Articles | Volume 13, issue 4
https://doi.org/10.5194/essd-13-1667-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-13-1667-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
21 Apr 2021
Data description paper |
| 21 Apr 2021
| 21 Apr 2021
CDIAC-FF: global and national CO2 emissions from fossil fuel combustion and cement manufacture: 1751–2017
Dennis Gilfillan
CORRESPONDING AUTHOR
Research Institute for Environment, Energy, and Economics,
Appalachian State University, Boone, North Carolina, USA
Department of Geological and Environmental Sciences, Appalachian
State University, Boone, North Carolina, USA
Gregg Marland
Research Institute for Environment, Energy, and Economics,
Appalachian State University, Boone, North Carolina, USA
Department of Geological and Environmental Sciences, Appalachian
State University, Boone, North Carolina, USA
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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.
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
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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.
Pierre Friedlingstein, Matthew W. Jones, Michael O'Sullivan, Robbie M. Andrew, Judith Hauck, Glen P. Peters, Wouter Peters, Julia Pongratz, Stephen Sitch, Corinne Le Quéré, Dorothee C. E. Bakker, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Peter Anthoni, Leticia Barbero, Ana Bastos, Vladislav Bastrikov, Meike Becker, Laurent Bopp, Erik Buitenhuis, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Kim I. Currie, Richard A. Feely, Marion Gehlen, Dennis Gilfillan, Thanos Gkritzalis, Daniel S. Goll, Nicolas Gruber, Sören Gutekunst, Ian Harris, Vanessa Haverd, Richard A. Houghton, George Hurtt, Tatiana Ilyina, Atul K. Jain, Emilie Joetzjer, Jed O. Kaplan, Etsushi Kato, Kees Klein Goldewijk, Jan Ivar Korsbakken, Peter Landschützer, Siv K. Lauvset, Nathalie Lefèvre, Andrew Lenton, Sebastian Lienert, Danica Lombardozzi, Gregg Marland, Patrick C. McGuire, Joe R. Melton, Nicolas Metzl, David R. Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Craig Neill, Abdirahman M. Omar, Tsuneo Ono, Anna Peregon, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Roland Séférian, Jörg Schwinger, Naomi Smith, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Francesco N. Tubiello, Guido R. van der Werf, Andrew J. Wiltshire, and Sönke Zaehle
Earth Syst. Sci. Data, 11, 1783–1838, https://doi.org/10.5194/essd-11-1783-2019, https://doi.org/10.5194/essd-11-1783-2019, 2019
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The Global Carbon Budget 2019 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.
C. Le Quéré, R. Moriarty, R. M. Andrew, G. P. Peters, P. Ciais, P. Friedlingstein, S. D. Jones, S. Sitch, P. Tans, A. Arneth, T. A. Boden, L. Bopp, Y. Bozec, J. G. Canadell, L. P. Chini, F. Chevallier, C. E. Cosca, I. Harris, M. Hoppema, R. A. Houghton, J. I. House, A. K. Jain, T. Johannessen, E. Kato, R. F. Keeling, V. Kitidis, K. Klein Goldewijk, C. Koven, C. S. Landa, P. Landschützer, A. Lenton, I. D. Lima, G. Marland, J. T. Mathis, N. Metzl, Y. Nojiri, A. Olsen, T. Ono, S. Peng, W. Peters, B. Pfeil, B. Poulter, M. R. Raupach, P. Regnier, C. Rödenbeck, S. Saito, J. E. Salisbury, U. Schuster, J. Schwinger, R. Séférian, J. Segschneider, T. Steinhoff, B. D. Stocker, A. J. Sutton, T. Takahashi, B. Tilbrook, G. R. van der Werf, N. Viovy, Y.-P. Wang, R. Wanninkhof, A. Wiltshire, and N. Zeng
Earth Syst. Sci. Data, 7, 47–85, https://doi.org/10.5194/essd-7-47-2015, https://doi.org/10.5194/essd-7-47-2015, 2015
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Carbon dioxide (CO2) emissions from human activities (burning fossil fuels and cement production, deforestation and other land-use change) are set to rise again in 2014.
This study (updated yearly) makes an accurate assessment of anthropogenic CO2 emissions and their redistribution between the atmosphere, ocean, and terrestrial biosphere in order to better understand the global carbon cycle, support the development of climate policies, and project future climate change.
