Articles | Volume 14, issue 5
https://doi.org/10.5194/esd-14-1039-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/esd-14-1039-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Dynamic savanna burning emission factors based on satellite data using a machine learning approach
Department of Earth Sciences, Faculty of Science, Vrije Universiteit
Amsterdam, Amsterdam, the Netherlands
Tom Eames
Department of Earth Sciences, Faculty of Science, Vrije Universiteit
Amsterdam, Amsterdam, the Netherlands
Jeremy Russell-Smith
Darwin Centre for Bushfire Research, Charles Darwin University,
Darwin, 0909 Northern Territory, Australia
International Savanna Fire Management Initiative (ISFMI), Level 4, 346 Kent Street, Sydney, 2000 New South Wales, Australia
Cameron Yates
Darwin Centre for Bushfire Research, Charles Darwin University,
Darwin, 0909 Northern Territory, Australia
International Savanna Fire Management Initiative (ISFMI), Level 4, 346 Kent Street, Sydney, 2000 New South Wales, Australia
Robin Beatty
International Savanna Fire Management Initiative (ISFMI), Level 4, 346 Kent Street, Sydney, 2000 New South Wales, Australia
321 Fire, Praia Do Tofo, Inhambane, 1300, Mozambique
Jay Evans
Darwin Centre for Bushfire Research, Charles Darwin University,
Darwin, 0909 Northern Territory, Australia
International Savanna Fire Management Initiative (ISFMI), Level 4, 346 Kent Street, Sydney, 2000 New South Wales, Australia
Andrew Edwards
Darwin Centre for Bushfire Research, Charles Darwin University,
Darwin, 0909 Northern Territory, Australia
International Savanna Fire Management Initiative (ISFMI), Level 4, 346 Kent Street, Sydney, 2000 New South Wales, Australia
Natasha Ribeiro
Faculty of Agronomy and Forest Engineering, Eduardo Mondlane
University, Maputo, Mozambique
Martin Wooster
Environmental Monitoring and Modelling Research Group, Department of Geography, King's College London, London, UK
National Centre for Earth Observation (NERC), Leicester, UK
Tercia Strydom
South African National Parks (SANParks), Scientific Services, Skukuza, South Africa
Marcos Vinicius Giongo
Center for Environmental Monitoring and Fire Management (CEMAF), Federal
University of Tocantins, Gurupi, Brazil
Marco Assis Borges
Chico Mendes institute for Conservation of Biodiversity (ICMBio), Rio
da Conceição, Brazil
Máximo Menezes Costa
Chico Mendes institute for Conservation of Biodiversity (ICMBio), Rio
da Conceição, Brazil
Ana Carolina Sena Barradas
Chico Mendes institute for Conservation of Biodiversity (ICMBio), Rio
da Conceição, Brazil
Dave van Wees
Department of Earth Sciences, Faculty of Science, Vrije Universiteit
Amsterdam, Amsterdam, the Netherlands
Guido R. Van der Werf
Department of Earth Sciences, Faculty of Science, Vrije Universiteit
Amsterdam, Amsterdam, the Netherlands
Related authors
Roland Vernooij, Patrik Winiger, Martin Wooster, Tercia Strydom, Laurent Poulain, Ulrike Dusek, Mark Grosvenor, Gareth J. Roberts, Nick Schutgens, and Guido R. van der Werf
Atmos. Meas. Tech., 15, 4271–4294, https://doi.org/10.5194/amt-15-4271-2022, https://doi.org/10.5194/amt-15-4271-2022, 2022
Short summary
Short summary
Landscape fires are a substantial emitter of greenhouse gases and aerosols. Previous studies have indicated savanna emission factors to be highly variable. Improving fire emission estimates, and understanding future climate- and human-induced changes in fire regimes, requires in situ measurements. We present a drone-based method that enables the collection of a large amount of high-quality emission factor measurements that do not have the biases of aircraft or surface measurements.
Roland Vernooij, Ulrike Dusek, Maria Elena Popa, Peng Yao, Anupam Shaikat, Chenxi Qiu, Patrik Winiger, Carina van der Veen, Thomas Callum Eames, Natasha Ribeiro, and Guido R. van der Werf
Atmos. Chem. Phys., 22, 2871–2890, https://doi.org/10.5194/acp-22-2871-2022, https://doi.org/10.5194/acp-22-2871-2022, 2022
Short summary
Short summary
Landscape fires are a major source of greenhouse gases and aerosols, particularly in sub-tropical savannas. Stable carbon isotopes in emissions can be used to trace the contribution of C3 plants (e.g. trees or shrubs) and C4 plants (e.g. savanna grasses) to greenhouse gases and aerosols if the process is well understood. This helps us to link individual vegetation types to emissions, identify biomass burning emissions in the atmosphere, and improve the reconstruction of historic fire regimes.
Roland Vernooij, Marcos Giongo, Marco Assis Borges, Máximo Menezes Costa, Ana Carolina Sena Barradas, and Guido R. van der Werf
Biogeosciences, 18, 1375–1393, https://doi.org/10.5194/bg-18-1375-2021, https://doi.org/10.5194/bg-18-1375-2021, 2021
Short summary
Short summary
We used drones to measure greenhouse gas emission factors from fires in the Brazilian Cerrado. We compared early-dry-season management fires and late-dry-season fires to determine if fire management can be a tool for abating emissions.
Although we found some evidence of increased CO and CH4 emission factors, the seasonal effect was smaller than that found in previous studies. For N2O, the third most important greenhouse gas, we found opposite trends in grass- and shrub-dominated areas.
Elizabeth Quaye, Ben T. Johnson, James M. Haywood, Guido R. van der Werf, Roland Vernooij, Stephen A. Sitch, and Tom Eames
EGUsphere, https://doi.org/10.5194/egusphere-2025-3936, https://doi.org/10.5194/egusphere-2025-3936, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
We find aerosol optical depths in a global climate model are overestimated during extreme wildfire events if emissions are scaled up by a factor of two, typically applied to improve simulated aerosol on seasonal–annual timescales. We propose a technique where a variable scaling factor is determined by fuel consumption, improving correlation in five fire-affected areas. We explore the impact of this change on aerosol radiative effects, during extreme events and on broader space and time scales.
Douglas I. Kelley, Chantelle Burton, Francesca Di Giuseppe, Matthew W. Jones, Maria L. F. Barbosa, Esther Brambleby, Joe R. McNorton, Zhongwei Liu, Anna S. I. Bradley, Katie Blackford, Eleanor Burke, Andrew Ciavarella, Enza Di Tomaso, Jonathan Eden, Igor José M. Ferreira, Lukas Fiedler, Andrew J. Hartley, Theodore R. Keeping, Seppe Lampe, Anna Lombardi, Guilherme Mataveli, Yuquan Qu, Patrícia S. Silva, Fiona R. Spuler, Carmen B. Steinmann, Miguel Ángel Torres-Vázquez, Renata Veiga, Dave van Wees, Jakob B. Wessel, Emily Wright, Bibiana Bilbao, Mathieu Bourbonnais, Gao Cong, Carlos M. Di Bella, Kebonye Dintwe, Victoria M. Donovan, Sarah Harris, Elena A. Kukavskaya, Brigitte N’Dri, Cristina Santín, Galia Selaya, Johan Sjöström, John Abatzoglou, Niels Andela, Rachel Carmenta, Emilio Chuvieco, Louis Giglio, Douglas S. Hamilton, Stijn Hantson, Sarah Meier, Mark Parrington, Mojtaba Sadegh, Jesus San-Miguel-Ayanz, Fernando Sedano, Marco Turco, Guido R. van der Werf, Sander Veraverbeke, Liana O. Anderson, Hamish Clarke, Paulo M. Fernandes, and Crystal A. Kolden
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-483, https://doi.org/10.5194/essd-2025-483, 2025
Preprint under review for ESSD
Short summary
Short summary
The second State of Wildfires report examines extreme wildfire events from 2024 to early 2025. It analyses key regional events in Southern California, Northeast Amazonia, Pantanal-Chiquitano, and the Congo Basin, assessing their drivers, predictability, and attributing them to climate change and land use. Seasonal outlooks and decadal projections are provided. Climate change greatly increased the likelihood of these fires, and without strong mitigation, such events will become more frequent.
