Articles | Volume 25, issue 23
https://doi.org/10.5194/acp-25-18111-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/acp-25-18111-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
10 Dec 2025
Research article |
| 10 Dec 2025
| 10 Dec 2025
A comparative analysis of China's anthropogenic CO2 emissions (2000–2023): insights from six bottom-up inventories and uncertainty assessment
Huirong Yang
Key Laboratory of Atmospheric Environment and Extreme Meteorology, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China
University of Chinese Academy of Sciences, Beijing, 101408, China
LAGEO & CNRC, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China
Kai Wu
CORRESPONDING AUTHOR
Key Laboratory of Atmospheric Environment and Extreme Meteorology, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China
LAGEO & CNRC, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China
Huizhong Shen
Guangdong Provincial Observation and Research Station for Coastal Atmosphere and Climate of the Greater Bay Area, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, 518055, China
Shenzhen Key Laboratory of Precision Measurement and Early Warning Technology for Urban Environmental Health Risks, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, 518055, China
Greet Janssens-Maenhout
European Commission, Joint Research Centre (JRC), Ispra (VA), 21027, Italy
Monica Crippa
European Commission, Joint Research Centre (JRC), Ispra (VA), 21027, Italy
Diego Guizzardi
European Commission, Joint Research Centre (JRC), Ispra (VA), 21027, Italy
Minqiang Zhou
CORRESPONDING AUTHOR
Key Laboratory of Atmospheric Environment and Extreme Meteorology, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China
LAGEO & CNRC, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China
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Atmos. Chem. Phys., 25, 18675–18696, https://doi.org/10.5194/acp-25-18675-2025, https://doi.org/10.5194/acp-25-18675-2025, 2025
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Earth Syst. Sci. Data, 17, 6461–6486, https://doi.org/10.5194/essd-17-6461-2025, https://doi.org/10.5194/essd-17-6461-2025, 2025
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Atmos. Meas. Tech., 18, 2439–2446, https://doi.org/10.5194/amt-18-2439-2025, https://doi.org/10.5194/amt-18-2439-2025, 2025
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Pengfei Han, Ning Zeng, Bo Yao, Wen Zhang, Weijun Quan, Pucai Wang, Ting Wang, Minqiang Zhou, Qixiang Cai, Yuzhong Zhang, Ruosi Liang, Wanqi Sun, and Shengxiang Liu
Atmos. Chem. Phys., 25, 4965–4988, https://doi.org/10.5194/acp-25-4965-2025, https://doi.org/10.5194/acp-25-4965-2025, 2025
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Methane (CH4) is a potent greenhouse gas. Northern China contributes a large proportion of CH4 emissions, yet large observation gaps exist. Here we compiled a comprehensive dataset, which is publicly available, that includes ground-based, satellite-based, inventory, and modeling results to show the CH4 concentrations, enhancements, and spatial–temporal variations. The data can benefit the research community and policy-makers for future observations, atmospheric inversions, and policy-making.
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
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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.
William Lamb, Robbie Andrew, Matthew Jones, Zebedee Nicholls, Glen Peters, Chris Smith, Marielle Saunois, Giacomo Grassi, Julia Pongratz, Steven Smith, Francesco Tubiello, Monica Crippa, Matthew Gidden, Pierre Friedlingstein, Jan Minx, and Piers Forster
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Revised manuscript under review for ESSD
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Ying Zhou, Congcong Qiao, Minqiang Zhou, Yilong Wang, Xiangjun Tian, Yinghong Wang, and Minzheng Duan
Atmos. Meas. Tech., 18, 1609–1619, https://doi.org/10.5194/amt-18-1609-2025, https://doi.org/10.5194/amt-18-1609-2025, 2025
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We developed an automated, flexible atmospheric sampling device for various platforms. During a 5 d field campaign in the Mount Qomolangma region, we performed 15 flights using the device mounted on a hexacopter unoccupied aerial vehicle (UAV). A total of 139 samples were analyzed using an Agilent 7890A gas chromatograph. Vertical profiles of four greenhouse gases (carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), and sulfur hexafluoride (SF6)) were analyzed and discussed.
Kelley C. Wells, Dylan B. Millet, Jared F. Brewer, Vivienne H. Payne, Karen E. Cady-Pereira, Rick Pernak, Susan Kulawik, Corinne Vigouroux, Nicholas Jones, Emmanuel Mahieu, Maria Makarova, Tomoo Nagahama, Ivan Ortega, Mathias Palm, Kimberly Strong, Matthias Schneider, Dan Smale, Ralf Sussmann, and Minqiang Zhou
Atmos. Meas. Tech., 18, 695–716, https://doi.org/10.5194/amt-18-695-2025, https://doi.org/10.5194/amt-18-695-2025, 2025
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Atmospheric volatile organic compounds (VOCs) affect both air quality and climate. Satellite measurements can help us to assess and predict their global impacts. We present new decadal (2012–2023) measurements of four key VOCs – methanol, ethene, ethyne, and hydrogen cyanide (HCN) – from the Cross-track Infrared Sounder. The measurements reflect emissions from major forests, wildfires, and industry and provide new information to advance understanding of these sources and their changes over time.
Minqiang Zhou, Pucai Wang, Bart Dils, Bavo Langerock, Geoff Toon, Christian Hermans, Weidong Nan, Qun Cheng, and Martine De Mazière
Atmos. Meas. Tech., 17, 6385–6396, https://doi.org/10.5194/amt-17-6385-2024, https://doi.org/10.5194/amt-17-6385-2024, 2024
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Solar absorption spectra near 2967 cm−1 recorded by a ground-based FTIR with a high spectral resolution of 0.0035 cm-1 are applied to retrieve C3H8 columns for the first time in Xianghe, China, within the NDACC-IRWG. The mean and standard deviation of the C3H8 columns are 1.80 ± 0.81 (1σ) × 1015 molec. cm-2. Good correlations are found between C3H8 and other non-methane hydrocarbons, such as C2H6 (R = 0.84) and C2H2 (R = 0.79), as well as between C3H8 and CO (R = 0.72).