P. Ciais, A. J. Dolman, A. Bombelli, R. Duren, A. Peregon, P. J. Rayner, C. Miller, N. Gobron, G. Kinderman, G. Marland, N. Gruber, F. Chevallier, R. J. Andres, G. Balsamo, L. Bopp, F.-M. Bréon, G. Broquet, R. Dargaville, T. J. Battin, A. Borges, H. Bovensmann, M. Buchwitz, J. Butler, J. G. Canadell, R. B. Cook, R. DeFries, R. Engelen, K. R. Gurney, C. Heinze, M. Heimann, A. Held, M. Henry, B. Law, S. Luyssaert, J. Miller, T. Moriyama, C. Moulin, R. B. Myneni, C. Nussli, M. Obersteiner, D. Ojima, Y. Pan, J.-D. Paris, S. L. Piao, B. Poulter, S. Plummer, S. Quegan, P. Raymond, M. Reichstein, L. Rivier, C. Sabine, D. Schimel, O. Tarasova, R. Valentini, R. Wang, G. van der Werf, D. Wickland, M. Williams, and C. Zehner
Biogeosciences, 11, 3547–3602, https://doi.org/10.5194/bg-11-3547-2014, https://doi.org/10.5194/bg-11-3547-2014, 2014
C. Le Quéré, G. P. Peters, R. J. Andres, R. M. Andrew, T. A. Boden, P. Ciais, P. Friedlingstein, R. A. Houghton, G. Marland, R. Moriarty, S. Sitch, P. Tans, A. Arneth, A. Arvanitis, D. C. E. Bakker, L. Bopp, J. G. Canadell, L. P. Chini, S. C. Doney, A. Harper, I. Harris, J. I. House, A. K. Jain, S. D. Jones, E. Kato, R. F. Keeling, K. Klein Goldewijk, A. Körtzinger, C. Koven, N. Lefèvre, F. Maignan, A. Omar, T. Ono, G.-H. Park, B. Pfeil, B. Poulter, M. R. Raupach, P. Regnier, C. Rödenbeck, S. Saito, J. Schwinger, J. Segschneider, B. D. Stocker, T. Takahashi, B. Tilbrook, S. van Heuven, N. Viovy, R. Wanninkhof, A. Wiltshire, and S. Zaehle
Earth Syst. Sci. Data, 6, 235–263, https://doi.org/10.5194/essd-6-235-2014, https://doi.org/10.5194/essd-6-235-2014, 2014
C. Le Quéré, R. J. Andres, T. Boden, T. Conway, R. A. Houghton, J. I. House, G. Marland, G. P. Peters, G. R. van der Werf, A. Ahlström, R. M. Andrew, L. Bopp, J. G. Canadell, P. Ciais, S. C. Doney, C. Enright, P. Friedlingstein, C. Huntingford, A. K. Jain, C. Jourdain, E. Kato, R. F. Keeling, K. Klein Goldewijk, S. Levis, P. Levy, M. Lomas, B. Poulter, M. R. Raupach, J. Schwinger, S. Sitch, B. D. Stocker, N. Viovy, S. Zaehle, and N. Zeng
Earth Syst. Sci. Data, 5, 165–185, https://doi.org/10.5194/essd-5-165-2013, https://doi.org/10.5194/essd-5-165-2013, 2013
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Meteorological, snow and soil data, CO2, water and energy fluxes from a low-Arctic valley of Northern Quebec
Systematically tracking the hourly progression of large wildfires using GOES satellite observations
Air pollution emission inventory using national high-resolution spatial parameters for the Nordic countries and analysis of PM2.5 spatial distribution for road transport and machinery and off-road sectors
A quality-assured dataset of nine radiation components observed at the Shangdianzi regional GAW station in China (2013–2022)
GloCAB: global cropland burned area from mid-2002 to 2020
CoCO2-MOSAIC 1.0: a global mosaic of regional, gridded, fossil, and biofuel CO2 emission inventories
A global catalogue of CO2 emissions and co-emitted species from power plants, including high-resolution vertical and temporal profiles
Greenhouse gas emissions and their trends over the last 3 decades across Africa
A coarse pixel-scale ground “truth” dataset based on global in situ site measurements to support validation and bias correction of satellite surface albedo products
Temporal and spatial mapping of theoretical biomass potential across the European Union
Global Carbon Budget 2023
Enhanced dataset of global marine isoprene emissions from biogenic and photochemical processes for the period 2001–2020
Multi-decadal trends and variability in burned area from the fifth version of the Global Fire Emissions Database (GFED5)
Spatiotemporally resolved emissions and concentrations of styrene, benzene, toluene, ethylbenzene, and xylenes (SBTEX) in the US Gulf region
High-resolution emission inventory of full-volatility organic compounds from cooking in China during 2015–2021
Global carbon uptake of cement carbonation accounts 1930–2021
A dense station-based, long-term and high-accuracy dataset of daily surface solar radiation in China
The consolidated European synthesis of CO2 emissions and removals for the European Union and United Kingdom: 1990–2020
Developing a spatially explicit global oil and gas infrastructure database for characterizing methane emission sources at high resolution
Decadal growth in emission load of major air pollutants in Delhi
Improved catalog of NOx point source emissions (version 2)
Die Hu, Yuan Wang, Han Jing, Linwei Yue, Qiang Zhang, Lei Fan, Qiangqiang Yuan, Huanfeng Shen, and Liangpei Zhang
Earth Syst. Sci. Data, 17, 2849–2872, https://doi.org/10.5194/essd-17-2849-2025, https://doi.org/10.5194/essd-17-2849-2025, 2025
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Existing L-band vegetation optical depth (L-VOD) products suffer from data gaps and coarse resolution of historical data. Therefore, it is necessary to integrate multi-temporal and multisource L-VOD products. Our study begins with the reconstruction of missing data and then develops a spatiotemporal fusion model to generate global daily seamless 9 km L-VOD products from 2010 to 2021, which are crucial for understanding the global carbon cycle.