Zhixuan Guo, Wei Li, Philippe Ciais, Stephen Sitch, Guido R. van der Werf, Simon P. K. Bowring, Ana Bastos, Florent Mouillot, Jiaying He, Minxuan Sun, Lei Zhu, Xiaomeng Du, Nan Wang, and Xiaomeng Huang
Earth Syst. Sci. Data, 17, 3599–3618, https://doi.org/10.5194/essd-17-3599-2025, https://doi.org/10.5194/essd-17-3599-2025, 2025
Short summary
Short summary
To address the limitations of short time spans in satellite data and spatiotemporal discontinuity in site records, we reconstructed global monthly burned area maps at a 0.5° resolution for 1901–2020 using machine learning models. The global burned area is predicted at 3.46 × 106–4.58 × 106 km² per year, showing a decline from 1901 to 1978, an increase from 1978 to 2008 and a sharper decrease from 2008 to 2020. This dataset provides a benchmark for studies on fire ecology and the carbon cycle.
Tom Eames, Nick Schutgens, Eleftherios Ioannidis, Ivar R. van der Velde, Max J. van Gerrevink, Roland Vernooij, and Guido R. van der Werf
EGUsphere, https://doi.org/10.5194/egusphere-2025-3394, https://doi.org/10.5194/egusphere-2025-3394, 2025
Short summary
Short summary
Prescribed burning is used as a landscape management tool in southern African savannas. By deliberately changing the timing of fires in this region, the climate effect (radiative forcing) of a fire season can be altered. We show that by burning earlier in the dry season a small climate cooling effect can be achieved, similar to that of a 10 % reduction in global commercial aviation emissions. Local effects must be considered before implementing a fire regime shift for climate change mitigation.
Haolin Wang, William Maslanka, Paul I. Palmer, Martin J. Wooster, Haofan Wang, Fei Yao, Liang Feng, Kai Wu, Xiao Lu, and Shaojia Fan
EGUsphere, https://doi.org/10.5194/egusphere-2025-2594, https://doi.org/10.5194/egusphere-2025-2594, 2025
Short summary
Short summary
We examine the impact of diurnally varying African biomass burning (BB) emissions on tropospheric ozone using GEOS-Chem simulations with a high-resolution satellite-derived emission inventory. Compared to coarser temporal resolutions, incorporating diurnal variations leads to significant changes in surface ozone and atmospheric oxidation capacity. Our findings highlight the importance of accurately representing BB emission timing in chemical transport models to improve ozone predictions.
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
Short summary
Short summary
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.
Courtney G. Reed, Michelle L. Budny, Johan T. du Toit, Ryan Helcoski, Joshua P. Schimel, Izak P. J. Smit, Tercia Strydom, Aimee Tallian, Dave I. Thompson, Helga van Coller, Nathan P. Lemoine, and Deron E. Burkepile
Biogeosciences, 22, 1583–1596, https://doi.org/10.5194/bg-22-1583-2025, https://doi.org/10.5194/bg-22-1583-2025, 2025
Short summary
Short summary
We seek to understand the ecological legacies of elephants after death. We sampled soil and leaves at elephant carcass sites in South Africa and found that elephant carcasses release nutrients into soil, which plants take up and make available for consumption by herbivores. This research reveals a key way that elephants contribute to nutrient cycling in savannas after death. It also highlights an important process that may be lost in areas where elephant populations are in decline.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Judith Hauck, Peter Landschützer, Corinne Le Quéré, Hongmei Li, Ingrid T. Luijkx, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Almut Arneth, Vivek Arora, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Carla F. Berghoff, Henry C. Bittig, Laurent Bopp, Patricia Cadule, Katie Campbell, Matthew A. Chamberlain, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Thomas Colligan, Jeanne Decayeux, Laique M. Djeutchouang, Xinyu Dou, Carolina Duran Rojas, Kazutaka Enyo, Wiley Evans, Amanda R. Fay, Richard A. Feely, Daniel J. Ford, Adrianna Foster, Thomas Gasser, Marion Gehlen, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Jens Heinke, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Andrew R. Jacobson, Atul K. Jain, Tereza Jarníková, Annika Jersild, Fei Jiang, Zhe Jin, Etsushi Kato, Ralph F. Keeling, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Xin Lan, Siv K. Lauvset, Nathalie Lefèvre, Zhu Liu, Junjie Liu, Lei Ma, Shamil Maksyutov, Gregg Marland, Nicolas Mayot, Patrick C. McGuire, Nicolas Metzl, Natalie M. Monacci, Eric J. Morgan, Shin-Ichiro Nakaoka, Craig Neill, Yosuke Niwa, Tobias Nützel, Lea Olivier, Tsuneo Ono, Paul I. Palmer, Denis Pierrot, Zhangcai Qin, Laure Resplandy, Alizée Roobaert, Thais M. Rosan, Christian Rödenbeck, Jörg Schwinger, T. Luke Smallman, Stephen M. Smith, Reinel Sospedra-Alfonso, Tobias Steinhoff, Qing Sun, Adrienne J. Sutton, Roland Séférian, Shintaro Takao, Hiroaki Tatebe, Hanqin Tian, Bronte Tilbrook, Olivier Torres, Etienne Tourigny, Hiroyuki Tsujino, Francesco Tubiello, Guido van der Werf, Rik Wanninkhof, Xuhui Wang, Dongxu Yang, Xiaojuan Yang, Zhen Yu, Wenping Yuan, Xu Yue, Sönke Zaehle, Ning Zeng, and Jiye Zeng
Earth Syst. Sci. Data, 17, 965–1039, https://doi.org/10.5194/essd-17-965-2025, https://doi.org/10.5194/essd-17-965-2025, 2025
Short summary
Short summary
The Global Carbon Budget 2024 describes the methodology, main results, and datasets used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, land ecosystems, and the ocean over the historical period (1750–2024). These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Farrer Owsley-Brown, Martin J. Wooster, Mark J. Grosvenor, and Yanan Liu
Atmos. Meas. Tech., 17, 6247–6264, https://doi.org/10.5194/amt-17-6247-2024, https://doi.org/10.5194/amt-17-6247-2024, 2024
Short summary
Short summary
Landscape fires produce vast amounts of smoke, affecting the atmosphere locally and globally. Whether a fire is flaming or smouldering strongly impacts the rate at which smoke is produced as well as its composition. This study tested two methods to determine these combustion phases in laboratory fires and compared them to the smoke emitted. One of these methods improved estimates of smoke emission significantly. This suggests potential for improvement in global emission estimates.
