang, Zhe Jin, Etsushi Kato, Ralph F. Keeling, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Xin Lan, Siv K. Lauvset, Nathalie Lefèvre, Zhu Liu, Junjie Liu, Lei Ma, Shamil Maksyutov, Gregg Marland, Nicolas Mayot, Patrick C. McGuire, Nicolas Metzl, Natalie M. Monacci, Eric J. Morgan, Shin-Ichiro Nakaoka, Craig Neill, Yosuke Niwa, Tobias Nützel, Lea Olivier, Tsuneo Ono, Paul I. Palmer, Denis Pierrot, Zhangcai Qin, Laure Resplandy, Alizée Roobaert, Thais M. Rosan, Christian Rödenbeck, Jörg Schwinger, T. Luke Smallman, Stephen M. Smith, Reinel Sospedra-Alfonso, Tobias Steinhoff, Qing Sun, Adrienne J. Sutton, Roland Séférian, Shintaro Takao, Hiroaki Tatebe, Hanqin Tian, Bronte Tilbrook, Olivier Torres, Etienne Tourigny, Hiroyuki Tsujino, Francesco Tubiello, Guido van der Werf, Rik Wanninkhof, Xuhui Wang, Dongxu Yang, Xiaojuan Yang, Zhen Yu, Wenping Yuan, Xu Yue, Sönke Zaehle, Ning Zeng, and Jiye Zeng
Earth Syst. Sci. Data, 17, 965–1039, https://doi.org/10.5194/essd-17-965-2025, https://doi.org/10.5194/essd-17-965-2025, 2025
Short summary
Short summary
The Global Carbon Budget 2024 describes the methodology, main results, and datasets used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, land ecosystems, and the ocean over the historical period (1750–2024). These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Takashi Sekiya, Emanuele Emili, Kazuyuki Miyazaki, Antje Inness, Zhen Qu, R. Bradley Pierce, Dylan Jones, Helen Worden, William Y. Y. Cheng, Vincent Huijnen, and Gerbrand Koren
Atmos. Chem. Phys., 25, 2243–2268, https://doi.org/10.5194/acp-25-2243-2025, https://doi.org/10.5194/acp-25-2243-2025, 2025
Short summary
Short summary
Five global chemical reanalysis datasets were used to assess the relative impacts of assimilating satellite ozone and its precursor measurements on tropospheric ozone analyses for 2010. The multiple reanalysis system comparison allows an evaluation of the dependency of the impacts on different reanalysis systems. The results suggested the importance of satellite ozone and its precursor measurements for improving ozone analysis in the whole troposphere, with varying magnitudes among the systems.
Chaim I. Garfinkel, Zachary D. Lawrence, Amy H. Butler, Etienne Dunn-Sigouin, Irene Erner, Alexey Y. Karpechko, Gerbrand Koren, Marta Abalos, Blanca Ayarzagüena, David Barriopedro, Natalia Calvo, Alvaro de la Cámara, Andrew Charlton-Perez, Judah Cohen, Daniela I. V. Domeisen, Javier García-Serrano, Neil P. Hindley, Martin Jucker, Hera Kim, Robert W. Lee, Simon H. Lee, Marisol Osman, Froila M. Palmeiro, Inna Polichtchouk, Jian Rao, Jadwiga H. Richter, Chen Schwartz, Seok-Woo Son, Masakazu Taguchi, Nicholas L. Tyrrell, Corwin J. Wright, and Rachel W.-Y. Wu
Weather Clim. Dynam., 6, 171–195, https://doi.org/10.5194/wcd-6-171-2025, https://doi.org/10.5194/wcd-6-171-2025, 2025
Short summary
Short summary
Variability in the extratropical stratosphere and troposphere is coupled, and because of the longer timescales characteristic of the stratosphere, this allows for a window of opportunity for surface prediction. This paper assesses whether models used for operational prediction capture these coupling processes accurately. We find that most processes are too weak; however downward coupling from the lower stratosphere to the near surface is too strong.
Saqr Munassar, Christian Rödenbeck, Michał Gałkowski, Frank-Thomas Koch, Kai U. Totsche, Santiago Botía, and Christoph Gerbig
Atmos. Chem. Phys., 25, 639–656, https://doi.org/10.5194/acp-25-639-2025, https://doi.org/10.5194/acp-25-639-2025, 2025
Short summary
Short summary
CO2 mole fractions simulated over a global set of stations showed an overestimation of CO2 if the diurnal cycle is missing in biogenic fluxes. This leads to biases in the estimated fluxes derived from the regional-scale inversions. Interannual variability of estimated biogenic fluxes is also affected by the exclusion of the CO2 diurnal cycle. The findings point to the importance of including the diurnal variations of CO2 in the biogenic fluxes used as priors in global and regional inversions.
Dylan Jones, Lucas Prates, Zhen Qu, William Cheng, Kazuyuki Miyazaki, Takashi Sekiya, Antje Inness, Rajesh Kumar, Xiao Tang, Helen Worden, Gerbrand Koren, and Vincent Huijen
EGUsphere, https://doi.org/10.5194/egusphere-2024-3759, https://doi.org/10.5194/egusphere-2024-3759, 2025
Short summary
Short summary
We evaluate five chemical reanalysis products to assess their potential to provide useful information on tropospheric ozone variability. We find that the reanalyses produce consistent information on ozone variations in the free troposphere, but have large discrepancies at the surface. The results suggests that improvements in the reanalyses are needed to better exploit the assimilated observations to enhance the utility of the reanalysis products at the surface.
David Ho, Michał Gałkowski, Friedemann Reum, Santiago Botía, Julia Marshall, Kai Uwe Totsche, and Christoph Gerbig
Geosci. Model Dev., 17, 7401–7422, https://doi.org/10.5194/gmd-17-7401-2024, https://doi.org/10.5194/gmd-17-7401-2024, 2024
Short summary
Short summary
Atmospheric model users often overlook the impact of the land–atmosphere interaction. This study accessed various setups of WRF-GHG simulations that ensure consistency between the model and driving reanalysis fields. We found that a combination of nudging and frequent re-initialization allows certain improvement by constraining the soil moisture fields and, through its impact on atmospheric mixing, improves atmospheric transport.
Ingrid Super, Tia Scarpelli, Arjan Droste, and Paul I. Palmer
Geosci. Model Dev., 17, 7263–7284, https://doi.org/10.5194/gmd-17-7263-2024, https://doi.org/10.5194/gmd-17-7263-2024, 2024
Short summary
Short summary
Monitoring greenhouse gas emission reductions requires a combination of models and observations, as well as an initial emission estimate. Each component provides information with a certain level of certainty and is weighted to yield the most reliable estimate of actual emissions. We describe efforts for estimating the uncertainty in the initial emission estimate, which significantly impacts the outcome. Hence, a good uncertainty estimate is key for obtaining reliable information on emissions.
Pharahilda M. Steur, Hubertus A. Scheeren, Gerbrand Koren, Getachew A. Adnew, Wouter Peters, and Harro A. J. Meijer
Atmos. Chem. Phys., 24, 11005–11027, https://doi.org/10.5194/acp-24-11005-2024, https://doi.org/10.5194/acp-24-11005-2024, 2024
Short summary
Short summary
We present records of the triple oxygen isotope signature (Δ(17O)) of atmospheric CO2 obtained with laser absorption spectroscopy from two mid-latitude stations. Significant interannual variability is observed in both records. A model sensitivity study suggests that stratosphere–troposphere exchange, which carries high-Δ(17O) CO2 from the stratosphere into the troposphere, causes most of the variability. This makes Δ(17O) a potential tracer for stratospheric intrusions into the troposphere.
Tia R. Scarpelli, Paul I. Palmer, Mark Lunt, Ingrid Super, and Arjan Droste
Atmos. Chem. Phys., 24, 10773–10791, https://doi.org/10.5194/acp-24-10773-2024, https://doi.org/10.5194/acp-24-10773-2024, 2024
Short summary
Short summary
Under the Paris Agreement, countries must track their anthropogenic greenhouse gas emissions. This study describes a method to determine self-consistent estimates for combustion emissions and natural fluxes of CO2 from atmospheric data. We report consistent estimates inferred using this approach from satellite data and ground-based data over Europe, suggesting that satellite data can be used to determine national anthropogenic CO2 emissions for countries where ground-based CO2 data are absent.
Pierluigi Renan Guaita, Riccardo Marzuoli, Leiming Zhang, Steven Turnock, Gerbrand Koren, Oliver Wild, Paola Crippa, and Giacomo Alessandro Gerosa
EGUsphere, https://doi.org/10.5194/egusphere-2024-2573, https://doi.org/10.5194/egusphere-2024-2573, 2024
Preprint archived
Short summary
Short summary
This study assesses the global impact of tropospheric ozone on wheat crops in the 21st century under various climate scenarios. The research highlights that ozone damage to wheat varies by region and depends on both ozone levels and climate. Vulnerable regions include East Asia, Northern Europe, and the Southern and Eastern edges of the Tibetan Plateau. Our results emphasize the need of policies to reduce ozone levels and mitigate climate change to protect global food security.
Luiz A. T. Machado, Jürgen Kesselmeier, Santiago Botía, Hella van Asperen, Meinrat O. Andreae, Alessandro C. de Araújo, Paulo Artaxo, Achim Edtbauer, Rosaria R. Ferreira, Marco A. Franco, Hartwig Harder, Sam P. Jones, Cléo Q. Dias-Júnior, Guido G. Haytzmann, Carlos A. Quesada, Shujiro Komiya, Jost Lavric, Jos Lelieveld, Ingeborg Levin, Anke Nölscher, Eva Pfannerstill, Mira L. Pöhlker, Ulrich Pöschl, Akima Ringsdorf, Luciana Rizzo, Ana M. Yáñez-Serrano, Susan Trumbore, Wanda I. D. Valenti, Jordi Vila-Guerau de Arellano, David Walter, Jonathan Williams, Stefan Wolff, and Christopher Pöhlker
Atmos. Chem. Phys., 24, 8893–8910, https://doi.org/10.5194/acp-24-8893-2024, https://doi.org/10.5194/acp-24-8893-2024, 2024
Short summary
Short summary
Composite analysis of gas concentration before and after rainfall, during the day and night, gives insight into the complex relationship between trace gas variability and precipitation. The analysis helps us to understand the sources and sinks of trace gases within a forest ecosystem. It elucidates processes that are not discernible under undisturbed conditions and contributes to a deeper understanding of the trace gas life cycle and its intricate interactions with cloud dynamics in the Amazon.
Kim A. P. Faassen, Jordi Vilà-Guerau de Arellano, Raquel González-Armas, Bert G. Heusinkveld, Ivan Mammarella, Wouter Peters, and Ingrid T. Luijkx
Biogeosciences, 21, 3015–3039, https://doi.org/10.5194/bg-21-3015-2024, https://doi.org/10.5194/bg-21-3015-2024, 2024
Short summary
Short summary
The ratio between atmospheric O2 and CO2 can be used to characterize the carbon balance at the surface. By combining a model and observations from the Hyytiälä forest (Finland), we show that using atmospheric O2 and CO2 measurements from a single height provides a weak constraint on the surface CO2 exchange because large-scale processes such as entrainment confound this signal. We therefore recommend always using multiple heights of O2 and CO2 measurements to study surface CO2 exchange.
Francesco Barbano, Erika Brattich, Carlo Cintolesi, Abdul Ghafoor Nizamani, Silvana Di Sabatino, Massimo Milelli, Esther E. M. Peerlings, Sjoerd Polder, Gert-Jan Steeneveld, and Antonio Parodi
Atmos. Meas. Tech., 17, 3255–3278, https://doi.org/10.5194/amt-17-3255-2024, https://doi.org/10.5194/amt-17-3255-2024, 2024
Short summary
Short summary
The characterization of the urban microclimate starts with atmospheric monitoring using a dense array of sensors to capture the spatial variations induced by the different morphology, land cover, and presence of vegetation. To provide a new sensor for this scope, this paper evaluates the outdoor performance of a commercial mobile sensor. The results mark the sensor's ability to capture the same atmospheric variability as the reference, making it a valid solution for atmospheric monitoring.