Piers M. Forster, Chris Smith, Tristram Walsh, William F. Lamb, Robin Lamboll, Christophe Cassou, Mathias Hauser, Zeke Hausfather, June-Yi Lee, Matthew D. Palmer, Karina von Schuckmann, Aimée B. A. Slangen, Sophie Szopa, Blair Trewin, Jeongeun Yun, Nathan P. Gillett, Stuart Jenkins, H. Damon Matthews, Krishnan Raghavan, Aurélien Ribes, Joeri Rogelj, Debbie Rosen, Xuebin Zhang, Myles Allen, Lara Aleluia Reis, Robbie M. Andrew, Richard A. Betts, Alex Borger, Jiddu A. Broersma, Samantha N. Burgess, Lijing Cheng, Pierre Friedlingstein, Catia M. Domingues, Marco Gambarini, Thomas Gasser, Johannes Gütschow, Masayoshi Ishii, Christopher Kadow, John Kennedy, Rachel E. Killick, Paul B. Krummel, Aurélien Liné, Didier P. Monselesan, Colin Morice, Jens Mühle, Vaishali Naik, Glen P. Peters, Anna Pirani, Julia Pongratz, Jan C. Minx, Matthew Rigby, Robert Rohde, Abhishek Savita, Sonia I. Seneviratne, Peter Thorne, Christopher Wells, Luke M. Western, Guido R. van der Werf, Susan E. Wijffels, Valérie Masson-Delmotte, and Panmao Zhai
Earth Syst. Sci. Data, 17, 2641–2680, https://doi.org/10.5194/essd-17-2641-2025, https://doi.org/10.5194/essd-17-2641-2025, 2025
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In a rapidly changing climate, evidence-based decision-making benefits from up-to-date and timely information. Here we compile monitoring datasets to track real-world changes over time. To make our work relevant to policymakers, we follow methods from the Intergovernmental Panel on Climate Change (IPCC). Human activities are increasing the Earth's energy imbalance and driving faster sea-level rise compared to the IPCC assessment.
Jianlei Lang, Zekang Yang, Ying Zhou, Chaoyu Wen, and Xiaoqing Cheng
Earth Syst. Sci. Data, 17, 2489–2506, https://doi.org/10.5194/essd-17-2489-2025, https://doi.org/10.5194/essd-17-2489-2025, 2025
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This study established a four-dimensional (hourly; 0.03° × 0.03° × 34 height layers) aircraft emission inventory dataset in the landing-and-takeoff cycle for China during 2019–2023 considering actual running time and flight trajectory. The dataset reflects unique horizontal and height spatial characteristics and hourly temporal variations of aircraft emissions and the impact of COVID-19 on these emissions, providing essential information for environmental analysis and policy decisions.
Brittany Engle, Ivan Bratoev, Morgan A. Crowley, Yanan Zhu, and Cornelius Senf
Earth Syst. Sci. Data, 17, 2249–2276, https://doi.org/10.5194/essd-17-2249-2025, https://doi.org/10.5194/essd-17-2249-2025, 2025
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The pan-boreal lightning-ignited wildfire (BoLtFire) dataset spans the entire boreal forest from 2012 to 2022, focusing on fires of at least 200 ha. Developed using a new methodology to match lightning to wildfires in the boreal region, it includes 6902 fires – 4201 in Eurasia and 2701 in North America. BoLtFire provides new opportunities to model the ignition and spread dynamics of boreal wildfires and offers deeper insights into lightning-driven fire activity globally.
Le Niu, Songbin Wu, Robbie M. Andrew, Zi Shao, Jiaoyue Wang, and Fengming Xi
Earth Syst. Sci. Data, 17, 2231–2247, https://doi.org/10.5194/essd-17-2231-2025, https://doi.org/10.5194/essd-17-2231-2025, 2025
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This study provides an accurate bottom-up quantification of cement carbonation sinks at national and global levels. It shows that the global CO2 uptake by cement materials increased from 7.74 Mt yr-1 in 1928 to 0.84 Gt yr-1 in 2023; for 2024, this value is projected to be 0.86 Gt yr-1. The accumulated CO2 uptake offsets about 46 % of cement process emissions. Dominance with respect to cement carbon uptake has shifted from the USA, Japan, and some European countries to emerging economies such as China and India.
Zhanhao Zhang, Shibo Fang, and Jiahao Han
Earth Syst. Sci. Data, 17, 1427–1439, https://doi.org/10.5194/essd-17-1427-2025, https://doi.org/10.5194/essd-17-1427-2025, 2025
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We generate a daily sunshine duration dataset in China at a spatial resolution of 5 km using Himawari AHI data from 2016 to 2023 fitted with an Ångström–Prescott model at different days of year (DOYs). These high-resolution sunshine duration data provide important support for accurate radiation resource assessments in China.
Zeqi Li, Bin Zhao, Shengyue Li, Zhezhe Shi, Dejia Yin, Qingru Wu, Fenfen Zhang, Xiao Yun, Guanghan Huang, Yun Zhu, and Shuxiao Wang
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-104, https://doi.org/10.5194/essd-2025-104, 2025
Revised manuscript accepted for ESSD
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This study uses an ensemble machine learning model to predict long-term, high-resolution cooking activity data, establishing China’s first county-level cooking emission inventory spanning 1990–2021. It covers key pollutants such as polycyclic aromatic hydrocarbons. It reveals emissions’ long-term spatiotemporal trends and driving factors, such as population migration and economic growth, offering efficient control strategies. This dataset is crucial for air pollution and health impact studies.
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
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This study reconciles national greenhouse gas (GHG) inventories with updated atmospheric inversion results to evaluate discrepancies for three principal GHG fluxes at the national level. Compared to our previous study, new satellite-based CO2 inversions were included and an updated mask of managed lands was used, improving agreement for Brazil and Canada. The proposed methodology can be regularly applied as a check to assess the gap between top-down inversions and bottom-up inventories.
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
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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.