Ana Maria Roxana Petrescu, Glen P. Peters, Richard Engelen, Sander Houweling, Dominik Brunner, Aki Tsuruta, Bradley Matthews, Prabir K. Patra, Dmitry Belikov, Rona L. Thompson, Lena Höglund-Isaksson, Wenxin Zhang, Arjo J. Segers, Giuseppe Etiope, Giancarlo Ciotoli, Philippe Peylin, Frédéric Chevallier, Tuula Aalto, Robbie M. Andrew, David Bastviken, Antoine Berchet, Grégoire Broquet, Giulia Conchedda, Stijn N. C. Dellaert, Hugo Denier van der Gon, Johannes Gütschow, Jean-Matthieu Haussaire, Ronny Lauerwald, Tiina Markkanen, Jacob C. A. van Peet, Isabelle Pison, Pierre Regnier, Espen Solum, Marko Scholze, Maria Tenkanen, Francesco N. Tubiello, Guido R. van der Werf, and John R. Worden
Earth Syst. Sci. Data, 16, 4325–4350, https://doi.org/10.5194/essd-16-4325-2024, https://doi.org/10.5194/essd-16-4325-2024, 2024
Short summary
Short summary
This study provides an overview of data availability from observation- and inventory-based CH4 emission estimates. It systematically compares them and provides recommendations for robust comparisons, aiming to steadily engage more parties in using observational methods to complement their UNFCCC submissions. Anticipating improvements in atmospheric modelling and observations, future developments need to resolve knowledge gaps in both approaches and to better quantify remaining uncertainty.
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
Short summary
Short summary
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.
Hanqin Tian, Naiqing Pan, Rona L. Thompson, Josep G. Canadell, Parvadha Suntharalingam, Pierre Regnier, Eric A. Davidson, Michael Prather, Philippe Ciais, Marilena Muntean, Shufen Pan, Wilfried Winiwarter, Sönke Zaehle, Feng Zhou, Robert B. Jackson, Hermann W. Bange, Sarah Berthet, Zihao Bian, Daniele Bianchi, Alexander F. Bouwman, Erik T. Buitenhuis, Geoffrey Dutton, Minpeng Hu, Akihiko Ito, Atul K. Jain, Aurich Jeltsch-Thömmes, Fortunat Joos, Sian Kou-Giesbrecht, Paul B. Krummel, Xin Lan, Angela Landolfi, Ronny Lauerwald, Ya Li, Chaoqun Lu, Taylor Maavara, Manfredi Manizza, Dylan B. Millet, Jens Mühle, Prabir K. Patra, Glen P. Peters, Xiaoyu Qin, Peter Raymond, Laure Resplandy, Judith A. Rosentreter, Hao Shi, Qing Sun, Daniele Tonina, Francesco N. Tubiello, Guido R. van der Werf, Nicolas Vuichard, Junjie Wang, Kelley C. Wells, Luke M. Western, Chris Wilson, Jia Yang, Yuanzhi Yao, Yongfa You, and Qing Zhu
Earth Syst. Sci. Data, 16, 2543–2604, https://doi.org/10.5194/essd-16-2543-2024, https://doi.org/10.5194/essd-16-2543-2024, 2024
Short summary
Short summary
Atmospheric concentrations of nitrous oxide (N2O), a greenhouse gas 273 times more potent than carbon dioxide, have increased by 25 % since the preindustrial period, with the highest observed growth rate in 2020 and 2021. This rapid growth rate has primarily been due to a 40 % increase in anthropogenic emissions since 1980. Observed atmospheric N2O concentrations in recent years have exceeded the worst-case climate scenario, underscoring the importance of reducing anthropogenic N2O emissions.
Piers M. Forster, Chris Smith, Tristram Walsh, William F. Lamb, Robin Lamboll, Bradley Hall, Mathias Hauser, Aurélien Ribes, Debbie Rosen, Nathan P. Gillett, Matthew D. Palmer, Joeri Rogelj, Karina von Schuckmann, Blair Trewin, Myles Allen, Robbie Andrew, Richard A. Betts, Alex Borger, Tim Boyer, Jiddu A. Broersma, Carlo Buontempo, Samantha Burgess, Chiara Cagnazzo, Lijing Cheng, Pierre Friedlingstein, Andrew Gettelman, Johannes Gütschow, Masayoshi Ishii, Stuart Jenkins, Xin Lan, Colin Morice, Jens Mühle, Christopher Kadow, John Kennedy, Rachel E. Killick, Paul B. Krummel, Jan C. Minx, Gunnar Myhre, Vaishali Naik, Glen P. Peters, Anna Pirani, Julia Pongratz, Carl-Friedrich Schleussner, Sonia I. Seneviratne, Sophie Szopa, Peter Thorne, Mahesh V. M. Kovilakam, Elisa Majamäki, Jukka-Pekka Jalkanen, Margreet van Marle, Rachel M. Hoesly, Robert Rohde, Dominik Schumacher, Guido van der Werf, Russell Vose, Kirsten Zickfeld, Xuebin Zhang, Valérie Masson-Delmotte, and Panmao Zhai
Earth Syst. Sci. Data, 16, 2625–2658, https://doi.org/10.5194/essd-16-2625-2024, https://doi.org/10.5194/essd-16-2625-2024, 2024
Short summary
Short summary
This paper tracks some key indicators of global warming through time, from 1850 through to the end of 2023. It is designed to give an authoritative estimate of global warming to date and its causes. We find that in 2023, global warming reached 1.3 °C and is increasing at over 0.2 °C per decade. This is caused by all-time-high greenhouse gas emissions.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Dorothee C. E. Bakker, Judith Hauck, Peter Landschützer, Corinne Le Quéré, Ingrid T. Luijkx, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Peter Anthoni, Leticia Barbero, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Bertrand Decharme, Laurent Bopp, Ida Bagus Mandhara Brasika, Patricia Cadule, Matthew A. Chamberlain, Naveen Chandra, Thi-Tuyet-Trang Chau, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Xinyu Dou, Kazutaka Enyo, Wiley Evans, Stefanie Falk, Richard A. Feely, Liang Feng, Daniel J. Ford, Thomas Gasser, Josefine Ghattas, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Jens Heinke, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Andrew R. Jacobson, Atul Jain, Tereza Jarníková, Annika Jersild, Fei Jiang, Zhe Jin, Fortunat Joos, Etsushi Kato, Ralph F. Keeling, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Arne Körtzinger, Xin Lan, Nathalie Lefèvre, Hongmei Li, Junjie Liu, Zhiqiang Liu, Lei Ma, Greg Marland, Nicolas Mayot, Patrick C. McGuire, Galen A. McKinley, Gesa Meyer, Eric J. Morgan, David R. Munro, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin M. O'Brien, Are Olsen, Abdirahman M. Omar, Tsuneo Ono, Melf Paulsen, Denis Pierrot, Katie Pocock, Benjamin Poulter, Carter M. Powis, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Thais M. Rosan, Jörg Schwinger, Roland Séférian, T. Luke Smallman, Stephen M. Smith, Reinel Sospedra-Alfonso, Qing Sun, Adrienne J. Sutton, Colm Sweeney, Shintaro Takao, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Hiroyuki Tsujino, Francesco Tubiello, Guido R. van der Werf, Erik van Ooijen, Rik Wanninkhof, Michio Watanabe, Cathy Wimart-Rousseau, Dongxu Yang, Xiaojuan Yang, Wenping Yuan, Xu Yue, Sönke Zaehle, Jiye Zeng, and Bo Zheng
Earth Syst. Sci. Data, 15, 5301–5369, https://doi.org/10.5194/essd-15-5301-2023, https://doi.org/10.5194/essd-15-5301-2023, 2023
Short summary
Short summary
The Global Carbon Budget 2023 describes the methodology, main results, and data sets used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, land ecosystems, and the ocean over the historical period (1750–2023). These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
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
Short summary
Short summary
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.