Jin Ma, Linda M. J. Kooijmans, Norbert Glatthor, Stephen A. Montzka, Marc von Hobe, Thomas Röckmann, and Maarten C. Krol
Atmos. Chem. Phys., 24, 6047–6070, https://doi.org/10.5194/acp-24-6047-2024, https://doi.org/10.5194/acp-24-6047-2024, 2024
Short summary
Short summary
The global budget of atmospheric COS can be optimised by inverse modelling using TM5-4DVAR, with the co-constraints of NOAA surface observations and MIPAS satellite data. We found reduced COS biosphere uptake from inversions and improved land and ocean separation using MIPAS satellite data assimilation. Further improvements are expected from better quantification of COS ocean and biosphere fluxes.
Juliëtte C. S. Anema, Klaas Folkert Boersma, Piet Stammes, Gerbrand Koren, William Woodgate, Philipp Köhler, Christian Frankenberg, and Jacqui Stol
Biogeosciences, 21, 2297–2311, https://doi.org/10.5194/bg-21-2297-2024, https://doi.org/10.5194/bg-21-2297-2024, 2024
Short summary
Short summary
To keep the Paris agreement goals within reach, negative emissions are necessary. They can be achieved with mitigation techniques, such as reforestation, which remove CO2 from the atmosphere. While governments have pinned their hopes on them, there is not yet a good set of tools to objectively determine whether negative emissions do what they promise. Here we show how satellite measurements of plant fluorescence are useful in detecting carbon uptake due to reforestation and vegetation regrowth.
Andreas Petzold, Ulrich Bundke, Anca Hienola, Paolo Laj, Cathrine Lund Myhre, Alex Vermeulen, Angeliki Adamaki, Werner Kutsch, Valerie Thouret, Damien Boulanger, Markus Fiebig, Markus Stocker, Zhiming Zhao, and Ari Asmi
Atmos. Chem. Phys., 24, 5369–5388, https://doi.org/10.5194/acp-24-5369-2024, https://doi.org/10.5194/acp-24-5369-2024, 2024
Short summary
Short summary
Easy and fast access to long-term and high-quality observational data is recognised as fundamental to environmental research and the development of climate forecasting and assessment services. We discuss the potential new directions in atmospheric sciences offered by the atmosphere-centric European research infrastructures ACTRIS, IAGOS, and ICOS, building on their capabilities for standardised provision of data through open access combined with tools and methods of data-intensive science.
Mugni Hadi Hariadi, Gerard van der Schrier, Gert-Jan Steeneveld, Samuel J. Sutanto, Edwin Sutanudjaja, Dian Nur Ratri, Ardhasena Sopaheluwakan, and Albert Klein Tank
Hydrol. Earth Syst. Sci., 28, 1935–1956, https://doi.org/10.5194/hess-28-1935-2024, https://doi.org/10.5194/hess-28-1935-2024, 2024
Short summary
Short summary
We utilize the high-resolution CMIP6 for extreme rainfall and streamflow projection over Southeast Asia. This region will experience an increase in both dry and wet extremes in the near future. We found a more extreme low flow and high flow, along with an increasing probability of low-flow and high-flow events. We reveal that the changes in low-flow events and their probabilities are not only influenced by extremely dry climates but also by the catchment characteristics.
Michael Steiner, Wouter Peters, Ingrid Luijkx, Stephan Henne, Huilin Chen, Samuel Hammer, and Dominik Brunner
Atmos. Chem. Phys., 24, 2759–2782, https://doi.org/10.5194/acp-24-2759-2024, https://doi.org/10.5194/acp-24-2759-2024, 2024
Short summary
Short summary
The Paris Agreement increased interest in estimating greenhouse gas (GHG) emissions of individual countries, but top-down emission estimation is not yet considered policy-relevant. It is therefore paramount to reduce large errors and to build systems that are based on the newest atmospheric transport models. In this study, we present the first application of ICON-ART in the inverse modeling of GHG fluxes with an ensemble Kalman filter and present our results for European CH4 emissions.
Samuel Upton, Markus Reichstein, Fabian Gans, Wouter Peters, Basil Kraft, and Ana Bastos
Atmos. Chem. Phys., 24, 2555–2582, https://doi.org/10.5194/acp-24-2555-2024, https://doi.org/10.5194/acp-24-2555-2024, 2024
Short summary
Short summary
Data-driven eddy-covariance upscaled estimates of the global land–atmosphere net CO2 exchange (NEE) show important mismatches with regional and global estimates based on atmospheric information. To address this, we create a model with a dual constraint based on bottom-up eddy-covariance data and top-down atmospheric inversion data. Our model overcomes shortcomings of each approach, producing improved NEE estimates from local to global scale, helping to reduce uncertainty in the carbon budget.
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.
Lammert Kooistra, Katja Berger, Benjamin Brede, Lukas Valentin Graf, Helge Aasen, Jean-Louis Roujean, Miriam Machwitz, Martin Schlerf, Clement Atzberger, Egor Prikaziuk, Dessislava Ganeva, Enrico Tomelleri, Holly Croft, Pablo Reyes Muñoz, Virginia Garcia Millan, Roshanak Darvishzadeh, Gerbrand Koren, Ittai Herrmann, Offer Rozenstein, Santiago Belda, Miina Rautiainen, Stein Rune Karlsen, Cláudio Figueira Silva, Sofia Cerasoli, Jon Pierre, Emine Tanır Kayıkçı, Andrej Halabuk, Esra Tunc Gormus, Frank Fluit, Zhanzhang Cai, Marlena Kycko, Thomas Udelhoven, and Jochem Verrelst
Biogeosciences, 21, 473–511, https://doi.org/10.5194/bg-21-473-2024, https://doi.org/10.5194/bg-21-473-2024, 2024
Short summary
Short summary
We reviewed optical remote sensing time series (TS) studies for monitoring vegetation productivity across ecosystems. Methods were categorized into trend analysis, land surface phenology, and assimilation into statistical or dynamic vegetation models. Due to progress in machine learning, TS processing methods will diversify, while modelling strategies will advance towards holistic processing. We propose integrating methods into a digital twin to improve the understanding of vegetation dynamics.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Dorothee C. E. Bakker, Judith Hauck, Peter Landschützer, Corinne Le Quéré, Ingrid T. Luijkx, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Peter Anthoni, Leticia Barbero, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Bertrand Decharme, Laurent Bopp, Ida Bagus Mandhara Brasika, Patricia Cadule, Matthew A. Chamberlain, Naveen Chandra, Thi-Tuyet-Trang Chau, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Xinyu Dou, Kazutaka Enyo, Wiley Evans, Stefanie Falk, Richard A. Feely, Liang Feng, Daniel J. Ford, Thomas Gasser, Josefine Ghattas, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Jens Heinke, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Andrew R. Jacobson, Atul Jain, Tereza Jarníková, Annika Jersild, Fei Jiang, Zhe Jin, Fortunat Joos, Etsushi Kato, Ralph F. Keeling, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Arne Körtzinger, Xin Lan, Nathalie Lefèvre, Hongmei Li, Junjie Liu, Zhiqiang Liu, Lei Ma, Greg Marland, Nicolas Mayot, Patrick C. McGuire, Galen A. McKinley, Gesa Meyer, Eric J. Morgan, David R. Munro, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin M. O'Brien, Are Olsen, Abdirahman M. Omar, Tsuneo Ono, Melf Paulsen, Denis Pierrot, Katie Pocock, Benjamin Poulter, Carter M. Powis, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Thais M. Rosan, Jörg Schwinger, Roland Séférian, T. Luke Smallman, Stephen M. Smith, Reinel Sospedra-Alfonso, Qing Sun, Adrienne J. Sutton, Colm Sweeney, Shintaro Takao, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Hiroyuki Tsujino, Francesco Tubiello, Guido R. van der Werf, Erik van Ooijen, Rik Wanninkhof, Michio Watanabe, Cathy Wimart-Rousseau, Dongxu Yang, Xiaojuan Yang, Wenping Yuan, Xu Yue, Sönke Zaehle, Jiye Zeng, and Bo Zheng
Earth Syst. Sci. Data, 15, 5301–5369, https://doi.org/10.5194/essd-15-5301-2023, https://doi.org/10.5194/essd-15-5301-2023, 2023
Short summary
Short summary
The Global Carbon Budget 2023 describes the methodology, main results, and data sets used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, land ecosystems, and the ocean over the historical period (1750–2023). These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
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.
Luana S. Basso, Chris Wilson, Martyn P. Chipperfield, Graciela Tejada, Henrique L. G. Cassol, Egídio Arai, Mathew Williams, T. Luke Smallman, Wouter Peters, Stijn Naus, John B. Miller, and Manuel Gloor
Atmos. Chem. Phys., 23, 9685–9723, https://doi.org/10.5194/acp-23-9685-2023, https://doi.org/10.5194/acp-23-9685-2023, 2023
Short summary
Short summary
The Amazon’s carbon balance may have changed due to forest degradation, deforestation and warmer climate. We used an atmospheric model and atmospheric CO2 observations to quantify Amazonian carbon emissions (2010–2018). The region was a small carbon source to the atmosphere, mostly due to fire emissions. Forest uptake compensated for ~ 50 % of the fire emissions, meaning that the remaining forest is still a small carbon sink. We found no clear evidence of weakening carbon uptake over the period.
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.
Eliane Gomes Alves, Raoni Aquino Santana, Cléo Quaresma Dias-Júnior, Santiago Botía, Tyeen Taylor, Ana Maria Yáñez-Serrano, Jürgen Kesselmeier, Efstratios Bourtsoukidis, Jonathan Williams, Pedro Ivo Lembo Silveira de Assis, Giordane Martins, Rodrigo de Souza, Sérgio Duvoisin Júnior, Alex Guenther, Dasa Gu, Anywhere Tsokankunku, Matthias Sörgel, Bruce Nelson, Davieliton Pinto, Shujiro Komiya, Diogo Martins Rosa, Bettina Weber, Cybelli Barbosa, Michelle Robin, Kenneth J. Feeley, Alvaro Duque, Viviana Londoño Lemos, Maria Paula Contreras, Alvaro Idarraga, Norberto López, Chad Husby, Brett Jestrow, and Iván Mauricio Cely Toro
Atmos. Chem. Phys., 23, 8149–8168, https://doi.org/10.5194/acp-23-8149-2023, https://doi.org/10.5194/acp-23-8149-2023, 2023
Short summary
Short summary
Isoprene is emitted mainly by plants and can influence atmospheric chemistry and air quality. But, there are uncertainties in model emission estimates and follow-up atmospheric processes. In our study, with long-term observational datasets of isoprene and biological and environmental factors from central Amazonia, we show that isoprene emission estimates could be improved when biological processes were mechanistically incorporated into the model.
Marc Guevara, Hervé Petetin, Oriol Jorba, Hugo Denier van der Gon, Jeroen Kuenen, Ingrid Super, Claire Granier, Thierno Doumbia, Philippe Ciais, Zhu Liu, Robin D. Lamboll, Sabine Schindlbacher, Bradley Matthews, and Carlos Pérez García-Pando
Atmos. Chem. Phys., 23, 8081–8101, https://doi.org/10.5194/acp-23-8081-2023, https://doi.org/10.5194/acp-23-8081-2023, 2023
Short summary
Short summary
This study provides an intercomparison of European 2020 emission changes derived from official inventories, which are reported by countries under the framework of several international conventions and directives, and non-official near-real-time estimates, the use of which has significantly grown since the COVID-19 outbreak. The results of the work are used to produce recommendations on how best to approach and make use of near-real-time emissions for modelling and monitoring applications.
Ara Cho, Linda M. J. Kooijmans, Kukka-Maaria Kohonen, Richard Wehr, and Maarten C. Krol
Biogeosciences, 20, 2573–2594, https://doi.org/10.5194/bg-20-2573-2023, https://doi.org/10.5194/bg-20-2573-2023, 2023
Short summary
Short summary
Carbonyl sulfide (COS) is a useful constraint for estimating photosynthesis. To simulate COS leaf flux better in the SiB4 model, we propose a novel temperature function for enzyme carbonic anhydrase (CA) activity and optimize conductances using observations. The optimal activity of CA occurs below 40 °C, and Ball–Woodrow–Berry parameters are slightly changed. These reduce/increase uptakes in the tropics/higher latitudes and contribute to resolving discrepancies in the COS global budget.
