Articles | Volume 26, issue 17
https://doi.org/10.5194/acp-26-12925-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-26-12925-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Hydrological drivers of hydrogen cyanide wildfire emissions from Indonesian peat fires during the 2015, 2019, and 2023 El Niño events
School of Physics and Astronomy, University of Leicester, Leicester, UK
National Centre for Earth Observation, University of Leicester, Leicester, UK
David P. Moore
School of Physics and Astronomy, University of Leicester, Leicester, UK
National Centre for Earth Observation, University of Leicester, Leicester, UK
Jeremy J. Harrison
School of Physics and Astronomy, University of Leicester, Leicester, UK
National Centre for Earth Observation, University of Leicester, Leicester, UK
Ailish Graham
School of Earth and Environment, University of Leeds, Leeds, UK
National Centre for Earth Observation, University of Leeds, Leeds, UK
Martyn P. Chipperfield
School of Earth and Environment, University of Leeds, Leeds, UK
National Centre for Earth Observation, University of Leeds, Leeds, UK
Corinne Vigouroux
Royal Belgian Institute for Space Aeronomy, Brussels, Belgium
Related authors
Antonio G. Bruno, Jeremy J. Harrison, Martyn P. Chipperfield, David P. Moore, Richard J. Pope, Christopher Wilson, Emmanuel Mahieu, and Justus Notholt
Atmos. Chem. Phys., 23, 4849–4861, https://doi.org/10.5194/acp-23-4849-2023, https://doi.org/10.5194/acp-23-4849-2023, 2023
Short summary
Short summary
A 3-D chemical transport model, TOMCAT; satellite data; and ground-based observations have been used to investigate hydrogen cyanide (HCN) variability. We found that the oxidation by O(1D) drives the HCN loss in the middle stratosphere and the currently JPL-recommended OH reaction rate overestimates HCN atmospheric loss. We also evaluated two different ocean uptake schemes. We found them to be unrealistic, and we need to scale these schemes to obtain good agreement with HCN observations.
Wolfgang Woiwode, Bärbel Vogel, Valentin Lauther, Jens-Uwe Grooß, Jeremy Harrison, Sören Johansson, Jörn Ungermann, Peter Braesicke, Markus Dick, Andreas Engel, Felix Friedl-Vallon, Norbert Glatthor, Thomas Gulde, Michael Höpfner, Markus Jesswein, Jan Kaumanns, Timo Keber, Anne Kleinert, Erik Kretschmer, Guido Maucher, Tom Neubert, Hans Nordmeyer, Christof Piesch, Felix Plöger, Peter Preusse, Markus Retzlaff, Sebastian Rhode, Heinz Rongen, Georg Schardt, Tanja Schuck, Björn-Martin Sinnhuber, Johannes Strobel, Franziska Trinkl, Ronja Van Luijt, Stefan Versick, C. Michael Volk, Gerald Wetzel, Peter Hoor, and Martin Riese
EGUsphere, https://doi.org/10.5194/egusphere-2026-3271, https://doi.org/10.5194/egusphere-2026-3271, 2026
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
Filaments of CH2Cl2-rich air are revealed by airborne infrared limb-imaging observations in late summer 2023 above the North Pacific, Canada and Alaska and traced back to the Asian Summer Monsoon region. Involving new spectroscopic data, high CH2Cl2 levels were retrieved in the troposphere and moderate enhancements also in air masses with characteristics of the lowermost stratosphere. Mesoscale filaments are shown to transport substantial amounts of CH2Cl2 across the North Pacific.
Louis Mirallie, Eliane Maillard Barras, Caroline Jonas, Corinne Vigouroux, Roeland Van Malderen, Irina Petropavlovskikh, Sophie Godin-Beekmann, Thierry Leblanc, Wolfgang Steinbrecht, Antoine Vadès, Rolf Ruefenacht, Alexander Haefele, Gunter Stober, Peter Effertz, Julian Gröbner, Gerard Ancellet, María Cazorla, Petra Duff, Matthias M. Frey, Michael Gill, James W. Hannigan, Nicholas Jones, Rigel Kivi, Raphael Köhler, Bogumil Kois, Debra E. Kollonige, Emmanuel Mahieu, Glen McConville, Johan Mellqvist, Gary Morris, Isao Murata, Tomoo Nagahama, Gerald E. Nedoluha, Shin-Ya Ogino, Richard Querel, Ryan M. Stauffer, Wolfgang Stremme, Kimberly Strong, Ralf Sussmann, Anne M. Thompson, and Yana Virolainen
Atmos. Chem. Phys., 26, 10303–10330, https://doi.org/10.5194/acp-26-10303-2026, https://doi.org/10.5194/acp-26-10303-2026, 2026
Short summary
Short summary
We present regional Bayesian composites of ground-based ozone partial column records. Defining coherent regions using a CAMS (Copernicus Atmosphere Monitoring Service) representativeness study, we merge five instrument types using the BASIC (Ball et al., 2017) algorithm, reducing trend uncertainties by 9.4 % compared to a weighted mean. Results confirm upper stratospheric recovery, predominantly negative middle stratospheric trends, while lower stratospheric trends remain mostly non-significant.
Dominique Gantois, Alexandre Baron, Michaël Sicard, Valentin Duflot, Niels Groenen, Nelson Bègue, Sabine Eckhardt, Nikolaos Evangeliou, Martine De Mazière, Corinne Vigouroux, Guillaume Payen, Nicolas Marquestaut, Jean-Marc Metzger, Patrick Chazette, and Cyrille Flamant
EGUsphere, https://doi.org/10.5194/egusphere-2026-3070, https://doi.org/10.5194/egusphere-2026-3070, 2026
Short summary
Short summary
Smoke from Southern African and South American wildfires can travel for thousands of kilometers before reaching the Indian Ocean and Reunion Island. In this study, we use instruments measuring from the ground, from satellites, as well as atmospheric models, to track these smoke plumes and identify their origins and properties. Our findings should help future research focusing on the impact of these plumes on the atmospheric temperature.
Ailish M. Graham, Dominick V. Spracklen, James B. McQuaid, Richard Rigby, Hanun Nurrahmawati, Devina Ayona, Resti Salmayenti, Kitso Kusin, Adi Jaya, Thomas E. L. Smith, Annisa Alifindira, Shofwan Al Banna Choiruzzad, and Richard Pope
EGUsphere, https://doi.org/10.5194/egusphere-2026-2746, https://doi.org/10.5194/egusphere-2026-2746, 2026
Short summary
Short summary
Indonesia peatlands have been extensively drained for agriculture, but this makes them very flammable in periods of drought, causing widespread air pollution. We measured fine particulate pollution across Central Kalimantan from 2023 to 2025 using >40 sensors. Pollution was highest during dry El Niño conditions but still degraded air pollution in wetter years. Thus, showing that climate strongly controls fires and air quality, and that reducing fires could improve air quality every year.
Irina Petropavlovskikh, Martine De Mazière, Anne M. Thompson, Jeannette D. Wild, James W. Hannigan, Henry B. Selkirk, Reem A. Hannun, Wolfgang Steinbrecht, Jean-Christopher Lambert, Roeland Van Malderen, Elizabeth Asher, Raul R. Cordero, Sophie Godin-Beekmann, Daan Hubert, Sergey Khaykin, Karin Kreher, Thierry Leblanc, Emmanuel Mahieu, Eliane Maillard Barras, Glen McConville, Gerald Nedoluha, Ivan Ortega, Alberto Redondas Marrero, Gunther Seckmeyer, Ryan M. Stauffer, Sarah A. Strode, Kim Strong, Takafumi Sugita, Michel Van Roozendael, Voltaire Velazco, Corinne Vigouroux, and Bärbel Vogel
Atmos. Chem. Phys., 26, 8637–8675, https://doi.org/10.5194/acp-26-8637-2026, https://doi.org/10.5194/acp-26-8637-2026, 2026
Short summary
Short summary
This introduction to the special issue "Achievements and perspectives of the Network for the Detection of Atmospheric Composition Change after 35 years of operation” provides an overview of important research findings achieved under the NDACC objectives. The future of NDACC is discussed in the light of the evolution of the scientific questions, evolving collaborations with partners and Cooperating Networks, and the current landscape of gaps in satellite and ground-based observations.