Ruben Prütz, Sabine Fuss, and Joeri Rogelj
Earth Syst. Sci. Data, 17, 221–231, https://doi.org/10.5194/essd-17-221-2025, https://doi.org/10.5194/essd-17-221-2025, 2025
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The AR6 Scenarios Database lacks data on carbon dioxide removal (CDR) via land sinks for many pathways, hindering secondary scenario analyses. We tested and compared regression models, identifying k-nearest neighbors regression as most effective to predict missing CDR data. We provide an imputation dataset for incomplete global scenarios (n = 404) and for regional scenario variants (n = 2358) and discuss the caveats of our study, its use cases, and how our dataset compares to other approaches.
Christian Asker, Eef van Dongen, and Olivier Tasse
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-462, https://doi.org/10.5194/essd-2024-462, 2025
Revised manuscript accepted for ESSD
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Air pollution adversely affects health, ecosystems and infrastructure. In this work we have developed a methodology and created a dataset for describing air pollution sources for heating of individual houses for the Western Balkan region. The dataset has high spatial resolution and can help understand the air pollution situation in the region.
Kai Qin, Hongrui Gao, Xuancen Liu, Qin He, Pravash Tiwari, and Jason Blake Cohen
Earth Syst. Sci. Data, 16, 5287–5310, https://doi.org/10.5194/essd-16-5287-2024, https://doi.org/10.5194/essd-16-5287-2024, 2024
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Satellites have brought new opportunities for monitoring atmospheric NO2, although the results are limited by clouds and other factors, resulting in missing data. This work proposes a new process to obtain reliable data products with high coverage by reconstructing the raw data from multiple satellites. The results are validated in terms of traditional methods as well as variance maximization and demonstrate a good ability to reproduce known polluted and clean areas around the world.
Anthony Rey-Pommier, Alexandre Héraud, Frédéric Chevallier, Philippe Ciais, Theodoros Christoudias, Jonilda Kushta, and Jean Sciare
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-410, https://doi.org/10.5194/essd-2024-410, 2024
Revised manuscript accepted for ESSD
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In this study, we estimate emissions of nitrogen oxides (NOx) in 2022 at high-resolution at the global scale, using satellite observations. We provide maps of the emissions and identify several types of sources. Our results are similar to the EDGAR emission inventory. However, differences are found in countries with lower observation densities and lower emissions.
Pascal Simon, Martin Otto Paul Ramacher, Stefan Hagemann, Volker Matthias, Hanna Joerss, and Johannes Bieser
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-236, https://doi.org/10.5194/essd-2024-236, 2024
Revised manuscript accepted for ESSD
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Per- and Polyfluorinated Alkyl Substances (PFAS) constitute a group of often toxic, persistent, and bioaccumulative substances. We constructed a global Emissions model and inventory based on multiple datasets for 23 widely used PFAS. The model computes temporally and spatially resolved model ready emissions distinguishing between emissions to air and emissions to water covering the time span from 1950 up until 2020 on an annual basis to be used for chemistry transport modelling.
Astrid Lampert, Rudolf Hankers, Thomas Feuerle, Thomas Rausch, Matthias Cremer, Maik Angermann, Mark Bitter, Jonas Füllgraf, Helmut Schulz, Ulf Bestmann, and Konrad B. Bärfuss
Earth Syst. Sci. Data, 16, 4777–4792, https://doi.org/10.5194/essd-16-4777-2024, https://doi.org/10.5194/essd-16-4777-2024, 2024
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We conducted flights above the North Sea and investigated changes in the wind field. The research aircraft measured wind speed, wind direction, temperature, humidity and sea surface at high resolution. Wind parks reduce the wind speed, and the data help to determine how long it takes for the wind speed to recover. The coast also plays an important role, and the wind speed varies with distance from the coast. The results help in wind park planning and better estimating the energy yield.
Liu Yan, Qiang Zhang, Bo Zheng, and Kebin He
Earth Syst. Sci. Data, 16, 4497–4509, https://doi.org/10.5194/essd-16-4497-2024, https://doi.org/10.5194/essd-16-4497-2024, 2024
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A new database of fuel-, vehicle-type-, and age-specific CO2 emissions from global on-road vehicles from 1970 to 2020 is developed with the fleet turnover model built in this study. Based on this database, the evolution of the global vehicle stock over 50 years is analyzed, the dominant emission contributors by vehicle and fuel type are identified, and the age distribution of on-road CO2 emissions is characterized further.
Ana Maria Roxana Petrescu, Glen P. Peters, Richard Engelen, Sander Houweling, Dominik Brunner, Aki Tsuruta, Bradley Matthews, Prabir K. Patra, Dmitry Belikov, Rona L. Thompson, Lena Höglund-Isaksson, Wenxin Zhang, Arjo J. Segers, Giuseppe Etiope, Giancarlo Ciotoli, Philippe Peylin, Frédéric Chevallier, Tuula Aalto, Robbie M. Andrew, David Bastviken, Antoine Berchet, Grégoire Broquet, Giulia Conchedda, Stijn N. C. Dellaert, Hugo Denier van der Gon, Johannes Gütschow, Jean-Matthieu Haussaire, Ronny Lauerwald, Tiina Markkanen, Jacob C. A. van Peet, Isabelle Pison, Pierre Regnier, Espen Solum, Marko Scholze, Maria Tenkanen, Francesco N. Tubiello, Guido R. van der Werf, and John R. Worden
Earth Syst. Sci. Data, 16, 4325–4350, https://doi.org/10.5194/essd-16-4325-2024, https://doi.org/10.5194/essd-16-4325-2024, 2024
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This study provides an overview of data availability from observation- and inventory-based CH4 emission estimates. It systematically compares them and provides recommendations for robust comparisons, aiming to steadily engage more parties in using observational methods to complement their UNFCCC submissions. Anticipating improvements in atmospheric modelling and observations, future developments need to resolve knowledge gaps in both approaches and to better quantify remaining uncertainty.