Theertha Kariyathan, Ana Bastos, Julia Marshall, Wouter Peters, Pieter Tans, and Markus Reichstein
Atmos. Meas. Tech., 16, 3299–3312, https://doi.org/10.5194/amt-16-3299-2023, https://doi.org/10.5194/amt-16-3299-2023, 2023
Short summary
Short summary
The timing and duration of the carbon uptake period (CUP) are sensitive to the occurrence of major phenological events, which are influenced by recent climate change. This study presents an ensemble-based approach for quantifying the timing and duration of the CUP and their uncertainty when derived from atmospheric CO2 measurements with noise and gaps. The CUP metrics derived with the approach are more robust and have less uncertainty than when estimated with the conventional methods.
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.
Kim A. P. Faassen, Linh N. T. Nguyen, Eadin R. Broekema, Bert A. M. Kers, Ivan Mammarella, Timo Vesala, Penelope A. Pickers, Andrew C. Manning, Jordi Vilà-Guerau de Arellano, Harro A. J. Meijer, Wouter Peters, and Ingrid T. Luijkx
Atmos. Chem. Phys., 23, 851–876, https://doi.org/10.5194/acp-23-851-2023, https://doi.org/10.5194/acp-23-851-2023, 2023
Short summary
Short summary
The exchange ratio (ER) between atmospheric O2 and CO2 provides a useful tracer for separately estimating photosynthesis and respiration processes in the forest carbon balance. This is highly relevant to better understand the expected biosphere sink, which determines future atmospheric CO2 levels. We therefore measured O2, CO2, and their ER above a boreal forest in Finland and investigated their diurnal behaviour for a representative day, and we show the most suitable way to determine the ER.
Stijn Naus, Lucas G. Domingues, Maarten Krol, Ingrid T. Luijkx, Luciana V. Gatti, John B. Miller, Emanuel Gloor, Sourish Basu, Caio Correia, Gerbrand Koren, Helen M. Worden, Johannes Flemming, Gabrielle Pétron, and Wouter Peters
Atmos. Chem. Phys., 22, 14735–14750, https://doi.org/10.5194/acp-22-14735-2022, https://doi.org/10.5194/acp-22-14735-2022, 2022
Short summary
Short summary
We assimilate MOPITT CO satellite data in the TM5-4D-Var inverse modelling framework to estimate Amazon fire CO emissions for 2003–2018. We show that fire emissions have decreased over the analysis period, coincident with a decrease in deforestation rates. However, interannual variations in fire emissions are large, and they correlate strongly with soil moisture. Our results reveal an important role for robust, top-down fire CO emissions in quantifying and attributing Amazon fire intensity.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Luke Gregor, Judith Hauck, Corinne Le Quéré, Ingrid T. Luijkx, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Ramdane Alkama, Almut Arneth, Vivek K. Arora, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Henry C. Bittig, Laurent Bopp, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Wiley Evans, Stefanie Falk, Richard A. Feely, Thomas Gasser, Marion Gehlen, Thanos Gkritzalis, Lucas Gloege, Giacomo Grassi, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Atul K. Jain, Annika Jersild, Koji Kadono, Etsushi Kato, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Peter Landschützer, Nathalie Lefèvre, Keith Lindsay, Junjie Liu, Zhu Liu, Gregg Marland, Nicolas Mayot, Matthew J. McGrath, Nicolas Metzl, Natalie M. Monacci, David R. Munro, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin O'Brien, Tsuneo Ono, Paul I. Palmer, Naiqing Pan, Denis Pierrot, Katie Pocock, Benjamin Poulter, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Carmen Rodriguez, Thais M. Rosan, Jörg Schwinger, Roland Séférian, Jamie D. Shutler, Ingunn Skjelvan, Tobias Steinhoff, Qing Sun, Adrienne J. Sutton, Colm Sweeney, Shintaro Takao, Toste Tanhua, Pieter P. Tans, Xiangjun Tian, Hanqin Tian, Bronte Tilbrook, Hiroyuki Tsujino, Francesco Tubiello, Guido R. van der Werf, Anthony P. Walker, Rik Wanninkhof, Chris Whitehead, Anna Willstrand Wranne, Rebecca Wright, Wenping Yuan, Chao Yue, Xu Yue, Sönke Zaehle, Jiye Zeng, and Bo Zheng
Earth Syst. Sci. Data, 14, 4811–4900, https://doi.org/10.5194/essd-14-4811-2022, https://doi.org/10.5194/essd-14-4811-2022, 2022
Short summary
Short summary
The Global Carbon Budget 2022 describes the datasets and methodology used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, the land ecosystems, and the ocean. These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Peter Bergamaschi, Arjo Segers, Dominik Brunner, Jean-Matthieu Haussaire, Stephan Henne, Michel Ramonet, Tim Arnold, Tobias Biermann, Huilin Chen, Sebastien Conil, Marc Delmotte, Grant Forster, Arnoud Frumau, Dagmar Kubistin, Xin Lan, Markus Leuenberger, Matthias Lindauer, Morgan Lopez, Giovanni Manca, Jennifer Müller-Williams, Simon O'Doherty, Bert Scheeren, Martin Steinbacher, Pamela Trisolino, Gabriela Vítková, and Camille Yver Kwok
Atmos. Chem. Phys., 22, 13243–13268, https://doi.org/10.5194/acp-22-13243-2022, https://doi.org/10.5194/acp-22-13243-2022, 2022
Short summary
Short summary
We present a novel high-resolution inverse modelling system, "FLEXVAR", and its application for the inverse modelling of European CH4 emissions in 2018. The new system combines a high spatial resolution of 7 km x 7 km with a variational data assimilation technique, which allows CH4 emissions to be optimized from individual model grid cells. The high resolution allows the observations to be better reproduced, while the derived emissions show overall good consistency with two existing models.
Kukka-Maaria Kohonen, Roderick Dewar, Gianluca Tramontana, Aleksanteri Mauranen, Pasi Kolari, Linda M. J. Kooijmans, Dario Papale, Timo Vesala, and Ivan Mammarella
Biogeosciences, 19, 4067–4088, https://doi.org/10.5194/bg-19-4067-2022, https://doi.org/10.5194/bg-19-4067-2022, 2022
Short summary
Short summary
Four different methods for quantifying photosynthesis (GPP) at ecosystem scale were tested, of which two are based on carbon dioxide (CO2) and two on carbonyl sulfide (COS) flux measurements. CO2-based methods are traditional partitioning, and a new method uses machine learning. We introduce a novel method for calculating GPP from COS fluxes, with potentially better applicability than the former methods. Both COS-based methods gave on average higher GPP estimates than the CO2-based estimates.
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.
Fabian Maier, Christoph Gerbig, Ingeborg Levin, Ingrid Super, Julia Marshall, and Samuel Hammer
Geosci. Model Dev., 15, 5391–5406, https://doi.org/10.5194/gmd-15-5391-2022, https://doi.org/10.5194/gmd-15-5391-2022, 2022
Short summary
Short summary
We show that the default representation of point source emissions in WRF–STILT leads to large overestimations when modelling fossil fuel CO2 concentrations for a 30 m high observation site during stable atmospheric conditions. We therefore introduce a novel point source modelling approach in WRF-STILT that takes into account their effective emission heights and results in a much better agreement with observations.
Marc Guevara, Hervé Petetin, Oriol Jorba, Hugo Denier van der Gon, Jeroen Kuenen, Ingrid Super, Jukka-Pekka Jalkanen, Elisa Majamäki, Lasse Johansson, Vincent-Henri Peuch, and Carlos Pérez García-Pando
Earth Syst. Sci. Data, 14, 2521–2552, https://doi.org/10.5194/essd-14-2521-2022, https://doi.org/10.5194/essd-14-2521-2022, 2022
Short summary
Short summary
To control the spread of the COVID-19 disease, European governments implemented mobility restriction measures that resulted in an unprecedented drop in anthropogenic emissions. This work presents a dataset of emission adjustment factors that allows quantifying changes in 2020 European primary emissions per country and pollutant sector at the daily scale. The resulting dataset can be used as input in modelling studies aiming at quantifying the impact of COVID-19 on air quality levels.
Pierre Friedlingstein, Matthew W. Jones, Michael O'Sullivan, Robbie M. Andrew, Dorothee C. E. Bakker, Judith Hauck, Corinne Le Quéré, Glen P. Peters, Wouter Peters, Julia Pongratz, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Rob B. Jackson, Simone R. Alin, Peter Anthoni, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Laurent Bopp, Thi Tuyet Trang Chau, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Kim I. Currie, Bertrand Decharme, Laique M. Djeutchouang, Xinyu Dou, Wiley Evans, Richard A. Feely, Liang Feng, Thomas Gasser, Dennis Gilfillan, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Ingrid T. Luijkx, Atul Jain, Steve D. Jones, Etsushi Kato, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Arne Körtzinger, Peter Landschützer, Siv K. Lauvset, Nathalie Lefèvre, Sebastian Lienert, Junjie Liu, Gregg Marland, Patrick C. McGuire, Joe R. Melton, David R. Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Yosuke Niwa, Tsuneo Ono, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Thais M. Rosan, Jörg Schwinger, Clemens Schwingshackl, Roland Séférian, Adrienne J. Sutton, Colm Sweeney, Toste Tanhua, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Francesco Tubiello, Guido R. van der Werf, Nicolas Vuichard, Chisato Wada, Rik Wanninkhof, Andrew J. Watson, David Willis, Andrew J. Wiltshire, Wenping Yuan, Chao Yue, Xu Yue, Sönke Zaehle, and Jiye Zeng
Earth Syst. Sci. Data, 14, 1917–2005, https://doi.org/10.5194/essd-14-1917-2022, https://doi.org/10.5194/essd-14-1917-2022, 2022
Short summary
Short summary
The Global Carbon Budget 2021 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
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
Short summary
Short summary
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).
Tobias Christoph Valentin Werner Riess, Klaas Folkert Boersma, Jasper van Vliet, Wouter Peters, Maarten Sneep, Henk Eskes, and Jos van Geffen
Atmos. Meas. Tech., 15, 1415–1438, https://doi.org/10.5194/amt-15-1415-2022, https://doi.org/10.5194/amt-15-1415-2022, 2022
Short summary
Short summary
This paper reports on improved monitoring of ship nitrogen oxide emissions by TROPOMI. With its fantastic resolution we can identify lanes of ship nitrogen dioxide (NO2) pollution not detected from space before. The quality of TROPOMI NO2 data over sea is improved further by recent upgrades in cloud retrievals and the use of sun glint scenes. Lastly, we study the impact of COVID-19 on ship NO2 in European seas and compare the found reductions to emission estimates gained from ship-specific data.
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.
Linh N. T. Nguyen, Harro A. J. Meijer, Charlotte van Leeuwen, Bert A. M. Kers, Hubertus A. Scheeren, Anna E. Jones, Neil Brough, Thomas Barningham, Penelope A. Pickers, Andrew C. Manning, and Ingrid T. Luijkx
Earth Syst. Sci. Data, 14, 991–1014, https://doi.org/10.5194/essd-14-991-2022, https://doi.org/10.5194/essd-14-991-2022, 2022
Short summary
Short summary
We present 20-year flask sample records of atmospheric CO2, O2, and APO from the stations Lutjewad (the Netherlands), Mace Head (Ireland), and Halley (Antarctica). Data from Lutjewad and Mace Head show similar long-term trends and seasonal cycles, agreeing with measurements from another station (Weybourne, UK). Measurements from Halley agree partly with those conducted by other institutes. From our 2002–2018 Lutjewad and Mace Head records, we find good agreement for global ocean carbon uptake.
Timo Vesala, Kukka-Maaria Kohonen, Linda M. J. Kooijmans, Arnaud P. Praplan, Lenka Foltýnová, Pasi Kolari, Markku Kulmala, Jaana Bäck, David Nelson, Dan Yakir, Mark Zahniser, and Ivan Mammarella
Atmos. Chem. Phys., 22, 2569–2584, https://doi.org/10.5194/acp-22-2569-2022, https://doi.org/10.5194/acp-22-2569-2022, 2022
Short summary
Short summary
Carbonyl sulfide (COS) provides new insights into carbon cycle research. We present an easy-to-use flux parameterization and the longest existing time series of forest–atmosphere COS exchange measurements, which allow us to study both seasonal and interannual variability. We observed only uptake of COS by the forest on an annual basis, with 37 % variability between years. Upscaling the boreal COS uptake using a biosphere model indicates a significant missing COS sink at high latitudes.