Beatriz Herrera, Enrico Dammers, Martine De Maziere, Omaira Garcia, Michel Grutter, James W. Hannigan, Dylan B. A. Jones, Nicholas Jones, Emmanuel Mahieu, Maria Makarova, Kazuyuki Miyazaki, Isamu Morino, Isao Murata, Ivan Ortega, Mathias Palm, Anatoly Poverovskii, Takashi Sekiya, Dan Smale, Hannah Sill, Wolfgang Stremme, Ralf Sussmann, Geoffrey Toon, Corinne Vigouroux, Wei Wang, Tyler Wizenberg, and Kimberly Strong
EGUsphere, https://doi.org/10.5194/egusphere-2026-3138, https://doi.org/10.5194/egusphere-2026-3138, 2026
Short summary
Short summary
This work investigates how atmospheric ammonia changes over time using long-term observations and simulations at locations around the world. While its main sources are related to agriculture, wildfires, vehicles, and volcanoes also contribute. The results show that ammonia levels vary strongly during the day and across seasons, and are rising at most locations. These findings improve our understanding of air pollution and its impacts.
Caroline Jonas, Corinne Vigouroux, Bavo Langerock, Robin Björklund, Anne Boynard, Thomas Carlund, Martine De Mazière, Peter Effertz, Quentin Errera, Matthias M. Frey, José Granville, James W. Hannigan, Arno Keppens, Nis Jepsen, Rigel Kivi, Norrie Lyall, Mathias Palm, Maxime Prignon, Viktoria F. Sofieva, Kimberly Strong, Tove Svendby, David Tarasick, Laura Thölix, Roeland Van Malderen, Yana Virolainen, Sibylle von Löwis, and Xiaoyi Zhao
Atmos. Chem. Phys., 26, 8089–8124, https://doi.org/10.5194/acp-26-8089-2026, https://doi.org/10.5194/acp-26-8089-2026, 2026
Short summary
Short summary
We study the evolution of ozone in the Arctic over the 2000–2024 period in the stratosphere (about 10 to 50 km) to assess the expected recovery of the ozone layer following the diminution of ozone-depleting substances. We merge ground-based data sets within spatially coherent regions to reduce uncertainties and we obtain positive trends for the total column everywhere in the Arctic and for the middle and upper stratosphere over Canada, but no significant trends in the lower stratosphere.
Viktoria F. Sofieva, Monika E. Szelag, Natalya A. Kramarova, Robert Damadeo, Wolfgang Steinbrecht, Irina Petropavlovskikh, Corinne Vigouroux, Eliane Maillard Barras, Daniel Zawada, Kleareti Tourpali, Stacey M. Frith, Jeannette D. Wild, Sean M. Davis, Carlo Arosio, Mark Weber, Alexei Rozanov, Brian Auffarth, Lucien Froidevaux, Ryan Fuller, Doug Degenstein, Kimberlee Dube, Peter Effertz, Thierry Leblanc, Gérard Ancellet, Sophie Godin-Beekmann, Glen McConville, Richard Querel, Dan Smale, Marie-Renee DeBacker, Emmanuel Mahieu, and Ralf Sussmann
Atmos. Chem. Phys., 26, 7387–7405, https://doi.org/10.5194/acp-26-7387-2026, https://doi.org/10.5194/acp-26-7387-2026, 2026
Short summary
Short summary
We present an updated evaluation of stratospheric ozone profile trends in the 60°S–60°N latitude range using long-term ground-based and satellite climate data records, as well as simulations by chemistry-climate models. Analyses confirm the statistically significant positive ozone trends in the upper stratosphere of ~1–3 % decade-1. The trends are close to zero in the middle stratosphere, and mostly negative in the lower stratosphere, but they are not statistically significant.
Xiaoyi Zhao, Vitali Fioletov, Irina Petropavlovskikh, Voltaire Velazco, Alberto Redondas, Anna Solomatnikova, Corinne Vigouroux, Kimberly Strong, Michel Van Roozendael, Andrea Pazmino, Thomas F. Hanisco, Alexander Cede, Martin Tiefengraber, Gordon Labow, Masatomo Fujiwara, Ronald van der A, Debora Griffin, Chris McLinden, Tom Kralidis, Wolfgang Steinbrecht, and Sum Chi Lee
EGUsphere, https://doi.org/10.5194/egusphere-2026-2009, https://doi.org/10.5194/egusphere-2026-2009, 2026
Short summary
Short summary
Total column ozone (TCO) records from six ground-based networks are compiled and evaluated using multiple satellites and reanalysis data. Station performance (1940–2024) is assessed using harmonized metrics. Ground-based annual means agree within ±2 %, while pre-satellite reanalyses show larger biases (up to −5 %). The resulting quality-assessed dataset supports trend analysis and satellite validation.
Jean-François Müller, Trissevgeni Stavrakou, Bruno Franco, Lieven Clarisse, Crist Amelynck, Niels Schoon, Bert W. D. Verreyken, Beata Opacka, Corinne Vigouroux, Alex B. Guenther, Emmanuel Mahieu, Maria Makarova, and Kimberly Strong
Atmos. Chem. Phys., 26, 5375–5406, https://doi.org/10.5194/acp-26-5375-2026, https://doi.org/10.5194/acp-26-5375-2026, 2026
Short summary
Short summary
We use an atmospheric model and aircraft measurements to evaluate methanol measurements from satellite sensors. The spaceborne data are found to be too low over source regions. Next, we use the model and the bias-corrected satellite data to derive improved terrestrial emissions of methanol between 2008 and 2019, and we evaluate the results against aircraft and ground-based measurements. This work shows that biogenic emissions of methanol might be ~ 60 % larger than previously estimated.
Bavo Langerock, Minqiang Zhou, Martine De Mazière, Mahesh Kumar Sha, Filip Desmet, Bart Dils, Corinne Vigouroux, Rigel Kivi, Isamu Morino, Mathias Palm, Gopala Krishna Darbha, Soumik Banerjee, Sujata Ray, and Mohmmed Talib
EGUsphere, https://doi.org/10.5194/egusphere-2026-1890, https://doi.org/10.5194/egusphere-2026-1890, 2026
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
Short summary
Short summary
This work describes an algorithm to correct measurements obtained from Fourier-Transform Infrared spectrometers (FTIR) for nonlinear detector response. The method is demonstrated for remote sensing observational networks for atmospheric gas products (NDACC, TCCON and COCCON). Diagnostic metrics are introduced and have the potential to characterize the cause of the underlying nonlinearity (saturation or optical misalignment). The algorithm is made available in python.
Maria P. Velásquez-García, Richard J. Pope, Steven T. Turnock, Chetan Deva, David P. Moore, Guilherme Mataveli, Steve R. Arnold, Ruth M. Doherty, and Martyn P. Chipperfield
Biogeosciences, 23, 1341–1364, https://doi.org/10.5194/bg-23-1341-2026, https://doi.org/10.5194/bg-23-1341-2026, 2026
Short summary
Short summary
Incorporating fire simulation into climate models is crucial for accurately representing interactions between fires, ecosystems, and climate, thereby enhancing climate projections. In South America, the INFERNO (Interactive Fires and Emissions algorithm for Natural Environments) fire model broadly captures CO emissions in active fire zones, e.g., the Amazon Arc of Deforestation. Still, it tends to overestimate emissions in tree-rich ecosystems, where INFERNO is too sensitive to low soil moisture, and to underestimate emissions in less tree-abundant ecosystems.