Mark Omara, Anthony Himmelberger, Katlyn MacKay, James P. Williams, Joshua Benmergui, Maryann Sargent, Steven C. Wofsy, and Ritesh Gautam
Earth Syst. Sci. Data, 16, 3973–3991, https://doi.org/10.5194/essd-16-3973-2024, https://doi.org/10.5194/essd-16-3973-2024, 2024
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We review, analyze, and synthesize previous peer-reviewed measurement-based data on facility-level oil and gas methane emissions and use these data to develop a high-resolution spatially explicit inventory of US basin-level and national methane emissions. This work provides an improved assessment of national methane emissions relative to government inventories in support of accurate and comprehensive methane emissions assessment, attribution, and mitigation.
Matthew W. Jones, Douglas I. Kelley, Chantelle A. Burton, Francesca Di Giuseppe, Maria Lucia F. Barbosa, Esther Brambleby, Andrew J. Hartley, Anna Lombardi, Guilherme Mataveli, Joe R. McNorton, Fiona R. Spuler, Jakob B. Wessel, John T. Abatzoglou, Liana O. Anderson, Niels Andela, Sally Archibald, Dolors Armenteras, Eleanor Burke, Rachel Carmenta, Emilio Chuvieco, Hamish Clarke, Stefan H. Doerr, Paulo M. Fernandes, Louis Giglio, Douglas S. Hamilton, Stijn Hantson, Sarah Harris, Piyush Jain, Crystal A. Kolden, Tiina Kurvits, Seppe Lampe, Sarah Meier, Stacey New, Mark Parrington, Morgane M. G. Perron, Yuquan Qu, Natasha S. Ribeiro, Bambang H. Saharjo, Jesus San-Miguel-Ayanz, Jacquelyn K. Shuman, Veerachai Tanpipat, Guido R. van der Werf, Sander Veraverbeke, and Gavriil Xanthopoulos
Earth Syst. Sci. Data, 16, 3601–3685, https://doi.org/10.5194/essd-16-3601-2024, https://doi.org/10.5194/essd-16-3601-2024, 2024
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This inaugural State of Wildfires report catalogues extreme fires of the 2023–2024 fire season. For key events, we analyse their predictability and drivers and attribute them to climate change and land use. We provide a seasonal outlook and decadal projections. Key anomalies occurred in Canada, Greece, and western Amazonia, with other high-impact events catalogued worldwide. Climate change significantly increased the likelihood of extreme fires, and mitigation is required to lessen future risk.
Yang Liu, Jie Chen, Yusheng Shi, Wei Zheng, Tianchan Shan, and Gang Wang
Earth Syst. Sci. Data, 16, 3495–3515, https://doi.org/10.5194/essd-16-3495-2024, https://doi.org/10.5194/essd-16-3495-2024, 2024
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Open biomass burning has a significant impact on regional and global air quality. To enhance the quantification of global emissions from open biomass burning, we have developed the Global Emissions Inventory from Open Biomass Burning (GEIOBB) dataset, which provides a global daily-scale database at 1 km resolution of multiple pollutant emissions. This database aids global-scale environmental analysis of biomass burning.
Yuying Cui, Qingru Wu, Shuxiao Wang, Kaiyun Liu, Shengyue Li, Zhezhe Shi, Daiwei Ouyang, Zhongyan Li, Qinqin Chen, Changwei Lü, Fei Xie, Yi Tang, Yan Wang, and Jiming Hao
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-252, https://doi.org/10.5194/essd-2024-252, 2024
Revised manuscript accepted for ESSD
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A comprehensive emission inventory has been developed at a resolution of 0.25°×0.3125° for total mercury (HgT) and each mercury species, namely gaseous elemental mercury (Hg0), gaseous oxidized mercury (HgII), and particulate-bound mercury (HgP). The inventory stems from the Point-source Integrated China Atmospheric Mercury Emission Model, ensuring both temporal and spatial coherence.
Chuanlong Zhou, Biqing Zhu, Antoine Halff, Steven J. Davis, Zhu Liu, Simon Bowring, Simon Ben Arous, and Philippe Ciais
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-173, https://doi.org/10.5194/essd-2024-173, 2024
Revised manuscript accepted for ESSD
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After Russia's 2022 invasion of Ukraine, Europe's energy dynamics shifted significantly. Our study introduces updated datasets tracking changes in natural gas supply, usage, and transmission within the EU27&UK. We discovered that Europe adapted to losing Russian gas by increasing LNG imports and shifting to renewables. Our insights could shape future energy policies and climate research.
Kang He, Xinyi Shen, and Emmanouil N. Anagnostou
Earth Syst. Sci. Data, 16, 3061–3081, https://doi.org/10.5194/essd-16-3061-2024, https://doi.org/10.5194/essd-16-3061-2024, 2024
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Forest fire risk is expected to increase as fire weather and drought conditions intensify. To improve quantification of the intensity and extent of forest fire damage, we have developed a global forest burn severity (GFBS) database that provides burn severity spectral indices (dNBR and RdNBR) at a 30 m spatial resolution. This database could be more reliable than prior sources of information for future studies of forest burn severity on the global scale in a computationally cost-effective way.