Philippe Ciais, Ana Bastos, Frédéric Chevallier, Ronny Lauerwald, Ben Poulter, Josep G. Canadell, Gustaf Hugelius, Robert B. Jackson, Atul Jain, Matthew Jones, Masayuki Kondo, Ingrid T. Luijkx, Prabir K. Patra, Wouter Peters, Julia Pongratz, Ana Maria Roxana Petrescu, Shilong Piao, Chunjing Qiu, Celso Von Randow, Pierre Regnier, Marielle Saunois, Robert Scholes, Anatoly Shvidenko, Hanqin Tian, Hui Yang, Xuhui Wang, and Bo Zheng
Geosci. Model Dev., 15, 1289–1316, https://doi.org/10.5194/gmd-15-1289-2022, https://doi.org/10.5194/gmd-15-1289-2022, 2022
Short summary
Short summary
The second phase of the Regional Carbon Cycle Assessment and Processes (RECCAP) will provide updated quantification and process understanding of CO2, CH4, and N2O emissions and sinks for ten regions of the globe. In this paper, we give definitions, review different methods, and make recommendations for estimating different components of the total land–atmosphere carbon exchange for each region in a consistent and complete approach.
Jeroen Kuenen, Stijn Dellaert, Antoon Visschedijk, Jukka-Pekka Jalkanen, Ingrid Super, and Hugo Denier van der Gon
Earth Syst. Sci. Data, 14, 491–515, https://doi.org/10.5194/essd-14-491-2022, https://doi.org/10.5194/essd-14-491-2022, 2022
Short summary
Short summary
This paper presents an 18-year time series for anthropogenic emissions for the main air pollutants in Europe, distinguishing 15 main source categories. It provides a complete overview of emissions to air and is designed to support air quality modelling. The data build where possible on official country total emissions used in the policy processes, but where necessary alternative data were used. The emission data are spatially distributed at high resolution (~ 6 km x 6 km) in a consistent way.
Ian Boutle, Wayne Angevine, Jian-Wen Bao, Thierry Bergot, Ritthik Bhattacharya, Andreas Bott, Leo Ducongé, Richard Forbes, Tobias Goecke, Evelyn Grell, Adrian Hill, Adele L. Igel, Innocent Kudzotsa, Christine Lac, Bjorn Maronga, Sami Romakkaniemi, Juerg Schmidli, Johannes Schwenkel, Gert-Jan Steeneveld, and Benoît Vié
Atmos. Chem. Phys., 22, 319–333, https://doi.org/10.5194/acp-22-319-2022, https://doi.org/10.5194/acp-22-319-2022, 2022
Short summary
Short summary
Fog forecasting is one of the biggest problems for numerical weather prediction. By comparing many models used for fog forecasting with others used for fog research, we hoped to help guide forecast improvements. We show some key processes that, if improved, will help improve fog forecasting, such as how water is deposited on the ground. We also showed that research models were not themselves a suitable baseline for comparison, and we discuss what future observations are required to improve them.
Linda M. J. Kooijmans, Ara Cho, Jin Ma, Aleya Kaushik, Katherine D. Haynes, Ian Baker, Ingrid T. Luijkx, Mathijs Groenink, Wouter Peters, John B. Miller, Joseph A. Berry, Jerome Ogée, Laura K. Meredith, Wu Sun, Kukka-Maaria Kohonen, Timo Vesala, Ivan Mammarella, Huilin Chen, Felix M. Spielmann, Georg Wohlfahrt, Max Berkelhammer, Mary E. Whelan, Kadmiel Maseyk, Ulli Seibt, Roisin Commane, Richard Wehr, and Maarten Krol
Biogeosciences, 18, 6547–6565, https://doi.org/10.5194/bg-18-6547-2021, https://doi.org/10.5194/bg-18-6547-2021, 2021
Short summary
Short summary
The gas carbonyl sulfide (COS) can be used to estimate photosynthesis. To adopt this approach on regional and global scales, we need biosphere models that can simulate COS exchange. So far, such models have not been evaluated against observations. We evaluate the COS biosphere exchange of the SiB4 model against COS flux observations. We find that the model is capable of simulating key processes in COS biosphere exchange. Still, we give recommendations for further improvement of the model.
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.
Thomas Luke Smallman, David Thomas Milodowski, Eráclito Sousa Neto, Gerbrand Koren, Jean Ometto, and Mathew Williams
Earth Syst. Dynam., 12, 1191–1237, https://doi.org/10.5194/esd-12-1191-2021, https://doi.org/10.5194/esd-12-1191-2021, 2021
Short summary
Short summary
Our study provides a novel assessment of model parameter, structure and climate change scenario uncertainty contribution to future predictions of the Brazilian terrestrial carbon stocks to 2100. We calibrated (2001–2017) five models of the terrestrial C cycle of varied structure. The calibrated models were then projected to 2100 under multiple climate change scenarios. Parameter uncertainty dominates overall uncertainty, being ~ 40 times that of either model structure or climate change scenario.
Margarita Choulga, Greet Janssens-Maenhout, Ingrid Super, Efisio Solazzo, Anna Agusti-Panareda, Gianpaolo Balsamo, Nicolas Bousserez, Monica Crippa, Hugo Denier van der Gon, Richard Engelen, Diego Guizzardi, Jeroen Kuenen, Joe McNorton, Gabriel Oreggioni, and Antoon Visschedijk
Earth Syst. Sci. Data, 13, 5311–5335, https://doi.org/10.5194/essd-13-5311-2021, https://doi.org/10.5194/essd-13-5311-2021, 2021
Short summary
Short summary
People worry that growing man-made carbon dioxide (CO2) concentrations lead to climate change. Global models, use of observations, and datasets can help us better understand behaviour of CO2. Here a tool to compute uncertainty in man-made CO2 sources per country per year and month is presented. An example of all sources separated into seven groups (intensive and average energy, industry, humans, ground and air transport, others) is presented. Results will be used to predict CO2 concentrations.
Mehliyar Sadiq, Paul I. Palmer, Mark F. Lunt, Liang Feng, Ingrid Super, Stijn N. C. Dellaert, and Hugo A. C. Denier van der Gon
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-816, https://doi.org/10.5194/acp-2021-816, 2021
Publication in ACP not foreseen
Short summary
Short summary
We make use of high-resolution emission inventory of CO2 and co-emitted tracers, satellite measurements, together with nested atmospheric transport model simulation, to investigate how reactive trace gases such as nitrogen dioxide and carbon monoxide can be used as proxies to determine the combustion contribution to atmospheric CO2 over Europe. We find stronger correlation in ratios of nitrogen dioxide and carbon dioxide between emission and satellite observed and modelled column concentration.
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.
Johannes G. M. Barten, Laurens N. Ganzeveld, Gert-Jan Steeneveld, and Maarten C. Krol
Atmos. Chem. Phys., 21, 10229–10248, https://doi.org/10.5194/acp-21-10229-2021, https://doi.org/10.5194/acp-21-10229-2021, 2021
Short summary
Short summary
We present an evaluation of ocean and snow/ice O3 deposition in explaining observed hourly surface O3 at 25 pan-Arctic sites using an atmospheric meteorology/chemistry model. The model includes a mechanistic representation of ocean O3 deposition as a function of ocean biogeochemical and mixing conditions. The mechanistic representation agrees better with O3 observations in terms of magnitude and temporal variability especially in the High Arctic (> 70° N).
Pharahilda M. Steur, Hubertus A. Scheeren, Dave D. Nelson, J. Barry McManus, and Harro A. J. Meijer
Atmos. Meas. Tech., 14, 4279–4304, https://doi.org/10.5194/amt-14-4279-2021, https://doi.org/10.5194/amt-14-4279-2021, 2021
Short summary
Short summary
For understanding the sources and sinks of atmospheric CO2, measurement of stable isotopes has proven to be highly valuable. We present a new method using laser absorption spectroscopy to simultaneously conduct measurements of three CO2 isotopes, directly on dry-air samples. This new method reduces sample preparation time significantly, compared to the conventional method in which measurements are conducted on pure CO2, and avoids measurement biases introduced by CO2 extraction.
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.
Fabienne Maignan, Camille Abadie, Marine Remaud, Linda M. J. Kooijmans, Kukka-Maaria Kohonen, Róisín Commane, Richard Wehr, J. Elliott Campbell, Sauveur Belviso, Stephen A. Montzka, Nina Raoult, Ulli Seibt, Yoichi P. Shiga, Nicolas Vuichard, Mary E. Whelan, and Philippe Peylin
Biogeosciences, 18, 2917–2955, https://doi.org/10.5194/bg-18-2917-2021, https://doi.org/10.5194/bg-18-2917-2021, 2021
Short summary
Short summary
The assimilation of carbonyl sulfide (COS) by continental vegetation has been proposed as a proxy for gross primary production (GPP). Using a land surface and a transport model, we compare a mechanistic representation of the plant COS uptake (Berry et al., 2013) to the classical leaf relative uptake (LRU) approach linking GPP and vegetation COS fluxes. We show that at high temporal resolutions a mechanistic approach is mandatory, but at large scales the LRU approach compares similarly.
Anteneh Getachew Mengistu, Gizaw Mengistu Tsidu, Gerbrand Koren, Maurits L. Kooreman, K. Folkert Boersma, Torbern Tagesson, Jonas Ardö, Yann Nouvellon, and Wouter Peters
Biogeosciences, 18, 2843–2857, https://doi.org/10.5194/bg-18-2843-2021, https://doi.org/10.5194/bg-18-2843-2021, 2021
Short summary
Short summary
In this study, we assess the usefulness of Sun-Induced Fluorescence of Terrestrial Ecosystems Retrieval (SIFTER) data from the GOME-2A instrument and near-infrared reflectance of vegetation (NIRv) from MODIS to capture the seasonality and magnitudes of gross primary production (GPP) derived from six eddy-covariance flux towers in Africa in the overlap years between 2007–2014. We also test the robustness of sun-induced fluoresence and NIRv to compare the seasonality of GPP for the major biomes.
Jin Ma, Linda M. J. Kooijmans, Ara Cho, Stephen A. Montzka, Norbert Glatthor, John R. Worden, Le Kuai, Elliot L. Atlas, and Maarten C. Krol
Atmos. Chem. Phys., 21, 3507–3529, https://doi.org/10.5194/acp-21-3507-2021, https://doi.org/10.5194/acp-21-3507-2021, 2021
Short summary
Short summary
Carbonyl sulfide is an important trace gas in the atmosphere and useful to estimating gross primary productivity in ecosystems, but its sources and sinks remain highly uncertain. Therefore, we applied inverse model system TM5-4DVAR to better constrain the global budget. Our finding is in line with earlier studies, pointing to missing sources in the tropics and more uptake in high latitudes. We also stress the necessity of more ground-based observations and satellite data assimilation in future.