Lilian Vallet, Martin Schwartz, Philippe Ciais, Dave van Wees, Aurelien de Truchis, and Florent Mouillot
Biogeosciences, 20, 3803–3825, https://doi.org/10.5194/bg-20-3803-2023, https://doi.org/10.5194/bg-20-3803-2023, 2023
Short summary
Short summary
This study analyzes the ecological impact of the 2022 summer fire season in France by using high-resolution satellite data. The total biomass loss was 2.553 Mt, equivalent to a 17 % increase of the average natural mortality of all French forests. While Mediterranean forests had a lower biomass loss, there was a drastic increase in burned area and biomass loss over the Atlantic pine forests and temperate forests. This result revisits the distinctiveness of the 2022 fire season.
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
Short summary
Short summary
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.
Hannah M. Nguyen, Jiangping He, and Martin J. Wooster
Atmos. Chem. Phys., 23, 2089–2118, https://doi.org/10.5194/acp-23-2089-2023, https://doi.org/10.5194/acp-23-2089-2023, 2023
Short summary
Short summary
This work presents novel advances in the estimation of open biomass burning emissions via the first fully "top-down" approach to exploit satellite-derived observations of fire radiative power and carbon monoxide over Africa. We produce a 16-year record of fire-generated CO emissions and dry matter consumed per unit area for Africa and evaluate these emissions estimates through their use in an atmospheric model, whose simulation output is then compared to independent satellite observations of CO.
Dave van Wees, Guido R. van der Werf, James T. Randerson, Brendan M. Rogers, Yang Chen, Sander Veraverbeke, Louis Giglio, and Douglas C. Morton
Geosci. Model Dev., 15, 8411–8437, https://doi.org/10.5194/gmd-15-8411-2022, https://doi.org/10.5194/gmd-15-8411-2022, 2022
Short summary
Short summary
We present a global fire emission model based on the GFED model framework with a spatial resolution of 500 m. The higher resolution allowed for a more detailed representation of spatial heterogeneity in fuels and emissions. Specific modules were developed to model, for example, emissions from fire-related forest loss and belowground burning. Results from the 500 m model were compared to GFED4s, showing that global emissions were relatively similar but that spatial differences were substantial.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Luke Gregor, Judith Hauck, Corinne Le Quéré, Ingrid T. Luijkx, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Ramdane Alkama, Almut Arneth, Vivek K. Arora, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Henry C. Bittig, Laurent Bopp, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Wiley Evans, Stefanie Falk, Richard A. Feely, Thomas Gasser, Marion Gehlen, Thanos Gkritzalis, Lucas Gloege, Giacomo Grassi, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Atul K. Jain, Annika Jersild, Koji Kadono, Etsushi Kato, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Peter Landschützer, Nathalie Lefèvre, Keith Lindsay, Junjie Liu, Zhu Liu, Gregg Marland, Nicolas Mayot, Matthew J. McGrath, Nicolas Metzl, Natalie M. Monacci, David R. Munro, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin O'Brien, Tsuneo Ono, Paul I. Palmer, Naiqing Pan, Denis Pierrot, Katie Pocock, Benjamin Poulter, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Carmen Rodriguez, Thais M. Rosan, Jörg Schwinger, Roland Séférian, Jamie D. Shutler, Ingunn Skjelvan, Tobias Steinhoff, Qing Sun, Adrienne J. Sutton, Colm Sweeney, Shintaro Takao, Toste Tanhua, Pieter P. Tans, Xiangjun Tian, Hanqin Tian, Bronte Tilbrook, Hiroyuki Tsujino, Francesco Tubiello, Guido R. van der Werf, Anthony P. Walker, Rik Wanninkhof, Chris Whitehead, Anna Willstrand Wranne, Rebecca Wright, Wenping Yuan, Chao Yue, Xu Yue, Sönke Zaehle, Jiye Zeng, and Bo Zheng
Earth Syst. Sci. Data, 14, 4811–4900, https://doi.org/10.5194/essd-14-4811-2022, https://doi.org/10.5194/essd-14-4811-2022, 2022
Short summary
Short summary
The Global Carbon Budget 2022 describes the datasets and methodology used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, the land ecosystems, and the ocean. These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Qirui Zhong, Nick Schutgens, Guido van der Werf, Twan van Noije, Kostas Tsigaridis, Susanne E. Bauer, Tero Mielonen, Alf Kirkevåg, Øyvind Seland, Harri Kokkola, Ramiro Checa-Garcia, David Neubauer, Zak Kipling, Hitoshi Matsui, Paul Ginoux, Toshihiko Takemura, Philippe Le Sager, Samuel Rémy, Huisheng Bian, Mian Chin, Kai Zhang, Jialei Zhu, Svetlana G. Tsyro, Gabriele Curci, Anna Protonotariou, Ben Johnson, Joyce E. Penner, Nicolas Bellouin, Ragnhild B. Skeie, and Gunnar Myhre
Atmos. Chem. Phys., 22, 11009–11032, https://doi.org/10.5194/acp-22-11009-2022, https://doi.org/10.5194/acp-22-11009-2022, 2022
Short summary
Short summary
Aerosol optical depth (AOD) errors for biomass burning aerosol (BBA) are evaluated in 18 global models against satellite datasets. Notwithstanding biases in satellite products, they allow model evaluations. We observe large and diverse model biases due to errors in BBA. Further interpretations of AOD diversities suggest large biases exist in key processes for BBA which require better constraining. These results can contribute to further model improvement and development.
Roland Vernooij, Patrik Winiger, Martin Wooster, Tercia Strydom, Laurent Poulain, Ulrike Dusek, Mark Grosvenor, Gareth J. Roberts, Nick Schutgens, and Guido R. van der Werf
Atmos. Meas. Tech., 15, 4271–4294, https://doi.org/10.5194/amt-15-4271-2022, https://doi.org/10.5194/amt-15-4271-2022, 2022
Short summary
Short summary
Landscape fires are a substantial emitter of greenhouse gases and aerosols. Previous studies have indicated savanna emission factors to be highly variable. Improving fire emission estimates, and understanding future climate- and human-induced changes in fire regimes, requires in situ measurements. We present a drone-based method that enables the collection of a large amount of high-quality emission factor measurements that do not have the biases of aircraft or surface measurements.