Gaia Pinardi, Martina M. Friedrich, Corinne Vigouroux, Bavo Langerock, Isabelle De Smedt, Caroline Fayt, Christian Hermans, Steffen Beirle, Thomas Wagner, Minqiang Zhou, Ting Wang, Pucai Wang, Martine De Mazière, and Michel Van Roozendael
Atmos. Meas. Tech., 19, 1259–1291, https://doi.org/10.5194/amt-19-1259-2026, https://doi.org/10.5194/amt-19-1259-2026, 2026
Short summary
Short summary
We evaluate ground-based remote-sensing measurements of formaldehyde from three techniques at a suburban site in China. A systematic −20 % bias in Multi-AXis Differential Optical Absorption Spectroscopy compared to direct-sun ultraviolet and infrared data is linked to limited sensitivity above a few kilometers and simplified vertical profiles assumptions. Using model-based priors and accounting for vertical sensitivity removes these differences, improving consistency for satellite validation.
Daniel J. L. Coxon, Jeremy J. Harrison, D. Chris Benner, and V. Malathy Devi
Atmos. Meas. Tech., 18, 7421–7444, https://doi.org/10.5194/amt-18-7421-2025, https://doi.org/10.5194/amt-18-7421-2025, 2025
Short summary
Short summary
Ammonia, a toxic gas produced largely through agricultural emissions, is one of the key pollutants that can be monitored by satellite instruments orbiting the Earth. Satellites rely on accurate spectral line parameters to interpret their data, which are obtained through fitting data from lab-based measurements. This work performs such experiments on the ammonia ν2 band, determining new line parameters which will provide a more accurate basis for modelling satellite measurements of ammonia.
Michael P. Cartwright, Jeremy J. Harrison, David P. Moore, Richard J. Pope, Martyn P. Chipperfield, Chris Wilson, and Wuhu Feng
Atmos. Chem. Phys., 25, 15913–15934, https://doi.org/10.5194/acp-25-15913-2025, https://doi.org/10.5194/acp-25-15913-2025, 2025
Short summary
Short summary
We use satellite measurements to estimate quantities of a gas called carbonyl sulfide (OCS) in the atmosphere. OCS is consumed during photosynthesis, much like carbon dioxide (CO2). Our data is focused mostly over the global oceans for the year 2018, and we find it compares well with past satellite observations, ground-based measurements and modelled OCS. We hope to extend this measurement record and use it in data-driven tools in the future to better understand the carbon cycle globally.
Roeland Van Malderen, Zhou Zang, Kai-Lan Chang, Robin Björklund, Owen R. Cooper, Jane Liu, Eliane Maillard Barras, Corinne Vigouroux, Irina Petropavlovskikh, Thierry Leblanc, Valérie Thouret, Pawel Wolff, Peter Effertz, Audrey Gaudel, David W. Tarasick, Herman G. J. Smit, Anne M. Thompson, Ryan M. Stauffer, Debra E. Kollonige, Deniz Poyraz, Gérard Ancellet, Marie-Renée De Backer, Matthias M. Frey, James W. Hannigan, José L. Hernandez, Bryan J. Johnson, Nicholas Jones, Rigel Kivi, Emmanuel Mahieu, Isamu Morino, Glen McConville, Katrin Müller, Isao Murata, Justus Notholt, Ankie Piters, Maxime Prignon, Richard Querel, Vincenzo Rizi, Dan Smale, Wolfgang Steinbrecht, Kimberly Strong, and Ralf Sussmann
Atmos. Chem. Phys., 25, 9905–9935, https://doi.org/10.5194/acp-25-9905-2025, https://doi.org/10.5194/acp-25-9905-2025, 2025
Short summary
Short summary
Tropospheric ozone is an important greenhouse gas and an air pollutant whose distribution and time variability are mainly governed by anthropogenic emissions and dynamics. In this paper, we assess regional trends of tropospheric ozone column amounts, based on two different approaches of merging or synthesizing ground-based observations and their trends within specific regions. Our findings clearly demonstrate regional trend differences but also consistently higher pre-COVID than post-COVID trends.
Roeland Van Malderen, Anne M. Thompson, Debra E. Kollonige, Ryan M. Stauffer, Herman G. J. Smit, Eliane Maillard Barras, Corinne Vigouroux, Irina Petropavlovskikh, Thierry Leblanc, Valérie Thouret, Pawel Wolff, Peter Effertz, David W. Tarasick, Deniz Poyraz, Gérard Ancellet, Marie-Renée De Backer, Stéphanie Evan, Victoria Flood, Matthias M. Frey, James W. Hannigan, José L. Hernandez, Marco Iarlori, Bryan J. Johnson, Nicholas Jones, Rigel Kivi, Emmanuel Mahieu, Glen McConville, Katrin Müller, Tomoo Nagahama, Justus Notholt, Ankie Piters, Natalia Prats, Richard Querel, Dan Smale, Wolfgang Steinbrecht, Kimberly Strong, and Ralf Sussmann
Atmos. Chem. Phys., 25, 7187–7225, https://doi.org/10.5194/acp-25-7187-2025, https://doi.org/10.5194/acp-25-7187-2025, 2025
Short summary
Short summary
Tropospheric ozone is an important greenhouse gas and is an air pollutant. The time variability of tropospheric ozone is mainly driven by anthropogenic emissions. In this paper, we study the distribution and time variability of ozone from harmonized ground-based observations from five different measurement techniques. Our findings provide clear standard references for atmospheric models and evolving tropospheric ozone satellite data for the 2000–2022 period.
Catalina Poraicu, Jean-François Müller, Trissevgeni Stavrakou, Crist Amelynck, Bert W. D. Verreyken, Niels Schoon, Corinne Vigouroux, Nicolas Kumps, Jérôme Brioude, Pierre Tulet, and Camille Mouchel-Vallon
Atmos. Chem. Phys., 25, 6903–6941, https://doi.org/10.5194/acp-25-6903-2025, https://doi.org/10.5194/acp-25-6903-2025, 2025
Short summary
Short summary
We investigated the sources and impacts of nitrogen oxides and organic compounds over a remote tropical island. Simulations of the high-resolution Weather Research and Forecasting model coupled with chemistry (WRF-Chem) were evaluated using in situ Fourier transform infrared spectroscopy (FTIR) and satellite measurements. This work highlights gaps in current models, like missing sources of key organic compounds and inaccuracies in emission inventories, emphasizing the importance of improving chemical and dynamical processes in atmospheric modelling for budget estimates in tropical regions.
Bavo Langerock, Martine De Mazière, Filip Desmet, Pauli Heikkinen, Rigel Kivi, Mahesh Kumar Sha, Corinne Vigouroux, Minqiang Zhou, Gopala Krishna Darbha, and Mohmmed Talib
Atmos. Meas. Tech., 18, 2439–2446, https://doi.org/10.5194/amt-18-2439-2025, https://doi.org/10.5194/amt-18-2439-2025, 2025
Short summary
Short summary
Ground-based Fourier transform interferometer instruments have been used for many decades to measure direct solar light in the infrared to obtain high-resolution spectra from which atmospheric gas profile concentrations can be derived. It is shown that the typical processing chain used to derive atmospheric gas columns can be sensitive to relatively small shortenings of the recorded interferograms. Low-resolution recordings, used in more recent years, are more sensitive to such adaptations.