Cited articles
Agustí-Panareda, A., Massart, S., Chevallier, F., Boussetta, S., Balsamo, G., Beljaars, A., Ciais, P., Deutscher, N. M., Engelen, R., Jones, L., Kivi, R., Paris, J.-D., Peuch, V.-H., Sherlock, V., Vermeulen, A. T., Wennberg, P. O., and Wunch, D.: Forecasting global atmospheric CO2, Atmos. Chem. Phys., 14, 11959–11983, https://doi.org/10.5194/acp-14-11959-2014, 2014. a, b, c
Agustí-Panareda, A., Massart, S., Chevallier, F., Balsamo, G., Boussetta, S., Dutra, E., and Beljaars, A.: A biogenic CO2 flux adjustment scheme for the mitigation of large-scale biases in global atmospheric CO2 analyses and forecasts, Atmos. Chem. Phys., 16, 10399–10418, https://doi.org/10.5194/acp-16-10399-2016, 2016. a, b
Andres, R. J., Marland, G., Fung, I., and Matthews, E.: A 1∘ × 1∘ distribution of carbon dioxide emissions from fossil fuel
consumption and cement manufacture, 1950–1990, Global Biogeochem. Cycles,
10, 419–429, https://doi.org/10.1029/96GB01523, 1996. a
Arriga, N., Goded, I., Manca, G., and ICOS Ecosystem Thematic Centre: Warm winter 2020 ecosystem eddy covariance flux prod35
uct from San Rossore 2, Warm Winter 2020 ecosystem eddy covariance flux product for 73 stations in FLUXNET-Archive format – release 2022-1 (Version 1.0), ICOS [data set],
https://doi.org/10.18160/EPYB-PSFM, 2022. a
Badgley, G., Anderegg, L. D., Berry, J. A., and Field, C. B.: Terrestrial
gross primary production: Using NIRV to scale from site to globe, Global
Change Biol., 25, 3731–3740, https://doi.org/10.1111/gcb.14729, 2019. a
Baker, I. T., Denning, A. S., and Stöckli, R.: North American gross
primary productivity: Regional characterization and interannual variability,
Tellus B, 62, 533–549,
https://doi.org/10.1111/j.1600-0889.2010.00492.x, 2010. a
Balsamo, G., Engelen, R., Thiemert, D., Agusti-Panareda, A., Bousserez, N.,
Broquet, G., Brunner, D., Buchwitz, M., Chevallier, F., Choulga, M., Denier
Van Der Gon, H., Florentie, L., Haussaire, J.-M., Janssens-Maenhout, G.,
Jones, M. W., Kaminski, T., Krol, M., Le Quéré, C., Marshall, J.,
McNorton, J., Prunet, P., Reuter, M., Peters, W., and Scholze, M.: The CO2
Human Emissions (CHE) Project: First Steps Towards a European Operational
Capacity to Monitor Anthropogenic CO2 Emissions, Frontiers in Remote
Sensing, 2, 32, https://doi.org/10.3389/frsen.2021.707247, 2021. a, b, c, d, e
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
Battle, M. O., Munger, J. W., Conley, M., Sofen, E., Perry, R., Hart, R., Davis, Z., Scheckman, J., Woogerd, J., Graeter, K., Seekins, S., David, S., and Carpenter, J.: Atmospheric measurements of the terrestrial O2 : CO2 exchange ratio of a midlatitude forest, Atmos. Chem. Phys., 19, 8687–8701, https://doi.org/10.5194/acp-19-8687-2019, 2019. a
Becker, M., Olsen, A., Landschützer, P., Omar, A., Rehder, G., Rödenbeck, C., and Skjelvan, I.: The northern European shelf as an increasing net sink for CO2, Biogeosciences, 18, 1127–1147, https://doi.org/10.5194/bg-18-1127-2021, 2021. a
Bergamaschi, P., Krol, M., Dentener, F., Vermeulen, A., Meinhardt, F., Graul, R., Ramonet, M., Peters, W., and Dlugokencky, E. J.: Inverse modelling of national and European CH4 emissions using the atmospheric zoom model TM5, Atmos. Chem. Phys., 5, 2431–2460, https://doi.org/10.5194/acp-5-2431-2005, 2005. a
Berke, J.: Renewable power generation in Germany led to negative electricity
cost,
https://www.businessinsider.com/renewable-power-germany-negative-electricity-cost-2017-12?international=true&r=US&IR=T (last access: 31 January 2023),
2017. a
Bernhofer, C., Gruenwald, J. T., and ICOS Ecosystem Thematic Centre: Warm winter 2020 ecosystem eddy covariance flux prod- 80
uct from Tharandt, Warm Winter 2020 ecosystem eddy covariance flux product for 73 stations in FLUXNET-Archive format – release 2022-1 (Version 1.0), ICOS [data set],
https://doi.org/10.18160/8FBV-1K18, 2022. a
Boon, A., Broquet, G., Clifford, D. J., Chevallier, F., Butterfield, D. M., Pison, I., Ramonet, M., Paris, J.-D., and Ciais, P.: Analysis of the potential of near-ground measurements of CO2 and CH4 in London, UK, for the monitoring of city-scale emissions using an atmospheric transport model, Atmos. Chem. Phys., 16, 6735–6756, https://doi.org/10.5194/acp-16-6735-2016, 2016. a
Boussetta, S., Balsamo, G., Beljaars, A., Panareda, A. A., Calvet, J. C.,
Jacobs, C., Van Den Hurk, B., Viterbo, P., Lafont, S., Dutra, E., Jarlan, L.,
Balzarolo, M., Papale, D., and Van Der Werf, G.: Natural land carbon dioxide
exchanges in the ECMWF integrated forecasting system: Implementation and
offline validation, J. Geophys. Res.-Atmos., 118,
5923–5946, https://doi.org/10.1002/jgrd.50488, 2013. a
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
Bréon, F. M., Broquet, G., Puygrenier, V., Chevallier, F., Xueref-Remy, I., Ramonet, M., Dieudonné, E., Lopez, M., Schmidt, M., Perrussel, O., and Ciais, P.: An attempt at estimating Paris area CO2 emissions from atmospheric concentration measurements, Atmos. Chem. Phys., 15, 1707–1724, https://doi.org/10.5194/acp-15-1707-2015, 2015. a
Bruemmer, C., Schrader, F., Delorme, J.-P., Lucas-Moffat, A., and ICOS
Ecosystem Thematic Centre: Warm winter 2020 ecosystem eddy covariance flux
product from Gebesee, Warm Winter 2020 ecosystem eddy covariance flux product for 73 stations in FLUXNET-Archive format – release 2022-1 (Version 1.0), ICOS [data set], https://doi.org/10.18160/KVAC-KYEX, 2022. 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
Brut, A., Tallec, T., Ceschia, E., and ICOS Ecosystem Thematic Centre: Warm
winter 2020 ecosystem eddy covariance flux product from Lamasquere, Warm Winter 2020 ecosystem eddy covariance flux product for 73 stations in FLUXNET-Archive format – release 2022-1 (Version 1.0), ICOS [data set],
https://doi.org/10.18160/D86P-B2W5, 2022. a
Buchmann, N., Hörtnagl, L., Merbold, L., Gharun, M., and ICOS Ecosystem
Thematic Centre: Warm winter 2020 ecosystem eddy covariance flux product
from Davos, Warm Winter 2020 ecosystem eddy covariance flux product for 73 stations in FLUXNET-Archive format – release 2022-1 (Version 1.0), ICOS [data set], https://doi.org/10.18160/1JA9-VJEV, 2022. a
Chen, H. W., Zhang, L. N., Zhang, F., Davis, K. J., Lauvaux, T., Pal, S.,
Gaudet, B., and DiGangi, J. P.: Evaluation of Regional CO2 Mole Fractions in
the ECMWF CAMS Real-Time Atmospheric Analysis and NOAA CarbonTracker
Near-Real-Time Reanalysis With Airborne Observations From ACT-America Field
Campaigns, J. Geophys. Res.-Atmos., 124, 8119–8133,
https://doi.org/10.1029/2018JD029992, 2019. a
Chevallier, F., Engelen, R. J., Carouge, C., Conway, T. J., Peylin, P.,
Pickett-Heaps, C., Ramonet, M., Rayner, P. J., and Xueref-Remy, I.:
AIRS-based versus flask-based estimation of carbon surface fluxes, J. Geophys. Res., 114, D20303, https://doi.org/10.1029/2009jd012311, 2009. a, b
Chevallier, F., Remaud, M., O'Dell, C. W., Baker, D., Peylin, P., and Cozic, A.: Objective evaluation of surface- and satellite-driven carbon dioxide atmospheric inversions, Atmos. Chem. Phys., 19, 14233–14251, https://doi.org/10.5194/acp-19-14233-2019, 2019. a
Ciais, P., Wang, Y., Andrew, R., Bréon, F. M., Chevallier, F., Broquet,
G., Nabuurs, G. J., Peters, G., Mcgrath, M., Meng, W., Zheng, B., and Tao,
S.: Biofuel burning and human respiration bias on satellite estimates of
fossil fuel CO2 emissions, Environ. Res. Lett., 15, 074036,
https://doi.org/10.1088/1748-9326/ab7835, 2020. a
Di Giuseppe, F., Rémy, S., Pappenberger, F., and Wetterhall, F.: Using the Fire Weather Index (FWI) to improve the estimation of fire emissions from fire radiative power (FRP) observations, Atmos. Chem. Phys., 18, 5359–5370, https://doi.org/10.5194/acp-18-5359-2018, 2018. a, b
Dou, X., Wang, Y., Ciais, P., Chevallier, F., Davis, S. J., Crippa, M.,
Janssens-Maenhout, G., Guizzardi, D., Solazzo, E., Yan, F., Huo, D., Bo, Z.,
Zhu, B., Cui, D., Ke, P., Sun, T., Wang, H., Zhang, Q., Gentine, P., Deng,
Z., and Liu, Z.: Near-real-time global gridded daily CO2 emissions, The
Innovation, 3, 100182, https://doi.org/10.1016/j.xinn.2021.100182, 2021. a, b, c, d, e, f, g, h
Drought 2018 Team and ICOS Atmosphere Thematic Centre: Drought-2018
atmospheric CO2 Mole Fraction product for 48 stations (96 sample heights),
ICOS [data set], https://doi.org/10.18160/ERE9-9D85, 2020. a, b
Dufrêne, E., Berveiller, D., Delpierre, N., and ICOS Ecosystem Thematic
Centre: Warm winter 2020 ecosystem eddy
covariance flux product from Fontainebleau-Barbeau, Warm winter 2020 ecosystem eddy covariance flux prod- 80
uct from Tharandt, Warm Winter 2020 ecosystem eddy covariance flux product for 73 stations in FLUXNET-Archive format – release 2022-1 (Version 1.0), ICOS [data set], https://doi.org/10.18160/X1J0-H684, 2022. a
ECDC: Data on country response measures to COVID-19, European Centre for
Disease Prevention and Control,
https://www.ecdc.europa.eu/en/publications-data/download-data-response-measures-covid-19 (last access: 31 January 2023),
2021. a
European Environment Agency: Bioenergy production must use resources more
efficiently,
https://www.eea.europa.eu/media/newsreleases/bioenergy-production-must-use-resources (last access: 31 January 2023),
2016. a
Friborg, T., Jensen, R., Jensen, R., and Rasmussen, L.: ETC L2 Fluxnet
(half-hourly), Voulundgaard, 2019-12-31–2021-12-31,
https://hdl.handle.net/11676/lE2EnZqqarSmqny87R8dSNzh (last access: 31 January 2023), 2022. a