Nana Wu, Guannan Geng, Ruochong Xu, Shigan Liu, Xiaodong Liu, Qinren Shi, Ying Zhou, Yu Zhao, Huan Liu, Yu Song, Junyu Zheng, Qiang Zhang, and Kebin He
Earth Syst. Sci. Data, 16, 2893–2915, https://doi.org/10.5194/essd-16-2893-2024, https://doi.org/10.5194/essd-16-2893-2024, 2024
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The commonly used method for developing large-scale air pollutant emission datasets for China faces challenges due to limited availability of detailed parameter information. In this study, we develop an efficient integrated framework to gather such information by harmonizing seven heterogeneous inventories from five research institutions. Emission characterizations are analyzed and validated, demonstrating that the dataset provides more accurate emission magnitudes and spatiotemporal patterns.
Zhe Jin, Xiangjun Tian, Yilong Wang, Hongqin Zhang, Min Zhao, Tao Wang, Jinzhi Ding, and Shilong Piao
Earth Syst. Sci. Data, 16, 2857–2876, https://doi.org/10.5194/essd-16-2857-2024, https://doi.org/10.5194/essd-16-2857-2024, 2024
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An accurate estimate of spatial distribution and temporal evolution of CO2 fluxes is a critical foundation for providing information regarding global carbon cycle and climate mitigation. Here, we present a global carbon flux dataset for 2015–2022, derived by assimilating satellite CO2 observations into the GONGGA inversion system. This dataset will help improve the broader understanding of global carbon cycle dynamics and their response to climate change.
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).
Simon Schulte, Arthur Jakobs, and Stefan Pauliuk
Earth Syst. Sci. Data, 16, 2669–2700, https://doi.org/10.5194/essd-16-2669-2024, https://doi.org/10.5194/essd-16-2669-2024, 2024
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Greenhouse gas (GHG) emission accounts record emissions according to the economic boundary of a country, irrespective of whether they occur within national borders or not. In this study, we explore the accuracy of those GHG emission accounts. We find that the accuracy varies significantly depending on the country and economic sector. For example, small countries with extensive aviation or shipping activities show a high degree of uncertainty in their GHG emission accounts.
Leonardo Hoinaski, Robson Will, and Camilo Bastos Ribeiro
Earth Syst. Sci. Data, 16, 2385–2405, https://doi.org/10.5194/essd-16-2385-2024, https://doi.org/10.5194/essd-16-2385-2024, 2024
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We introduce the Brazilian Atmospheric Inventories (BRAIN), the first comprehensive database for air quality studies in Brazil. The database encompasses hourly datasets of meteorology, emission sources, and ambient concentrations of multiple air pollutants covering the Brazilian territory. It combines local inventories, consolidated datasets, and internationally recommended models to provide essential data for developing air pollution control policies, even in data-scarce areas.
Kanishka B. Narayan, Brian C. O'Neill, Stephanie Waldhoff, and Claudia Tebaldi
Earth Syst. Sci. Data, 16, 2333–2349, https://doi.org/10.5194/essd-16-2333-2024, https://doi.org/10.5194/essd-16-2333-2024, 2024
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Here, we present a consistent dataset of income distributions across 190 countries from 1958 to 2015 measured in terms of net income. We complement the observed values in this dataset with values imputed from a summary measure of the income distribution, specifically the Gini coefficient. We also present another version of this dataset aggregated from the country level to 32 geographical regions.
Florent Domine, Denis Sarrazin, Daniel F. Nadeau, Georg Lackner, and Maria Belke-Brea
Earth Syst. Sci. Data, 16, 1523–1541, https://doi.org/10.5194/essd-16-1523-2024, https://doi.org/10.5194/essd-16-1523-2024, 2024
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The forest–tundra ecotone is the transition region between the boreal forest and Arctic tundra. It spans over 13 000 km across the Arctic and is evolving rapidly because of climate change. We provide extensive data sets of two sites 850 m apart, one in tundra and one in forest in this ecotone for use in various models. Data include meteorological and flux data and unique snow and soil physics data.
Tianjia Liu, James T. Randerson, Yang Chen, Douglas C. Morton, Elizabeth B. Wiggins, Padhraic Smyth, Efi Foufoula-Georgiou, Roy Nadler, and Omer Nevo
Earth Syst. Sci. Data, 16, 1395–1424, https://doi.org/10.5194/essd-16-1395-2024, https://doi.org/10.5194/essd-16-1395-2024, 2024
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To improve our understanding of extreme wildfire behavior, we use geostationary satellite data to develop the GOFER algorithm and track the hourly fire progression of large wildfires. GOFER fills a key temporal gap present in other fire tracking products that rely on low-Earth-orbit imagery and reveals considerable variability in fire spread rates on diurnal timescales. We create a product of hourly fire perimeters, active-fire lines, and fire spread rates for 28 fires in California.
Ville-Veikko Paunu, Niko Karvosenoja, David Segersson, Susana López-Aparicio, Ole-Kenneth Nielsen, Marlene Schmidt Plejdrup, Throstur Thorsteinsson, Dam Thanh Vo, Jeroen Kuenen, Hugo Denier van der Gon, Jukka-Pekka Jalkanen, Jørgen Brandt, and Camilla Geels
Earth Syst. Sci. Data, 16, 1453–1474, https://doi.org/10.5194/essd-16-1453-2024, https://doi.org/10.5194/essd-16-1453-2024, 2024
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Air pollution is an important cause of adverse health effects, even in Nordic countries. To assess their health impacts, emission inventories with high spatial resolution are needed. We studied how national data and methods for the spatial distribution of the emissions compare to a European level inventory. For road transport the methods are well established, but for machinery and off-road emissions the current recommendations for the spatial distribution of these emissions should be improved.