Amir H. Souri, Gonzalo González Abad, Glenn M. Wolfe, Tijl Verhoelst, Corinne Vigouroux, Gaia Pinardi, Steven Compernolle, Bavo Langerock, Bryan N. Duncan, and Matthew S. Johnson
Atmos. Chem. Phys., 25, 2061–2086, https://doi.org/10.5194/acp-25-2061-2025, https://doi.org/10.5194/acp-25-2061-2025, 2025
Short summary
Short summary
We establish a simple yet robust relationship between ozone production rates and geophysical parameters obtained from several intensive atmospheric composition campaigns. We show that satellite remote sensing data can effectively constrain these parameters, enabling us to produce the first global maps of ozone production rates with unprecedented resolution.
Aishah I. Shittu, Kirsty J. Pringle, Stephen R. Arnold, Richard J. Pope, Ailish M. Graham, Carly Reddington, Richard Rigby, and James B. McQuaid
Atmos. Meas. Tech., 18, 817–828, https://doi.org/10.5194/amt-18-817-2025, https://doi.org/10.5194/amt-18-817-2025, 2025
Short summary
Short summary
The study highlighted the performance of Atmotube PRO sensor particulate matter (PM) data. The result showed inter-sensor variability among the Atmotube PRO sensor data. This study showed 62.5 % of the sensors used for the study exhibited greater precision in their PM2.5 measurements. The overall performance showed that sensors passed the base testing using 1 h averaged data and that a multiple linear regression model using relative humidity values improved the performance of the PM2.5 data.
Kelley C. Wells, Dylan B. Millet, Jared F. Brewer, Vivienne H. Payne, Karen E. Cady-Pereira, Rick Pernak, Susan Kulawik, Corinne Vigouroux, Nicholas Jones, Emmanuel Mahieu, Maria Makarova, Tomoo Nagahama, Ivan Ortega, Mathias Palm, Kimberly Strong, Matthias Schneider, Dan Smale, Ralf Sussmann, and Minqiang Zhou
Atmos. Meas. Tech., 18, 695–716, https://doi.org/10.5194/amt-18-695-2025, https://doi.org/10.5194/amt-18-695-2025, 2025
Short summary
Short summary
Atmospheric volatile organic compounds (VOCs) affect both air quality and climate. Satellite measurements can help us to assess and predict their global impacts. We present new decadal (2012–2023) measurements of four key VOCs – methanol, ethene, ethyne, and hydrogen cyanide (HCN) – from the Cross-track Infrared Sounder. The measurements reflect emissions from major forests, wildfires, and industry and provide new information to advance understanding of these sources and their changes over time.
Robin Björklund, Corinne Vigouroux, Peter Effertz, Omaira E. García, Alex Geddes, James Hannigan, Koji Miyagawa, Michael Kotkamp, Bavo Langerock, Gerald Nedoluha, Ivan Ortega, Irina Petropavlovskikh, Deniz Poyraz, Richard Querel, John Robinson, Hisako Shiona, Dan Smale, Penny Smale, Roeland Van Malderen, and Martine De Mazière
Atmos. Meas. Tech., 17, 6819–6849, https://doi.org/10.5194/amt-17-6819-2024, https://doi.org/10.5194/amt-17-6819-2024, 2024
Short summary
Short summary
Different ground-based ozone measurements from the last 2 decades at Lauder are compared to each other. We want to know why different trends have been observed in the stratosphere. Also, the quality and relevance of tropospheric datasets need to be evaluated. While remaining drifts are still present, our study explains roughly half of the differences in observed trends in previous studies and shows the necessity for continuous review and improvement of the measurements.
Connor J. Clayton, Daniel R. Marsh, Steven T. Turnock, Ailish M. Graham, Kirsty J. Pringle, Carly L. Reddington, Rajesh Kumar, and James B. McQuaid
Atmos. Chem. Phys., 24, 10717–10740, https://doi.org/10.5194/acp-24-10717-2024, https://doi.org/10.5194/acp-24-10717-2024, 2024
Short summary
Short summary
We demonstrate that strong climate mitigation could improve air quality in Europe; however, less ambitious mitigation does not result in these co-benefits. We use a high-resolution atmospheric chemistry model. This allows us to demonstrate how this varies across European countries and analyse the underlying chemistry. This may help policy-facing researchers understand which sectors and regions need to be prioritised to achieve strong air quality co-benefits of climate mitigation.
Chris Wilson, Brian J. Kerridge, Richard Siddans, David P. Moore, Lucy J. Ventress, Emily Dowd, Wuhu Feng, Martyn P. Chipperfield, and John J. Remedios
Atmos. Chem. Phys., 24, 10639–10653, https://doi.org/10.5194/acp-24-10639-2024, https://doi.org/10.5194/acp-24-10639-2024, 2024
Short summary
Short summary
The leaks from the Nord Stream gas pipelines in September 2022 released a large amount of methane (CH4) into the atmosphere. We provide observational data from a satellite instrument that shows a large CH4 plume over the North Sea off the coast of Scandinavia. We use this together with atmospheric models to quantify the CH4 leaked into the atmosphere from the pipelines. We find that 219–427 Gg CH4 was emitted, making this the largest individual fossil-fuel-related CH4 leak on record.
Gitaek T. Lee, Rokjin J. Park, Hyeong-Ahn Kwon, Eunjo S. Ha, Sieun D. Lee, Seunga Shin, Myoung-Hwan Ahn, Mina Kang, Yong-Sang Choi, Gyuyeon Kim, Dong-Won Lee, Deok-Rae Kim, Hyunkee Hong, Bavo Langerock, Corinne Vigouroux, Christophe Lerot, Francois Hendrick, Gaia Pinardi, Isabelle De Smedt, Michel Van Roozendael, Pucai Wang, Heesung Chong, Yeseul Cho, and Jhoon Kim
Atmos. Chem. Phys., 24, 4733–4749, https://doi.org/10.5194/acp-24-4733-2024, https://doi.org/10.5194/acp-24-4733-2024, 2024
Short summary
Short summary
This study evaluates the Geostationary Environment Monitoring Spectrometer (GEMS) HCHO product by comparing its vertical column densities (VCDs) with those of TROPOMI and ground-based observations. Based on some sensitivity tests, obtaining radiance references under clear-sky conditions significantly improves HCHO retrieval quality. GEMS HCHO VCDs captured seasonal and diurnal variations well during the first year of observation, showing consistency with TROPOMI and ground-based observations.
Jean-François Müller, Trissevgeni Stavrakou, Glenn-Michael Oomen, Beata Opacka, Isabelle De Smedt, Alex Guenther, Corinne Vigouroux, Bavo Langerock, Carlos Augusto Bauer Aquino, Michel Grutter, James Hannigan, Frank Hase, Rigel Kivi, Erik Lutsch, Emmanuel Mahieu, Maria Makarova, Jean-Marc Metzger, Isamu Morino, Isao Murata, Tomoo Nagahama, Justus Notholt, Ivan Ortega, Mathias Palm, Amelie Röhling, Wolfgang Stremme, Kimberly Strong, Ralf Sussmann, Yao Té, and Alan Fried
Atmos. Chem. Phys., 24, 2207–2237, https://doi.org/10.5194/acp-24-2207-2024, https://doi.org/10.5194/acp-24-2207-2024, 2024
Short summary
Short summary
Formaldehyde observations from satellites can be used to constrain the emissions of volatile organic compounds, but those observations have biases. Using an atmospheric model, aircraft and ground-based remote sensing data, we quantify these biases, propose a correction to the data, and assess the consequence of this correction for the evaluation of emissions.