Friedlingstein, P., Jones, M. W., O'Sullivan, M., Andrew, R. M., Bakker, D. C. E., Hauck, J., Le Quéré, C., Peters, G. P., Peters, W., Pongratz, J., Sitch, S., Canadell, J. G., Ciais, P., Jackson, R. B., Alin, S. R., Anthoni, P., Bates, N. R., Becker, M., Bellouin, N., Bopp, L., Chau, T. T. T., Chevallier, F., Chini, L. P., Cronin, M., Currie, K. I., Decharme, B., Djeutchouang, L. M., Dou, X., Evans, W., Feely, R. A., Feng, L., Gasser, T., Gilfillan, D., Gkritzalis, T., Grassi, G., Gregor, L., Gruber, N., Gürses, Ö., Harris, I., Houghton, R. A., Hurtt, G. C., Iida, Y., Ilyina, T., Luijkx, I. T., Jain, A., Jones, S. D., Kato, E., Kennedy, D., Klein Goldewijk, K., Knauer, J., Korsbakken, J. I., Körtzinger, A., Landschützer, P., Lauvset, S. K., Lefèvre, N., Lienert, S., Liu, J., Marland, G., McGuire, P. C., Melton, J. R., Munro, D. R., Nabel, J. E. M. S., Nakaoka, S.-I., Niwa, Y., Ono, T., Pierrot, D., Poulter, B., Rehder, G., Resplandy, L., Robertson, E., Rödenbeck, C., Rosan, T. M., Schwinger, J., Schwingshackl, C., Séférian, R., Sutton, A. J., Sweeney, C., Tanhua, T., Tans, P. P., Tian, H., Tilbrook, B., Tubiello, F., van der Werf, G. R., Vuichard, N., Wada, C., Wanninkhof, R., Watson, A. J., Willis, D., Wiltshire, A. J., Yuan, W., Yue, C., Yue, X., Zaehle, S., and Zeng, J.: Global Carbon Budget 2021, Earth Syst. Sci. Data, 14, 1917–2005, https://doi.org/10.5194/essd-14-1917-2022, 2022a. a, b
Friedlingstein, P., O'Sullivan, M., Jones, M. W., Andrew, R. M., Gregor, L., Hauck, J., Le Quéré, C., Luijkx, I. T., Olsen, A., Peters, G. P., Peters, W., Pongratz, J., Schwingshackl, C., Sitch, S., Canadell, J. G., Ciais, P., Jackson, R. B., Alin, S. R., Alkama, R., Arneth, A., Arora, V. K., Bates, N. R., Becker, M., Bellouin, N., Bittig, H. C., Bopp, L., Chevallier, F., Chini, L. P., Cronin, M., Evans, W., Falk, S., Feely, R. A., Gasser, T., Gehlen, M., Gkritzalis, T., Gloege, L., Grassi, G., Gruber, N., Gürses, Ö., Harris, I., Hefner, M., Houghton, R. A., Hurtt, G. C., Iida, Y., Ilyina, T., Jain, A. K., Jersild, A., Kadono, K., Kato, E., Kennedy, D., Klein Goldewijk, K., Knauer, J., Korsbakken, J. I., Landschützer, P., Lefèvre, N., Lindsay, K., Liu, J., Liu, Z., Marland, G., Mayot, N., McGrath, M. J., Metzl, N., Monacci, N. M., Munro, D. R., Nakaoka, S.-I., Niwa, Y., O'Brien, K., Ono, T., Palmer, P. I., Pan, N., Pierrot, D., Pocock, K., Poulter, B., Resplandy, L., Robertson, E., Rödenbeck, C., Rodriguez, C., Rosan, T. M., Schwinger, J., Séférian, R., Shutler, J. D., Skjelvan, I., Steinhoff, T., Sun, Q., Sutton, A. J., Sweeney, C., Takao, S., Tanhua, T., Tans, P. P., Tian, X., Tian, H., Tilbrook, B., Tsujino, H., Tubiello, F., van der Werf, G. R., Walker, A. P., Wanninkhof, R., Whitehead, C., Willstrand Wranne, A., Wright, R., Yuan, W., Yue, C., Yue, X., Zaehle, S., Zeng, J., and Zheng, B.: Global Carbon Budget 2022, Earth Syst. Sci. Data, 14, 4811–4900, https://doi.org/10.5194/essd-14-4811-2022, 2022b. a, b, c, d
Friedrich, R. and Reis, S. (Eds.):
Emissions of Air Pollutants, in: Emissions of Air Pollutants, Springer Berlin Heidelberg, https://doi.org/10.1007/978-3-662-07015-4, 2004. a, b
Geels, C., Gloor, M., Ciais, P., Bousquet, P., Peylin, P., Vermeulen, A. T., Dargaville, R., Aalto, T., Brandt, J., Christensen, J. H., Frohn, L. M., Haszpra, L., Karstens, U., Rödenbeck, C., Ramonet, M., Carboni, G., and Santaguida, R.: Comparing atmospheric transport models for future regional inversions over Europe – Part 1: mapping the atmospheric CO2 signals, Atmos. Chem. Phys., 7, 3461–3479, https://doi.org/10.5194/acp-7-3461-2007, 2007. a
Gerbig, C., Lin, J. C., Wofsy, S. C., Daube, B. C., Andrews, A. E., Stephens,
B. B., Bakwin, P. S., and Granier, C.: Toward constraining regional-scale
fluxes of CO2 with atmospheric observations over a continent: 1. Observed
spatial variability from airborne platforms, J. Geophys. Res.-Atmos., 108, 4756, https://doi.org/10.1029/2002jd003018, 2003. a
Guevara, M., Jorba, O., Tena, C., Denier van der Gon, H., Kuenen, J., Elguindi, N., Darras, S., Granier, C., and Pérez García-Pando, C.: Copernicus Atmosphere Monitoring Service TEMPOral profiles (CAMS-TEMPO): global and European emission temporal profile maps for atmospheric chemistry modelling, Earth Syst. Sci. Data, 13, 367–404, https://doi.org/10.5194/essd-13-367-2021, 2021. a, b, c, d, e
Guevara, M., Petetin, H., Jorba, O., Denier van der Gon, H., Kuenen, J., Super, I., Jalkanen, J.-P., Majamäki, E., Johansson, L., Peuch, V.-H., and Pérez García-Pando, C.: European primary emissions of criteria pollutants and greenhouse gases in 2020 modulated by the COVID-19 pandemic disruptions, Earth Syst. Sci. Data, 14, 2521–2552, https://doi.org/10.5194/essd-14-2521-2022, 2022. a, b
Guo, M., Li, J., Xu, J., Wang, X., He, H., and Wu, L.: CO2 emissions from the
2010 Russian wildfires using GOSAT data, Environ. Pollut., 226,
60–68, https://doi.org/10.1016/j.envpol.2017.04.014, 2017. a
Haynes, K. D., Baker, I. T., Denning, A. S., Wolf, S., Wohlfahrt, G., Kiely,
G., Minaya, R. C., and Haynes, J. M.: Representing Grasslands Using Dynamic
Prognostic Phenology Based on Biological Growth Stages: Part 2. Carbon
Cycling, J. Adv. Model. Earth Sy., 11, 4440–4465,
https://doi.org/10.1029/2018MS001541, 2019. a, b, c
Heinesch, B., De Ligne, A., Manise, T., Longdoz, B., and ICOS Ecosystem
Thematic Centre: Warm winter 2020 ecosystem eddy covariance flux product
from Lonzee, Warm Winter 2020 ecosystem eddy covariance flux product for 73 stations in FLUXNET-Archive format – release 2022-1 (Version 1.0), ICOS [data set], https://doi.org/10.18160/46P3-WT1D, 2022. a
Heliasz, M., Holst, J., and ICOS Ecosystem Thematic Centre: Warm winter 2020
ecosystem eddy covariance flux product from Hyltemossa, Warm Winter 2020 ecosystem eddy covariance flux product for 73 stations in FLUXNET-Archive format – release 2022-1 (Version 1.0), ICOS [data set],
https://doi.org/10.18160/HQJA-PCXX, 2022. 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
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, b
Hoag, K. J.: Triple oxygen isotope composition of tropospheric carbon dioxide
as a tracer of terrestrial gross carbon fluxes, Geophys. Res.
Lett., 32, L02802, https://doi.org/10.1029/2004GL021011, 2005. a
Hussy, C., Klaasen, E., Koornneef, J., and Wigand, F.: International
Comparison of Fossil Power Efficiency and CO2 Intensity-UPDATE 2014, Tech.
rep., http://www.ecofys.com (last access: 6 January 2022), 2014. a
ICOS Research Infrastructure: ICOS Near Real-Time (Level 1) Atmospheric Greenhouse Gas Mole Fractions of CO2, CO and CH4, growing time series starting from latest Level 2 release (Version 1.0), ICOS ERIC, https://doi.org/10.18160/ATM_NRT_CO2_CH4, 2018. a
Intergovernmental Panel on Climate Change: Sixth Assessment Report,
https://www.ipcc.ch/report/ar6/wg1/ (last access: 31 January 2023),
2021. a
Ishidoya, S., Murayama, S., Kondo, H., Saigusa, N., Kishimoto-Mo, A. W., and
Yamamoto, S.: Observation of O2:CO2 exchange ratio for net turbulent fluxes
and its application to forest carbon cycles, Ecol. Res., 30,
225–234, https://doi.org/10.1007/s11284-014-1241-3, 2015. a
Jacobson, A. R., Schuldt, K. N., Miller, J. B., Tans, P., Arlyn Andrews,
Mund, J., Aalto, T., Abshire, J. B., Aikin, K., Aoki, S., Apadula, F., Baier,
B., Bakwin, P., Bartyzel, J., Bentz, G., Bergamaschi, P., Beyersdorf, A.,
Biermann, T., Biraud, S. C., Bowling, D., Brailsford, G., Van Den Bulk, P.,
Chen, G., Huilin Chen, Lukasz Chmura, Clark, S., Coletta, J. D., Colomb,
A., Commane, R., Conil, S., Cox, A., Cristofanelli, P., Cuevas, E., Curcoll,
R., Daube, B., Davis, K., Delmotte, M., DiGangi, J. P., Van Dinther, D.,
Dlugokencky, E., Elkins, J. W., Emmenegger, L., Fischer, M. L., Forster, G.,
Frumau, A., Galkowski, M., Gatti, L. V., Francois Gheusi, Gloor, E.,
Gomez-Trueba, V., Goto, D., Griffis, T., Hammer, S., Hanson, C., Haszpra, L.,
Hatakka, J., Heliasz, M., Hensen, A., Hermanssen, O., Hintsa, E., Holst, J.,
Jaffe, D., Joubert, W., Karion, A., Kawa, S. R., Kazan, V., Keeling, R.,
Keronen, P., Kolari, P., Kominkova, K., Kort, E., Krummel, P., Kubistin, D.,
Labuschagne, C., Langenfelds, R., Laurent, O., Laurila, T., Lauvaux, T., Law,
B., Lee, J., Lehner, I., Leuenberger, M., Levin, I., Levula, J., Lin, J.,
Lindauer, M., Loh, Z., Lopez, M., Machida, T., Mammarella, I., Manca, G.,
Manning, A., Manning, A., Marek, M. V., Martin, M. Y., Matsueda, H.,
De Mazière, M., McKain, K., Meijer, H., Meinhardt, F., Merchant, L.,
N. Mihalopoulos, Miles, N., Miller, C. E., Mitchell, L., Mölder, M.,
Montzka, S., Moore, F., Morgan, E., Josep-Anton Morgui, Morimoto, S.,
Müller-Williams, J., Munger, B., Myhre, C. L., Jaroslaw Necki,
Newman, S., Nichol, S., Niwa, Y., O'Doherty, S., Paplawsky, B., Peischl, J.,
Peltola, O., Piacentino, S., Pichon, J. M., Piper, S., Plass-Duelmer, C.,
Plass-Duelmer, C., Ramonet, M., Ramos, R., Reyes-Sanchez, E., Richardson, S.,
Riris, H., Rivas, P. P., Ryerson, T., Saito, K., Sargent, M., Di Sarra,
A. G., Sawa, Y., Say, D., Scheeren, B., Schmidt, M., Schumacher, M., Sha,
M. K., Shepson, P., Shook, M., Sloop, C. D., Smith, P., Steinbacher, M.,
Stephens, B., Sweeney, C., Thoning, K., Torn, M., Tørseth, K., Trisolino,
P., Turnbull, J., Vermeulen, A., Viner, B., Vitkova, G., Walker, S.,
De Wekker, S., Wofsy, S., Worthy, D., Dickon Young, and Miroslaw Zimnoch:
CarbonTracker Near-Real Time, CT-NRT.v2022-1, NOAA Earth System Research Laboratory, Global Monitoring Division, https://doi.org/10.25925/V0VA-CY20,
2022. a
Janssens, I., De Meulder, T., Roland, M., Segers, J., and ICOS Ecosystem
Thematic Centre: Warm winter 2020 ecosystem eddy covariance flux product
