Articles | Volume 19, issue 7
https://doi.org/10.5194/bg-19-2059-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-19-2059-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Sensitivity of biomass burning emissions estimates to land surface information
Earth System Division, National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Japan
Tomohiro Shiraishi
Earth System Division, National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Japan
Ryuichi Hirata
Earth System Division, National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Japan
Yosuke Niwa
Earth System Division, National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Japan
Kazuyuki Saito
Atmosphere and Ocean Department, Japan Meteorological Agency, 1-3-4 Ote-machi, Chiyoda-ku, Tokyo, Japan
Martin Steinbacher
Swiss Federal Laboratories for Materials Science and Technology, Ueberlandstrasse 129, 8600 Dübendorf, Switzerland
Doug Worthy
Climate Research Division, Environment and Climate Change Canada, 4905 Dufferin Street, Toronto, Ontario, Canada
Tsuneo Matsunaga
Earth System Division, National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Japan
Related authors
Tatsuya Miyauchi, Makoto Saito, Hibiki M. Noda, Akihiko Ito, Tomomichi Kato, and Tsuneo Matsunaga
Geosci. Model Dev., 18, 2329–2347, https://doi.org/10.5194/gmd-18-2329-2025, https://doi.org/10.5194/gmd-18-2329-2025, 2025
Short summary
Short summary
Solar-induced chlorophyll fluorescence (SIF) is an effective indicator for monitoring photosynthetic activity. This paper introduces VISIT-SIF, a biogeochemical model developed based on the Vegetation Integrative Simulator for Trace gases (VISIT) to represent satellite-observed SIF. Our simulations reproduced the global distribution and seasonal variations in observed SIF. VISIT-SIF helps to improve photosynthetic processes through a combination of biogeochemical modeling and observed SIF.
Hirofumi Ohyama, Matthias M. Frey, Isamu Morino, Kei Shiomi, Masahide Nishihashi, Tatsuya Miyauchi, Hiroko Yamada, Makoto Saito, Masanobu Wakasa, Thomas Blumenstock, and Frank Hase
Atmos. Chem. Phys., 23, 15097–15119, https://doi.org/10.5194/acp-23-15097-2023, https://doi.org/10.5194/acp-23-15097-2023, 2023
Short summary
Short summary
We conducted a field campaign for CO2 column measurements in the Tokyo metropolitan area with three ground-based Fourier transform spectrometers. The model simulations using prior CO2 fluxes were generally in good agreement with the observations. We developed an urban-scale inversion system in which spatially resolved CO2 fluxes and a scaling factor of large point source emissions were estimated. The posterior total CO2 emissions agreed with emission inventories within the posterior uncertainty.
Shamil Maksyutov, Tomohiro Oda, Makoto Saito, Rajesh Janardanan, Dmitry Belikov, Johannes W. Kaiser, Ruslan Zhuravlev, Alexander Ganshin, Vinu K. Valsala, Arlyn Andrews, Lukasz Chmura, Edward Dlugokencky, László Haszpra, Ray L. Langenfelds, Toshinobu Machida, Takakiyo Nakazawa, Michel Ramonet, Colm Sweeney, and Douglas Worthy
Atmos. Chem. Phys., 21, 1245–1266, https://doi.org/10.5194/acp-21-1245-2021, https://doi.org/10.5194/acp-21-1245-2021, 2021
Short summary
Short summary
In order to improve the top-down estimation of the anthropogenic greenhouse gas emissions, a high-resolution inverse modelling technique was developed for applications to global transport modelling of carbon dioxide and other greenhouse gases. A coupled Eulerian–Lagrangian transport model and its adjoint are combined with surface fluxes at 0.1° resolution to provide high-resolution forward simulation and inverse modelling of surface fluxes accounting for signals from emission hot spots.
Martine Collaud Coen, Benjamin Tobias Brem, Martin Gysel-Beer, Robin Modini, Stephan Henne, Martin Steinbacher, Davide Putero, Maria I. Gini, and Kostantinos Eleftheriadis
EGUsphere, https://doi.org/10.5194/egusphere-2025-4162, https://doi.org/10.5194/egusphere-2025-4162, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
Saharan dust is transported over long distances by large-scale atmospheric circulation and it reaches 30 to 150 times per year the Jungfraujoch high-altitude station. The study analyzes the influence of the instrument types on SD detected by the single scattering albedo spectral dependence. This method is then compared to detection methods based on the size distribution and the back-trajectories. A source sensitivity and a 23-year climatology of the dust frequency and mass are also performed.
Yosuke Niwa, Yasunori Tohjima, Yukio Terao, Tazu Saeki, Akihiko Ito, Taku Umezawa, Kyohei Yamada, Motoki Sasakawa, Toshinobu Machida, Shin-Ichiro Nakaoka, Hideki Nara, Hiroshi Tanimoto, Hitoshi Mukai, Yukio Yoshida, Shinji Morimoto, Shinya Takatsuji, Kazuhiro Tsuboi, Yousuke Sawa, Hidekazu Matsueda, Kentaro Ishijima, Ryo Fujita, Daisuke Goto, Xin Lan, Kenneth Schuldt, Michal Heliasz, Tobias Biermann, Lukasz Chmura, Jarsolaw Necki, Irène Xueref-Remy, and Damiano Sferlazzo
Atmos. Chem. Phys., 25, 6757–6785, https://doi.org/10.5194/acp-25-6757-2025, https://doi.org/10.5194/acp-25-6757-2025, 2025
Short summary
Short summary
This study estimated regional and sectoral emission contributions to the unprecedented surge of atmospheric methane for 2020–2022. The methane is the second most important greenhouse gas, and its emissions reduction is urgently required to mitigate global warming. Numerical modeling-based estimates with three different sets of atmospheric observations consistently suggested large contributions of biogenic emissions from South Asia and Southeast Asia to the surge of atmospheric methane.
Lubna Dada, Benjamin T. Brem, Lidia-Marta Amarandi-Netedu, Martine Collaud Coen, Nikolaos Evangeliou, Christoph Hueglin, Nora Nowak, Robin Modini, Martin Steinbacher, and Martin Gysel-Beer
Aerosol Research, 3, 315–336, https://doi.org/10.5194/ar-3-315-2025, https://doi.org/10.5194/ar-3-315-2025, 2025
Short summary
Short summary
We investigated the sources of ultrafine particles (UFPs) in Payerne, Switzerland, highlighting the significant role of secondary processes in elevating UFP concentrations to levels comparable to urban areas. As the first study in rural midland Switzerland to analyze new particle formation events and secondary contributions, it offers key insights for air quality regulation and the role of agriculture in Switzerland and central Europe.
Hanyu Liu, Felix R. Vogel, Misa Ishizawa, Zhen Zhang, Benjamin Poulter, Doug E. J. Worthy, Leyang Feng, Anna L. Gagné-Landmann, Ao Chen, Ziting Huang, Dylan C. Gaeta, Joe R. Melton, Douglas Chan, Vineet Yadav, Deborah Huntzinger, and Scot M. Miller
EGUsphere, https://doi.org/10.5194/egusphere-2025-2150, https://doi.org/10.5194/egusphere-2025-2150, 2025
Short summary
Short summary
We find that the state-of-the-art process-based methane flux models have both lower flux magnitude and reduced inter-model uncertainty compared to a previous model inter-comparison from over a decade ago. Despite these improvements, methane flux estimates from process-based models are still likely too high compared to atmospheric observations. We also find that models with simpler parameterizations often result in better agreement with atmospheric observations in high-latitude North America.