Ailish M. Graham, Richard J. Pope, Martyn P. Chipperfield, Sandip S. Dhomse, Matilda Pimlott, Wuhu Feng, Vikas Singh, Ying Chen, Oliver Wild, Ranjeet Sokhi, and Gufran Beig
Atmos. Chem. Phys., 24, 789–806, https://doi.org/10.5194/acp-24-789-2024, https://doi.org/10.5194/acp-24-789-2024, 2024
Short summary
Short summary
Our paper uses novel satellite datasets and high-resolution emissions datasets alongside a back-trajectory model to investigate the balance of local and external sources influencing NOx air pollution changes in Delhi. We find in the post-monsoon season that NOx from local and non-local transport emissions contributes most to poor air quality in Delhi. Therefore, air quality mitigation strategies in Delhi and surrounding regions are used to control this issue.
Glenn-Michael Oomen, Jean-François Müller, Trissevgeni Stavrakou, Isabelle De Smedt, Thomas Blumenstock, Rigel Kivi, Maria Makarova, Mathias Palm, Amelie Röhling, Yao Té, Corinne Vigouroux, Martina M. Friedrich, Udo Frieß, François Hendrick, Alexis Merlaud, Ankie Piters, Andreas Richter, Michel Van Roozendael, and Thomas Wagner
Atmos. Chem. Phys., 24, 449–474, https://doi.org/10.5194/acp-24-449-2024, https://doi.org/10.5194/acp-24-449-2024, 2024
Short summary
Short summary
Natural emissions from vegetation have a profound impact on air quality for their role in the formation of harmful tropospheric ozone and organic aerosols, yet these emissions are highly uncertain. In this study, we quantify emissions of organic gases over Europe using high-quality satellite measurements of formaldehyde. These satellite observations suggest that emissions from vegetation are much higher than predicted by models, especially in southern Europe.
Richard J. Pope, Brian J. Kerridge, Martyn P. Chipperfield, Richard Siddans, Barry G. Latter, Lucy J. Ventress, Matilda A. Pimlott, Wuhu Feng, Edward Comyn-Platt, Garry D. Hayman, Stephen R. Arnold, and Ailish M. Graham
Atmos. Chem. Phys., 23, 13235–13253, https://doi.org/10.5194/acp-23-13235-2023, https://doi.org/10.5194/acp-23-13235-2023, 2023
Short summary
Short summary
In the summer of 2018, Europe experienced several persistent large-scale ozone (O3) pollution episodes. Satellite tropospheric O3 and surface O3 data recorded substantial enhancements in 2018 relative to other years. Targeted model simulations showed that meteorological processes and emissions controlled the elevated surface O3, while mid-tropospheric O3 enhancements were dominated by stratospheric O3 intrusion and advection of North Atlantic O3-rich air masses into Europe.
Michael P. Cartwright, Richard J. Pope, Jeremy J. Harrison, Martyn P. Chipperfield, Chris Wilson, Wuhu Feng, David P. Moore, and Parvadha Suntharalingam
Atmos. Chem. Phys., 23, 10035–10056, https://doi.org/10.5194/acp-23-10035-2023, https://doi.org/10.5194/acp-23-10035-2023, 2023
Short summary
Short summary
A 3-D chemical transport model, TOMCAT, is used to simulate global atmospheric carbonyl sulfide (OCS) distribution. Modelled OCS compares well with satellite observations of OCS from limb-sounding satellite observations. Model simulations also compare adequately with surface and atmospheric observations and suitably capture the seasonality of OCS and background concentrations.
Antonio G. Bruno, Jeremy J. Harrison, Martyn P. Chipperfield, David P. Moore, Richard J. Pope, Christopher Wilson, Emmanuel Mahieu, and Justus Notholt
Atmos. Chem. Phys., 23, 4849–4861, https://doi.org/10.5194/acp-23-4849-2023, https://doi.org/10.5194/acp-23-4849-2023, 2023
Short summary
Short summary
A 3-D chemical transport model, TOMCAT; satellite data; and ground-based observations have been used to investigate hydrogen cyanide (HCN) variability. We found that the oxidation by O(1D) drives the HCN loss in the middle stratosphere and the currently JPL-recommended OH reaction rate overestimates HCN atmospheric loss. We also evaluated two different ocean uptake schemes. We found them to be unrealistic, and we need to scale these schemes to obtain good agreement with HCN observations.
Amir H. Souri, Matthew S. Johnson, Glenn M. Wolfe, James H. Crawford, Alan Fried, Armin Wisthaler, William H. Brune, Donald R. Blake, Andrew J. Weinheimer, Tijl Verhoelst, Steven Compernolle, Gaia Pinardi, Corinne Vigouroux, Bavo Langerock, Sungyeon Choi, Lok Lamsal, Lei Zhu, Shuai Sun, Ronald C. Cohen, Kyung-Eun Min, Changmin Cho, Sajeev Philip, Xiong Liu, and Kelly Chance
Atmos. Chem. Phys., 23, 1963–1986, https://doi.org/10.5194/acp-23-1963-2023, https://doi.org/10.5194/acp-23-1963-2023, 2023
Short summary
Short summary
We have rigorously characterized different sources of error in satellite-based HCHO / NO2 tropospheric columns, a widely used metric for diagnosing near-surface ozone sensitivity. Specifically, the errors were categorized/quantified into (i) an inherent chemistry error, (ii) the decoupled relationship between columns and the near-surface concentration, (iii) the spatial representativeness error of ground satellite pixels, and (iv) the satellite retrieval errors.
Minqiang Zhou, Bavo Langerock, Pucai Wang, Corinne Vigouroux, Qichen Ni, Christian Hermans, Bart Dils, Nicolas Kumps, Weidong Nan, and Martine De Mazière
Atmos. Meas. Tech., 16, 273–293, https://doi.org/10.5194/amt-16-273-2023, https://doi.org/10.5194/amt-16-273-2023, 2023
Short summary
Short summary
The ground-based FTIR measurements at Xianghe provide carbon monoxide (CO), acetylene (C2H2), ethane (C2H6), formaldehyde (H2CO), and hydrogen cyanide (HCN) total columns between June 2018 and November 2021. The retrieval strategies, information, and uncertainties of these five important trace gases are presented and discussed. This study provides insight into the time series, variations, and correlations of these five species in northern China.
Sophie Godin-Beekmann, Niramson Azouz, Viktoria F. Sofieva, Daan Hubert, Irina Petropavlovskikh, Peter Effertz, Gérard Ancellet, Doug A. Degenstein, Daniel Zawada, Lucien Froidevaux, Stacey Frith, Jeannette Wild, Sean Davis, Wolfgang Steinbrecht, Thierry Leblanc, Richard Querel, Kleareti Tourpali, Robert Damadeo, Eliane Maillard Barras, René Stübi, Corinne Vigouroux, Carlo Arosio, Gerald Nedoluha, Ian Boyd, Roeland Van Malderen, Emmanuel Mahieu, Dan Smale, and Ralf Sussmann
Atmos. Chem. Phys., 22, 11657–11673, https://doi.org/10.5194/acp-22-11657-2022, https://doi.org/10.5194/acp-22-11657-2022, 2022
Short summary
Short summary
An updated evaluation up to 2020 of stratospheric ozone profile long-term trends at extrapolar latitudes based on satellite and ground-based records is presented. Ozone increase in the upper stratosphere is confirmed, with significant trends at most latitudes. In this altitude region, a very good agreement is found with trends derived from chemistry–climate model simulations. Observed and modelled trends diverge in the lower stratosphere, but the differences are non-significant.