from Brasschaat, Warm Winter 2020 ecosystem eddy covariance flux product for 73 stations in FLUXNET-Archive format – release 2022-1 (Version 1.0), ICOS [data set], https://doi.org/10.18160/YVBQ-K6WF, 2022. a
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
Janssens-Maenhout, G., Pinty, B., Dowell, M., Zunker, H., Andersson, E.,
Balsamo, G., Bézy, J. L., Brunhes, T., Bösch, H., Bojkov, B.,
Brunner, D., Buchwitz, M., Crisp, D., Ciais, P., Counet, P., Dee, D., Denier
van der Gon, H., Dolman, H., Drinkwater, M. R., Dubovik, O., Engelen, R.,
Fehr, T., Fernandez, V., Heimann, M., Holmlund, K., Houweling, S., Husband,
R., Juvyns, O., Kentarchos, A., Landgraf, J., Lang, R., Löscher, A.,
Marshall, J., Meijer, Y., Nakajima, M., Palmer, P. I., Peylin, P., Rayner,
P., Scholze, M., Sierk, B., Tamminen, J., and Veefkind, P.: Toward an
operational anthropogenic CO2 emissions monitoring and verification support
capacity, B. Am. Meteorol. Soc., 101,
E1439–E1451, https://doi.org/10.1175/BAMS-D-19-0017.1, 2021. a
Jones, L. A., Kimball, J. S., Reichle, R. H., Madani, N., Glassy, J.,
Ardizzone, J. V., Colliander, A., Cleverly, J., Desai, A. R., Eamus, D.,
Euskirchen, E. S., Hutley, L., Macfarlane, C., and Scott, R. L.: The SMAP
Level 4 Carbon Product for Monitoring Ecosystem Land-Atmosphere CO2
Exchange, IEEE T. Geosci. Remote, 55,
6517–6532, https://doi.org/10.1109/TGRS.2017.2729343, 2017. a
Jones, M. W., Andrew, R. M., Peters, G. P., Janssens-Maenhout, G., De-Gol,
A. J., Ciais, P., Patra, P. K., Chevallier, F., and Le Quéré, C.:
Gridded fossil CO2 emissions and related O2 combustion consistent with
national inventories 1959–2018, Sci. Data, 8, 1–23,
https://doi.org/10.1038/s41597-020-00779-6, 2021. a, b, c, d
Jung, M., Schwalm, C., Migliavacca, M., Walther, S., Camps-Valls, G., Koirala, S., Anthoni, P., Besnard, S., Bodesheim, P., Carvalhais, N., Chevallier, F., Gans, F., Goll, D. S., Haverd, V., Köhler, P., Ichii, K., Jain, A. K., Liu, J., Lombardozzi, D., Nabel, J. E. M. S., Nelson, J. A., O'Sullivan, M., Pallandt, M., Papale, D., Peters, W., Pongratz, J., Rödenbeck, C., Sitch, S., Tramontana, G., Walker, A., Weber, U., and Reichstein, M.: Scaling carbon fluxes from eddy covariance sites to globe: synthesis and evaluation of the FLUXCOM approach, Biogeosciences, 17, 1343–1365, https://doi.org/10.5194/bg-17-1343-2020, 2020. a, b, c, d
Konovalov, I. B., Berezin, E. V., Ciais, P., Broquet, G., Zhuravlev, R. V., and Janssens-Maenhout, G.: Estimation of fossil-fuel CO2 emissions using satellite measurements of “proxy” species, Atmos. Chem. Phys., 16, 13509–13540, https://doi.org/10.5194/acp-16-13509-2016, 2016. a
Kooijmans, L. M. J., Cho, A., Ma, J., Kaushik, A., Haynes, K. D., Baker, I., Luijkx, I. T., Groenink, M., Peters, W., Miller, J. B., Berry, J. A., Ogée, J., Meredith, L. K., Sun, W., Kohonen, K.-M., Vesala, T., Mammarella, I., Chen, H., Spielmann, F. M., Wohlfahrt, G., Berkelhammer, M., Whelan, M. E., Maseyk, K., Seibt, U., Commane, R., Wehr, R., and Krol, M.: Evaluation of carbonyl sulfide biosphere exchange in the Simple Biosphere Model (SiB4), Biogeosciences, 18, 6547–6565, https://doi.org/10.5194/bg-18-6547-2021, 2021. a
Koren, G., Schneider, L., Velde, I. R., Schaik, E., Gromov, S. S., Adnew,
G. A., Mrozek Martino, D. J., Hofmann, M. E. G., Liang, M., Mahata, S.,
Bergamaschi, P., Laan‐Luijkx, I. T., Krol, M. C., Röckmann, T., and
Peters, W.: Global 3‐D Simulations of the Triple Oxygen Isotope Signature
Δ 17O in Atmospheric CO2, J. Geophys. Res.-Atmos., 124, 8808–8836, https://doi.org/10.1029/2019JD030387, 2019. a
Krol, M., Houweling, S., Bregman, B., van den Broek, M., Segers, A., van Velthoven, P., Peters, W., Dentener, F., and Bergamaschi, P.: The two-way nested global chemistry-transport zoom model TM5: algorithm and applications, Atmos. Chem. Phys., 5, 417–432, https://doi.org/10.5194/acp-5-417-2005, 2005. a, b
Krol, M., Peters, W., Hooghiemstra, P., George, M., Clerbaux, C., Hurtmans, D., McInerney, D., Sedano, F., Bergamaschi, P., El Hajj, M., Kaiser, J. W., Fisher, D., Yershov, V., and Muller, J.-P.: How much CO was emitted by the 2010 fires around Moscow?, Atmos. Chem. Phys., 13, 4737–4747, https://doi.org/10.5194/acp-13-4737-2013, 2013. a
Kuenen, J., Dellaert, S., Visschedijk, A., Jalkanen, J.-P., Super, I., and Denier van der Gon, H.: CAMS-REG-v4: a state-of-the-art high-resolution European emission inventory for air quality modelling, Earth Syst. Sci. Data, 14, 491–515, https://doi.org/10.5194/essd-14-491-2022, 2022. a, b, c, d, e, f, g, h, i, j, k, l, m
Laskar, A. H., Mahata, S., and Liang, M.-C.: Identification of Anthropogenic
CO2 Using Triple Oxygen and Clumped Isotopes, Environ. Sci.
Technol., 50, 11806–11814, https://doi.org/10.1021/acs.est.6b02989, 2016. a
Le Quéré, C., Jackson, R. B., Jones, M. W., Smith, A. J.,
Abernethy, S., Andrew, R. M., De-Gol, A. J., Willis, D. R., Shan, Y.,
Canadell, J. G., Friedlingstein, P., Creutzig, F., and Peters, G. P.:
Temporary reduction in daily global CO2 emissions during the COVID-19 forced
confinement, Nat. Clim. Change, 10, 647–653,
https://doi.org/10.1038/s41558-020-0797-x, 2020. a, b, c, d, e, f, g
Levin, I., Hammer, S., Eichelmann, E., and Vogel, F. R.: Verification of
greenhouse gas emission reductions: The prospect of atmospheric monitoring in
polluted areas, Philos. T. Roy. Soc. A, 369, 1906–1924,
https://doi.org/10.1098/rsta.2010.0249, 2011. 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
Lin, J. C., Gerbig, C., Wofsy, S. C., Andrews, A. E., Daube, B. C., Davis,
K. J., and Grainger, C. A.: A near-field tool for simulating the upstream
influence of atmospheric observations: The Stochastic Time-Inverted
Lagrangian Transport (STILT) model, J. Geophys. Res.-Atmos., 108, 4493, https://doi.org/10.1029/2002jd003161, 2003. a
Liu, Z., Ciais, P., Deng, Z., Lei, R., Davis, S. J., Feng, S., Zheng, B., Cui,
D., Dou, X., Zhu, B., Guo, R., Ke, P., Sun, T., Lu, C., He, P., Wang, Y.,
Yue, X., Wang, Y., Lei, Y., Zhou, H., Cai, Z., Wu, Y., Guo, R., Han, T., Xue,
J., Boucher, O., Boucher, E., Chevallier, F., Tanaka, K., Wei, Y., Zhong, H.,
Kang, C., Zhang, N., Chen, B., Xi, F., Liu, M., Bréon, F. M., Lu, Y.,
Zhang, Q., Guan, D., Gong, P., Kammen, D. M., He, K., and Schellnhuber,
H. J.: Near-real-time monitoring of global CO2 emissions reveals the effects
of the COVID-19 pandemic, Nat. Commun., 11, 5172,
https://doi.org/10.1038/s41467-020-18922-7, 2020. a, b, c, d, e, f, g, h, i
Lokupitiya, E., Denning, S., Paustian, K., Baker, I., Schaefer, K., Verma, S., Meyers, T., Bernacchi, C. J., Suyker, A., and Fischer, M.: Corrigendum to “Incorporation of crop phenology in Simple Biosphere Model (SiBcrop) to improve land-atmosphere carbon exchanges from croplands” published in Biogeosciences, 6, 969–986, 2009, Biogeosciences, 6, 1103–1103, https://doi.org/10.5194/bg-6-1103-2009, 2009. a
Loustau, D., Chipeaux, C., and ICOS Ecosystem Thematic Centre: Warm winter
2020 ecosystem eddy covariance flux product from Bilos, Warm Winter 2020 ecosystem eddy covariance flux product for 73 stations in FLUXNET-Archive format – release 2022-1 (Version 1.0), ICOS [data set],
https://doi.org/10.18160/MSRT-T1YA, 2022. 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, GB2005, 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
Mammarella, I., Vesala, T., Kolari, P., and ICOS Ecosystem Thematic Centre:
Warm winter 2020 ecosystem eddy covariance flux product from
Hyytiälä, Warm Winter 2020 ecosystem eddy covariance flux product for 73 stations in FLUXNET-Archive format – release 2022-1 (Version 1.0), ICOS [data set], https://doi.org/10.18160/XTBV-XCJV, 2022. a
Manning, A. J., O'Doherty, S., Jones, A. R., Simmonds, P. G., and Derwent,
R. G.: Estimating UK methane and nitrous oxide emissions from 1990 to 2007
using an inversion modeling approach, J. Geophys. Res., 116,
D02305, https://doi.org/10.1029/2010JD014763, 2011. a
Miller, J. B., Lehman, S. J., Verhulst, K. R., Miller, C. E., Duren, R. M.,
Yadav, V., Newman, S., and Sloop, C. D.: Large and seasonally varying
biospheric CO2 fluxes in the Los Angeles megacity revealed by atmospheric
radiocarbon, P. Natl. Acad. Sci. USA, 117, 26681–26687, https://doi.org/10.1073/pnas.2005253117,
2020. a
Mölder, M., Lankreijer, H., Lagergren, F., Holst, J., and ICOS Ecosystem
Thematic Centre: Warm winter 2020 ecosystem eddy covariance flux product
from Norunda, Warm Winter 2020 ecosystem eddy covariance flux product for 73 stations in FLUXNET-Archive format – release 2022-1 (Version 1.0), ICOS [data set], https://doi.org/10.18160/87R1-0HRM, 2022. a
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
Mues, A., Kuenen, J., Hendriks, C., Manders, A., Segers, A., Scholz, Y., Hueglin, C., Builtjes, P., and Schaap, M.: Sensitivity of air pollution simulations with LOTOS-EUROS to the temporal distribution of anthropogenic emissions, Atmos. Chem. Phys., 14, 939–955, https://doi.org/10.5194/acp-14-939-2014, 2014. a, b, c, d, e
Nalini, K., Lauvaux, T., Abdallah, C., Lian, J., Ciais, P., Utard, H., Laurent,
O., and Ramonet, M.: High-Resolution Lagrangian Inverse Modeling of CO2
Emissions Over the Paris Region During the First 2020 Lockdown Period,
J. Geophys. Res.-Atmos., 127, e2021JD036032,
https://doi.org/10.1029/2021JD036032, 2022. a
Nassar, R., Napier-Linton, L., Gurney, K. R., Andres, R. J., Oda, T., Vogel,
F. R., and Deng, F.: Improving the temporal and spatial distribution of CO2
emissions from global fossil fuel emission data sets, J. Geophys.