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
EGUsphere, https://doi.org/10.5194/egusphere-2025-1736, https://doi.org/10.5194/egusphere-2025-1736, 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 exchange 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.
Marielle Saunois, Adrien Martinez, Benjamin Poulter, Zhen Zhang, Peter A. Raymond, Pierre Regnier, Josep G. Canadell, Robert B. Jackson, Prabir K. Patra, Philippe Bousquet, Philippe Ciais, Edward J. Dlugokencky, Xin Lan, George H. Allen, David Bastviken, David J. Beerling, Dmitry A. Belikov, Donald R. Blake, Simona Castaldi, Monica Crippa, Bridget R. Deemer, Fraser Dennison, Giuseppe Etiope, Nicola Gedney, Lena Höglund-Isaksson, Meredith A. Holgerson, Peter O. Hopcroft, Gustaf Hugelius, Akihiko Ito, Atul K. Jain, Rajesh Janardanan, Matthew S. Johnson, Thomas Kleinen, Paul B. Krummel, Ronny Lauerwald, Tingting Li, Xiangyu Liu, Kyle C. McDonald, Joe R. Melton, Jens Mühle, Jurek Müller, Fabiola Murguia-Flores, Yosuke Niwa, Sergio Noce, Shufen Pan, Robert J. Parker, Changhui Peng, Michel Ramonet, William J. Riley, Gerard Rocher-Ros, Judith A. Rosentreter, Motoki Sasakawa, Arjo Segers, Steven J. Smith, Emily H. Stanley, Joël Thanwerdas, Hanqin Tian, Aki Tsuruta, Francesco N. Tubiello, Thomas S. Weber, Guido R. van der Werf, Douglas E. J. Worthy, Yi Xi, Yukio Yoshida, Wenxin Zhang, Bo Zheng, Qing Zhu, Qiuan Zhu, and Qianlai Zhuang
Earth Syst. Sci. Data, 17, 1873–1958, https://doi.org/10.5194/essd-17-1873-2025, https://doi.org/10.5194/essd-17-1873-2025, 2025
Short summary
Short summary
Methane (CH4) is the second most important human-influenced greenhouse gas in terms of climate forcing after carbon dioxide (CO2). A consortium of multi-disciplinary scientists synthesise and update the budget of the sources and sinks of CH4. This edition benefits from important progress in estimating emissions from lakes and ponds, reservoirs, and streams and rivers. For the 2010s decade, global CH4 emissions are estimated at 575 Tg CH4 yr-1, including ~65 % from anthropogenic sources.
Liang Feng, Paul Palmer, Luke Smallman, Jingfeng Xiao, Paulo Cristofanelli, Ove Hermansen, John Lee, Casper Labuschagne, Simonetta Montaguti, Steffen Noe, Stephen Platt, Xinrong Ren, Martin Steinbacher, and Irene Xueref-Remy
EGUsphere, https://doi.org/10.5194/egusphere-2025-1793, https://doi.org/10.5194/egusphere-2025-1793, 2025
Short summary
Short summary
2023 saw an unexpectedly high global atmospheric CO2 growth. Satellite data reveal a role for increased emissions over the tropics. Larger emissions over eastern Brazil can be explained by warmer temperatures, while changes in rainfall and soil moisture play more of a role in emission increases elsewhere in the tropics.
Tatsuya Miyauchi, Makoto Saito, Hibiki M. Noda, Akihiko Ito, Tomomichi Kato, and Tsuneo Matsunaga
Geosci. Model Dev., 18, 2329–2347, https://doi.org/10.5194/gmd-18-2329-2025, https://doi.org/10.5194/gmd-18-2329-2025, 2025
Short summary
Short summary
Solar-induced chlorophyll fluorescence (SIF) is an effective indicator for monitoring photosynthetic activity. This paper introduces VISIT-SIF, a biogeochemical model developed based on the Vegetation Integrative Simulator for Trace gases (VISIT) to represent satellite-observed SIF. Our simulations reproduced the global distribution and seasonal variations in observed SIF. VISIT-SIF helps to improve photosynthetic processes through a combination of biogeochemical modeling and observed SIF.
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.
Sina Voshtani, Dylan B. A. Jones, Debra Wunch, Drew C. Pendergrass, Paul O. Wennberg, David F. Pollard, Isamu Morino, Hirofumi Ohyama, Nicholas M. Deutscher, Frank Hase, Ralf Sussmann, Damien Weidmann, Rigel Kivi, Omaira García, Yao Té, Jack Chen, Kerry Anderson, Robin Stevens, Shobha Kondragunta, Aihua Zhu, Douglas Worthy, Senen Racki, Kathryn McKain, Maria V. Makarova, Nicholas Jones, Emmanuel Mahieu, Andrea Cadena-Caicedo, Paolo Cristofanelli, Casper Labuschagne, Elena Kozlova, Thomas Seitz, Martin Steinbacher, Reza Mahdi, and Isao Murata
EGUsphere, https://doi.org/10.5194/egusphere-2025-858, https://doi.org/10.5194/egusphere-2025-858, 2025
Short summary
Short summary
We assess the complementarity of the greater temporal coverage provided by ground-based remote sensing data with the spatial coverage of satellite observations when these data are used together to quantify CO emissions from extreme wildfires in 2023. Our results reveal that the commonly used biomass burning emission inventories significantly underestimate the fire emissions and emphasize the importance of the ground-based remote sensing data in reducing uncertainties in the estimated emissions.
Yuri Brugnara, Martin Steinbacher, Simone Baffelli, and Lukas Emmenegger
EGUsphere, https://doi.org/10.5194/egusphere-2024-3556, https://doi.org/10.5194/egusphere-2024-3556, 2024
Short summary
Short summary
GAW-QC is an interactive dashboard for the quality control of in-situ atmospheric composition measurements made at stations taking part in the Global Atmosphere Watch network. Even though it is mainly targeted at station operators who want to analyze recent, not yet published measurements, it allows anybody to verify the quality of already published measurements using various anomaly detection algorithms as well as visual comparisons.
Reza Kusuma Nurrohman, Tomomichi Kato, Hideki Ninomiya, Lea Végh, Nicolas Delbart, Tatsuya Miyauchi, Hisashi Sato, Tomohiro Shiraishi, and Ryuichi Hirata
Biogeosciences, 21, 4195–4227, https://doi.org/10.5194/bg-21-4195-2024, https://doi.org/10.5194/bg-21-4195-2024, 2024
Short summary
Short summary
SPITFIRE (SPread and InTensity of FIRE) was integrated into a spatially explicit individual-based dynamic global vegetation model to improve the accuracy of depicting Siberian forest fire frequency, intensity, and extent. Fires showed increased greenhouse gas and aerosol emissions in 2006–2100 for Representative Concentration Pathways. This study contributes to understanding fire dynamics, land ecosystem–climate interactions, and global material cycles under the threat of escalating fires.