Pierre Friedlingstein, Matthew W. Jones, Michael O'Sullivan, Robbie M. Andrew, Dorothee C. E. Bakker, Judith Hauck, Corinne Le Quéré, Glen P. Peters, Wouter Peters, Julia Pongratz, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Rob B. Jackson, Simone R. Alin, Peter Anthoni, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Laurent Bopp, Thi Tuyet Trang Chau, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Kim I. Currie, Bertrand Decharme, Laique M. Djeutchouang, Xinyu Dou, Wiley Evans, Richard A. Feely, Liang Feng, Thomas Gasser, Dennis Gilfillan, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Ingrid T. Luijkx, Atul Jain, Steve D. Jones, Etsushi Kato, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Arne Körtzinger, Peter Landschützer, Siv K. Lauvset, Nathalie Lefèvre, Sebastian Lienert, Junjie Liu, Gregg Marland, Patrick C. McGuire, Joe R. Melton, David R. Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Yosuke Niwa, Tsuneo Ono, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Thais M. Rosan, Jörg Schwinger, Clemens Schwingshackl, Roland Séférian, Adrienne J. Sutton, Colm Sweeney, Toste Tanhua, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Francesco Tubiello, Guido R. van der Werf, Nicolas Vuichard, Chisato Wada, Rik Wanninkhof, Andrew J. Watson, David Willis, Andrew J. Wiltshire, Wenping Yuan, Chao Yue, Xu Yue, Sönke Zaehle, and Jiye Zeng
Earth Syst. Sci. Data, 14, 1917–2005, https://doi.org/10.5194/essd-14-1917-2022, https://doi.org/10.5194/essd-14-1917-2022, 2022
Short summary
Short summary
The Global Carbon Budget 2021 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Roland Vernooij, Ulrike Dusek, Maria Elena Popa, Peng Yao, Anupam Shaikat, Chenxi Qiu, Patrik Winiger, Carina van der Veen, Thomas Callum Eames, Natasha Ribeiro, and Guido R. van der Werf
Atmos. Chem. Phys., 22, 2871–2890, https://doi.org/10.5194/acp-22-2871-2022, https://doi.org/10.5194/acp-22-2871-2022, 2022
Short summary
Short summary
Landscape fires are a major source of greenhouse gases and aerosols, particularly in sub-tropical savannas. Stable carbon isotopes in emissions can be used to trace the contribution of C3 plants (e.g. trees or shrubs) and C4 plants (e.g. savanna grasses) to greenhouse gases and aerosols if the process is well understood. This helps us to link individual vegetation types to emissions, identify biomass burning emissions in the atmosphere, and improve the reconstruction of historic fire regimes.
Roland Vernooij, Marcos Giongo, Marco Assis Borges, Máximo Menezes Costa, Ana Carolina Sena Barradas, and Guido R. van der Werf
Biogeosciences, 18, 1375–1393, https://doi.org/10.5194/bg-18-1375-2021, https://doi.org/10.5194/bg-18-1375-2021, 2021
Short summary
Short summary
We used drones to measure greenhouse gas emission factors from fires in the Brazilian Cerrado. We compared early-dry-season management fires and late-dry-season fires to determine if fire management can be a tool for abating emissions.
Although we found some evidence of increased CO and CH4 emission factors, the seasonal effect was smaller than that found in previous studies. For N2O, the third most important greenhouse gas, we found opposite trends in grass- and shrub-dominated areas.
Ivar R. van der Velde, Guido R. van der Werf, Sander Houweling, Henk J. Eskes, J. Pepijn Veefkind, Tobias Borsdorff, and Ilse Aben
Atmos. Chem. Phys., 21, 597–616, https://doi.org/10.5194/acp-21-597-2021, https://doi.org/10.5194/acp-21-597-2021, 2021
Short summary
Short summary
This paper compares the relative atmospheric enhancements of CO and NO2 measured by the space-based instrument TROPOMI over different fire-prone ecosystems around the world. We find distinct spatial and temporal patterns in the ΔNO2 / ΔCO ratio that correspond to regional differences in combustion efficiency. This joint analysis provides a better understanding of regional-scale combustion characteristics and can help the fire modeling community to improve existing global emission inventories.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Judith Hauck, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Stephen Sitch, Corinne Le Quéré, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone Alin, Luiz E. O. C. Aragão, Almut Arneth, Vivek Arora, Nicholas R. Bates, Meike Becker, Alice Benoit-Cattin, Henry C. Bittig, Laurent Bopp, Selma Bultan, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Wiley Evans, Liesbeth Florentie, Piers M. Forster, Thomas Gasser, Marion Gehlen, Dennis Gilfillan, Thanos Gkritzalis, Luke Gregor, Nicolas Gruber, Ian Harris, Kerstin Hartung, Vanessa Haverd, Richard A. Houghton, Tatiana Ilyina, Atul K. Jain, Emilie Joetzjer, Koji Kadono, Etsushi Kato, Vassilis Kitidis, Jan Ivar Korsbakken, Peter Landschützer, Nathalie Lefèvre, Andrew Lenton, Sebastian Lienert, Zhu Liu, Danica Lombardozzi, Gregg Marland, Nicolas Metzl, David R. Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin O'Brien, Tsuneo Ono, Paul I. Palmer, Denis Pierrot, Benjamin Poulter, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Jörg Schwinger, Roland Séférian, Ingunn Skjelvan, Adam J. P. Smith, Adrienne J. Sutton, Toste Tanhua, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Guido van der Werf, Nicolas Vuichard, Anthony P. Walker, Rik Wanninkhof, Andrew J. Watson, David Willis, Andrew J. Wiltshire, Wenping Yuan, Xu Yue, and Sönke Zaehle
Earth Syst. Sci. Data, 12, 3269–3340, https://doi.org/10.5194/essd-12-3269-2020, https://doi.org/10.5194/essd-12-3269-2020, 2020
Short summary
Short summary
The Global Carbon Budget 2020 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Tianran Zhang, Mark C. de Jong, Martin J. Wooster, Weidong Xu, and Lili Wang
Atmos. Chem. Phys., 20, 10687–10705, https://doi.org/10.5194/acp-20-10687-2020, https://doi.org/10.5194/acp-20-10687-2020, 2020
Short summary
Short summary
With strong public concern regarding air pollution problems in eastern China, where megacities like Beijing and Shanghai are located, smoke from agricultural fires burning during the post-harvest season has been blamed as one of the major causes. This research uses advanced satellite remote sensing data and methods to estimate the smoke emissions from agricultural fires in eastern China. Up to a 22 % contribution to PM2.5 was found during extreme cases.
Cited articles
Adzhar, R., Kelley, D. I., Dong, N., George, C., Torello Raventos, M., Veenendaal, E., Feldpausch, T. R., Phillips, O. L., Lewis, S. L., Sonké, B., Taedoumg, H., Schwantes Marimon, B., Domingues, T., Arroyo, L., Djagbletey, G., Saiz, G., and Gerard, F.: MODIS Vegetation Continuous Fields tree cover needs calibrating in tropical savannas, Biogeosciences, 19, 1377–1394, https://doi.org/10.5194/bg-19-1377-2022, 2022.
Akagi, S. K., Yokelson, R. J., Wiedinmyer, C., Alvarado, M. J., Reid, J. S., Karl, T., Crounse, J. D., and Wennberg, P. O.: Emission factors for open and domestic biomass burning for use in atmospheric models, Atmos. Chem. Phys., 11, 4039–4072, https://doi.org/10.5194/acp-11-4039-2011, 2011.
Andela, N., Kaiser, J. W., van der Werf, G. R., and Wooster, M. J.: New fire diurnal cycle characterizations to improve fire radiative energy assessments made from MODIS observations, Atmos. Chem. Phys., 15, 8831–8846, https://doi.org/10.5194/acp-15-8831-2015, 2015.
Anderson, M. C., Norman, J. M., Mecikalski, J. R., Otkin, J. A., and Kustas,
W. P.: A climatological study of evapotranspiration and moisture stress
across the continental United States based on thermal remote sensing: 1.
Model formulation, J. Geophys. Res.-Atmos., 112, 1–17,
https://doi.org/10.1029/2006JD007506, 2007.
Andreae, M. O.: Emission of trace gases and aerosols from biomass burning – an updated assessment, Atmos. Chem. Phys., 19, 8523–8546, https://doi.org/10.5194/acp-19-8523-2019, 2019.
Andreae, M. O. and Merlet, P.: Emission of trace gases and aerosols from
biomass burning, Biogeochemistry, 15, 955–966, https://doi.org/10.1029/2000GB001382,
2001.
Bertschi, I., Yokelson, R. J., Ward, D. E., Babbitt, R. E., Susott, R. A., Goode, J. G., and Hao, W. M.: Trace gas and particle emissions from fires in large diameter and belowground biomass fuels, J. Geophys. Res.-Atmos., 108, 1–12, https://doi.org/10.1029/2002JD002100, 2003.
Bullock, A.: Dambo hydrology in southern Africa-review and reassessment, J.
Hydrol., 134, 373–396, https://doi.org/10.1016/0022-1694(92)90043-U, 1992.
Bustamante, M. M. C., Medina, E., Asner, G. P., Nardoto, G. B., and
Garcia-Montiel, D. C.: Nitrogen cycling in tropical and temperate savannas,
Biogeochemistry, 79, 209–237, https://doi.org/10.1007/s10533-006-9006-x, 2006.
Chen, L.-W. A., Verburg, P., Shackelford, A., Zhu, D., Susfalk, R., Chow, J. C., and Watson, J. G.: Moisture effects on carbon and nitrogen emission from burning of wildland biomass, Atmos. Chem. Phys., 10, 6617–6625, https://doi.org/10.5194/acp-10-6617-2010, 2010.
Chen, Y., Hall, J., van Wees, D., Andela, N., Hantson, S., Giglio, L., van der Werf, G. R., Morton, D. C., and Randerson, J. T.: Multi-decadal trends and variability in burned area from the 5th version of the Global Fire Emissions Database (GFED5), Earth Syst. Sci. Data Discuss. [preprint], https://doi.org/10.5194/essd-2023-182, in review, 2023.
Cofer, W. R., Levine, J. S., Winstead, E. L., Cahoon, D. R., Sebacher, D.
I., Pinto, P., and Stocks, B. J.: Source compositions of trace gases released
during African savanna fires, J. Geophys. Res., 101, 23597–23602, 1996.
Di Giuseppe, F., Remy, S., Wetterhall, F., and Pappenberger, F.: Improving
CAMS biomass burning estimations by means of the Global ECMWF Fire Forecast
system (GEFF), Technical memorandum, https://doi.org/10.21957/uygqqtyh7, 2016.
DiMiceli, C., Carroll, M., Sohlberg, R., Kim, D., Kelly, M., and Townshend,
J.: MOD44B MODIS/Terra Vegetation Continuous Fields Yearly L3 Global 250 m
SIN Grid V006 [data set], NASA EOSDIS L. Process. DAAC,
https://doi.org/10.5067/MODIS/MOD44B.006, 2015.
Eames, T., Russell-Smith, J., Yates, C., Edwards, A., Vernooij, R., Ribeiro,
N., Steinbruch, F., and van der Werf, G. R.: Instantaneous pre-fire biomass
and fuel load measurements from multi-spectral UAS mapping in southern
African Savannas, Fire, 4, 1–19, https://doi.org/10.3390/fire4010002, 2021.
Eck, T. F., Holben, B. N., Reid, J. S., Mukelabai, M. M., Piketh, S. J.,
Torres, O., Jethva, H. T., Hyer, E. J., Ward, D. E., Dubovik, O., Sinyuk,
A., Schafer, J. S., Giles, D. M., Sorokin, M., Smirnov, A., and Slutsker, I.:
A seasonal trend of single scattering albedo in southern African
biomass-burning particles: Implications for satellite products and
estimates of emissions for the world's largest biomass-burning source, J.
Geophys. Res.-Atmos., 118, 6414–6432, https://doi.org/10.1002/jgrd.50500, 2013.
Field, R. D., Spessa, A. C., Aziz, N. A., Camia, A., Cantin, A., Carr, R., de Groot, W. J., Dowdy, A. J., Flannigan, M. D., Manomaiphiboon, K., Pappenberger, F., Tanpipat, V., and Wang, X.: Development of a Global Fire Weather Database, Nat. Hazards Earth Syst. Sci., 15, 1407–1423, https://doi.org/10.5194/nhess-15-1407-2015, 2015.
Friedl, M. and Sulla-Menashe, D.: MCD12Q1 MODIS/Terra + Aqua Land Cover Type
Yearly L3 Global 500 m SIN Grid V006 [data set], NASA EOSDIS L. Process.
DAAC, https://doi.org/10.5067/MODIS/MCD12Q1.006, 2019.
Gonçalves, R. V. S., Cardoso, J. C. F., Oliveira, P. E., Raymundo, D.,
and de Oliveira, D. C.: The role of topography, climate, soil and the
surrounding matrix in the distribution of Veredas wetlands in central
Brazil, Wetl. Ecol. Manag., 30, 1261–1279,
https://doi.org/10.1007/s11273-022-09895-z, 2022.
De Groot, W. J.: Interpreting the canadian forest fire weather index (FWI)
system, in Fourth Central Regional Fire Weather Committee Scientific and
Technical Seminar,Canadian Forestry Service, Northern Forestry
Centre, Edmonton, Alberta, 3–14, 1987.
Hao, W. M., Scharffe, D., Lob, J. M., and Crutzen, P. J.: Emissions of N20
from the Burning of Biomass in an Experimental System, Geophys. Res. Lett.,
18, 999–1002, 1991.
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A.,
Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D.,
Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P.,
Biavati, G., Bidlot, J., Bonavita, M., Chiara, G., Dahlgren, P., Dee, D.,
Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer,
A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková,
M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., Rosnay, P.,
Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J.: The ERA5 global
reanalysis, Q. J. Roy. Meteor. Soc., 146, 1999–2049,
https://doi.org/10.1002/qj.3803, 2020.
Hurst, D. F., Griffith, D. W. T., Carras, J. N., Williams, D. J., and Fraser,
P. J.: Measurements of trace gases emitted by Australian savanna fires
during the 1990 dry season, J. Atmos. Chem., 18, 33–56,
https://doi.org/10.1007/BF00694373, 1994.
Kaiser, J. W., Heil, A., Andreae, M. O., Benedetti, A., Chubarova, N., Jones, L., Morcrette, J.-J., Razinger, M., Schultz, M. G., Suttie, M., and van der Werf, G. R.: Biomass burning emissions estimated with a global fire assimilation system based on observed fire radiative power, Biogeosciences, 9, 527–554, https://doi.org/10.5194/bg-9-527-2012, 2012.
Korontzi, S.: Seasonal patterns in biomass burning emissions from southern
African vegetation fires for the year 2000, Glob. Chang. Biol., 11,
1680–1700, https://doi.org/10.1111/j.1365-2486.2005.001024.x, 2005.
Korontzi, S., Ward, D. E., Susott, R. A., Yokelson, R. J., Justice, C. O.,
Hobbs, P. V., Smithwick, E. A. H., and Hao, W. M.: Seasonal variation and
ecosystem dependence of emission factors for selected trace gases and PM2.5
for southern African savanna fires, J. Geophys. Res.-Atmos., 108,
https://doi.org/10.1029/2003JD003730, 2003.
Laris, P.: On the problems and promises of savanna fire regime change, Nat.
Commun., 12, 1–5, https://doi.org/10.1038/s41467-021-25141-1, 2021.
Laris, P., Koné, M., Dembélé, F., Yang, L., and Jacobs, R.:
Methane gas emissions from savanna fires: What analysis of local burning
regimes in a working West African landscape tell us, (March), 1–20, 2021.
Liu, S., Aiken, A. C., Arata, C., Dubey, M. K., Stockwell, C. E., Yokelson,
R. J., Stone, E. A., Jayarathne, T., Robinson, A. L., DeMott, P. J., and
Kreidenweis, S. M.: Aerosol single scattering albedo dependence on biomass
combustion efficiency: Laboratory and field studies, Geophys. Res. Lett.,
41, 742–748, https://doi.org/10.1002/2013GL058392, 2014.
Loveland, T. R. and Belward, A. S.: The International Geosphere Biosphere
Programme Data and Information System global land cover data set (DISCover),
Acta Astronaut., 41, 681–689, https://doi.org/10.1016/S0094-5765(98)00050-2,
1997.
Meyer, C. P., Cook, G. D., Reisen, F., Smith, T. E. L., Tattaris, M.,
Russell-Smith, J., Maier, S. W., Yates, C. P., and Wooster, M. J.: Direct
measurements of the seasonality of emission factors from savanna fires in
northern Australia, J. Geophys. Res.-Atmos., 117, D20305,
https://doi.org/10.1029/2012JD017671, 2012.
Mu, M., Randerson, J. T., Van Der Werf, G. R., Giglio, L., Kasibhatla, P.,
Morton, D., Collatz, G. J., Defries, R. S., Hyer, E. J., Prins, E. M.,
Griffith, D. W. T., Wunch, D., Toon, G. C., Sherlock, V., and Wennberg, P.
O.: Daily and 3-hourly variability in global fire emissions and consequences
for atmospheric model predictions of carbon monoxide, J. Geophys. Res.-Atmos., 116, 1–19, https://doi.org/10.1029/2011JD016245, 2011.
Muñoz-Sabater, J., Dutra, E., Agustí-Panareda, A., Albergel, C., Arduini, G., Balsamo, G., Boussetta, S., Choulga, M., Harrigan, S., Hersbach, H., Martens, B., Miralles, D. G., Piles, M., Rodríguez-Fernández, N. J., Zsoter, E., Buontempo, C., and Thépaut, J.-N.: ERA5-Land: a state-of-the-art global reanalysis dataset for land applications, Earth Syst. Sci. Data, 13, 4349–4383, https://doi.org/10.5194/essd-13-4349-2021, 2021.
Muzio, L. J. and Kramlich, J. C.: An artifact in the measurement of N2O from
combustion sources, Geophys. Res. Lett., 15, 1369–1372,
https://doi.org/10.1029/GL015i012p01369, 1988.
Myneni, R., Knyazikhin, Y., and Park, T.: MCD15A2H MODIS/Terra + Aqua Leaf
Area Index/FPAR 8-day L4 Global 500 m SIN Grid V006 [data set],
https://doi.org/10.5067/MODIS/MCD15A2H.006, 2015.
N'Dri, A. B., Soro, T. D., Gignoux, J., Dosso, K., Koné, M., N'Dri, J.
K., Koné, N. A., and Barot, S.: Season affects fire behavior in annually
burned humid savanna of West Africa, Fire Ecol., 14, 2,
https://doi.org/10.1186/s42408-018-0005-9, 2018.
Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel,
O., Blondel, M., Prettenhofer, P., Weiss, R., Dubourg, V., and Vanderplas,
J.: Scikit-learn: Machine Learning in Python Fabian, J. Mach. Learn. Res.,
12, 2825–2830, 2011.
Pokhrel, R. P., Wagner, N. L., Langridge, J. M., Lack, D. A., Jayarathne, T., Stone, E. A., Stockwell, C. E., Yokelson, R. J., and Murphy, S. M.: Parameterization of single-scattering albedo (SSA) and absorption Ångström exponent (AAE) with for aerosol emissions from biomass burning, Atmos. Chem. Phys., 16, 9549–9561, https://doi.org/10.5194/acp-16-9549-2016, 2016.
Randerson, J. T., Chen, Y., Van Der Werf, G. R., Rogers, B. M., and Morton,
D. C.: Global burned area and biomass burning emissions from small fires, J.
Geophys. Res.-Biogeo., 117, G04012, https://doi.org/10.1029/2012JG002128, 2012.
Roteta, E., Bastarrika, A., Franquesa, M. and Chuvieco, E.: Landsat and
sentinel-2 based burned area mapping tools in google earth engine, Remote
Sens., 13(4), 1–30, https://doi.org/10.3390/rs13040816, 2021.
Roy, D. P., Huang, H., Boschetti, L., Giglio, L., Yan, L., Zhang, H. H., and
Li, Z.: Landsat-8 and Sentinel-2 burned area mapping - A combined sensor
multi-temporal change detection approach, Remote Sens. Environ., 231, 111254, https://doi.org/10.1016/j.rse.2019.111254, 2019.
Russell-smith, J., Yates, C., Vernooij, R., Eames, T., Werf, G. Van Der,
Ribeiro, N., Edwards, A., Beatty, R., Lekoko, O., Mafoko, J., Monagle, C.,
and Johnston, S.: Opportunities and challenges for savanna burning emissions
abatement in southern Africa, J. Environ. Manage., 288, 112414,
https://doi.org/10.1016/j.jenvman.2021.112414, 2021.
Russell-Smith, J., Cook, G. D., Cooke, P. M., Edwards, A. C., Lendrum, M.,
Meyer, C., and Whitehead, P. J.: Managing fire regimes in north
Australian savannas: applying Aboriginal approaches to contemporary global
problems, Front. Ecol. Environ., 11, 55–63, https://doi.org/10.1890/120251, 2013.
Schmidt, I. B., Moura, L. C., Ferreira, M. C., Eloy, L., Sampaio, A. B.,
Dias, P. A., and Berlinck, C. N.: Fire management in the Brazilian savanna:
First steps and the way forward, J. Appl. Ecol., 55, 2094–2101,
https://doi.org/10.1111/1365-2664.13118, 2018.
Selimovic, V., Yokelson, R. J., Warneke, C., Roberts, J. M., de Gouw, J., Reardon, J., and Griffith, D. W. T.: Aerosol optical properties and trace gas emissions by PAX and OP-FTIR for laboratory-simulated western US wildfires during FIREX, Atmos. Chem. Phys., 18, 2929–2948, https://doi.org/10.5194/acp-18-2929-2018, 2018.
Shea, R. W., Shea, B. W., Kauffman, J. B., Ward, D. E., Haskins, C. I., and Scholes, M. C.: Fuel biomass and combustion factors associated with fires in savanna ecosystems of South Africa and Zambia, J. Geophys. Res., 101, 23551–23568, https://doi.org/10.1029/95JD02047, 1996.
Sinha, P., Hobbs, P. V., Yokelson, R. J., Blake, D. R., Gao, S., and
Kirchstetter, T. W.: Emissions from miombo woodland and dambo grassland
savanna fires, J. Geophys. Res.-Atmos., 109, D11305, https://doi.org/10.1029/2004JD004521,
2004.
Surawski, N. C., Sullivan, A. L., Meyer, C. P., Roxburgh, S. H., and Polglase, P. J.: Greenhouse gas emissions from laboratory-scale fires in wildland fuels depend on fire spread mode and phase of combustion, Atmos. Chem. Phys., 15, 5259–5273, https://doi.org/10.5194/acp-15-5259-2015, 2015.
Susott, R. A., Olbu, G., Baker, S. P., Ward, D. E., Kauffman, J. B., and
Shea, R. W.: Carbon, hydrogen, nitrogen, and thermogravimetric analysis of
tropical ecosystem biomass, in Biomass Burning and Global Change: Remote
sensing, modeling and inventory Development and Biomass Burning in Africa,
edited by: Levine, J. S., MIT Press, Cambridge, Mass., 350–360, 1996.
Tetens, O.: Uber einige meteorologische Begriffe, Zeitschrift fur Geophys.,
6, 297–309, 1930.
van Wees, D. and van der Werf, G. R.: Modelling biomass burning emissions and the effect of spatial resolution: a case study for Africa based on the Global Fire Emissions Database (GFED), Geosci. Model Dev., 12, 4681–4703, https://doi.org/10.5194/gmd-12-4681-2019, 2019.
van Leeuwen, T. T. and van der Werf, G. R.: Spatial and temporal variability in the ratio of trace gases emitted from biomass burning, Atmos. Chem. Phys., 11, 3611–3629, https://doi.org/10.5194/acp-11-3611-2011, 2011.
van der Werf, G. R., Randerson, J. T., Giglio, L., van Leeuwen, T. T., Chen, Y., Rogers, B. M., Mu, M., van Marle, M. J. E., Morton, D. C., Collatz, G. J., Yokelson, R. J., and Kasibhatla, P. S.: Global fire emissions estimates during 1997–2016, Earth Syst. Sci. Data, 9, 697–720, https://doi.org/10.5194/essd-9-697-2017, 2017.
Van Wagner, C. E.: Development and structure of the Canadian forest fire weather index system, ISBN 0662151984, 1987.
Vermote, E.: MOD09A1 MODIS Surface Reflectance 8-Day L3 Global 500 m SIN Grid
V006, NASA EOSDIS L. Process. DAAC, https://doi.org/10.5067/MODIS/MOD09A1.006, 2015.
Vernooij, R.: Measurements of savanna landscap fire emission factors for
CO2, CO, CH4 and N2O using a UAV-based sampling methodology, Zenodo [data
set], https://doi.org/10.5281/zenodo.7689032, 2023.
Vernooij, R., Giongo, M., Borges, M. A., Costa, M. M., Barradas, A. C. S., and van der Werf, G. R.: Intraseasonal variability of greenhouse gas emission factors from biomass burning in the Brazilian Cerrado, Biogeosciences, 18, 1375–1393, https://doi.org/10.5194/bg-18-1375-2021, 2021.
Vernooij, R., Dusek, U., Popa, M. E., Yao, P., Shaikat, A., Qiu, C., Winiger, P., van der Veen, C., Eames, T. C., Ribeiro, N., and van der Werf, G. R.: Stable carbon isotopic composition of biomass burning emissions – implications for estimating the contribution of C3 and C4 plants, Atmos. Chem. Phys., 22, 2871–2890, https://doi.org/10.5194/acp-22-2871-2022, 2022a.
Vernooij, R., Winiger, P., Wooster, M., Strydom, T., Poulain, L., Dusek, U., Grosvenor, M., Roberts, G. J., Schutgens, N., and van der Werf, G. R.: A quadcopter unmanned aerial system (UAS)-based methodology for measuring biomass burning emission factors, Atmos. Meas. Tech., 15, 4271–4294, https://doi.org/10.5194/amt-15-4271-2022, 2022b.
Vitolo, C., Di Giuseppe, F., Barnard, C., Coughlan, R., San-Miguel-Ayanz,
J., Libertá, G., and Krzeminski, B.: ERA5-based global meteorological
wildfire danger maps, Sci. Data, 7, 1–11, https://doi.org/10.1038/s41597-020-0554-z,
2020.
Ward, D. E., Susott, R. A., Kauffman, J. B., Babbitt, R. E., Cummings, D.
L., Dias, B., Holben, B. N., Kaufman, Y. J., Rasmussen, R. A., and Setzer, A.
W.: Smoke and fire characteristics for cerrado and deforestation burns in
Brazil: BASE-B Experiment, J. Geophys. Res., 97, 14601–14619,
https://doi.org/10.1029/92JD01218, 1992.
Ward, D. E. and Radke, L. F.: Emissions Measurements from Vegetation Fires:
A Comparative Evaluation of Methods and Results, in Fire in the Environment:
The Ecological, Atmospheric, and Climatic Importance of Vegetation Fires,
edited by: P. J. Crutzen and J. G. Goldammer, Chischester,
England, 53–76, 1993.
Wiedinmyer, C., Kimura, Y., McDonald-Buller, E. C., Emmons, L. K., Buchholz, R. R., Tang, W., Seto, K., Joseph, M. B., Barsanti, K. C., Carlton, A. G., and Yokelson, R.: The Fire Inventory from NCAR version 2.5: an updated global fire emissions model for climate and chemistry applications, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2023-124, 2023.
Winter, F., Wartha, C., and Hofbauer, H.: The Relative Importance of Radicals
on the N2O and NO Formation and Destruction Paths in a Quartz CFBC, J.
Energy Resour. Technol., 121, 131–136, https://doi.org/10.1115/1.2795068, 1999.
Wooster, M. J., Freeborn, P. H., Archibald, S., Oppenheimer, C., Roberts, G. J., Smith, T. E. L., Govender, N., Burton, M., and Palumbo, I.: Field determination of biomass burning emission ratios and factors via open-path FTIR spectroscopy and fire radiative power assessment: headfire, backfire and residual smouldering combustion in African savannahs, Atmos. Chem. Phys., 11, 11591–11615, https://doi.org/10.5194/acp-11-11591-2011, 2011.
Yokelson, R. J., Bertschi, I. T., Christian, T. J., Hobbs, P. V., Ward, D.
E., and Hao, W. M.: Trace gas measurements in nascent, aged, and
cloud-processed smoke from African savanna fires by airborne Fourier
transform infrared spectroscopy (AFTIR), J. Geophys. Res.-Atmos., 108, 8478,
https://doi.org/10.1029/2002jd002322, 2003.
Yokelson, R. J., Burling, I. R., Urbanski, S. P., Atlas, E. L., Adachi, K., Buseck, P. R., Wiedinmyer, C., Akagi, S. K., Toohey, D. W., and Wold, C. E.: Trace gas and particle emissions from open biomass burning in Mexico, Atmos. Chem. Phys., 11, 6787–6808, https://doi.org/10.5194/acp-11-6787-2011, 2011.
Short summary
Savannas account for over half of global landscape fire emissions. Although environmental and fuel conditions affect the ratio of species the fire emits, these dynamics have not been implemented in global models. We measured CO2, CO, CH4, and N2O emission factors (EFs), fuel parameters, and fire severity proxies during 129 individual fires. We identified EF patterns and trained models to estimate EFs of these species based on satellite observations, reducing the estimation error by 60–85 %.
Savannas account for over half of global landscape fire emissions. Although environmental and...
Altmetrics
Final-revised paper
Preprint