Res.-Atmos., 118, 917–933, https://doi.org/10.1029/2012JD018196, 2013. a
Nicolini, G., Antoniella, G., Carotenuto, F., Christen, A., Ciais, P.,
Feigenwinter, C., Gioli, B., Stagakis, S., Velasco, E., Vogt, R., Ward,
H. C., Barlow, J., Chrysoulakis, N., Duce, P., Graus, M., Helfter, C.,
Heusinkveld, B., Järvi, L., Karl, T., Marras, S., Masson, V., Matthews,
B., Meier, F., Nemitz, E., Sabbatini, S., Scherer, D., Schume, H., Sirca, C.,
Steeneveld, G.-J., Vagnoli, C., Wang, Y., Zaldei, A., Zheng, B., and Papale,
D.: Direct observations of CO2 emission reductions due to COVID-19 lockdown
across European urban districts, Sci. Total Environ., 830,
154662, https://doi.org/10.1016/j.scitotenv.2022.154662, 2022. a
Peichl, M., Ottosson Lofvenius, M., Nilsson, M. B., Marklund, P., and ICOS
Ecosystem Thematic Centre: Warm winter 2020 ecosystem eddy covariance flux
product from Svartberget, Warm Winter 2020 ecosystem eddy covariance flux product for 73 stations in FLUXNET-Archive format – release 2022-1 (Version 1.0), ICOS [data set], https://doi.org/10.18160/XWNX-9FWC, 2022. a
Peters, W., Jacobson, A. R., Sweeney, C., Andrews, A. E., Conway, T. J.,
Masarie, K. A., Miller, J. B., Bruhwiler, L. M., Pétron, G., Hirsch,
A. I., Worthy, D. E., Van Der Werf, G. R., Randerson, J. T., Wennberg, P. O.,
Krol, M. C., and Tans, P. P.: An atmospheric perspective on North American
carbon dioxide exchange: CarbonTracker, P. Natl. Acad. Sci. USA, 104, 18925–18930,
https://doi.org/10.1073/pnas.0708986104, 2007. a
Peters, W., Bastos, A., Ciais, P., and Vermeulen, A.: A historical, geographical and ecological perspective on the 2018 European summer drought, Philos. T. Roy. Soc. B, 375, 20190505, https://doi.org/10.1098/rstb.2019.0505,
2020. a
Piao, S., Wang, X., Wang, K., Li, X., Bastos, A., Canadell, J. G., Ciais, P.,
Friedlingstein, P., and Sitch, S.: Interannual variation of terrestrial
carbon cycle: Issues and perspectives, Global Change Biol., 26, 300–318,
https://doi.org/10.1111/gcb.14884, 2020. a
Pickers, P. A., Manning, A. C., Quéré, C. L., Forster, G. L.,
Luijkx, I. T., Gerbig, C., Fleming, L. S., and Sturges, W. T.: Novel
quantification of regional fossil fuel CO2 reductions during COVID-19
lockdowns using atmospheric oxygen measurements, Sci. Adv., 8, 9250,
https://doi.org/10.1126/SCIADV.ABL9250, 2022. a
Pinty, B., Janssens-Maenhout, G., and Dowell, M.: An Operational Anthropogenic CO2 Emissions Monitoring & Verification Support Capacity, report, European Commission Joint Research Centre, 2018, 3–4,
https://doi.org/10.2760/08644, 2017. a
Ramonet, M., Ciais, P., Apadula, F., Bartyzel, J., Bastos, A., Bergamaschi, P.,
Blanc, P. E., Brunner, D., Caracciolo Di Torchiarolo, L., Calzolari, F.,
Chen, H., Chmura, L., Colomb, A., Conil, S., Cristofanelli, P., Cuevas, E.,
Curcoll, R., Delmotte, M., Di Sarra, A., Emmenegger, L., Forster, G., Frumau,
A., Gerbig, C., Gheusi, F., Hammer, S., Haszpra, L., Hatakka, J., Hazan, L.,
Heliasz, M., Henne, S., Hensen, A., Hermansen, O., Keronen, P., Kivi, R.,
Komínková, K., Kubistin, D., Laurent, O., Laurila, T., Lavric,
J. V., Lehner, I., Lehtinen, K. E., Leskinen, A., Leuenberger, M., Levin, I.,
Lindauer, M., Lopez, M., Myhre, C. L., Mammarella, I., Manca, G., Manning,
A., Marek, M. V., Marklund, P., Martin, D., Meinhardt, F., Mihalopoulos, N.,
Mölder, M., Morgui, J. A., Necki, J., O'Doherty, S., O'Dowd, C.,
Ottosson, M., Philippon, C., Piacentino, S., Pichon, J. M., Plass-Duelmer,
C., Resovsky, A., Rivier, L., Rodó, X., Sha, M. K., Scheeren, H. A.,
Sferlazzo, D., Spain, T. G., Stanley, K. M., Steinbacher, M., Trisolino, P.,
Vermeulen, A., Vítková, G., Weyrauch, D., Xueref-Remy, I., Yala,
K., and Yver Kwok, C.: The fingerprint of the summer 2018 drought in Europe
on ground-based atmospheric CO2 measurements: Atmospheric CO2 anomaly,
Philos. T. Roy. Soc. B, 375, 20190513,
https://doi.org/10.1098/rstb.2019.0513, 2020. a, b
Rebmann, C., Dienstbach, L., Gimper, S., and ICOS Ecosystem Thematic Centre:
Warm winter 2020 ecosystem eddy covariance flux product from Hohes Holz, Warm Winter 2020 ecosystem eddy covariance flux product for 73 stations in FLUXNET-Archive format – release 2022-1 (Version 1.0), ICOS [data set],
https://doi.org/10.18160/RRBD-7EME, 2022. a
Reuter, M., Buchwitz, M., Schneising, O., Krautwurst, S., O'Dell, C. W., Richter, A., Bovensmann, H., and Burrows, J. P.: Towards monitoring localized CO2 emissions from space: co-located regional CO2 and NO2 enhancements observed by the OCO-2 and S5P satellites, Atmos. Chem. Phys., 19, 9371–9383, https://doi.org/10.5194/acp-19-9371-2019, 2019. a
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, b, c
Rödenbeck, C., Zaehle, S., Keeling, R., and Heimann, M.: How does the terrestrial carbon exchange respond to inter-annual climatic variations? A quantification based on atmospheric CO2 data, Biogeosciences, 15, 2481–2498, https://doi.org/10.5194/bg-15-2481-2018, 2018. a
Rödenbeck, C., Zaehle, S., Keeling, R., and Heimann, M.: The European
carbon cycle response to heat and drought as seen from atmospheric CO2 data
for 1999–2018: Carbon cycle response in summer, Philos. T. Roy. Soc. B, 375, 20190506,
https://doi.org/10.1098/rstb.2019.0506, 2020. a
Schmidt, M., Graf, A., Dolfus, D., and ICOS Ecosystem Thematic Centre: Warm
winter 2020 ecosystem eddy covariance flux product from Selhausen Juelich, Warm Winter 2020 ecosystem eddy covariance flux product for 73 stations in FLUXNET-Archive format – release 2022-1 (Version 1.0), ICOS [data set],
https://doi.org/10.18160/BS3C-CVQ0, 2022. a
Shvidenko, A. Z., Shchepashchenko, D. G., Vaganov, E. A., Sukhinin, A. I.,
Maksyutov, S. S., McCallum, I., and Lakyda, I. P.: Impact of wildfire in Russia between 1998–2010 on ecosystems and the global carbon budget, Doklady Earth Sciences, 441, 1678–1682,
https://doi.org/10.1134/S1028334X11120075, 2011. a
Smith, N. E., Kooijmans, L. M., Koren, G., Van Schaik, E., Van Der Woude,
A. M., Wanders, N., Ramonet, M., Xueref-Remy, I., Siebicke, L., Manca, G.,
Brümmer, C., Baker, I. T., Haynes, K. D., Luijkx, I. T., and Peters,
W.: Spring enhancement and summer reduction in carbon uptake during the 2018
drought in northwestern Europe: Carbon uptake during 2018 Eur. drought,
Philos. T. Roy. Soc. B, 375, 20190509,
https://doi.org/10.1098/rstb.2019.0509, 2020. a, b, c, d, e, f, g, h, i, j, k, l
Steeneveld, G.-J., van der Horst, S., and Heusinkveld, B.: Observing the surface radiation and energy balance, carbon dioxide and methane fluxes over the city centre of Amsterdam, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1547, https://doi.org/10.5194/egusphere-egu2020-1547, 2020. a, b, c
Steur, P. M., Scheeren, H. A., Nelson, D. D., McManus, J. B., and Meijer, H. A. J.: Simultaneous measurement of δ13C, δ18O and δ17O of atmospheric CO2 – performance assessment of a dual-laser absorption spectrometer, Atmos. Meas. Tech., 14, 4279–4304, https://doi.org/10.5194/amt-14-4279-2021, 2021. 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, 2020a. a, b, c, d
Super, I., Denier van der Gon, H. A. C., van der Molen, M. K., Dellaert, S. N. C., and Peters, W.: Optimizing a dynamic fossil fuel CO2 emission model with CTDAS (CarbonTracker Data Assimilation Shell, v1.0) for an urban area using atmospheric observations of CO2, CO, NOx, and SO2, Geosci. Model Dev., 13, 2695–2721, https://doi.org/10.5194/gmd-13-2695-2020, 2020b. a, b, c, d, e, f
Takahashi, T., Sutherland, S. C., Wanninkhof, R., Sweeney, C., Feely, R. A., Chipman, D. W., Hales, B., Friederich, G., Chavez, F., Sabine, C., Watson, A., Bakker, D. C. E., Schuster, U., Metzl, N., Yoshikawa-Inoue, H., Ishii, M., Midorikawa, T., Nojiri, Y., Körtzinger, A., Steinhoff, T., Hoppema, M., Olafsson, J., Arnarson, T. S., Tilbrook, B., Johannessen, T., Olsen, A., Bellerby, R., Wong, C. S., Delille, B., Bates, N. R., and de Baar, H. J. W.: Climatological mean and decadal change in surface ocean pCO2, and net sea-air CO2 flux over the global oceans, Deep-Sea Res. Pt. II, 56, 554–577, 2009. a
Thompson, R. L., Groot Zwaaftink, C. D., Brunner, D., Tsuruta, A., Aalto, T.,
Raivonen, M., Crippa, M., Solazzo, E., Guizzardi, D., Regnier, P., and
Maisonnier, M.: Effects of extreme meteorological conditions in 2018 on
European methane emissions estimated using atmospheric inversions,
Philos. T. Roy. Soc. A, 380, 20200443, https://doi.org/10.1098/rsta.2020.0443, 2022. a, b
Turner, A. J., Kim, J., Fitzmaurice, H., Newman, C., Worthington, K., Chan, K.,
Wooldridge, P. J., Köehler, P., Frankenberg, C., and Cohen, R. C.:
Observed Impacts of COVID-19 on Urban CO2 Emissions, Geophys. Res.
Lett., 47, e2020GL090037, https://doi.org/10.1029/2020GL090037, 2020. a
United Nations economic comission for Europe: Guidelines for Reporting
Emissions and Projections Data under the Convention on Long-range
Transboundary Air Pollution. Economic and Social Council. Economic Commission
for Europe. 2014, ECE/EB.AIR/125, Tech. rep.,
http://www.unece.org (last access: 26 April 2022), 2014. a
Van der Laan, S., Karstens, U., Neubert, R. E., Van Der Laan-Luijkx, I. T., and
Meijer, H. A.: Observation-based estimates of fossil fuel-derived CO2
emissions in the Netherlands using Δ14C, CO and 222Radon, Tellus B, 62, 389–402,
https://doi.org/10.1111/j.1600-0889.2010.00493.x, 2010. a
van der Laan-Luijkx, I. T., van der Velde, I. R., van der Veen, E., Tsuruta, A., Stanislawska, K., Babenhauserheide, A., Zhang, H. F., Liu, Y., He, W., Chen, H., Masarie, K. A., Krol, M. C., and Peters, W.: The CarbonTracker Data Assimilation Shell (CTDAS) v1.0: implementation and global carbon balance 2001–2015, Geosci. Model Dev., 10, 2785–2800, https://doi.org/10.5194/gmd-10-2785-2017, 2017. a, b, c
van der Woude, A.: Near real time fluxes, ICOS [data set], https://doi.org/10.18160/20Z1-AYJ2, 2022a. a, b, c
Van Der Woude, A.: CTE-HR (1.0), Zenodo [code], https://doi.org/10.5281/zenodo.6477331, 2022b. a
Vincke, C., Heinesch, B., Longdoz, B., and ICOS Ecosystem Thematic Centre:
Warm winter 2020 ecosystem eddy covariance flux product from Vielsalm, Warm Winter 2020 ecosystem eddy covariance flux product for 73 stations in FLUXNET-Archive format – release 2022-1 (Version 1.0), ICOS [data set],
https://doi.org/10.18160/DF9X-QMRK, 2022. 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
Wanninkhof, R.: Relationship between wind speed and gas exchange over the
ocean, J. Geophys. Res., 97, 7373–7382,
https://doi.org/10.1029/92JC00188, 1992. a, b, c, d
Watter, H.: Regenerative Energiesysteme, Springer Fachmedien Wiesbaden,
https://doi.org/10.1007/978-3-658-09638-0, 2015. a
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.
To monitor the progress towards the CO2 emission goals set out in the Paris Agreement, the...
Altmetrics
Final-revised paper
Preprint