Weijun Quan, Zhenfa Wang, Lin Qiao, Xiangdong Zheng, Junli Jin, Yinruo Li, Xiaomei Yin, Zhiqiang Ma, and Martin Wild
Earth Syst. Sci. Data, 16, 961–983, https://doi.org/10.5194/essd-16-961-2024, https://doi.org/10.5194/essd-16-961-2024, 2024
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Radiation components play important roles in various fields such as the Earth’s surface radiation budget, ecosystem productivity, and human health. In this study, a dataset consisting of quality-assured daily data of nine radiation components is presented based on the in situ measurements at the Shangdianzi regional GAW station in China during 2013–2022. The dataset can be applied in the validation of satellite products and numerical models and investigation of atmospheric radiation.
Joanne V. Hall, Fernanda Argueta, Maria Zubkova, Yang Chen, James T. Randerson, and Louis Giglio
Earth Syst. Sci. Data, 16, 867–885, https://doi.org/10.5194/essd-16-867-2024, https://doi.org/10.5194/essd-16-867-2024, 2024
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Crop-residue burning is a widespread practice often occurring close to population centers. Its recurrent nature requires accurate mapping of the area burned – a key input into air quality models. Unlike larger fires, crop fires require a specific burned area (BA) methodology, which to date has been ignored in global BA datasets. Our global cropland-focused BA product found a significant increase in global cropland BA (81 Mha annual average) compared to the widely used MCD64A1 (32 Mha).
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.
Marc Guevara, Santiago Enciso, Carles Tena, Oriol Jorba, Stijn Dellaert, Hugo Denier van der Gon, and Carlos Pérez García-Pando
Earth Syst. Sci. Data, 16, 337–373, https://doi.org/10.5194/essd-16-337-2024, https://doi.org/10.5194/essd-16-337-2024, 2024
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A global dataset of emissions from thermal power plants was created for the year 2018. The resulting catalogue reports annual emissions of CO2 and co-emitted species (NOx, CO, SO2 and CH4) for more than 16000 individual facilities at their exact geographical locations. Information on the temporal and vertical distributions of the emissions is also provided at the facility level. The dataset is intended to support current and future satellite emission monitoring and inverse modelling efforts.
Mounia Mostefaoui, Philippe Ciais, Matthew J. McGrath, Philippe Peylin, Prabir K. Patra, and Yolandi Ernst
Earth Syst. Sci. Data, 16, 245–275, https://doi.org/10.5194/essd-16-245-2024, https://doi.org/10.5194/essd-16-245-2024, 2024
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Our aim is to assess African anthropogenic greenhouse gas emissions and removals by using different data products, including inventories and process-based models, and to compare their relative merits with inversion data coming from satellites. We show a good match among the various estimates in terms of overall trends at a regional level and on a decadal basis, but large differences exist even among similar data types, which is a limit to the possibility of verification of country-reported data.
Fei Pan, Xiaodan Wu, Qicheng Zeng, Rongqi Tang, Jingping Wang, Xingwen Lin, Dongqin You, Jianguang Wen, and Qing Xiao
Earth Syst. Sci. Data, 16, 161–176, https://doi.org/10.5194/essd-16-161-2024, https://doi.org/10.5194/essd-16-161-2024, 2024
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To effectively tackle the challenges posed by spatial-scale differences and spatial heterogeneity, this paper presents a distinctive coarse pixel-scale ground “truth" dataset by upscaling sparsely distributed in situ measurements. This dataset is a valuable resource for validating and correcting global surface albedo products, enhancing reference data accuracy by 6.04 %. Remarkably, it substantially enhances 17.09 % in regions with strong spatial heterogeneity.
Susann Günther, Tom Karras, Friederike Naegeli de Torres, Sebastian Semella, and Daniela Thrän
Earth Syst. Sci. Data, 16, 59–74, https://doi.org/10.5194/essd-16-59-2024, https://doi.org/10.5194/essd-16-59-2024, 2024
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The following study was undertaken to provide a continuous open access dataset for 2010-2020 from country to local level. In order to understand the reliability of the final dataset and to enable further use, the modelled data were validated against statistics, which is a novelty in this field. The dataset has been shown to be in good agreement with the statistical data. Biomass potentials modelled in this study are published in an open access database.
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
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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.
Lehui Cui, Yunting Xiao, Wei Hu, Lei Song, Yujue Wang, Chao Zhang, Pingqing Fu, and Jialei Zhu
Earth Syst. Sci. Data, 15, 5403–5425, https://doi.org/10.5194/essd-15-5403-2023, https://doi.org/10.5194/essd-15-5403-2023, 2023
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Isoprene is a crucial non-methane biogenic volatile organic compound with the largest global emissions, which has high chemical reactivity and serves as the primary source of natural secondary organic aerosols. This study built a module to present a 20-year global hourly dataset of marine phytoplankton-generated biological and photochemistry-generated isoprene emissions in the sea microlayers based on the latest advancements in biological, physical, and chemical processes.
Yang Chen, Joanne Hall, Dave van Wees, Niels Andela, Stijn Hantson, Louis Giglio, Guido R. van der Werf, Douglas C. Morton, and James T. Randerson
Earth Syst. Sci. Data, 15, 5227–5259, https://doi.org/10.5194/essd-15-5227-2023, https://doi.org/10.5194/essd-15-5227-2023, 2023
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Using multiple sets of remotely sensed data, we created a dataset of monthly global burned area from 1997 to 2020. The estimated annual global burned area is 774 million hectares, significantly higher than previous estimates. Burned area declined by 1.21% per year due to extensive fire loss in savanna, grassland, and cropland ecosystems. This study enhances our understanding of the impact of fire on the carbon cycle and climate system, and may improve the predictions of future fire changes.