Shigeyuki Ishidoya, Kazuhiro Tsuboi, Hiroaki Kondo, Kentaro Ishijima, Nobuyuki Aoki, Hidekazu Matsueda, and Kazuyuki Saito
Atmos. Chem. Phys., 24, 1059–1077, https://doi.org/10.5194/acp-24-1059-2024, https://doi.org/10.5194/acp-24-1059-2024, 2024
Short summary
Short summary
A method evaluating techniques for carbon neutrality, such as carbon capture and storage (CCS), is important. This study presents a method to evaluate CO2 emissions from a cement plant based on atmospheric O2 and CO2 measurements. The method will also be useful for evaluating CO2 capture from flue gas at CCS plants, since the plants remove CO2 from the atmosphere without causing any O2 changes, just as cement plants do, differing only in the direction of CO2 exchange with the atmosphere.
Davide Putero, Paolo Cristofanelli, Kai-Lan Chang, Gaëlle Dufour, Gregory Beachley, Cédric Couret, Peter Effertz, Daniel A. Jaffe, Dagmar Kubistin, Jason Lynch, Irina Petropavlovskikh, Melissa Puchalski, Timothy Sharac, Barkley C. Sive, Martin Steinbacher, Carlos Torres, and Owen R. Cooper
Atmos. Chem. Phys., 23, 15693–15709, https://doi.org/10.5194/acp-23-15693-2023, https://doi.org/10.5194/acp-23-15693-2023, 2023
Short summary
Short summary
We investigated the impact of societal restriction measures during the COVID-19 pandemic on surface ozone at 41 high-elevation sites worldwide. Negative ozone anomalies were observed for spring and summer 2020 for all of the regions considered. In 2021, negative anomalies continued for Europe and partially for the eastern US, while western US sites showed positive anomalies due to wildfires. IASI satellite data and the Carbon Monitor supported emission reductions as a cause of the anomalies.
Paolo Cristofanelli, Cosimo Fratticioli, Lynn Hazan, Mali Chariot, Cedric Couret, Orestis Gazetas, Dagmar Kubistin, Antti Laitinen, Ari Leskinen, Tuomas Laurila, Matthias Lindauer, Giovanni Manca, Michel Ramonet, Pamela Trisolino, and Martin Steinbacher
Atmos. Meas. Tech., 16, 5977–5994, https://doi.org/10.5194/amt-16-5977-2023, https://doi.org/10.5194/amt-16-5977-2023, 2023
Short summary
Short summary
We investigated the application of two automatic methods for detecting spikes due to local emissions in greenhouse gas (GHG) observations at a subset of sites from the ICOS Atmosphere network. We analysed the sensitivity to the spike frequency of using different methods and settings. We documented the impact of the de-spiking on different temporal aggregations (i.e. hourly, monthly and seasonal averages) of CO2, CH4 and CO 1 min time series.
Hirofumi Ohyama, Matthias M. Frey, Isamu Morino, Kei Shiomi, Masahide Nishihashi, Tatsuya Miyauchi, Hiroko Yamada, Makoto Saito, Masanobu Wakasa, Thomas Blumenstock, and Frank Hase
Atmos. Chem. Phys., 23, 15097–15119, https://doi.org/10.5194/acp-23-15097-2023, https://doi.org/10.5194/acp-23-15097-2023, 2023
Short summary
Short summary
We conducted a field campaign for CO2 column measurements in the Tokyo metropolitan area with three ground-based Fourier transform spectrometers. The model simulations using prior CO2 fluxes were generally in good agreement with the observations. We developed an urban-scale inversion system in which spatially resolved CO2 fluxes and a scaling factor of large point source emissions were estimated. The posterior total CO2 emissions agreed with emission inventories within the posterior uncertainty.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Dorothee C. E. Bakker, Judith Hauck, Peter Landschützer, Corinne Le Quéré, Ingrid T. Luijkx, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Peter Anthoni, Leticia Barbero, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Bertrand Decharme, Laurent Bopp, Ida Bagus Mandhara Brasika, Patricia Cadule, Matthew A. Chamberlain, Naveen Chandra, Thi-Tuyet-Trang Chau, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Xinyu Dou, Kazutaka Enyo, Wiley Evans, Stefanie Falk, Richard A. Feely, Liang Feng, Daniel J. Ford, Thomas Gasser, Josefine Ghattas, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Jens Heinke, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Andrew R. Jacobson, Atul Jain, Tereza Jarníková, Annika Jersild, Fei Jiang, Zhe Jin, Fortunat Joos, Etsushi Kato, Ralph F. Keeling, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Arne Körtzinger, Xin Lan, Nathalie Lefèvre, Hongmei Li, Junjie Liu, Zhiqiang Liu, Lei Ma, Greg Marland, Nicolas Mayot, Patrick C. McGuire, Galen A. McKinley, Gesa Meyer, Eric J. Morgan, David R. Munro, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin M. O'Brien, Are Olsen, Abdirahman M. Omar, Tsuneo Ono, Melf Paulsen, Denis Pierrot, Katie Pocock, Benjamin Poulter, Carter M. Powis, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Thais M. Rosan, Jörg Schwinger, Roland Séférian, T. Luke Smallman, Stephen M. Smith, Reinel Sospedra-Alfonso, Qing Sun, Adrienne J. Sutton, Colm Sweeney, Shintaro Takao, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Hiroyuki Tsujino, Francesco Tubiello, Guido R. van der Werf, Erik van Ooijen, Rik Wanninkhof, Michio Watanabe, Cathy Wimart-Rousseau, Dongxu Yang, Xiaojuan Yang, Wenping Yuan, Xu Yue, Sönke Zaehle, Jiye Zeng, and Bo Zheng
Earth Syst. Sci. Data, 15, 5301–5369, https://doi.org/10.5194/essd-15-5301-2023, https://doi.org/10.5194/essd-15-5301-2023, 2023
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.
Leonard Kirago, Örjan Gustafsson, Samuel Mwaniki Gaita, Sophie L. Haslett, Michael J. Gatari, Maria Elena Popa, Thomas Röckmann, Christoph Zellweger, Martin Steinbacher, Jörg Klausen, Christian Félix, David Njiru, and August Andersson
Atmos. Chem. Phys., 23, 14349–14357, https://doi.org/10.5194/acp-23-14349-2023, https://doi.org/10.5194/acp-23-14349-2023, 2023
Short summary
Short summary
This study provides ground-observational evidence that supports earlier suggestions that savanna fires are the main emitters and modulators of carbon monoxide gas in Africa. Using isotope-based techniques, the study has shown that about two-thirds of this gas is emitted from savanna fires, while for urban areas, in this case Nairobi, primary sources approach 100 %. The latter has implications for air quality policy, suggesting primary emissions such as traffic should be targeted.
Yu Someya, Yukio Yoshida, Hirofumi Ohyama, Shohei Nomura, Akihide Kamei, Isamu Morino, Hitoshi Mukai, Tsuneo Matsunaga, Joshua L. Laughner, Voltaire A. Velazco, Benedikt Herkommer, Yao Té, Mahesh Kumar Sha, Rigel Kivi, Minqiang Zhou, Young Suk Oh, Nicholas M. Deutscher, and David W. T. Griffith
Atmos. Meas. Tech., 16, 1477–1501, https://doi.org/10.5194/amt-16-1477-2023, https://doi.org/10.5194/amt-16-1477-2023, 2023
Short summary
Short summary
The updated retrieval algorithm for the Greenhouse gases Observing SATellite level 2 product is presented. The main changes in the algorithm from the previous one are the treatment of cirrus clouds, the degradation model of the sensor, solar irradiance, and gas absorption coefficient tables. The retrieval results showed improvements in fitting accuracy and an increase in the data amount over land. On the other hand, there are still large biases of XCO2 which should be corrected over the ocean.