Bart Dils, Minqiang Zhou, Claude Camy-Peyret, Martine De Mazière, Yannick Kangah, Bavo Langerock, Pascal Prunet, Carmine Serio, Richard Siddans, and Brian Kerridge
Atmos. Meas. Tech., 17, 5491–5524, https://doi.org/10.5194/amt-17-5491-2024, https://doi.org/10.5194/amt-17-5491-2024, 2024
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The paper discusses two very distinct methane products from the IASI instrument aboard the MetOp-A satellite. One (referred to as LMD NLISv8.3) uses a machine-learning approach, while the other (RALv2.0) uses a more conventional optimal estimation approach. We used a variety of model and independent reference measurement data to assess both products' overall quality, their differences, and specific aspects of each product that would benefit from further analysis by the product development teams.
Fengxin Xie, Tao Ren, Changying Zhao, Yuan Wen, Yilei Gu, Minqiang Zhou, Pucai Wang, Kei Shiomi, and Isamu Morino
Atmos. Meas. Tech., 17, 3949–3967, https://doi.org/10.5194/amt-17-3949-2024, https://doi.org/10.5194/amt-17-3949-2024, 2024
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This study demonstrates a new machine learning approach to efficiently and accurately estimate atmospheric carbon dioxide levels from satellite data. Rather than using traditional complex physics-based retrieval methods, neural network models are trained on simulated data to rapidly predict CO2 concentrations directly from satellite spectral measurements.
Shao Shi, Jinghao Zhai, Xin Yang, Yechun Ruan, Yuanlong Huang, Xujian Chen, Antai Zhang, Jianhuai Ye, Guomao Zheng, Baohua Cai, Yaling Zeng, Yixiang Wang, Chunbo Xing, Yujie Zhang, Tzung-May Fu, Lei Zhu, Huizhong Shen, and Chen Wang
Atmos. Chem. Phys., 24, 7001–7012, https://doi.org/10.5194/acp-24-7001-2024, https://doi.org/10.5194/acp-24-7001-2024, 2024
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The determination of ions in the mass spectra of individual particles remains uncertain. We have developed a standard-free mass calibration algorithm applicable to more than 98 % of ambient particles. With our algorithm, ions with ~ 0.05 Th mass difference could be determined. Therefore, many more atmospheric species could be determined and involved in the source apportionment of aerosols, the study of chemical reaction mechanisms, and the analysis of single-particle mixing states.
Monica Crippa, Diego Guizzardi, Federico Pagani, Marcello Schiavina, Michele Melchiorri, Enrico Pisoni, Francesco Graziosi, Marilena Muntean, Joachim Maes, Lewis Dijkstra, Martin Van Damme, Lieven Clarisse, and Pierre Coheur
Earth Syst. Sci. Data, 16, 2811–2830, https://doi.org/10.5194/essd-16-2811-2024, https://doi.org/10.5194/essd-16-2811-2024, 2024
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Knowing where emissions occur is essential for planning effective emission reduction measures and atmospheric modelling. Disaggregating national emissions over high-resolution grids requires spatial proxies that contain information on the location of different emission sources. This work incorporates state-of-the-art spatial information to improve the spatial representation of global emissions with the Emissions Database for Global Atmospheric Research (EDGAR).
Philippe Thunis, Jeroen Kuenen, Enrico Pisoni, Bertrand Bessagnet, Manjola Banja, Lech Gawuc, Karol Szymankiewicz, Diego Guizardi, Monica Crippa, Susana Lopez-Aparicio, Marc Guevara, Alexander De Meij, Sabine Schindlbacher, and Alain Clappier
Geosci. Model Dev., 17, 3631–3643, https://doi.org/10.5194/gmd-17-3631-2024, https://doi.org/10.5194/gmd-17-3631-2024, 2024
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An ensemble emission inventory is created with the aim of monitoring the status and progress made with the development of EU-wide inventories. This emission ensemble serves as a common benchmark for the screening and allows for the comparison of more than two inventories at a time. Because the emission “truth” is unknown, the approach does not tell which inventory is the closest to reality, but it identifies inconsistencies that require special attention.
Antonin Soulie, Claire Granier, Sabine Darras, Nicolas Zilbermann, Thierno Doumbia, Marc Guevara, Jukka-Pekka Jalkanen, Sekou Keita, Cathy Liousse, Monica Crippa, Diego Guizzardi, Rachel Hoesly, and Steven J. Smith
Earth Syst. Sci. Data, 16, 2261–2279, https://doi.org/10.5194/essd-16-2261-2024, https://doi.org/10.5194/essd-16-2261-2024, 2024
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Anthropogenic emissions are the result of transportation, power generation, industrial, residential and commercial activities as well as waste treatment and agriculture practices. This work describes the new CAMS-GLOB-ANT gridded inventory of 2000–2023 anthropogenic emissions of air pollutants and greenhouse gases. The methodology to generate the emissions is explained and the datasets are analysed and compared with publicly available global and regional inventories for selected world regions.
Joshua L. Laughner, Geoffrey C. Toon, Joseph Mendonca, Christof Petri, Sébastien Roche, Debra Wunch, Jean-Francois Blavier, David W. T. Griffith, Pauli Heikkinen, Ralph F. Keeling, Matthäus Kiel, Rigel Kivi, Coleen M. Roehl, Britton B. Stephens, Bianca C. Baier, Huilin Chen, Yonghoon Choi, Nicholas M. Deutscher, Joshua P. DiGangi, Jochen Gross, Benedikt Herkommer, Pascal Jeseck, Thomas Laemmel, Xin Lan, Erin McGee, Kathryn McKain, John Miller, Isamu Morino, Justus Notholt, Hirofumi Ohyama, David F. Pollard, Markus Rettinger, Haris Riris, Constantina Rousogenous, Mahesh Kumar Sha, Kei Shiomi, Kimberly Strong, Ralf Sussmann, Yao Té, Voltaire A. Velazco, Steven C. Wofsy, Minqiang Zhou, and Paul O. Wennberg
Earth Syst. Sci. Data, 16, 2197–2260, https://doi.org/10.5194/essd-16-2197-2024, https://doi.org/10.5194/essd-16-2197-2024, 2024
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This paper describes a new version, called GGG2020, of a data set containing column-integrated observations of greenhouse and related gases (including CO2, CH4, CO, and N2O) made by ground stations located around the world. Compared to the previous version (GGG2014), improvements have been made toward site-to-site consistency. This data set plays a key role in validating space-based greenhouse gas observations and in understanding the carbon cycle.