Minqiang Zhou, Bavo Langerock, Pucai Wang, Corinne Vigouroux, Qichen Ni, Christian Hermans, Bart Dils, Nicolas Kumps, Weidong Nan, and Martine De Mazière
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2022-354, https://doi.org/10.5194/acp-2022-354, 2022
Revised manuscript not accepted
Short summary
Short summary
The ground-based FTIR measurements at Xianghe provide carbon monoxide (CO), acetylene (C2H2), ethane (C2H6), formaldehyde (H2CO), and hydrogen cyanide (HCN) total columns between June 2018 and November 2021. The retrieval strategies, retrieval information, and uncertainties of these five important trace gases are presented and discussed. This study provides an insight into the time series, variations, and correlations of these five species in North China.
Richard J. Pope, Rebecca Kelly, Eloise A. Marais, Ailish M. Graham, Chris Wilson, Jeremy J. Harrison, Savio J. A. Moniz, Mohamed Ghalaieny, Steve R. Arnold, and Martyn P. Chipperfield
Atmos. Chem. Phys., 22, 4323–4338, https://doi.org/10.5194/acp-22-4323-2022, https://doi.org/10.5194/acp-22-4323-2022, 2022
Short summary
Short summary
Nitrogen oxides (NOx) are potent air pollutants which directly impact on human health. In this study, we use satellite nitrogen dioxide (NO2) data to evaluate the spatial distribution and temporal evolution of the UK official NOx emissions inventory, with reasonable agreement. We also derived satellite-based NOx emissions for several UK cities. In the case of London and Birmingham, the NAEI NOx emissions are potentially too low by >50%.
Piera Raspollini, Enrico Arnone, Flavio Barbara, Massimo Bianchini, Bruno Carli, Simone Ceccherini, Martyn P. Chipperfield, Angelika Dehn, Stefano Della Fera, Bianca Maria Dinelli, Anu Dudhia, Jean-Marie Flaud, Marco Gai, Michael Kiefer, Manuel López-Puertas, David P. Moore, Alessandro Piro, John J. Remedios, Marco Ridolfi, Harjinder Sembhi, Luca Sgheri, and Nicola Zoppetti
Atmos. Meas. Tech., 15, 1871–1901, https://doi.org/10.5194/amt-15-1871-2022, https://doi.org/10.5194/amt-15-1871-2022, 2022
Short summary
Short summary
The MIPAS instrument onboard the ENVISAT satellite provided 10 years of measurements of the atmospheric emission al limb that allow for the retrieval of latitude- and altitude-resolved atmospheric composition. We describe the improvements implemented in the retrieval algorithm used for the full mission reanalysis, which allows for the generation of the global distributions of 21 atmospheric constituents plus temperature with increased accuracy with respect to previously generated data.
Mahesh Kumar Sha, Bavo Langerock, Jean-François L. Blavier, Thomas Blumenstock, Tobias Borsdorff, Matthias Buschmann, Angelika Dehn, Martine De Mazière, Nicholas M. Deutscher, Dietrich G. Feist, Omaira E. García, David W. T. Griffith, Michel Grutter, James W. Hannigan, Frank Hase, Pauli Heikkinen, Christian Hermans, Laura T. Iraci, Pascal Jeseck, Nicholas Jones, Rigel Kivi, Nicolas Kumps, Jochen Landgraf, Alba Lorente, Emmanuel Mahieu, Maria V. Makarova, Johan Mellqvist, Jean-Marc Metzger, Isamu Morino, Tomoo Nagahama, Justus Notholt, Hirofumi Ohyama, Ivan Ortega, Mathias Palm, Christof Petri, David F. Pollard, Markus Rettinger, John Robinson, Sébastien Roche, Coleen M. Roehl, Amelie N. Röhling, Constantina Rousogenous, Matthias Schneider, Kei Shiomi, Dan Smale, Wolfgang Stremme, Kimberly Strong, Ralf Sussmann, Yao Té, Osamu Uchino, Voltaire A. Velazco, Corinne Vigouroux, Mihalis Vrekoussis, Pucai Wang, Thorsten Warneke, Tyler Wizenberg, Debra Wunch, Shoma Yamanouchi, Yang Yang, and Minqiang Zhou
Atmos. Meas. Tech., 14, 6249–6304, https://doi.org/10.5194/amt-14-6249-2021, https://doi.org/10.5194/amt-14-6249-2021, 2021
Short summary
Short summary
This paper presents, for the first time, Sentinel-5 Precursor methane and carbon monoxide validation results covering a period from November 2017 to September 2020. For this study, we used global TCCON and NDACC-IRWG network data covering a wide range of atmospheric and surface conditions across different terrains. We also show the influence of a priori alignment, smoothing uncertainties and the sensitivity of the validation results towards the application of advanced co-location criteria.
Minqiang Zhou, Bavo Langerock, Corinne Vigouroux, Bart Dils, Christian Hermans, Nicolas Kumps, Weidong Nan, Jean-Marc Metzger, Emmanuel Mahieu, Ting Wang, Pucai Wang, and Martine De Mazière
Atmos. Meas. Tech., 14, 6233–6247, https://doi.org/10.5194/amt-14-6233-2021, https://doi.org/10.5194/amt-14-6233-2021, 2021
Short summary
Short summary
NO is a key active trace gas in the atmosphere, which affects the atmospheric environment and human health. In this study, we show that the tropospheric and stratospheric NO partial columns can be observed from the ground-based FTIR measurements at a polluted site (Xianghe, China), but only stratospheric NO partial columns can be observed at a background site (Maïdo, Reunion Island). The variations in the NO observed by the FTIR measurements at the two sites are analyzed and discussed.
Cited articles
Akagi, S. K., Yokelson, R. J., Wiedinmyer, C., Alvarado, M. J., Reid, J. S., Karl, T., Crounse, J. D., and Wennberg, P. O.: Emission factors for open and domestic biomass burning for use in atmospheric models, Atmos. Chem. Phys., 11, 4039–4072, https://doi.org/10.5194/acp-11-4039-2011, 2011. a, b
Baray, J.-L., Courcoux, Y., Keckhut, P., Portafaix, T., Tulet, P., Cammas, J.-P., Hauchecorne, A., Godin Beekmann, S., De Mazière, M., Hermans, C., Desmet, F., Sellegri, K., Colomb, A., Ramonet, M., Sciare, J., Vuillemin, C., Hoareau, C., Dionisi, D., Duflot, V., Vérèmes, H., Porteneuve, J., Gabarrot, F., Gaudo, T., Metzger, J.-M., Payen, G., Leclair de Bellevue, J., Barthe, C., Posny, F., Ricaud, P., Abchiche, A., and Delmas, R.: Maïdo observatory: a new high-altitude station facility at Reunion Island (21° S, 55° E) for long-term atmospheric remote sensing and in situ measurements, Atmos. Meas. Tech., 6, 2865–2877, https://doi.org/10.5194/amt-6-2865-2013, 2013. a
Barnston, A. G., Chelliah, M., and Goldenberg, S. B.: Documentation of a highly ENSO‐related sst region in the equatorial pacific: Research note, Atmos.-Ocean, 35, 367–383, https://doi.org/10.1080/07055900.1997.9649597, 1997. a
Bauer-Marschallinger, B., Paulik, C., Hochstöger, S., Mistelbauer, T., Modanesi, S., Ciabatta, L., Massari, C., Brocca, L., and Wagner, W.: Soil Moisture from Fusion of Scatterometer and SAR: Closing the Scale Gap with Temporal Filtering, Remote Sens., 10, https://doi.org/10.3390/rs10071030, 2018. a