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.
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.
Matthias Schneider, Benjamin Ertl, Qiansi Tu, Christopher J. Diekmann, Farahnaz Khosrawi, Amelie N. Röhling, Frank Hase, Darko Dubravica, Omaira E. García, Eliezer Sepúlveda, Tobias Borsdorff, Jochen Landgraf, Alba Lorente, André Butz, Huilin Chen, Rigel Kivi, Thomas Laemmel, Michel Ramonet, Cyril Crevoisier, Jérome Pernin, Martin Steinbacher, Frank Meinhardt, Kimberly Strong, Debra Wunch, Thorsten Warneke, Coleen Roehl, Paul O. Wennberg, Isamu Morino, Laura T. Iraci, Kei Shiomi, Nicholas M. Deutscher, David W. T. Griffith, Voltaire A. Velazco, and David F. Pollard
Atmos. Meas. Tech., 15, 4339–4371, https://doi.org/10.5194/amt-15-4339-2022, https://doi.org/10.5194/amt-15-4339-2022, 2022
Short summary
Short summary
We present a computationally very efficient method for the synergetic use of level 2 remote-sensing data products. We apply the method to IASI vertical profile and TROPOMI total column space-borne methane observations and thus gain sensitivity for the tropospheric methane partial columns, which is not achievable by the individual use of TROPOMI and IASI. These synergetic effects are evaluated theoretically and empirically by inter-comparisons to independent references of TCCON, AirCore, and GAW.
Naveen Chandra, Prabir K. Patra, Yousuke Niwa, Akihiko Ito, Yosuke Iida, Daisuke Goto, Shinji Morimoto, Masayuki Kondo, Masayuki Takigawa, Tomohiro Hajima, and Michio Watanabe
Atmos. Chem. Phys., 22, 9215–9243, https://doi.org/10.5194/acp-22-9215-2022, https://doi.org/10.5194/acp-22-9215-2022, 2022
Short summary
Short summary
This paper is intended to accomplish two goals: (1) quantify mean and uncertainty in non-fossil-fuel CO2 fluxes estimated by inverse modeling and (2) provide in-depth analyses of regional CO2 fluxes in support of emission mitigation policymaking. CO2 flux variability and trends are discussed concerning natural climate variability and human disturbances using multiple lines of evidence.
Cyril Brunner, Benjamin T. Brem, Martine Collaud Coen, Franz Conen, Martin Steinbacher, Martin Gysel-Beer, and Zamin A. Kanji
Atmos. Chem. Phys., 22, 7557–7573, https://doi.org/10.5194/acp-22-7557-2022, https://doi.org/10.5194/acp-22-7557-2022, 2022
Short summary
Short summary
Microscopic particles called ice-nucleating particles (INPs) are essential for ice crystals to form in clouds. INPs are a tiny proportion of atmospheric aerosol, and their abundance is poorly constrained. We study how the concentration of INPs changes diurnally and seasonally at a mountaintop station in central Europe. Unsurprisingly, a diurnal cycle is only found when considering air masses that have had lower-altitude ground contact. The highest INP concentrations occur in spring.
Shigeyuki Ishidoya, Kazuhiro Tsuboi, Yosuke Niwa, Hidekazu Matsueda, Shohei Murayama, Kentaro Ishijima, and Kazuyuki Saito
Atmos. Chem. Phys., 22, 6953–6970, https://doi.org/10.5194/acp-22-6953-2022, https://doi.org/10.5194/acp-22-6953-2022, 2022
Short summary
Short summary
The atmospheric O2 / N2 ratio and CO2 concentration over the western North Pacific are presented. We found significant modification of the seasonal APO cycle in the middle troposphere due to the interhemispheric mixing of air. APO driven by the net marine biological activities indicated annual sea–air O2 flux during El Niño. Terrestrial biospheric and oceanic CO2 uptakes during 2012–2019 were estimated to be 1.8 and 2.8 Pg C a−1, respectively.
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.
Jiye Zeng, Tsuneo Matsunaga, and Tomoko Shirai
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-71, https://doi.org/10.5194/essd-2022-71, 2022
Manuscript not accepted for further review
Short summary
Short summary
We have extracted the increase rates of ocean CO2 with three types of machine learning models. The results are new and important because scarce data made it difficult to use machine learning models for for ocean CO2 reconstruction and oceanic CO2 sink estimate. One of the approaches is to remove the trend in CO2 data obtained in multiple-years so that the models can learn the non-linear dependence of CO2 on seawater properties better.
Cyril Brunner, Benjamin T. Brem, Martine Collaud Coen, Franz Conen, Maxime Hervo, Stephan Henne, Martin Steinbacher, Martin Gysel-Beer, and Zamin A. Kanji
Atmos. Chem. Phys., 21, 18029–18053, https://doi.org/10.5194/acp-21-18029-2021, https://doi.org/10.5194/acp-21-18029-2021, 2021
Short summary
Short summary
Special microscopic particles called ice-nucleating particles (INPs) are essential for ice crystals to form in the atmosphere. INPs are sparse and their atmospheric concentration and properties are not well understood. Mineral dust particles make up a significant fraction of INPs but how much remains unknown. Here, we address this knowledge gap by studying periods when mineral particles are present in large quantities at a mountaintop station in central Europe.
Larissa Lacher, Hans-Christian Clemen, Xiaoli Shen, Stephan Mertes, Martin Gysel-Beer, Alireza Moallemi, Martin Steinbacher, Stephan Henne, Harald Saathoff, Ottmar Möhler, Kristina Höhler, Thea Schiebel, Daniel Weber, Jann Schrod, Johannes Schneider, and Zamin A. Kanji
Atmos. Chem. Phys., 21, 16925–16953, https://doi.org/10.5194/acp-21-16925-2021, https://doi.org/10.5194/acp-21-16925-2021, 2021
Short summary
Short summary
We investigate ice-nucleating particle properties at Jungfraujoch during the 2017 joint INUIT/CLACE field campaign, to improve the knowledge about those rare particles in a cloud-relevant environment. By quantifying ice-nucleating particles in parallel to single-particle mass spectrometry measurements, we find that mineral dust and aged sea spray particles are potential candidates for ice-nucleating particles. Our findings are supported by ice residual analysis and source region modeling.
Alex Resovsky, Michel Ramonet, Leonard Rivier, Jerome Tarniewicz, Philippe Ciais, Martin Steinbacher, Ivan Mammarella, Meelis Mölder, Michal Heliasz, Dagmar Kubistin, Matthias Lindauer, Jennifer Müller-Williams, Sebastien Conil, and Richard Engelen
Atmos. Meas. Tech., 14, 6119–6135, https://doi.org/10.5194/amt-14-6119-2021, https://doi.org/10.5194/amt-14-6119-2021, 2021
Short summary
Short summary
We present a technical description of a statistical methodology for extracting synoptic- and seasonal-length anomalies from greenhouse gas time series. The definition of what represents an anomalous signal is somewhat subjective, which we touch on throughout the paper. We show, however, that the method performs reasonably well in extracting portions of time series influenced by significant North Atlantic Oscillation weather episodes and continent-wide terrestrial biospheric aberrations.
Yosuke Niwa, Yousuke Sawa, Hideki Nara, Toshinobu Machida, Hidekazu Matsueda, Taku Umezawa, Akihiko Ito, Shin-Ichiro Nakaoka, Hiroshi Tanimoto, and Yasunori Tohjima
Atmos. Chem. Phys., 21, 9455–9473, https://doi.org/10.5194/acp-21-9455-2021, https://doi.org/10.5194/acp-21-9455-2021, 2021
Short summary
Short summary
Fires in Equatorial Asia release a large amount of carbon into the atmosphere. Extensively using high-precision atmospheric carbon dioxide (CO2) data from a commercial aircraft observation project, we estimated fire carbon emissions in Equatorial Asia induced by the big El Niño event in 2015. Additional shipboard measurement data elucidated the validity of the analysis and the best estimate indicated 273 Tg C for fire emissions during September–October 2015.
Dac-Loc Nguyen, Hendryk Czech, Simone M. Pieber, Jürgen Schnelle-Kreis, Martin Steinbacher, Jürgen Orasche, Stephan Henne, Olga B. Popovicheva, Gülcin Abbaszade, Guenter Engling, Nicolas Bukowiecki, Nhat-Anh Nguyen, Xuan-Anh Nguyen, and Ralf Zimmermann
Atmos. Chem. Phys., 21, 8293–8312, https://doi.org/10.5194/acp-21-8293-2021, https://doi.org/10.5194/acp-21-8293-2021, 2021
Short summary
Short summary
Southeast Asia is well-known for emission-intense and recurring wildfires and after-harvest crop residue burning during the pre-monsoon season from February to April. We describe a biomass burning (BB) plume arriving at remote Pha Din meteorological station, outline its carbonaceous particulate matter (PM) constituents based on more than 50 target compounds and discuss possible BB sources. This study adds valuable information on chemical PM composition for a region with scarce data availability.
Shigeyuki Ishidoya, Satoshi Sugawara, Yasunori Tohjima, Daisuke Goto, Kentaro Ishijima, Yosuke Niwa, Nobuyuki Aoki, and Shohei Murayama
Atmos. Chem. Phys., 21, 1357–1373, https://doi.org/10.5194/acp-21-1357-2021, https://doi.org/10.5194/acp-21-1357-2021, 2021
Short summary
Short summary
The surface Ar / N2 ratio showed not only secular increasing trends, but also interannual variations in phase with the global ocean heat content (OHC). Sensitivity test by using a two-dimensional model indicated that the secular trend in the Ar / N2 ratio is modified by the gravitational separation in the stratosphere. The analytical results imply that the surface Ar/N2 ratio is an important tracer for detecting spatiotemporally integrated changes in OHC and stratospheric circulation.
Shamil Maksyutov, Tomohiro Oda, Makoto Saito, Rajesh Janardanan, Dmitry Belikov, Johannes W. Kaiser, Ruslan Zhuravlev, Alexander Ganshin, Vinu K. Valsala, Arlyn Andrews, Lukasz Chmura, Edward Dlugokencky, László Haszpra, Ray L. Langenfelds, Toshinobu Machida, Takakiyo Nakazawa, Michel Ramonet, Colm Sweeney, and Douglas Worthy
Atmos. Chem. Phys., 21, 1245–1266, https://doi.org/10.5194/acp-21-1245-2021, https://doi.org/10.5194/acp-21-1245-2021, 2021
Short summary
Short summary
In order to improve the top-down estimation of the anthropogenic greenhouse gas emissions, a high-resolution inverse modelling technique was developed for applications to global transport modelling of carbon dioxide and other greenhouse gases. A coupled Eulerian–Lagrangian transport model and its adjoint are combined with surface fluxes at 0.1° resolution to provide high-resolution forward simulation and inverse modelling of surface fluxes accounting for signals from emission hot spots.
Camille Yver-Kwok, Carole Philippon, Peter Bergamaschi, Tobias Biermann, Francescopiero Calzolari, Huilin Chen, Sebastien Conil, Paolo Cristofanelli, Marc Delmotte, Juha Hatakka, Michal Heliasz, Ove Hermansen, Kateřina Komínková, Dagmar Kubistin, Nicolas Kumps, Olivier Laurent, Tuomas Laurila, Irene Lehner, Janne Levula, Matthias Lindauer, Morgan Lopez, Ivan Mammarella, Giovanni Manca, Per Marklund, Jean-Marc Metzger, Meelis Mölder, Stephen M. Platt, Michel Ramonet, Leonard Rivier, Bert Scheeren, Mahesh Kumar Sha, Paul Smith, Martin Steinbacher, Gabriela Vítková, and Simon Wyss
Atmos. Meas. Tech., 14, 89–116, https://doi.org/10.5194/amt-14-89-2021, https://doi.org/10.5194/amt-14-89-2021, 2021
Short summary
Short summary
The Integrated Carbon Observation System (ICOS) is a pan-European research infrastructure which provides harmonized and high-precision scientific data on the carbon cycle and the greenhouse gas (GHG) budget. All stations have to undergo a rigorous assessment before being labeled, i.e., receiving approval to join the network. In this paper, we present the labeling process for the ICOS atmospheric network through the 23 stations that were labeled between November 2017 and November 2019.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Judith Hauck, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Stephen Sitch, Corinne Le Quéré, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone Alin, Luiz E. O. C. Aragão, Almut Arneth, Vivek Arora, Nicholas R. Bates, Meike Becker, Alice Benoit-Cattin, Henry C. Bittig, Laurent Bopp, Selma Bultan, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Wiley Evans, Liesbeth Florentie, Piers M. Forster, Thomas Gasser, Marion Gehlen, Dennis Gilfillan, Thanos Gkritzalis, Luke Gregor, Nicolas Gruber, Ian Harris, Kerstin Hartung, Vanessa Haverd, Richard A. Houghton, Tatiana Ilyina, Atul K. Jain, Emilie Joetzjer, Koji Kadono, Etsushi Kato, Vassilis Kitidis, Jan Ivar Korsbakken, Peter Landschützer, Nathalie Lefèvre, Andrew Lenton, Sebastian Lienert, Zhu Liu, Danica Lombardozzi, Gregg Marland, Nicolas Metzl, David R. Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin O'Brien, Tsuneo Ono, Paul I. Palmer, Denis Pierrot, Benjamin Poulter, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Jörg Schwinger, Roland Séférian, Ingunn Skjelvan, Adam J. P. Smith, Adrienne J. Sutton, Toste Tanhua, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Guido van der Werf, Nicolas Vuichard, Anthony P. Walker, Rik Wanninkhof, Andrew J. Watson, David Willis, Andrew J. Wiltshire, Wenping Yuan, Xu Yue, and Sönke Zaehle
Earth Syst. Sci. Data, 12, 3269–3340, https://doi.org/10.5194/essd-12-3269-2020, https://doi.org/10.5194/essd-12-3269-2020, 2020
Short summary
Short summary
The Global Carbon Budget 2020 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.
Hirofumi Ohyama, Isamu Morino, Voltaire A. Velazco, Theresa Klausner, Gerry Bagtasa, Matthäus Kiel, Matthias Frey, Akihiro Hori, Osamu Uchino, Tsuneo Matsunaga, Nicholas M. Deutscher, Joshua P. DiGangi, Yonghoon Choi, Glenn S. Diskin, Sally E. Pusede, Alina Fiehn, Anke Roiger, Michael Lichtenstern, Hans Schlager, Pao K. Wang, Charles C.-K. Chou, Maria Dolores Andrés-Hernández, and John P. Burrows
Atmos. Meas. Tech., 13, 5149–5163, https://doi.org/10.5194/amt-13-5149-2020, https://doi.org/10.5194/amt-13-5149-2020, 2020
Short summary
Short summary
Column-averaged dry-air mole fractions of CO2 and CH4 measured by a solar viewing portable Fourier transform spectrometer (EM27/SUN) were validated with in situ profile data obtained during the transfer flights of two aircraft campaigns. Atmospheric dynamical properties based on ERA5 and WRF-Chem were used as criteria for selecting the best aircraft profiles for the validation. The resulting air-mass-independent correction factors for the EM27/SUN data were 0.9878 for CO2 and 0.9829 for CH4.
Cited articles
Akagi, S. K., Yokelson, R. J., Wiedinmyer, C., Alvarado, M. J., Reid, J. S., Karl, T., Crounse, J. D., and Wennberg, P. O.: Emission factors for open and domestic biomass burning for use in atmospheric models, Atmos. Chem. Phys., 11, 4039–4072, https://doi.org/10.5194/acp-11-4039-2011, 2011. a
Andreae, M. O.: Emission of trace gases and aerosols from biomass burning – an updated assessment, Atmos. Chem. Phys., 19, 8523–8546, https://doi.org/10.5194/acp-19-8523-2019, 2019. a, b, c
Andreae, M. O. and Merlet, P.: Emission of trace gases and aerosols from
biomass burning, Global Biogeochem. Cy., 15, 955–966, 2001. a
Avitabile, V., Herold, M., Heuvelink, G. B. M., Lewis, S. L., Phillips,
O. L., Asner, G. P., Armston, J., Ashton, P. S., Banin, L., Bayol, N.,
Berry, N. J., Boeckx, P., de Jong, B. H. J., DeVries, B., Girardin, C. A.
J., Kearsley, E., Lindsell, J. A., Lopez-Gonzalez, G., Lucas, R., Malhi,
Y., Morel, A., Mitchard, E. T. A., Nagy, L., Qie, L., Quinones, M. J.,
Ryan, C. M., Ferry, S. J. W., Sunderland, T., Laurin, G. V., Gatti, R. C.,
Valentini, R., Verbeeck, H., Wijaya, A., and Willcock, S.: An
integrated pan-tropical biomass map using multiple reference datasets, Glob. Change Biol., 22, 1406–1420, 2016. a, b, c
Baccini, A., Goetz, S. J., Walker, W. S., Laporte, N. T., Sun, M., Sulla-
Menashe, D., Hackler, J., Beck, P. S. A., Dubayah, R., Friedl, M. A.,
Samanta, S., and Houghton, R. A.: Estimated carbon
dioxide emissions from tropical deforestation improved by carbon-density
maps, Nat. Clim. Change, 2, 182–185, 2012. a
Balch, J. K., Bradley, B. A., Abatzoglou, J. T., Nagy, R. C., Fusco, E. J., and
Mahood, A. L.: Human-started wildfires expand the fire niche across the
United States, P. Natl. Acad. Sci. USA, 114,
2946–2951, 2017. a
Bartholomé, E. and Belward, A. S.: GLC2000: a new approach to global land
cover mapping from Earth observation data,
Int. J. Remote Sens., 26, 1959–1977, 2005. a
Bougiatioti, A., Stavroulas, I., Kostenidou, E., Zarmpas, P., Theodosi, C., Kouvarakis, G., Canonaco, F., Prévôt, A. S. H., Nenes, A., Pandis, S. N., and Mihalopoulos, N.: Processing of biomass-burning aerosol in the eastern Mediterranean during summertime, Atmos. Chem. Phys., 14, 4793–4807, https://doi.org/10.5194/acp-14-4793-2014, 2014. a
Bouvet, A., Mermoz, S., Le Toan, T., Villard, L., Mathieu, R., Naidoo, L., and
Asner, G. P.: An above-ground biomass map of African savannahs and woodlands
at 25 m resolution derived from ALOS PALSAR,
Remote Sens. Environ.,
206, 156–173, 2018. a
Carreiras, J. M., Vasconcelos, M. J., and Lucas, R. M.: Understanding the
relationship between aboveground biomass and ALOS PALSAR data in the forests
of Guinea-Bissau (West Africa), Remote Sens. Environ., 121, 426–442,
2012. a
Chen, Y., Li, Q., Randerson, J. T., Lyons, E. A., Kahn, R. A., Nelson, D. L., and Diner, D. J.: The sensitivity of CO and aerosol transport to the temporal and vertical distribution of North American boreal fire emissions, Atmos. Chem. Phys., 9, 6559–6580, https://doi.org/10.5194/acp-9-6559-2009, 2009. a
Clerici, N., Valbuena Calderón, C. A., and Posada, J. M.: Fusion of
Sentinel-1A and Sentinel-2A data for land cover mapping: a case study in
the lower Magdalena region, Colombia, J. Maps, 13, 718–726, 2017. a
Deeter, M., Mao, D., Martínez-Alonso, S., Worden, H., Andreae, M., and
Schlager, H.: Impacts of MOPITT cloud detection revisions on observation
frequency and mapping of highly polluted scenes,
Remote Sens. Environ., 262, 112–516, 2021. a
Deeter, M. N.: Calculation and application of MOPITT averaging kernels, Tech.
rep., National Center for Atmospheric Research (NCAR), Boulder, CO, 1–9, 2002. a
Deeter, M. N., Emmons, L. K., Francis, G. L., Edwards, D. P., Gille, J. C.,
Warner, J. X., Khattatov, B., Ziskin, D., Lamarque, J. F., Ho, S. P., Yudin,
V., Attié, J. L., Packman, D., Chen, J., Mao, D., and Drummond, J. R.:
Operational carbon monoxide retrieval algorithm and selected results for the
MOPITT instrument, J. Geophys. Res., 108, 4399, https://doi.org/10.1029/2002JD003186, 2003. a
Deeter, M. N., Martínez-Alonso, S., Edwards, D. P., Emmons, L. K., Gille, J. C., Worden, H. M., Sweeney, C., Pittman, J. V., Daube, B. C., and Wofsy, S. C.: The MOPITT Version 6 product: algorithm enhancements and validation, Atmos. Meas. Tech., 7, 3623–3632, https://doi.org/10.5194/amt-7-3623-2014, 2014. 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
Dutta, R., Das, A., and Aryal, J.: Big data integration shows Australian
bush-fire frequency is increasing significantly,
Roy. Soc. Open Sci.,
3, 150–241, 2016. a
Giglio, L., van der Werf, G. R., Randerson, J. T., Collatz, G. J., and Kasibhatla, P.: Global estimation of burned area using MODIS active fire observations, Atmos. Chem. Phys., 6, 957–974, https://doi.org/10.5194/acp-6-957-2006, 2006. a, b
Giglio, L., Schroeder, W., and Justice, C. O.: The collection 6 MODIS active
fire detection algorithm and fire products, Remote Sens. Environ.,
178, 31–41, 2016. a
Goetz, S. J., Baccini, A., Laporte, N. T., Johns, T., Walker, W., Kellndorfer,
J., Houghton, R. A., and Sun, M.: Mapping and monitoring carbon stocks with
satellite observations: a comparison of methods,
Carbon Balance and Management, 4, 2, https://doi.org/10.1186/1750-0680-4-2, 2009. a
Hart, S. J., Henkelman, J., McLoughlin, P. D., Nielsen, S. E., Truchon-Savard,
A., and Johnstone, J. F.: Examining forest resilience to changing fire
frequency in a fire-prone region of boreal forest, Glob. Change Biol., 25,
869–884, 2019. a
Hayashi, K., Ono, K., Kajiura, M., Sudo, S., Yonemura, S., Fushimi, A., Saitoh,
K., Fujitani, Y., and Tanabe, K.: Trace gas and particle emissions from open
burning of three cereal crop residues: Increase in residue moistness enhances
emissions of carbon monoxide, methane, and particulate organic carbon,
Atmos. Environ., 95, 36–44, 2014. a
Hooghiemstra, P. B., Krol, M. C., Meirink, J. F., Bergamaschi, P., van der Werf, G. R., Novelli, P. C., Aben, I., and Röckmann, T.: Optimizing global CO emission estimates using a four-dimensional variational data assimilation system and surface network observations, Atmos. Chem. Phys., 11, 4705–4723, https://doi.org/10.5194/acp-11-4705-2011, 2011. a, b
Ito, A.: Disequilibrium of terrestrial ecosystem CO2 budget caused by disturbance-induced emissions and non-CO2 carbon export flows: a global model assessment, Earth Syst. Dynam., 10, 685–709, https://doi.org/10.5194/esd-10-685-2019, 2019. 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
Kaiser, J. W., Heil, A., Andreae, M. O., Benedetti, A., Chubarova, N., Jones, L., Morcrette, J.-J., Razinger, M., Schultz, M. G., Suttie, M., and van der Werf, G. R.: Biomass burning emissions estimated with a global fire assimilation system based on observed fire radiative power, Biogeosciences, 9, 527–554, https://doi.org/10.5194/bg-9-527-2012, 2012. a
Kim, M.: Variations and Sources of Atmospheric CO2 Measured at East Trout
Lake, Canada, PhD thesis, University of Waterloo, http://hdl.handle.net/10012/10140 (last access: 22 February 2021), 2016. a
bayashi, S., Ota, Y., Harada Y., Ebita, A., Moriya, M., Onoda, H.,
Onogi, K., Kamahori, H., Kobayashi, C., Endo, H., Miyaoka, K., and
Takahashi, K.: The JRA-55 reanalysis:
General specifications and basic characteristics,
J. Meteorol. Soc. Jpn., 93, 5–48, 2015. a
Lucas, R., Armston, J., Fairfax, R., Fensham, R., Accad, A., Carreiras,
J., Kelley, J., Bunting, P., Clewley, D., Bray, S., Metcalfe, D., Dwyer, J.,
Bowen, M., Eyre, T., Laidlaw, M., and Shimada, M.: An evaluation of the
ALOS PALSAR L-band backscatter-Above ground biomass relationship
Queensland, Australia: Impacts of surface moisture condition and vegetation
structure,
IEEE J. Sel. Top. Appl., 3, 576–593, 2010. a
Michel, C., Liousse, C., Grégoire, J.-M., Tansey, K., Carmichael, G., and
Woo, J.-H.: Biomass burning emission inventory from burnt area data given by
the SPOT-VEGETATION system in the frame of TRACE-P and ACE-Asia campaigns,
J. Geophys. Res.-Atmos., 110, D09304, https://doi.org/10.1029/2004JD005461, 2005. a
Mitchard, E. T., Saatchi, S. S., Baccini, A., Asner, G. P., Goetz, S. J.,
Harris, N. L., and Brown, S.: Uncertainty in the spatial distribution of
tropical forest biomass: a comparison of pan-tropical maps,
Carbon Balance and Management, 8, 10, https://doi.org/10.1186/1750-0680-8-10, 2013. a
Mu, M., Randerson, J. T., van der Werf, G. R., Giglio, L., Kasibhatla,
P., Morton, D., Collatz, G. J., DeFries, R. S., Hyer, E. J., Prins, E. M.,
Griffith, D. W. T., Wunch, D., Toon, G. C., Sherlock, V., and Wennberg,
P. O.: Daily and 3-hourly
variability in global fire emissions and consequences for atmospheric model
predictions of carbon monoxide, J. Geophys. Res.-Atmos.,
116, D24303, https://doi.org/10.1029/2011JD016245, 2011. a, b
Niwa, Y., Patra, P. K., Sawa, Y., Machida, T., Matsueda, H., Belikov, D., Maki, T., Ikegami, M., Imasu, R., Maksyutov, S., Oda, T., Satoh, M., and Takigawa, M.: Three-dimensional variations of atmospheric CO2: aircraft measurements and multi-transport model simulations, Atmos. Chem. Phys., 11, 13359–13375, https://doi.org/10.5194/acp-11-13359-2011, 2011. a
Niwa, Y., Tomita, H., Satoh, M., Imasu, R., Sawa, Y., Tsuboi, K., Matsueda, H., Machida, T., Sasakawa, M., Belan, B., and Saigusa, N.: A 4D-Var inversion system based on the icosahedral grid model (NICAM-TM 4D-Var v1.0) – Part 1: Offline forward and adjoint transport models, Geosci. Model Dev., 10, 1157–1174, https://doi.org/10.5194/gmd-10-1157-2017, 2017. a
Niwa, Y., Sawa, Y., Nara, H., Machida, T., Matsueda, H., Umezawa, T., Ito, A., Nakaoka, S.-I., Tanimoto, H., and Tohjima, Y.: Estimation of fire-induced carbon emissions from Equatorial Asia in 2015 using in situ aircraft and ship observations, Atmos. Chem. Phys., 21, 9455–9473, https://doi.org/10.5194/acp-21-9455-2021, 2021. a
Office for Global Environmental Data Integration and Analytics: Global Environmental
Database, National Institute for Environmental Studies [data set], https://db.cger.nies.go.jp/portal/overviews/index?lang=eng, last access: 12 April 2022. a
Pan, X., Ichoku, C., Chin, M., Bian, H., Darmenov, A., Colarco, P., Ellison, L., Kucsera, T., da Silva, A., Wang, J., Oda, T., and Cui, G.: Six global biomass burning emission datasets: intercomparison and application in one global aerosol model, Atmos. Chem. Phys., 20, 969–994, https://doi.org/10.5194/acp-20-969-2020, 2020. a, b
Patra, P. K., Houweling, S., Krol, M., Bousquet, P., Belikov, D., Bergmann, D., Bian, H., Cameron-Smith, P., Chipperfield, M. P., Corbin, K., Fortems-Cheiney, A., Fraser, A., Gloor, E., Hess, P., Ito, A., Kawa, S. R., Law, R. M., Loh, Z., Maksyutov, S., Meng, L., Palmer, P. I., Prinn, R. G., Rigby, M., Saito, R., and Wilson, C.: TransCom model simulations of CH4 and related species: linking transport, surface flux and chemical loss with CH4 variability in the troposphere and lower stratosphere, Atmos. Chem. Phys., 11, 12813–12837, https://doi.org/10.5194/acp-11-12813-2011, 2011. a
Popescu, S. C., Zhao, K., Neuenschwander, A., and Lin, C.: Satellite lidar vs.
small footprint airborne lidar: Comparing the accuracy of aboveground biomass
estimates and forest structure metrics at footprint level, Remote Sens.
Environ., 115, 2786–2797, 2011. a
Potter, C. S., Randerson, J. T., Field, C. B., Matson, P. A., Vitousek, P. M.,
Moonet, H. A., and Klooster, S. A.: Terrestrial ecosystem production: a
process model based on global satellite and surface data, Global Biogeochem.
Cy., 7, 811–841, 1993. a
Rodriguez-Galiano, V. F., Ghimire, B., Rogan, J., Chica-Olmo, M., and
Rigol-Sanchez, J. P.: An assessment of the effectiveness of a random forest
classifier for land-cover classification,
ISPRS J. Photogramm., 67, 93–104, 2012. a
Saatchi, S. S., Harris, N. L., Brown, S., Lefsky, M., Mitchard, E. T. A.,
Salas, W., Zutta, B. R., Buermann, W., Lewis, S. L., Hagen, S., Petrova, S.,
White, L., Silman, M., and Morel, A.: Benchmark map of forest carbon stocks
in tropical regions across three continents, P. Natl.
Acad. Sci. USA, 108, 9899–9904, 2011. a
Saito, M., Luyssaert, S., Poulter, B., Williams, M., Ciais, P., Bellassen, V.,
Ryan, C. M., Yue, C., Cadule, P., and Peylin, P.: Fire regimes and
variability in aboveground woody biomass in miombo woodland, J.
Geophys. Res.-Biogeo., 119, 1014–1029, 2014. a
Santoro, M.: GlobBiomass – global datasets of forest biomass,
PANGAEA [data set], https://doi.org/10.1594/PANGAEA.894711, 2018. a
Satoh, M.: Conservative scheme for the compressible nonhydrostatic models with
the horizontally explicit and vertically implicit time integration scheme,
Mon. Weather Rev., 130, 1227–1245, 2002. a
Seiler, W. and Crutzen, P. J.: Estimates of gross and net fluxes of carbon
between the biosphere and the atmosphere from biomass burning, Climatic
Change, 2, 207–247, 1980. a
Shi, Y., Matsunaga, T., Saito, M., Yamaguchi, Y., and Chen, X.: Comparison of
global inventories of CO2 emissions from biomass burning during
2002–2011 derived from multiple satellite products, Environ.
Pollut., 206, 479–487, 2015. a
Shiraishi, T., Hirata, R., and Hirano, T.: New inventories of global carbon
dioxide emissions through biomass burning in 2001–2020, Remote Sensing, 13,
1914, https://doi.org/10.3390/rs13101914, 2021. a
Sulla-Menashe, D., Gray, J. M., Abercrombie, S. P., and Friedl, M. A.:
Hierarchical mapping of annual global land cover 2001 to present: The MODIS
Collection 6 Land Cover product, Remote Sens. Environ., 222,
183–194, 2019. a
Turetsky, M. R., Benscoter, B., Page, S., Rein, G., Van Der Werf, G. R., and
Watts, A.: Global vulnerability of peatlands to fire and carbon loss, Nat.
Geosci., 8, 11–14, 2015. a
van der Werf, G. R., Randerson, J. T., Giglio, L., van Leeuwen, T. T., Chen, Y., Rogers, B. M., Mu, M., van Marle, M. J. E., Morton, D. C., Collatz, G. J., Yokelson, R. J., and Kasibhatla, P. S.: Global fire emissions estimates during 1997–2016, Earth Syst. Sci. Data, 9, 697–720, https://doi.org/10.5194/essd-9-697-2017, 2017. a, b, c, d, e, f, g
Van Wagner, C. E.: Development and Structure of the
Canadian Forest FireWeather Index System, Canadian Forestry Service
Ottawa, 1987. a
van Wees, D. and van der Werf, G. R.: Modelling biomass burning emissions and the effect of spatial resolution: a case study for Africa based on the Global Fire Emissions Database (GFED), Geosci. Model Dev., 12, 4681–4703, https://doi.org/10.5194/gmd-12-4681-2019, 2019. a
Watanabe, F., Uchino, O., Joo, Y., Aono, M., Higashijima, K., Hirano, Y.,
Tsuboi, K., and Suda, K.: Interannual variation of growth rate of atmospheric
carbon dioxide concentration observed at the JMA's three monitoring
stations: Large increase in concentration of atmospheric carbon dioxide in
1998, J. Meteorol. Soc. Jpn., 78, 673–682,
2000. a
Wiedinmyer, C., Akagi, S. K., Yokelson, R. J., Emmons, L. K., Al-Saadi, J. A., Orlando, J. J., and Soja, A. J.: The Fire INventory from NCAR (FINN): a high resolution global model to estimate the emissions from open burning, Geosci. Model Dev., 4, 625–641, https://doi.org/10.5194/gmd-4-625-2011, 2011. a
Willmott, C. J., Ackleson, S. G., Davis, R. E., Feddema, J. J., Klink, K. M.,
Legates, D. R., O'donnell, J., and Rowe, C. M.: Statistics for the evaluation
and comparison of models, J. Geophys. Res.-Oceans, 90,
8995–9005, 1985. a
Yarragunta, Y., Srivastava, S., Mitra, D., and Chandola, H. C.: Source
apportionment of carbon monoxide over India: a quantitative analysis using
MOZART-4, Environ. Sci. Pollut. Res., 28, 8722–8742, 2021. a
Yokota, T., Yoshida, Y., Eguchi, N., Ota, Y., Tanaka, T., Watanabe, H., and
Maksyutov, S.: Global concentrations of CO2 and CH4 retrieved
from GOSAT: first preliminary results, SOLA, 5, 160–163, 2009. a
Zellweger, C., Steinbacher, M., and Buchmann, B.: System and performance audit
of surface ozone, carbon monoxide, methane, and carbon dioxide at the Global
GAW Station Bukit Kototabang, Indonesia, WCC-Empa Report 19/1,
https://www.empa.ch/web/s503/wcc-empa (last access: 11 August 2021), 2019. a
Short summary
This study tested combinations of two sources of AGB data and two sources of LCC data and used the same burned area satellite data to estimate BB CO emissions. Our analysis showed large discrepancies in annual mean CO emissions and explicit differences in the simulated CO concentrations among the BB emissions estimates. This study has confirmed that BB emissions estimates are sensitive to the land surface information on which they are based.
This study tested combinations of two sources of AGB data and two sources of LCC data and used...
Altmetrics
Final-revised paper
Preprint