Ruben Urraca, Greet Janssens-Maenhout, Nicolás Álamos, Lucas Berna-Peña, Monica Crippa, Sabine Darras, Stijn Dellaert, Hugo Denier van der Gon, Mark Dowell, Nadine Gobron, Claire Granier, Giacomo Grassi, Marc Guevara, Diego Guizzardi, Kevin Gurney, Nicolás Huneeus, Sekou Keita, Jeroen Kuenen, Ana Lopez-Noreña, Enrique Puliafito, Geoffrey Roest, Simone Rossi, Antonin Soulie, and Antoon Visschedijk
Earth Syst. Sci. Data, 16, 501–523, https://doi.org/10.5194/essd-16-501-2024, https://doi.org/10.5194/essd-16-501-2024, 2024
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CoCO2-MOSAIC 1.0 is a global mosaic of regional bottom-up inventories providing gridded (0.1×0.1) monthly emissions of anthropogenic CO2. Regional inventories include country-specific information and finer spatial resolution than global inventories. CoCO2-MOSAIC provides harmonized access to these datasets and can be considered as a regionally accepted reference to assess the quality of global inventories, as done in the current paper.
Minqiang Zhou, Bavo Langerock, Mahesh Kumar Sha, Christian Hermans, Nicolas Kumps, Rigel Kivi, Pauli Heikkinen, Christof Petri, Justus Notholt, Huilin Chen, and Martine De Mazière
Atmos. Meas. Tech., 16, 5593–5608, https://doi.org/10.5194/amt-16-5593-2023, https://doi.org/10.5194/amt-16-5593-2023, 2023
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Atmospheric N2O and CH4 columns are successfully retrieved from low-resolution FTIR spectra recorded by a Bruker VERTEX 70. The 1-year measurements at Sodankylä show that the N2O total columns retrieved from 125HR and VERTEX 70 spectra are −0.3 ± 0.7 % with an R value of 0.93. The relative differences between the CH4 total columns retrieved from the 125HR and VERTEX spectra are 0.0 ± 0.8 % with an R value of 0.87. Such a technique can help to fill the gap in NDACC N2O and CH4 measurements.
Sieglinde Callewaert, Minqiang Zhou, Bavo Langerock, Pucai Wang, Ting Wang, Emmanuel Mahieu, and Martine De Mazière
EGUsphere, https://doi.org/10.5194/egusphere-2023-2103, https://doi.org/10.5194/egusphere-2023-2103, 2023
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We used an atmospheric transport model and satellite data to study greenhouse gas observations at Xianghe, China. Our study shows the key source sectors that influence the concentrations and their respective importance. Furthermore, meteorological factors such as wind direction are discussed. This research highlights the challenges in accurately simulating these kind of measurements and helps us to better understand greenhouse gas variability in the region.
Matthew J. McGrath, Ana Maria Roxana Petrescu, Philippe Peylin, Robbie M. Andrew, Bradley Matthews, Frank Dentener, Juraj Balkovič, Vladislav Bastrikov, Meike Becker, Gregoire Broquet, Philippe Ciais, Audrey Fortems-Cheiney, Raphael Ganzenmüller, Giacomo Grassi, Ian Harris, Matthew Jones, Jürgen Knauer, Matthias Kuhnert, Guillaume Monteil, Saqr Munassar, Paul I. Palmer, Glen P. Peters, Chunjing Qiu, Mart-Jan Schelhaas, Oksana Tarasova, Matteo Vizzarri, Karina Winkler, Gianpaolo Balsamo, Antoine Berchet, Peter Briggs, Patrick Brockmann, Frédéric Chevallier, Giulia Conchedda, Monica Crippa, Stijn N. C. Dellaert, Hugo A. C. Denier van der Gon, Sara Filipek, Pierre Friedlingstein, Richard Fuchs, Michael Gauss, Christoph Gerbig, Diego Guizzardi, Dirk Günther, Richard A. Houghton, Greet Janssens-Maenhout, Ronny Lauerwald, Bas Lerink, Ingrid T. Luijkx, Géraud Moulas, Marilena Muntean, Gert-Jan Nabuurs, Aurélie Paquirissamy, Lucia Perugini, Wouter Peters, Roberto Pilli, Julia Pongratz, Pierre Regnier, Marko Scholze, Yusuf Serengil, Pete Smith, Efisio Solazzo, Rona L. Thompson, Francesco N. Tubiello, Timo Vesala, and Sophia Walther
Earth Syst. Sci. Data, 15, 4295–4370, https://doi.org/10.5194/essd-15-4295-2023, https://doi.org/10.5194/essd-15-4295-2023, 2023
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Accurate estimation of fluxes of carbon dioxide from the land surface is essential for understanding future impacts of greenhouse gas emissions on the climate system. A wide variety of methods currently exist to estimate these sources and sinks. We are continuing work to develop annual comparisons of these diverse methods in order to clarify what they all actually calculate and to resolve apparent disagreement, in addition to highlighting opportunities for increased understanding.
Ruosi Liang, Yuzhong Zhang, Wei Chen, Peixuan Zhang, Jingran Liu, Cuihong Chen, Huiqin Mao, Guofeng Shen, Zhen Qu, Zichong Chen, Minqiang Zhou, Pucai Wang, Robert J. Parker, Hartmut Boesch, Alba Lorente, Joannes D. Maasakkers, and Ilse Aben
Atmos. Chem. Phys., 23, 8039–8057, https://doi.org/10.5194/acp-23-8039-2023, https://doi.org/10.5194/acp-23-8039-2023, 2023
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We compare and evaluate East Asian methane emissions inferred from different satellite observations (GOSAT and TROPOMI). The results show discrepancies over northern India and eastern China. Independent ground-based observations are more consistent with TROPOMI-derived emissions in northern India and GOSAT-derived emissions in eastern China.