Bernath, P., Crouse, J., Hughes, R., and Boone, C.: The Atmospheric Chemistry Experiment Fourier transform spectrometer (ACE-FTS) version 4.1 retrievals: Trends and seasonal distributions, J. Quant. Spectrosc. Radiat. Transfer, 259, 107409, https://doi.org/10.1016/j.jqsrt.2020.107409, 2021. a
Berrisford, P., Dee, D., Poli, P., Brugge, R., Fielding, M., Fuentes, M., Kållberg, P., Kobayashi, S., Uppala, S., and Simmons, A.: The ERA-Interim archive Version 2.0, Shinfield Park, Reading, https://www.ecmwf.int/en/elibrary/73682-era-interim-archive-version-20 (last access: 25 August 2026), 2011. a
Boone, C., Bernath, P., Cok, D., Jones, S., and Steffen, J.: Version 4 retrievals for the atmospheric chemistry experiment Fourier transform spectrometer (ACE-FTS) and imagers, J. Quant. Spectrosc. Radiat. Transfer, 247, 106939, https://doi.org/10.1016/j.jqsrt.2020.106939, 2020. a
Bruno, A. G.: Investigating The Trace Gas Emissions Of Biomass Burning In The Earth System, PhD Thesis, University of Leicester, https://doi.org/10.25392/leicester.data.25680108.v1, 2024a. a
Bruno, A. G.: Investigating The Trace Gas Emissions Of Biomass Burning In The Earth System, PhD thesis, https://doi.org/10.25392/LEICESTER.DATA.25680108, 2024b. a
Bruno, A. G., Harrison, J. J., Moore, D. P., Chipperfield, M. P., and Pope, R. P.: Satellite observations and modelling of hydrogen cyanide in the Earth's atmosphere, Il Nuovo Cimento C, 6, https://doi.org/10.1393/ncc/i2022-22184-6, 2022. a, b, c
Bruno, A. G., Harrison, J. J., Chipperfield, M. P., Moore, D. P., Pope, R. J., Wilson, C., Mahieu, E., and Notholt, J.: Atmospheric distribution of HCN from satellite observations and 3-D model simulations, Atmos. Chem. Phys., 23, 4849–4861, https://doi.org/10.5194/acp-23-4849-2023, 2023. a, b, c, d
Bruno, A. G., Moore, D. P., and Harrison, J. J.: Hydrological drivers of hydrogen cyanide wildfire emissions from Indonesian peat fires during the 2015, 2019, and 2023 El Niño events – IASI gridded data, Zenodo [data set], https://doi.org/10.5281/zenodo.20584609, 2026a. a
Bruno, A. G., Moore, D. P., Harrison, J. J., Graham, A., and Chipperfield, M.: Hydrological drivers of hydrogen cyanide wildfire emissions from Indonesian peat fires during the 2015, 2019, and 2023 El Niño events – TOMCAT data part 1, Zenodo [data set], https://doi.org/10.5281/zenodo.18848199, 2026b. a
Bruno, A. G., Moore, D. P., Harrison, J. J., Graham, A., and Chipperfield, M.: Hydrological drivers of hydrogen cyanide wildfire emissions from Indonesian peat fires during the 2015, 2019, and 2023 Niño events – TOMCAT data part 2, Zenodo [data set], https://doi.org/10.5281/zenodo.18848214, 2026c. a
Callewaert, S., Brioude, J., Langerock, B., Duflot, V., Fonteyn, D., Müller, J.-F., Metzger, J.-M., Hermans, C., Kumps, N., Ramonet, M., Lopez, M., Mahieu, E., and De Mazière, M.: Analysis of CO2, CH4, and CO surface and column concentrations observed at Réunion Island by assessing WRF-Chem simulations, Atmos. Chem. Phys., 22, 7763–7792, https://doi.org/10.5194/acp-22-7763-2022, 2022. a
Chipperfield, M. P.: New version of the TOMCAT/SLIMCAT off-line chemical transport model: Intercomparison of stratospheric tracer experiments, Q. J. R. Meteorol. Soc., 132, 1179–1203, https://doi.org/10.1256/qj.05.51, 2006. a
Chipperfield, M. P., Cariolle, D., Simon, P., Ramaroson, R., and Lary, D. J.: A three-dimensional modeling study of trace species in the Arctic lower stratosphere during winter 1989–1990, J. Geophys. Res.: Atmos., 98, 7199–7218, https://doi.org/10.1029/92JD02977, 1993. a
Chipperfield, M. P., Dhomse, S., Hossaini, R., Feng, W., Santee, M. L., Weber, M., Burrows, J. P., Wild, J. D., Loyola, D., and Coldewey-Egbers, M.: On the Cause of Recent Variations in Lower Stratospheric Ozone, Geophys. Res. Lett., 45, 5718–5726, https://doi.org/10.1029/2018GL078071, 2018. a
Cho, K., Negrón-Juárez, R., Colliander, A., Cosio, E. G., Salinas, N., De Araujo, A., Chambers, J. Q., and Wang, J.: Calibration of the SMAP Soil Moisture Retrieval Algorithm to Reduce Bias Over the Amazon Rainforest, IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens., 17, 8724–8736, https://doi.org/10.1109/JSTARS.2024.3388914, 2024. a
Christian, T. J., Kleiss, B., Yokelson, R. J., Holzinger, R., Crutzen, P., Hao, W. M., Saharjo, B., and Ward, D. E.: Comprehensive laboratory measurements of biomass-burning emissions: 1. Emissions from Indonesian, African, and other fuels, J. Geophys. Res.: Atmos., 108, 4719, https://doi.org/10.1029/2003JD003704, 2003. a, b
Clarisse, L., R'Honi, Y., Coheur, P.-F., Hurtmans, D., and Clerbaux, C.: Thermal infrared nadir observations of 24 atmospheric gases, Geophys. Res. Lett., 38, https://doi.org/10.1029/2011GL047271, 2011. a, b
Clerbaux, C., Boynard, A., Clarisse, L., George, M., Hadji-Lazaro, J., Herbin, H., Hurtmans, D., Pommier, M., Razavi, A., Turquety, S., Wespes, C., and Coheur, P.-F.: Monitoring of atmospheric composition using the thermal infrared IASI/MetOp sounder, Atmos. Chem. Phys., 9, 6041–6054, https://doi.org/10.5194/acp-9-6041-2009, 2009. a, b, c
Coheur, P.-F., Clarisse, L., Turquety, S., Hurtmans, D., and Clerbaux, C.: IASI measurements of reactive trace species in biomass burning plumes, Atmos. Chem. Phys., 9, 5655–5667, https://doi.org/10.5194/acp-9-5655-2009, 2009. a
Dargie, G. C., Lewis, S. L., Lawson, I. T., Mitchard, E. T. A., Page, S. E., Bocko, Y. E., and Ifo, S. A.: Age, extent and carbon storage of the central Congo Basin peatland complex, Nature, 542, 86–90, 2017. a
De Longueville, H., Clarisse, L., Whitburn, S., Franco, B., Bauduin, S., Clerbaux, C., Camy-Peyret, C., and Coheur, P.-F.: Identification of Short and Long-Lived Atmospheric Trace Gases From IASI Space Observations, Geophys. Res. Lett., 48, e2020GL091742, https://doi.org/10.1029/2020GL091742, 2021. a
De Mazière, M., Thompson, A. M., Kurylo, M. J., Wild, J. D., Bernhard, G., Blumenstock, T., Braathen, G. O., Hannigan, J. W., Lambert, J.-C., Leblanc, T., McGee, T. J., Nedoluha, G., Petropavlovskikh, I., Seckmeyer, G., Simon, P. C., Steinbrecht, W., and Strahan, S. E.: The Network for the Detection of Atmospheric Composition Change (NDACC): history, status and perspectives, Atmos. Chem. Phys., 18, 4935–4964, https://doi.org/10.5194/acp-18-4935-2018, 2018. a