Chi-Tsan Wang, Bok H. Baek, William Vizuete, Lawrence S. Engel, Jia Xing, Jaime Green, Marc Serre, Richard Strott, Jared Bowden, and Jung-Hun Woo
Earth Syst. Sci. Data, 15, 5261–5279, https://doi.org/10.5194/essd-15-5261-2023, https://doi.org/10.5194/essd-15-5261-2023, 2023
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Hazardous air pollutant (HAP) human exposure studies usually rely on local measurements or dispersion model methods, but those methods are limited under spatial and temporal conditions. We processed the US EPA emission data to simulate the hourly HAP emission patterns and applied the chemical transport model to simulate the HAP concentrations. The modeled HAP results exhibit good agreement (R is 0.75 and NMB is −5.6 %) with observational data.
Zeqi Li, Shuxiao Wang, Shengyue Li, Xiaochun Wang, Guanghan Huang, Xing Chang, Lyuyin Huang, Chengrui Liang, Yun Zhu, Haotian Zheng, Qian Song, Qingru Wu, Fenfen Zhang, and Bin Zhao
Earth Syst. Sci. Data, 15, 5017–5037, https://doi.org/10.5194/essd-15-5017-2023, https://doi.org/10.5194/essd-15-5017-2023, 2023
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This study developed the first full-volatility organic emission inventory for cooking sources in China, presenting high-resolution cooking emissions during 2015–2021. It identified the key subsectors and hotspots of cooking emissions, analyzed emission trends and drivers, and proposed future control strategies. The dataset is valuable for accurately simulating organic aerosol formation and evolution and for understanding the impact of organic emissions on air pollution and climate change.
Zi Huang, Jiaoyue Wang, Longfei Bing, Yijiao Qiu, Rui Guo, Ying Yu, Mingjing Ma, Le Niu, Dan Tong, Robbie M. Andrew, Pierre Friedlingstein, Josep G. Canadell, Fengming Xi, and Zhu Liu
Earth Syst. Sci. Data, 15, 4947–4958, https://doi.org/10.5194/essd-15-4947-2023, https://doi.org/10.5194/essd-15-4947-2023, 2023
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This is about global and regional cement process carbon emissions and CO2 uptake calculations from 1930 to 2019. The global cement production is rising to 4.4 Gt, causing processing carbon emission of 1.81 Gt (95% CI: 1.75–1.88 Gt CO2) in 2021. Plus, in 2021, cement’s carbon accumulated uptake (22.9 Gt, 95% CI: 19.6–22.6 Gt CO2) has offset 55.2% of cement process CO2 emissions (41.5 Gt, 95% CI: 38.7–47.1 Gt CO2) since 1930.
Wenjun Tang, Junmei He, Jingwen Qi, and Kun Yang
Earth Syst. Sci. Data, 15, 4537–4551, https://doi.org/10.5194/essd-15-4537-2023, https://doi.org/10.5194/essd-15-4537-2023, 2023
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In this study, we have developed a dense station-based, long-term dataset of daily surface solar radiation in China with high accuracy. The dataset consists of estimates of global, direct and diffuse radiation at 2473 meteorological stations from the 1950s to 2021. Validation indicates that our station-based radiation dataset clearly outperforms the satellite-based radiation products. Our dataset will contribute to climate change research and solar energy applications in the future.
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.
Mark Omara, Ritesh Gautam, Madeleine A. O'Brien, Anthony Himmelberger, Alex Franco, Kelsey Meisenhelder, Grace Hauser, David R. Lyon, Apisada Chulakadabba, Christopher Chan Miller, Jonathan Franklin, Steven C. Wofsy, and Steven P. Hamburg
Earth Syst. Sci. Data, 15, 3761–3790, https://doi.org/10.5194/essd-15-3761-2023, https://doi.org/10.5194/essd-15-3761-2023, 2023
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We acquire, integrate, and analyze ~ 6 million geospatial oil and gas infrastructure data records based on information available in the public domain and develop an open-access global database including all the major oil and gas facility types that are important sources of methane emissions. This work helps fulfill a crucial geospatial data need, in support of the assessment, attribution, and mitigation of global oil and gas methane emissions at high resolution.
Saroj Kumar Sahu, Poonam Mangaraj, and Gufran Beig
Earth Syst. Sci. Data, 15, 3183–3202, https://doi.org/10.5194/essd-15-3183-2023, https://doi.org/10.5194/essd-15-3183-2023, 2023
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The developed emission inventory identifies all the potential anthropogenic sources active in the Delhi NCR. The decadal change (2010–2020) and the changing policies have also been illustrated to observe the modulation in the sectorial emission trend. Emission hotspots with possible source-specific mitigation strategies have also been highlighted to improve the air quality of the Delhi NCR. The provided dataset is a vital tool for air quality and chemical transport modeling studies.
Steffen Beirle, Christian Borger, Adrian Jost, and Thomas Wagner
Earth Syst. Sci. Data, 15, 3051–3073, https://doi.org/10.5194/essd-15-3051-2023, https://doi.org/10.5194/essd-15-3051-2023, 2023
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We present a catalog of nitrogen oxide emissions from point sources (like power plants or metal smelters) based on satellite observations of NO2 combined with meteorological wind fields.
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