Monica Crippa, Diego Guizzardi, Tim Butler, Terry Keating, Rosa Wu, Jacek Kaminski, Jeroen Kuenen, Junichi Kurokawa, Satoru Chatani, Tazuko Morikawa, George Pouliot, Jacinthe Racine, Michael D. Moran, Zbigniew Klimont, Patrick M. Manseau, Rabab Mashayekhi, Barron H. Henderson, Steven J. Smith, Harrison Suchyta, Marilena Muntean, Efisio Solazzo, Manjola Banja, Edwin Schaaf, Federico Pagani, Jung-Hun Woo, Jinseok Kim, Fabio Monforti-Ferrario, Enrico Pisoni, Junhua Zhang, David Niemi, Mourad Sassi, Tabish Ansari, and Kristen Foley
Earth Syst. Sci. Data, 15, 2667–2694, https://doi.org/10.5194/essd-15-2667-2023, https://doi.org/10.5194/essd-15-2667-2023, 2023
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This study responds to the global and regional atmospheric modelling community's need for a mosaic of air pollutant emissions with global coverage, long time series, spatially distributed data at a high time resolution, and a high sectoral resolution in order to enhance the understanding of transboundary air pollution. The mosaic approach to integrating official regional emission inventories with a global inventory based on a consistent methodology ensures policy-relevant results.
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
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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.
Ana Maria Roxana Petrescu, Chunjing Qiu, Matthew J. McGrath, Philippe Peylin, Glen P. Peters, Philippe Ciais, Rona L. Thompson, Aki Tsuruta, Dominik Brunner, Matthias Kuhnert, Bradley Matthews, Paul I. Palmer, Oksana Tarasova, Pierre Regnier, Ronny Lauerwald, David Bastviken, Lena Höglund-Isaksson, Wilfried Winiwarter, Giuseppe Etiope, Tuula Aalto, Gianpaolo Balsamo, Vladislav Bastrikov, Antoine Berchet, Patrick Brockmann, Giancarlo Ciotoli, Giulia Conchedda, Monica Crippa, Frank Dentener, Christine D. Groot Zwaaftink, Diego Guizzardi, Dirk Günther, Jean-Matthieu Haussaire, Sander Houweling, Greet Janssens-Maenhout, Massaer Kouyate, Adrian Leip, Antti Leppänen, Emanuele Lugato, Manon Maisonnier, Alistair J. Manning, Tiina Markkanen, Joe McNorton, Marilena Muntean, Gabriel D. Oreggioni, Prabir K. Patra, Lucia Perugini, Isabelle Pison, Maarit T. Raivonen, Marielle Saunois, Arjo J. Segers, Pete Smith, Efisio Solazzo, Hanqin Tian, Francesco N. Tubiello, Timo Vesala, Guido R. van der Werf, Chris Wilson, and Sönke Zaehle
Earth Syst. Sci. Data, 15, 1197–1268, https://doi.org/10.5194/essd-15-1197-2023, https://doi.org/10.5194/essd-15-1197-2023, 2023
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This study updates the state-of-the-art scientific overview of CH4 and N2O emissions in the EU27 and UK in Petrescu et al. (2021a). Yearly updates are needed to improve the different respective approaches and to inform on the development of formal verification systems. It integrates the most recent emission inventories, process-based model and regional/global inversions, comparing them with UNFCCC national GHG inventories, in support to policy to facilitate real-time verification procedures.
Minqiang Zhou, Bavo Langerock, Pucai Wang, Corinne Vigouroux, Qichen Ni, Christian Hermans, Bart Dils, Nicolas Kumps, Weidong Nan, and Martine De Mazière
Atmos. Meas. Tech., 16, 273–293, https://doi.org/10.5194/amt-16-273-2023, https://doi.org/10.5194/amt-16-273-2023, 2023
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The ground-based FTIR measurements at Xianghe provide carbon monoxide (CO), acetylene (C2H2), ethane (C2H6), formaldehyde (H2CO), and hydrogen cyanide (HCN) total columns between June 2018 and November 2021. The retrieval strategies, information, and uncertainties of these five important trace gases are presented and discussed. This study provides insight into the time series, variations, and correlations of these five species in northern China.
Xun Li, Momei Qin, Lin Li, Kangjia Gong, Huizhong Shen, Jingyi Li, and Jianlin Hu
Atmos. Chem. Phys., 22, 14799–14811, https://doi.org/10.5194/acp-22-14799-2022, https://doi.org/10.5194/acp-22-14799-2022, 2022
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Photochemical indicators have been widely used to predict O3–NOx–VOC sensitivity with given thresholds. Here we assessed the effectiveness of four indicators with a case study in the Yangtze River Delta, China. The overall performance was good, while some indicators showed inconsistencies with the O3 isopleths. The methodology used to determine the thresholds may produce uncertainties. These results would improve our understanding of the use of photochemical indicators in policy implications.
Xiangyu Zeng, Wei Wang, Cheng Liu, Changgong Shan, Yu Xie, Peng Wu, Qianqian Zhu, Minqiang Zhou, Martine De Mazière, Emmanuel Mahieu, Irene Pardo Cantos, Jamal Makkor, and Alexander Polyakov
Atmos. Meas. Tech., 15, 6739–6754, https://doi.org/10.5194/amt-15-6739-2022, https://doi.org/10.5194/amt-15-6739-2022, 2022
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CFC-11 and CFC-12, which are classified as ozone-depleting substances, also have high global warming potentials. This paper describes obtaining the CFC-11 and CFC-12 total columns from the solar spectra based on ground-based Fourier transform infrared spectroscopy at Hefei, China. The seasonal variation and annual trend of the two gases are analyzed, and then the data are compared with other independent datasets.
Minqiang Zhou, Bavo Langerock, Pucai Wang, Corinne Vigouroux, Qichen Ni, Christian Hermans, Bart Dils, Nicolas Kumps, Weidong Nan, and Martine De Mazière
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2022-354, https://doi.org/10.5194/acp-2022-354, 2022
Revised manuscript not accepted
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The ground-based FTIR measurements at Xianghe provide carbon monoxide (CO), acetylene (C2H2), ethane (C2H6), formaldehyde (H2CO), and hydrogen cyanide (HCN) total columns between June 2018 and November 2021. The retrieval strategies, retrieval information, and uncertainties of these five important trace gases are presented and discussed. This study provides an insight into the time series, variations, and correlations of these five species in North China.