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B., Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P., Köhler, M., Matricardi, M., McNally, A. P., Monge-Sanz, B. M., Morcrette, J.-J., Park, B.-K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J.-N., and Vitart, F.: The ERA-Interim reanalysis: configuration and performance of the data assimilation system, Q. J. R. Meteorol. Soc., 137, 553–597, https://doi.org/10.1002/qj.828, 2011. a
Deeter, M. N.: Calculation and Application of MOPITT Averaging Kernels, Tech. note, https://api.semanticscholar.org/CorpusID:111388701 (last access: 25 August 2026), 2002. a
Dudhia, A.: The Reference Forward Model (RFM), J. Quant. Spectrosc. Radiat. Transfer, 186, 243–253, https://doi.org/10.1016/j.jqsrt.2016.06.018, 2017. a
Duflot, V., Dils, B., Baray, J. L., De Mazière, M., Attié, J. L., Vanhaelewyn, G., Senten, C., Vigouroux, C., Clain, G., and Delmas, R.: Analysis of the origin of the distribution of CO in the subtropical southern Indian Ocean in 2007, J. Geophys. Res.: Atmos., 115, https://doi.org/10.1029/2010JD013994, 2010. a
Duflot, V., Hurtmans, D., Clarisse, L., R'honi, Y., Vigouroux, C., De Mazière, M., Mahieu, E., Servais, C., Clerbaux, C., and Coheur, P.-F.: Measurements of hydrogen cyanide (HCN) and acetylene (C2H2) from the Infrared Atmospheric Sounding Interferometer (IASI), Atmos. Meas. Tech., 6, 917–925, https://doi.org/10.5194/amt-6-917-2013, 2013. a, b
Duflot, V., Wespes, C., Clarisse, L., Hurtmans, D., Ngadi, Y., Jones, N., Paton-Walsh, C., Hadji-Lazaro, J., Vigouroux, C., De Mazière, M., Metzger, J.-M., Mahieu, E., Servais, C., Hase, F., Schneider, M., Clerbaux, C., and Coheur, P.-F.: Acetylene (C2H2) and hydrogen cyanide (HCN) from IASI satellite observations: global distributions, validation, and comparison with model, Atmos. Chem. Phys., 15, 10509–10527, https://doi.org/10.5194/acp-15-10509-2015, 2015. a, b
Entekhabi, D., Yueh, S., and De Lannoy, G.: SMAP handbook, https://smap.jpl.nasa.gov/files/smap2/SMAP_Handbook_FINAL_1_JULY_2014_Web.pdf (last access: 25 August 2026), 2014. a
Eyring, V., Bony, S., Meehl, G. A., Senior, C. A., Stevens, B., Stouffer, R. J., and Taylor, K. E.: Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization, Geosci. Model Dev., 9, 1937–1958, https://doi.org/10.5194/gmd-9-1937-2016, 2016. a
Fang, B., Lakshmi, V., and Zhang, R.: Validation of downscaled 1‐km SMOS and SMAP soil moisture data in 2010–2021, Vadose Zone Journal, 23, e20305, https://doi.org/10.1002/vzj2.20305, 2024. a
Field, R. D., van der Werf, G. R., Fanin, T., Fetzer, E. J., Fuller, R., Jethva, H., Levy, R., Livesey, N. J., Luo, M., Torres, O., and Worden, H. M.: Indonesian fire activity and smoke pollution in 2015 show persistent nonlinear sensitivity to El Niño-induced drought, Proc. Natl. Aca. Sci. USA, 113, 9204–9209, https://doi.org/10.1073/pnas.1524888113, 2016. a, b, c
Goode, J. G., Yokelson, R. J., Ward, D. E., Susott, R. A., Babbitt, R. E., Davies, M. A., and Hao, W. M.: Measurements of excess O3, CO2, CO, CH4, C2H4, C2H2, HCN, NO, NH3, HCOOH, CH3COOH, HCHO, and CH3OH in 1997 Alaskan biomass burning plumes by airborne Fourier transform infrared spectroscopy (AFTIR), J. Geophys. Res.: Atmos., 105, 22147–22166, https://doi.org/10.1029/2000JD900287, 2000. a
Graham, A. M., Spracklen, D. V., McQuaid, J. B., Smith, T. E. L., Nurrahmawati, H., Ayona, D., Mulawarman, H., Adam, C., Papargyropoulou, E., Rigby, R., Padfield, R., and Choiruzzad, S.: Updated Smoke Exposure Estimate for Indonesian Peatland Fires Using a Network of Low‐Cost PM2.5 Sensors and a Regional Air Quality Model, GeoHealth, 8, e2024GH001125, https://doi.org/10.1029/2024GH001125, 2024. a
Hayasaka, H., Usup, A., and Naito, D.: New Approach Evaluating Peatland Fires in Indonesian Factors, Remote Sens., 12, https://doi.org/10.3390/rs12122055, 2020. a, b
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., De 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., de Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J.-N.: The ERA5 global reanalysis, Q. J. R. Meteorol. Soc., 146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020. a
Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., and Thépaut, J.-N.: ERA5 monthly averaged data on pressure levels from 1940 to present, Climate Data Store [data set], https://doi.org/10.24381/cds.6860a573, 2023. a
Hilton, F., Armante, R., August, T., Barnet, C., Bouchard, A., Camy-Peyret, C., Capelle, V., Clarisse, L., Clerbaux, C., Coheur, P.-F., Collard, A., Crevoisier, C., Dufour, G., Edwards, D., Faijan, F., Fourrié, N., Gambacorta, A., Goldberg, M., Guidard, V., Hurtmans, D., Illingworth, S., Jacquinet-Husson, N., Kerzenmacher, T., Klaes, D., Lavanant, L., Masiello, G., Matricardi, M., McNally, A., Newman, S., Pavelin, E., Payan, S., Péquignot, E., Peyridieu, S., Phulpin, T., Remedios, J., Schlüssel, P., Serio, C., Strow, L., Stubenrauch, C., Taylor, J., Tobin, D., Wolf, W., and Zhou, D.: Hyperspectral Earth Observation from IASI: Five Years of Accomplishments, Bull. Am. Meteorol. Soc., 93, 347–370, https://doi.org/10.1175/BAMS-D-11-00027.1, 2012. a
Hooijer, A. and Vernimmen, R.: Peatland maps for Indonesia. Including accuracy assessment and recommendations for improvement, elevation mapping and evaluation of future flood risk, Quick Assessment and Nationwide Screening (QANS) of Peat and Lowland Resources and Action Planning for the Implementation of a National Lowland Strategy – PVW3A10002, Agentschap NL 6201068 QANS Lowland Development, Government of Indonesia and Partners for Water (Netherlands), https://www.deltares.nl/app/uploads/2015/03/QANS-Peat-mapping-report-final-with-cover.pdf (last access: 30 September 2025), 2013. a
Hu, Y., Fernandez-Anez, N., Smith, T. E. L., and Rein, G.: Review of emissions from smouldering peat fires and their contribution to regional haze episodes, Int. J. Wildland Fire, 27, 293–312, https://doi.org/10.1071/WF17084, 2018. a
Hu, Y., Christensen, E., Restuccia, F., and Rein, G.: Transient gas and particle emissions from smouldering combustion of peat, Proc. Combust. Inst., 37, 4035–4042, https://doi.org/10.1016/j.proci.2018.06.008, 2019. a
Huang, B., Thorne, P. W., Banzon, V. F., Boyer, T., Chepurin, G., Lawrimore, J. H., Menne, M. J., Smith, T. M., Vose, R. S., and Zhang, H.-M.: Extended Reconstructed Sea Surface Temperature, Version 5 (ERSSTv5): Upgrades, Validations, and Intercomparisons, J. Clim., 30, 8179–8205, https://doi.org/10.1175/JCLI-D-16-0836.1, 2017. a
Huffman, G., