Articles | Volume 18, issue 4
https://doi.org/10.5194/bg-18-1375-2021
© 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/bg-18-1375-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
23 Feb 2021
Research article |
| 23 Feb 2021
| 23 Feb 2021
Intraseasonal variability of greenhouse gas emission factors from biomass burning in the Brazilian Cerrado
Department of Earth Sciences, Faculty of Science, Vrije Universiteit
Amsterdam, Amsterdam, the Netherlands
Marcos 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
Guido R. van der Werf
Department of Earth Sciences, Faculty of Science, Vrije Universiteit
Amsterdam, Amsterdam, the Netherlands
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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 %.
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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.
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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.
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EGUsphere, https://doi.org/10.5194/egusphere-2025-3936, https://doi.org/10.5194/egusphere-2025-3936, 2025
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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
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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
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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
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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
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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.
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
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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
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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
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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.
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.
Roland Vernooij, Tom Eames, Jeremy Russell-Smith, Cameron Yates, Robin Beatty, Jay Evans, Andrew Edwards, Natasha Ribeiro, Martin Wooster, Tercia Strydom, Marcos Vinicius Giongo, Marco Assis Borges, Máximo Menezes Costa, Ana Carolina Sena Barradas, Dave van Wees, and Guido R. Van der Werf
Earth Syst. Dynam., 14, 1039–1064, https://doi.org/10.5194/esd-14-1039-2023, https://doi.org/10.5194/esd-14-1039-2023, 2023
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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 %.
Ana Maria Roxana Petrescu, Chunjing Qiu, Matthew J. McGrath, Philippe Peylin, Glen P. Peters, Philippe Ciais, Rona L. Thompson, Aki Tsuruta, Dominik Brunner, Matthias Kuhnert, Bradley Matthews, Paul I. Palmer, Oksana Tarasova, Pierre Regnier, Ronny Lauerwald, David Bastviken, Lena Höglund-Isaksson, Wilfried Winiwarter, Giuseppe Etiope, Tuula Aalto, Gianpaolo Balsamo, Vladislav Bastrikov, Antoine Berchet, Patrick Brockmann, Giancarlo Ciotoli, Giulia Conchedda, Monica Crippa, Frank Dentener, Christine D. Groot Zwaaftink, Diego Guizzardi, Dirk Günther, Jean-Matthieu Haussaire, Sander Houweling, Greet Janssens-Maenhout, Massaer Kouyate, Adrian Leip, Antti Leppänen, Emanuele Lugato, Manon Maisonnier, Alistair J. Manning, Tiina Markkanen, Joe McNorton, Marilena Muntean, Gabriel D. Oreggioni, Prabir K. Patra, Lucia Perugini, Isabelle Pison, Maarit T. Raivonen, Marielle Saunois, Arjo J. Segers, Pete Smith, Efisio Solazzo, Hanqin Tian, Francesco N. Tubiello, Timo Vesala, Guido R. van der Werf, Chris Wilson, and Sönke Zaehle
Earth Syst. Sci. Data, 15, 1197–1268, https://doi.org/10.5194/essd-15-1197-2023, https://doi.org/10.5194/essd-15-1197-2023, 2023
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This study updates the state-of-the-art scientific overview of CH4 and N2O emissions in the EU27 and UK in Petrescu et al. (2021a). Yearly updates are needed to improve the different respective approaches and to inform on the development of formal verification systems. It integrates the most recent emission inventories, process-based model and regional/global inversions, comparing them with UNFCCC national GHG inventories, in support to policy to facilitate real-time verification procedures.
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
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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
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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
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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
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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
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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.
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
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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
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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.
Cited articles
Abreu, R. C. R., Hoffmann, W. A., Vasconcelos, H. L., Pilon, N. A.,
Rossatto, D. R., and Durigan, G.: The biodiversity cost of carbon
sequestration in tropical savanna, Sci. Adv., 3, 1–8,
https://doi.org/10.1126/sciadv.1701284, 2017.
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.
Anderson, R., Beatty, R., Russell-Smith, J., and van der Werf, G. R.: The
global potential of indigenous fire management: findings of the regional
feasibility assessments, UNU-IAS, Tokyo, available at: https://i.unu.edu/media/tfm.unu.edu/news/2151/Final-Report-Findings-Regional-Feasibility-Assessments-ISFMI.pdf (last access: 19 February 2021), 2015.
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.
Australian Government, Department of the Environment and Energy:
Explanatory Statement – Carbon Credits (Carbon Farming Initiative) Act
2011, Australian government, Canbera, available at: https://www.legislation.gov.au/Details/F2017L01038/Explanatory Statement/Text (last access: 19 February 2021), 2018.
Barradas, A. C. S.: A gestão do fogo na Estação Ecológica Serra Geral do Tocantins, Brasil. Mestrado Profissional em Biodiversidade em Unidades de Conservação, master thesis, Instituto de Pesquisas Jardim Botânico do Rio de Janeiro, 2017.
Barradas, A. C. S., Borges, M. A., and Costa, M. M.: Plano de manejo
integrado do fogo – Estação Ecológica Serra Geral do Tocantins,
Rio da Conceição, ICMBIO, Rio da Conceição, 2018.
Barradas, A. C. S., Borges, M. A., Costa, M. M., and Ribeiro, K. T.:
Paradigmas da Gestão do Fogo em Áreas Protegidas no Mundo e o Caso
da Estação Ecológica Serra Geral do Tocantins, Biodiversidade
Bras., 10, 71–86, https://doi.org/10.37002/biobrasil.v10i2.1474, 2020.
Beringer, J., Hutley, L. B., Tapper, N. J., and Cernusak, L. A.: Savanna
fires and their impact on net ecosystem productivity in North Australia,
Glob. Change Biol., 13, 990–1004, https://doi.org/10.1111/j.1365-2486.2007.01334.x,
2007.
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.
Bistinas, I., Harrison, S. P., Prentice, I. C., and Pereira, J. M. C.: Causal relationships versus emergent patterns in the global controls of fire frequency, Biogeosciences, 11, 5087–5101, https://doi.org/10.5194/bg-11-5087-2014, 2014.
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.
Christian, T. J., Yokelson, R. J., Jr, A. C., Griffith, D. W. T., Alvarado,
E. C., Santos, C., Gomes, T., Neto, S., Veras, C. A. G., and Hao, W. M.: The
tropical forest and fire emissions experiment: Trace gases emitted by
smoldering logs and dung from deforestation and pasture fires in Brazil, J.
Geophys. Res., 112, 1–14, https://doi.org/10.1029/2006JD008147, 2007.
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.
Cook, G. D., Liedloff, A. C., and Murphy, B. P.: Towards a methodology for
increased carbon sequestration in dead fuels through implementation of less
severe fire regimes in savannas, in: Carbon Accounting and Savanna Fire
Management, edited by: Murphy, B. P., Edwards, A. C., Meyer, M., and Russell-Smith, J., CSIRO Publishing, Clayton South, Australia, 321–326, 2015.
Crutzen, P. J. and Zimmermann, P. H.: The changing photochemistry of the
troposphere, Tellus, 43, 136–151, https://doi.org/10.1034/j.1600-0870.1991.00012.x,
1991.
Daniel, J. S. and Solomon, S.: On the climate forcing of carbon monoxide, J.
Geophys. Res.-Atmos., 103, 13249–13260, https://doi.org/10.1029/98JD00822, 1998.
DiMiceli, C., Carroll, M., Sohlberg, R., Kim, D., Kelly, M., and Townshend, J.: MOD44B MODIS/Terra Vegetation Continuous Fields Yearly L3 Global 250m SIN Grid V006 [Data set], NASA EOSDIS Land Processes DAAC, https://doi.org/10.5067/MODIS/MOD44B.006, 2015.
Durigan, G., Ratter, J. A., State, P., and Box, P. O.: The need for a
consistent fire policy for Cerrado conservation, J. Appl. Ecol., 53, 11–15, https://doi.org/10.1111/1365-2664.12559, 2016.
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.
Ferek, R. J., Reid, J. S., Hobbs, P. V., Blake, D. R., and Liousse, C.:
Emission factors of hydrocarbons, halocarbons, trace gases and particles
from biomass burning in Brazil, J. Geophys. Res., 103, 32107–32118,
https://doi.org/10.1029/98JD00692, 1998.
Fidelis, A. and Fernanda, M.: Above- and below-ground biomass and carbon
dynamics in Brazilian Cerrado wet grasslands, J. Veg. Sci., 24, 356–364,
https://doi.org/10.1111/j.1654-1103.2012.01465.x, 2013.
Fidelis, A., Alvarado, S., Barradas, A., Pivello, V., Fidelis, A., Alvarado,
S. T., Barradas, A. C. S., and Pivello, V. R.: The Year 2017: Megafires and
Management in the Cerrado, Fire, 1, 49,
https://doi.org/10.3390/FIRE1030049, 2018.
Franke, J., Barradas, A. C. S., Borges, M. A., Menezes Costa, M., Dias, P.
A., Hoffmann, A. A., Orozco Filho, J. C., Melchiori, A. E., and Siegert, F.:
Fuel load mapping in the Brazilian Cerrado in support of integrated fire
management, Remote Sens. Environ., 217, 221–232,
https://doi.org/10.1016/j.rse.2018.08.018, 2018.
Fry, M. M., Naik, V., West, J. J., Schwarzkopf, M. D., Fiore, A. M.,
Collins, W. J., Dentener, F. J., Shindell, D. T., Atherton, C., Bergmann,
D., Duncan, B. N., Hess, P., MacKenzie, I. A., Marmer, E., Schultz, M. G.,
Szopa, S., Wild, O., and Zeng, G.: The influence of ozone precursor emissions
from four world regions on tropospheric composition and radiative climate
forcing, J. Geophys. Res.-Atmos., 117, 1–16, https://doi.org/10.1029/2011JD017134,
2012.
Fuglestvedt, J. S., Shine, K. P., Berntsen, T., Cook, J., Lee, D. S.,
Stenke, A., Skeie, R. B., Velders, G. J. M., and Waitz, I. A.: Transport
impacts on atmosphere and climate: Metrics, Atmos. Environ., 44,
4648–4677, https://doi.org/10.1016/j.atmosenv.2009.04.044, 2010.
Giglio, L. and Justice, C. O.: MOD14A1 MODIS/Terra Thermal Anomalies/Fire
Daily L3 Global 1km SIN Grid V006, NASA EOSDIS,
https://doi.org/10.5067/MODIS/MOD14A1.006, 2015.
Giglio, L., Boschetti, L., Roy, D. P., Humber, M. L., and Justice, C. O.: The
Collection 6 MODIS burned area mapping algorithm and product, Remote Sens.
Environ., 217, 72–85, https://doi.org/10.1016/j.rse.2018.08.005, 2018.
Goodwin, J., Gillenwater, M., Romano, D., and Radunsky, K.: Precursors and
indirect emissions, in: 2019 Refinement to the 2006 IPCC Guidelines for
National Greenhouse Gas Inventories – General Guidance and Reporting, Volume
1, edited by: Gómez, D. and Irving, W., Institute for Global Environmental
Strategies (IGES) for the IPCC, available at:
https://www.ipcc.ch/report/2019-refinement-to-the-2006-ipcc-guidelines-for-national-greenhouse-gas-inventories/ (last access: 10 December 2020),
2019.
Govender, N., Trollope, W. S. W., and Van Wilgen, B. W.: The effect of fire
season, fire frequency, rainfall and management on fire intensity in savanna
vegetation in South Africa, J. Appl. Ecol., 43, 748–758,
https://doi.org/10.1111/j.1365-2664.2006.01184.x, 2006.
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.
Hoffa, E. A., Ward, D. E., Hao, W. M., Susott, R. A., and Wakimoto, R. H.:
Seasonality of carbon emissions from biomass burning in a Zambian savanna,
J. Geophys. Res., 104, 13841–13853, https://doi.org/10.1029/1999JD900091, 1999.
Hurst, D. F., Griffith, D. W. T., Carras, J. C., 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, 1994a.
Hurst, D. F., Griffith, D. W. T., and Cook, G. D.: Trace gas emissions from
biomass burning in tropical Australian savannas, J. Geophys. Res., 99,
16441, https://doi.org/10.1029/94JD00670, 1994b.
Ito, A. and Penner, J. E.: Global estimates of biomass burning emissions
based on satellite imagery for the year 2000, J. Geophys. Res.-Atmos.,
109, 1–18, https://doi.org/10.1029/2003JD004423, 2004.
Jones, M. W., Santín, C., van der Werf, G. R., and Doerr, S. H.: Global
fire emissions buffered by the production of pyrogenic carbon, Nat. Geosci.,
12, 742–747, https://doi.org/10.1038/s41561-019-0403-x, 2019.
Kauffman, J. B., Cummings, D. L., and Ward, D. E.: Relationships of Fire,
Biomass and Nutrient Dynamics along a Vegetation Gradient in the Brazilian
Cerrado, J. Ecol., 82, 519–531, https://doi.org/10.2307/2261261, 1994.
Kilpinen, P. and Hupa, M.: Homogeneous N2O chemistry at fluidized bed
combustion conditions: A kinetic modeling study, Combust. Flame, 85,
94–104, https://doi.org/10.1016/0010-2180(91)90179-F, 1991.
Klink, C. A. and Machado, R. B.: Conservation of the Brazilian Cerrado,
Conserv. Biol., 19, 707–713, https://doi.org/10.1111/j.1523-1739.2005.00702.x, 2005.
Korontzi, S.: Seasonal patterns in biomass burning emissions from southern
African vegetation fires for the year 2000, Glob. Change Biol., 11,
1680–1700, https://doi.org/10.1111/j.1365-2486.2005.001024.x, 2005.
Korontzi, S., Justice, C. O., and Scholes, R. J.: Influence of timing and
spatial extent of savanna fires in southern Africa on atmospheric emissions,
J. Arid Environ., 395–404, https://doi.org/10.1006/jare.2002.1098, 2003a.
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, 4758,
https://doi.org/10.1029/2003jd003730, 2003b.
Landry, J.-S. and Matthews, H. D.: Non-deforestation fire vs. fossil fuel combustion: the source of CO2 emissions affects the global carbon cycle and climate responses, Biogeosciences, 13, 2137–2149, https://doi.org/10.5194/bg-13-2137-2016, 2016.
Lipsett-Moore, G. J., Wolff, N. H., and Game, E. T.: Emissions mitigation
opportunities for savanna countries from early dry season fire management,
Nat. Commun., 9, 1–8, https://doi.org/10.1038/s41467-018-04687-7, 2018.
Lobert, J. M. and Warnatz, J.: Emissions from the Combustion Process in
Vegetation,
in: Fire in the Environment: The Ecological, Atmospheric, and Climatic Importance of Vegetation Fires, edited by: Crutzen, P. J. and Goldammer, J. G., John Wiley and Sons, Hoboken, NJ, USA,
15–38, 1993.
Maraseni, T. N., Smith, K. R., Griffiths, G., and Apan, A.: Savanna burning
methodology for fire management and emissions reduction: a critical review
of influencing factors, Carbon Balance Manag., 11, 25,
https://doi.org/10.1186/s13021-016-0067-4, 2016.
Melchiori, A. E., Setzer, A. W., Morelli, F., Libonati, R., Cândido, P.
D. A., and De Jesús, S. C.: A Landsat-TM/OLI algorithm for burned areas
in the Brazilian Cerrado – preliminary results A Landsat-TM/OLI algorithm
for burned areas in the Brazilian Cerrado – preliminary results, VII International Conference on Forest Fire Research, edited by: Viegas, D. X., 2014, https://doi.org/10.14195/978-989-26-0884-6, 2015.
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.
Miranda, H. S., Sato, M. N., Neto, W. N., and Aires, F. S.: Fires in the
cerrado, the Brazilian savanna, in: Tropical Fire Ecology,
edited by: Mason, J.,
Springer, Berlin and Heidelberg, Germany, 427–450, 2009.
Murphy, B. P., Russell-Smith, J., and Prior, L. D.: Frequent fires reduce
tree growth in northern Australian savannas: implications for tree
demography and carbon sequestration, Glob. Change Biol., 16, 331–343,
https://doi.org/10.1111/j.1365-2486.2009.01933.x, 2010.
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.
Myhre, G., Shindell, D., Bréon, F.-M., Collins, W., Fuglestvedt, J., Huang, J., Koch, D., Lamarque, J.-F., Lee, D., Mendoza, B., Nakajima, T., Robock, A., Stephens, G., Takemura, T., and Zhang, H.: Anthropogenic and Natural Radiative Forcing, in: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S. K., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P. M., Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 659 pp., 2013.
N'Dri, B., Soro, T. D., Gignoux, J., Dosso, K., Koné, M., Dri, J. K. N.,
Koné, N. A., and Barot, S.: Season affects fire behavior in annually
burned humid savanna of West Africa, Fire Ecol., 14, 5,
https://doi.org/10.1186/s42408-018-0005-9, 2018.
Oliveira, S. L. J., Campagnolo, M. L., Price, O. F., Edwards, A. C.,
Russell-Smith, J., and Pereira, J. M. C.: Ecological implications of
fine-scale fire patchiness and severity in tropical savannas of northern
Australia, Fire Ecol., 11, 10–31, https://doi.org/10.4996/fireecology.1101010, 2015.
Oliveras, I., Meirelles, S. T., Hirakuri, V. L., Freitas, C. R., Miranda, H.
S., and Pivello, V. R.: Effects of fire regimes on herbaceous biomass and
nutrient dynamics in the Brazilian savanna, Int. J. Wildl. Fire, 22,
368–380, https://doi.org/10.1071/WF10136, 2013.
Orozco-Filho, J. C.: Avaliação do uso da abordagem orientada-objeto
com imagens de alta resolução RapidEye na classificação das
fitofisionomias do cerrado, Universidade de Brasília, Brasilia, available at: https://repositorio.unb.br/bitstream/10482/31183/1/2017_JuanCarlosOrozcoFilho.pdf (last access: 19 February 2021), 2017.
Pellegrini, A. F. A., Ahlström, A., Hobbie, S. E., Reich, P. B.,
Nieradzik, L. P., Staver, A. C., Scharenbroch, B. C., Jumpponen, A., and
Anderegg, W. R. L.: Fire frequency drives decadal changes in soil carbon and
nitrogen and ecosystem productivity, Nature, 553, 194–198, https://doi.org/10.1038/nature24668, 2018.
Penman, T. D., Christie, F. J., Andersen, A. N., Bradstock, R. A., Cary, G.
J., Henderson, M. K., Price, O., Tran, C., Wardle, G. M., Williams, R. J.,
and York, A.: Prescribed burning: how can it work to conserve the things we
value?, Int. J. Wildl. Fire, 20, 721, https://doi.org/10.1071/WF09131, 2011.
Penner, J. E., Quaas, J., Storelvmo, T., Takemura, T., Boucher, O., Guo, H., Kirkevåg, A., Kristjánsson, J. E., and Seland, Ø.: Model intercomparison of indirect aerosol effects, Atmos. Chem. Phys., 6, 3391–3405, https://doi.org/10.5194/acp-6-3391-2006, 2006.
Pivello, V. R.: The use of fire on the cerrado and amazonian rainforrests,
Fire Ecol., 7, 24–39, https://doi.org/10.4996/fireecology.0701024, 2011.
Price, O. F., Russell-Smith, J., and Watt, F.: The influence of prescribed
fire on the extent of wildfire in savanna landscapes of western Arnhem Land,
Australia, Int. J. Wildl. Fire, 21, 297–305, https://doi.org/10.1071/WF10079, 2012.
Ramos-Neto, M. B. and Pivello, V. R.: Lightning Fires in a Brazilian Savanna
National Park: Rethinking Management Strategies, Environ. Manage., 26,
675–684, https://doi.org/10.1007/s002670010124, 2000.
Reid, J. S., Koppmann, R., Eck, T. F., and Eleuterio, D. P.: A review of biomass burning emissions part II: intensive physical properties of biomass burning particles, Atmos. Chem. Phys., 5, 799–825, https://doi.org/10.5194/acp-5-799-2005, 2005.
Ribeiro, J. F. and Walter, B. M. T.: As principais Fitofisionomias do Bioma
Cerrado, in: Cerrado: ecologia e flora,
Embrapa cerrados, Brasilia,
152–212, 1998.
Rissi, M. N., Baeza, J., Gorgone-barbosa, E., Zupo, T., and Fidelis, A.: Does
season affect fire behaviour in the Cerrado?, Int. J. Wildl. Fire, 26,
427–433, https://doi.org/10.1071/WF14210, 2017.
Russell-Smith, J., Cook, G. D., Cooke, P. M., Edwards, A. C., Lendrum, M.,
Meyer, C. P., and Whitehead, P. J.: Managing fire regimes in north Australian
savannas: Applying Aboriginal approaches to contemporary global problems,
Front. Ecol. Environ., 11, e55–e63, https://doi.org/10.1890/120251, 2013.
Santos, M. M., Batista, A. C., Silva, A. D. P. da, Ganassoli Neto, E., Barradas, A. C. S., and Giongo, M.: Characterization and Dynamics of Surface Fuel of Cerrado Grassland in Jalapão Region – Tocantins, Brazil, Floresta, 51, 127, https://doi.org/10.5380/rf.v51i1.67440, 2020.
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.
Scott, K., Setterfield, S. A., Douglas, M. M., Parr, C. L., Schatz, J. O. N.,
and Andersen, A. N.: Does long-term fire exclusion in an Australian tropical
savanna result in a biome shift? A test using the reintroduction of fire, Austral Ecol., 37,
693–711, https://doi.org/10.1111/j.1442-9993.2012.02379.x, 2012.
Seiler, W. and Crutzen, P. J.: Estimates of Gross and Net Fluxes of Carbon
Between the biosphere and the athmosphere from biomass burning, Clim.
Change, 2, 207–247, 1980.
Seplan: Zoneamento Ecológico Econômico de Tocantins, available at: http://www.seplan.to.gov.br/ (last access: 10 December 2020), 2003.
Sexton, J. O., Song, X. P., Feng, M., Noojipady, P., Anand, A., Huang, C.,
Kim, D. H., Collins, K. M., Channan, S., DiMiceli, C., and Townshend, J. R.
G.: Global, 30-m resolution continuous fields of tree cover: Landsat-based
rescaling of MODIS Vegetation Continuous Fields with lidar-based estimates
of error, Int. J. Digit. Earth, 6, 427–448, https://doi.org/10.1080/17538947.2013.786146, 2013.
Shindell, D. T., Faluvegi, G., Koch, D. M., Schmidt, G. A., Unger, N., and
Bauer, S. E.: Improved Attribution of Climate Forcing to Emissions,
Interactions, 326, 716–718, 2009.
Staver, A. C., Archibald, S., and Levin, S. A.: The Global Extent and
Determinants of Savanna and Forest as Alternative Biome States, Science,
334, 230–232, https://doi.org/10.1126/science.1210465, 2011a.
Staver, A. C., Archibald, S., and Levin, S.: Tree cover in sub-Saharan
Africa: Rainfall and fire constrain forest and savanna as alternative stable
states, Ecology, 92, 1063–1072, https://doi.org/10.1890/10-1684.1, 2011b.
Sudo, K. and Akimoto, H.: Global source attribution of tropospheric ozone:
Long-range transport from various source regions, J. Geophys. Res.-Atmos.,
112, D12302, https://doi.org/10.1029/2006JD007992, 2007.
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.
Surawski, N. C., Sullivan, A. L., Roxburgh, S. H., Meyer, C. P. M., and
Polglase, P. J.: Incorrect interpretation of carbon mass balance biases
global vegetation fire emission estimates, Nat. Commun., 7, 1–5,
https://doi.org/10.1038/ncomms11536, 2016.
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, MA, USA,
350–360, 1996.
Urbanski, S.: Forest Ecology and Management Wildland fire emissions, carbon,
and climate: Emission factors, Forest Ecol. Manage., 317, 51–60,
https://doi.org/10.1016/j.foreco.2013.05.045, 2014.
Urbanski, S. P.: Combustion efficiency and emission factors for wildfire-season fires in mixed conifer forests of the northern Rocky Mountains, US, Atmos. Chem. Phys., 13, 7241–7262, https://doi.org/10.5194/acp-13-7241-2013, 2013.
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 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 Leeuwen, T. T., van der Werf, G. R., Hoffmann, A. A., Detmers, R. G., Rücker, G., French, N. H. F., Archibald, S., Carvalho Jr., J. A., Cook, G. D., de Groot, W. J., Hély, C., Kasischke, E. S., Kloster, S., McCarty, J. L., Pettinari, M. L., Savadogo, P., Alvarado, E. C., Boschetti, L., Manuri, S., Meyer, C. P., Siegert, F., Trollope, L. A., and Trollope, W. S. W.: Biomass burning fuel consumption rates: a field measurement database, Biogeosciences, 11, 7305–7329, https://doi.org/10.5194/bg-11-7305-2014, 2014.
Veenendaal, E. M., Torello-Raventos, M., Miranda, H. S., Sato, N. M.,
Oliveras, I., Langevelde, F., Van, Asner, G. P., Lloyd, J., and Lloyd, J.: On
the relationship between fire regime and vegetation structure in the
tropics, New Phytol., 218, 153–166, https://doi.org/10.1111/nph.14940, 2018.
Ward, D. E., Setzer, A. W., Kaufman, Y. J., and Rasmussen, R. A.:
Characteristics of smoke emissions from biomass fires of the Amazon region –
BASE-A experiment, in: Global Biomass Burning – Atmospheric, Climatic and
Biospheric Implications, edited by: Levine, J. S.,
The MIT
press, Cambridge, MA, USA,
394–401, 1991.
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.-Atmos., 97, 14601–14619,
https://doi.org/10.1029/92JD01218, 1992.
Winter, F., Wartha, C., and Hofbauer, H.: NO and N2O formation during the
combustion of wood, straw, malt waste and peat, Bioresour. Technol., 70,
39–49, https://doi.org/10.1016/S0960-8524(99)00019-X, 1999a.
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, 1999b.
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.
Yates, C. P., Russell-Smith, J., Murphy, B. P., Desailly, M., Evans, J.,
Legge, S., Lewis, F., Lynch, D., and Edwards, A. C.: Fuel accumulation,
consumption and fire patchiness in the lower rainfall savanna region, in:
Carbon Accounting and Savanna Fire Management, edited by: Murphy, B. P., Edwards, A. C., Meyer, M., and Russell-Smith, J., CSIRO Publishing, Clayton South, Australia,
115–127,
2015.
Yokelson, R. J., Goode, J. G., Ward, D. E., Susott, R. A., Babbitt, R. E.,
Wade, D. D., Bertschi, I., Griffith, D. W. T., and Hao, W. M.: Emissions of
formaldehyde, acetic acid, methanol, and other trace gases from biomass
fires in North Carolina measured by airborne Fourier transform infrared
spectroscopy, J. Geophys. Res.-Atmos., 104, 30109–30125,
https://doi.org/10.1029/1999JD900817, 1999.
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.
Yokelson, R. J., Burling, I. R., Gilman, J. B., Warneke, C., Stockwell, C. E., de Gouw, J., Akagi, S. K., Urbanski, S. P., Veres, P., Roberts, J. M., Kuster, W. C., Reardon, J., Griffith, D. W. T., Johnson, T. J., Hosseini, S., Miller, J. W., Cocker III, D. R., Jung, H., and Weise, D. R.: Coupling field and laboratory measurements to estimate the emission factors of identified and unidentified trace gases for prescribed fires, Atmos. Chem. Phys., 13, 89–116, https://doi.org/10.5194/acp-13-89-2013, 2013.
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.
We used drones to measure greenhouse gas emission factors from fires in the Brazilian Cerrado....
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