Andrea Pozzer, Simon F. Reifenberg, Vinod Kumar, Bruno Franco, Matthias Kohl, Domenico Taraborrelli, Sergey Gromov, Sebastian Ehrhart, Patrick Jöckel, Rolf Sander, Veronica Fall, Simon Rosanka, Vlassis Karydis, Dimitris Akritidis, Tamara Emmerichs, Monica Crippa, Diego Guizzardi, Johannes W. Kaiser, Lieven Clarisse, Astrid Kiendler-Scharr, Holger Tost, and Alexandra Tsimpidi
Geosci. Model Dev., 15, 2673–2710, https://doi.org/10.5194/gmd-15-2673-2022, https://doi.org/10.5194/gmd-15-2673-2022, 2022
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A newly developed setup of the chemistry general circulation model EMAC (ECHAM5/MESSy for Atmospheric Chemistry) is evaluated here. A comprehensive organic degradation mechanism is used and coupled with a volatility base model.
The results show that the model reproduces most of the tracers and aerosols satisfactorily but shows discrepancies for oxygenated organic gases. It is also shown that this model configuration can be used for further research in atmospheric chemistry.
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
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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.
Jan C. Minx, William F. Lamb, Robbie M. Andrew, Josep G. Canadell, Monica Crippa, Niklas Döbbeling, Piers M. Forster, Diego Guizzardi, Jos Olivier, Glen P. Peters, Julia Pongratz, Andy Reisinger, Matthew Rigby, Marielle Saunois, Steven J. Smith, Efisio Solazzo, and Hanqin Tian
Earth Syst. Sci. Data, 13, 5213–5252, https://doi.org/10.5194/essd-13-5213-2021, https://doi.org/10.5194/essd-13-5213-2021, 2021
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We provide a synthetic dataset on anthropogenic greenhouse gas (GHG) emissions for 1970–2018 with a fast-track extension to 2019. We show that GHG emissions continued to rise across all gases and sectors. Annual average GHG emissions growth slowed, but absolute decadal increases have never been higher in human history. We identify a number of data gaps and data quality issues in global inventories and highlight their importance for monitoring progress towards international climate goals.
Mahesh Kumar Sha, Bavo Langerock, Jean-François L. Blavier, Thomas Blumenstock, Tobias Borsdorff, Matthias Buschmann, Angelika Dehn, Martine De Mazière, Nicholas M. Deutscher, Dietrich G. Feist, Omaira E. García, David W. T. Griffith, Michel Grutter, James W. Hannigan, Frank Hase, Pauli Heikkinen, Christian Hermans, Laura T. Iraci, Pascal Jeseck, Nicholas Jones, Rigel Kivi, Nicolas Kumps, Jochen Landgraf, Alba Lorente, Emmanuel Mahieu, Maria V. Makarova, Johan Mellqvist, Jean-Marc Metzger, Isamu Morino, Tomoo Nagahama, Justus Notholt, Hirofumi Ohyama, Ivan Ortega, Mathias Palm, Christof Petri, David F. Pollard, Markus Rettinger, John Robinson, Sébastien Roche, Coleen M. Roehl, Amelie N. Röhling, Constantina Rousogenous, Matthias Schneider, Kei Shiomi, Dan Smale, Wolfgang Stremme, Kimberly Strong, Ralf Sussmann, Yao Té, Osamu Uchino, Voltaire A. Velazco, Corinne Vigouroux, Mihalis Vrekoussis, Pucai Wang, Thorsten Warneke, Tyler Wizenberg, Debra Wunch, Shoma Yamanouchi, Yang Yang, and Minqiang Zhou
Atmos. Meas. Tech., 14, 6249–6304, https://doi.org/10.5194/amt-14-6249-2021, https://doi.org/10.5194/amt-14-6249-2021, 2021
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This paper presents, for the first time, Sentinel-5 Precursor methane and carbon monoxide validation results covering a period from November 2017 to September 2020. For this study, we used global TCCON and NDACC-IRWG network data covering a wide range of atmospheric and surface conditions across different terrains. We also show the influence of a priori alignment, smoothing uncertainties and the sensitivity of the validation results towards the application of advanced co-location criteria.
Minqiang Zhou, Bavo Langerock, Corinne Vigouroux, Bart Dils, Christian Hermans, Nicolas Kumps, Weidong Nan, Jean-Marc Metzger, Emmanuel Mahieu, Ting Wang, Pucai Wang, and Martine De Mazière
Atmos. Meas. Tech., 14, 6233–6247, https://doi.org/10.5194/amt-14-6233-2021, https://doi.org/10.5194/amt-14-6233-2021, 2021
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NO is a key active trace gas in the atmosphere, which affects the atmospheric environment and human health. In this study, we show that the tropospheric and stratospheric NO partial columns can be observed from the ground-based FTIR measurements at a polluted site (Xianghe, China), but only stratospheric NO partial columns can be observed at a background site (Maïdo, Reunion Island). The variations in the NO observed by the FTIR measurements at the two sites are analyzed and discussed.
Yang Yang, Minqiang Zhou, Ting Wang, Bo Yao, Pengfei Han, Denghui Ji, Wei Zhou, Yele Sun, Gengchen Wang, and Pucai Wang
Atmos. Chem. Phys., 21, 11741–11757, https://doi.org/10.5194/acp-21-11741-2021, https://doi.org/10.5194/acp-21-11741-2021, 2021
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This study introduces the in situ CO2 measurement system installed in Beijing (urban), Xianghe (suburban), and Xinglong (rural) in North China for the first time. The spatial and temporal variations in CO2 mole fractions at the three sites between June 2018 and April 2020 are discussed on both seasonal and diurnal scales.
Bingqing Zhang, Huizhong Shen, Pengfei Liu, Hongyu Guo, Yongtao Hu, Yilin Chen, Shaodong Xie, Ziyan Xi, T. Nash Skipper, and Armistead G. Russell
Atmos. Chem. Phys., 21, 8341–8356, https://doi.org/10.5194/acp-21-8341-2021, https://doi.org/10.5194/acp-21-8341-2021, 2021
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Extended ground-level measurements are coupled with model simulations to comprehensively compare the aerosol acidity in China and the United States. Aerosols in China are significantly less acidic than those in the United States, with pH values 1–2 units higher. Higher aerosol mass concentrations and the abundance of ammonia and ammonium in China, compared to the United States, are leading causes of the pH difference between these two countries.
Ana Maria Roxana Petrescu, Chunjing Qiu, Philippe Ciais, Rona L. Thompson, Philippe Peylin, Matthew J. McGrath, Efisio Solazzo, Greet Janssens-Maenhout, Francesco N. Tubiello, Peter Bergamaschi, Dominik Brunner, Glen P. Peters, Lena Höglund-Isaksson, Pierre Regnier, Ronny Lauerwald, David Bastviken, Aki Tsuruta, Wilfried Winiwarter, Prabir K. Patra, Matthias Kuhnert, Gabriel D. Oreggioni, Monica Crippa, Marielle Saunois, Lucia Perugini, Tiina Markkanen, Tuula Aalto, Christine D. Groot Zwaaftink, Hanqin Tian, Yuanzhi Yao, Chris Wilson, Giulia Conchedda, Dirk Günther, Adrian Leip, Pete Smith, Jean-Matthieu Haussaire, Antti Leppänen, Alistair J. Manning, Joe McNorton, Patrick Brockmann, and Albertus Johannes Dolman
Earth Syst. Sci. Data, 13, 2307–2362, https://doi.org/10.5194/essd-13-2307-2021, https://doi.org/10.5194/essd-13-2307-2021, 2021
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This study is topical and provides a state-of-the-art scientific overview of data availability from bottom-up and top-down CH4 and N2O emissions in the EU27 and UK. The data integrate recent emission inventories with process-based model data and regional/global inversions for the European domain, aiming at reconciling them with official country-level UNFCCC national GHG inventories in support to policy and to facilitate real-time verification procedures.
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
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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.
Efisio Solazzo, Monica Crippa, Diego Guizzardi, Marilena Muntean, Margarita Choulga, and Greet Janssens-Maenhout
Atmos. Chem. Phys., 21, 5655–5683, https://doi.org/10.5194/acp-21-5655-2021, https://doi.org/10.5194/acp-21-5655-2021, 2021
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We conducted an extensive analysis of the structural uncertainty of the Emissions Database for Global Atmospheric Research (EDGAR) emission inventory of greenhouse gases, which adds a much needed reliability dimension to the accuracy of the emission estimates. The study undertakes in-depth analyses of the implication of aggregating emissions from different sources and/or countries on the accuracy. Results are presented for all emissions sectors according to IPCC definitions.
Cited articles
Akimoto, H., Ohara, T., Kurokawa, J., and Horii, N.: Verification of energy consumption in China during 1996–2003 by using satellite observational data, Atmospheric Environment, 40, 7663–7667, https://doi.org/10.1016/j.atmosenv.2006.07.052, 2006.
Andres, R. J., Boden, T. A., and Higdon, D. M.: Gridded uncertainty in fossil fuel carbon dioxide emission maps, a CDIAC example, Atmos. Chem. Phys., 16, 14979–14995, https://doi.org/10.5194/acp-16-14979-2016, 2016.
Cai, B., Liang, S., Zhou, J., Wang, J., Cao, L., Qu, S., Xu, M., and Yang, Z.: China high resolution emission database (CHRED) with point emission sources, gridded emission data, and supplementary socioeconomic data, Resources, Conservation and Recycling, 129, 232–239, https://doi.org/10.1016/j.resconrec.2017.10.036, 2018.
Che, K., Cai, Z., Liu, Y., Wu, L., Yang, D., Chen, Y., Meng, X., Zhou, M., Wang, J., Yao, L., and Wang, P.: Lagrangian inversion of anthropogenic CO 2 emissions from Beijing using differential column measurements, Environ. Res. Lett., 17, 075001, https://doi.org/10.1088/1748-9326/ac7477, 2022.
Etheridge, D. M., Steele, L. P., Langenfelds, R. L., Francey, R. J., Barnola, J.-M., and Morgan, V. I.: Natural and anthropogenic changes in atmospheric CO2 over the last 1000 years from air in Antarctic ice and firn, Journal of Geophysical Research: Atmospheres, 101, 4115–4128, https://doi.org/10.1029/95JD03410, 1996.
Guan, D., Liu, Z., Geng, Y., Lindner, S., and Klaus, H.: The gigatonne gap in China's carbon dioxide inventories, Nature Climate Change, 2, 672–675, https://doi.org/10.1038/nclimate1560, 2012.
Guan, D., Shan, Y., and Meng, J.: Carbon Emission Accounts and Datasets (CEADs), Tsinghua University [data set] https://www.ceads.net.cn/data/ (last access: 19 April 2025), 2017.
Guan, Y., Shan, Y., Huang, Q., Chen, H., Wang, D., and Hubacek, K.: Assessment to China's Recent Emission Pattern Shifts, Earth's Future, 9, e2021EF002241, https://doi.org/10.1029/2021EF002241, 2021.
Han, P., Zeng, N., Oda, T., Zhang, W., Lin, X., Liu, D., Cai, Q., Ma, X., Meng, W., Wang, G., Wang, R., and Zheng, B.: A city-level comparison of fossil-fuel and industry processes-induced CO2 emissions over the Beijing-Tianjin-Hebei region from eight emission inventories, Carbon Balance Manage, 15, 25, https://doi.org/10.1186/s13021-020-00163-2, 2020a.
Han, P., Zeng, N., Oda, T., Lin, X., Crippa, M., Guan, D., Janssens-Maenhout, G., Ma, X., Liu, Z., Shan, Y., Tao, S., Wang, H., Wang, R., Wu, L., Yun, X., Zhang, Q., Zhao, F., and Zheng, B.: Evaluating China's fossil-fuel CO2 emissions from a comprehensive dataset of nine inventories, Atmos. Chem. Phys., 20, 11371–11385, https://doi.org/10.5194/acp-20-11371-2020, 2020b.
Hong, C., Zhang, Q., He, K., Guan, D., Li, M., Liu, F., and Zheng, B.: Variations of China's emission estimates: response to uncertainties in energy statistics, Atmos. Chem. Phys., 17, 1227–1239, https://doi.org/10.5194/acp-17-1227-2017, 2017.
IPCC: Climate Change 2007: Synthesis Report. Contribution of Working Groups I, II and III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, Core Writing Team, Pachauri, R. K. and Reisinger, A. (Eds.), IPCC, Geneva, Switzerland, 104 pp., https://www.ipcc.ch/site/assets/uploads/2018/02/ar4_syr_full_report.pdf (last access: 21 June 2025), 2007.
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.
Janssens-Maenhout, G., Crippa, M., and Guizzardi, D.: Emissions Database for Global Atmospheric Research (EDGAR) 2024, European Commission, Joint Research Centre (JRC) [data set], https://edgar.jrc.ec.europa.eu/dataset_ghg2024#p1 (last access: 19 April 2025), 2024.
Li, M., Liu, H., Geng, G., Hong, C., Liu, F., Song, Y., Tong, D., Zheng, B., Cui, H., Man, H., Zhang, Q., and He, K.: Anthropogenic emission inventories in China: a review, National Science Review, 4, 834–866, https://doi.org/10.1093/nsr/nwx150, 2017a.
Li, M., Zhang, Q., Kurokawa, J.-I., Woo, J.-H., He, K., Lu, Z., Ohara, T., Song, Y., Streets, D. G., Carmichael, G. R., Cheng, Y., Hong, C., Huo, H., Jiang, X., Kang, S., Liu, F., Su, H., and Zheng, B.: MIX: a mosaic Asian anthropogenic emission inventory under the international collaboration framework of the MICS-Asia and HTAP, Atmos. Chem. Phys., 17, 935–963, https://doi.org/10.5194/acp-17-935-2017, 2017b.
Liu, M., Wang, H., Wang, H., Oda, T., Zhao, Y., Yang, X., Zang, R., Zang, B., Bi, J., and Chen, J.: Refined estimate of China's CO2 emissions in spatiotemporal distributions, Atmos. Chem. Phys., 13, 10873–10882, https://doi.org/10.5194/acp-13-10873-2013, 2013.
Liu, F., Zhang, Q., Tong, D., Zheng, B., Li, M., Huo, H., and He, K. B.: High-resolution inventory of technologies, activities, and emissions of coal-fired power plants in China from 1990 to 2010, Atmos. Chem. Phys., 15, 13299–13317, https://doi.org/10.5194/acp-15-13299-2015, 2015.
Liu, H., Hu, C., Xiao, Q., Zhang, J., Sun, F., Shi, X., Chen, X., Yang, Y., and Xiao, W.: Analysis of anthropogenic CO2 emission uncertainty and influencing factors at city scale in Yangtze River Delta region: One of the world's largest emission hotspots, Atmospheric Pollution Research, 15, 102281, https://doi.org/10.1016/j.apr.2024.102281, 2024.
Oda, T. and Maksyutov, S.: A very high-resolution (1 km × 1 km) global fossil fuel CO2 emission inventory derived using a point source database and satellite observations of nighttime lights, Atmos. Chem. Phys., 11, 543–556, https://doi.org/10.5194/acp-11-543-2011, 2011.
Oda, T., Maksyutov, S., and Andres, R. J.: The Open-source Data Inventory for Anthropogenic CO2, version 2016 (ODIAC2016): a global monthly fossil fuel CO2 gridded emissions data product for tracer transport simulations and surface flux inversions, Earth Syst. Sci. Data, 10, 87–107, https://doi.org/10.5194/essd-10-87-2018, 2018.
Oda, T., Bun, R., Kinakh, V., Topylko, P., Halushchak, M., Marland, G., Lauvaux, T., Jonas, M., Maksyutov, S., Nahorski, Z., Lesiv, M., Danylo, O., and Horabik-Pyzel, J.: Errors and uncertainties in a gridded carbon dioxide emissions inventory, Mitig. Adapt. Strateg. Glob. Change, 24, 1007–1050, https://doi.org/10.1007/s11027-019-09877-2, 2019.
Oda, T. and Maksyutov, S.: Open-source Data Inventory for Anthropogenic CO2 emissions (ODIAC) 2023, Center for Global Environmental Research (CGER) [data set], https://db.cger.nies.go.jp/dataset/ODIAC/DL_odiac2023.html (last access: 19 April 2025), 2024.
Peylin, P., Law, R. M., Gurney, K. R., Chevallier, F., Jacobson, A. R., Maki, T., Niwa, Y., Patra, P. K., Peters, W., Rayner, P. J., Rödenbeck, C., van der Laan-Luijkx, I. T., and Zhang, X.: Global atmospheric carbon budget: results from an ensemble of atmospheric CO2 inversions, Biogeosciences, 10, 6699–6720, https://doi.org/10.5194/bg-10-6699-2013, 2013.
Schleussner, C.-F., Rogelj, J., Schaeffer, M., Lissner, T., Licker, R., Fischer, E. M., Knutti, R., Levermann, A., Frieler, K., and Hare, W.: Science and policy characteristics of the Paris Agreement temperature goal, Nature Clim. Change, 6, 827–835, https://doi.org/10.1038/nclimate3096, 2016.
Shan, Y., Guan, D., Zheng, H., Ou, J., Li, Y., Meng, J., Mi, Z., Liu, Z., and Zhang, Q.: China CO2 emission accounts 1997–2015, Sci. Data, 5, 170201, https://doi.org/10.1038/sdata.2017.201, 2018.
Shan, Y., Huang, Q., Guan, D., and Hubacek, K.: China CO2 emission accounts 2016–2017, Sci. Data, 7, 54, https://doi.org/10.1038/s41597-020-0393-y, 2020.
Shen, H. and Tao, S: Global Emission Monitoring System (GEMS) v1.0, Peking University and Southern University of Science and Technology [data set], https://gems.pku.edu.cn/data/database (last access: 19 April 2025), 2024.
Shi, Q., Zheng, B., Zheng, Y., Tong, D., Liu, Y., Ma, H., Hong, C., Geng, G., Guan, D., He, K., and Zhang, Q.: Co-benefits of CO2 emission reduction from China's clean air actions between 2013–2020, Nat. Commun., 13, 5061, https://doi.org/10.1038/s41467-022-32656-8, 2022.
Soulie, A., Zilbermann, N., Granier, C., Darras, S.: Global anthropogenic emissions for the Copernicus Atmosphere Monitoring Service (CAMS-GLOB-ANT) v6.2, ECMWF [data set], https://eccad.sedoo.fr/#/metadata/479 (last access: 19 April 2025), 2023.
Soulie, A., Granier, C., Darras, S., Zilbermann, N., Doumbia, T., Guevara, M., Jalkanen, J.-P., Keita, S., Liousse, C., Crippa, M., Guizzardi, D., Hoesly, R., and Smith, S. J.: Global anthropogenic emissions (CAMS-GLOB-ANT) for the Copernicus Atmosphere Monitoring Service simulations of air quality forecasts and reanalyses, Earth Syst. Sci. Data, 16, 2261–2279, https://doi.org/10.5194/essd-16-2261-2024, 2024.
Tao, S., Ru, M. Y., Du, W., Zhu, X., Zhong, Q. R., Li, B. G., Shen, G. F., Pan, X. L., Meng, W. J., Chen, Y. L., Shen, H. Z., Lin, N., Su, S., Zhuo, S. J., Huang, T. B., Xu, Y., Yun, X., Liu, J. F., Wang, X. L., Liu, W. X., Cheng, H. F., and Zhu, D. Q.: Quantifying the rural residential energy transition in China from 1992 to 2012 through a representative national survey, Nat. Energy, 3, 567–573, https://doi.org/10.1038/s41560-018-0158-4, 2018.
Wang, R., Tao, S., Ciais, P., Shen, H. Z., Huang, Y., Chen, H., Shen, G. F., Wang, B., Li, W., Zhang, Y. Y., Lu, Y., Zhu, D., Chen, Y. C., Liu, X. P., Wang, W. T., Wang, X. L., Liu, W. X., Li, B. G., and Piao, S. L.: High-resolution mapping of combustion processes and implications for CO2 emissions, Atmos. Chem. Phys., 13, 5189–5203, https://doi.org/10.5194/acp-13-5189-2013, 2013.
Wei, C.: Historical trend and drivers of China's CO2 emissions from 2000 to 2020, Environ. Dev. Sustain., 1–20, https://doi.org/10.1007/s10668-022-02811-8, 2022.
World Meteorological Organization (WMO): State of the Global Climate 2024. WMO-No. 1368, Geneva, Switzerland, 42 pp., https://library.wmo.int/viewer/69455/download?file=WMO-1368-2025_en.pdf&type=pdf (last access: 21 June 2025), 2025.
Xia, L., Liu, R., Fan, W., and Ren, C.: Emerging carbon dioxide hotspots in East Asia identified by a top-down inventory, Commun. Earth Environ., 6, 1–13, https://doi.org/10.1038/s43247-024-01991-7, 2025.
Xu, J., Guan, Y., Oldfield, J., Guan, D., and Shan, Y.: China carbon emission accounts 2020-2021, Applied Energy, 360, 122837, https://doi.org/10.1016/j.apenergy.2024.122837, 2024a.
Xu, R., Tong, D., Xiao, Q., Qin, X., Chen, C., Yan, L., Cheng, J., Cui, C., Hu, H., Liu, W., Yan, X., Wang, H., Liu, X., Geng, G., Lei, Y., Guan, D., He, K., and Zhang, Q.: MEIC-global-CO2: A new global CO2 emission inventory with highly-resolved source category and sub-country information, Sci. China Earth Sci., 67, 450–465, https://doi.org/10.1007/s11430-023-1230-3, 2024b.
Yang, H., Wu, K., Wang, T., Wang, P., and Zhou, M.: Atmospheric anthropogenic CO2 variations observed by tower in-situ measurements and simulated by the STILT model in the Beijing megacity region, Atmospheric Research, 325, 108258, https://doi.org/10.1016/j.atmosres.2025.108258, 2025.
Zhang, Q.: Multi-resolution Emission Inventory model for Climate and air pollution research (MEIC-Global-CO2) v1.0, Tsinghua University [data set], http://meicmodel.org.cn/?page_id=2341 (last access: 19 April 2025), 2024.
Zhang, Y., Zheng, X., Cai, W., Liu, Y., Luo, H., Guo, K., Bu, C., Li, J., and Wang, C.: Key drivers of the rebound trend of China's CO2 emissions, Environ. Res. Lett., 15, 104049, https://doi.org/10.1088/1748-9326/aba1bf, 2020.
Zhao, F., Bai, F., Liu, X., and Liu, Z.: A Review on Renewable Energy Transition under China's Carbon Neutrality Target, Sustainability, 14, 15006, https://doi.org/10.3390/su142215006, 2022.
Zhao, Y., Nielsen, C. P., and McElroy, M. B.: China's CO2 emissions estimated from the bottom up: Recent trends, spatial distributions, and quantification of uncertainties, Atmospheric Environment, 59, 214–223, https://doi.org/10.1016/j.atmosenv.2012.05.027, 2012.
Zheng, B., Tong, D., Li, M., Liu, F., Hong, C., Geng, G., Li, H., Li, X., Peng, L., Qi, J., Yan, L., Zhang, Y., Zhao, H., Zheng, Y., He, K., and Zhang, Q.: Trends in China's anthropogenic emissions since 2010 as the consequence of clean air actions, Atmos. Chem. Phys., 18, 14095–14111, https://doi.org/10.5194/acp-18-14095-2018, 2018.
Zheng, B., Cheng, J., Geng, G., Wang, X., Li, M., Shi, Q., Qi, J., Lei, Y., Zhang, Q., and He, K.: Mapping anthropogenic emissions in China at 1 km spatial resolution and its application in air quality modeling, Science Bulletin, 66, 612–620, https://doi.org/10.1016/j.scib.2020.12.008, 2021.
Zheng, L., Li, S., Hu, X., Zheng, F., Cai, K., Li, N., and Chen, Y.: Spatiotemporal comparative analysis of three carbon emission inventories in mainland China, Atmospheric Pollution Research, 16, 102417, https://doi.org/10.1016/j.apr.2025.102417, 2025.
Short summary
We compare six major anthropogenic CO2 emission inventories in China during the period 2000–2023 to assess emission trends and uncertainties. National emissions show a clear three‑phase pattern, with uncertainties below 5 % (1σ) at the national scale but much higher at the provincial level (10–50 %, 1σ). High-emission regions often have the largest uncertainties. Our findings support more accurate emission estimates and the verification emission reduction policies.
We compare six major anthropogenic CO2 emission inventories in China during the period 2000–2023...
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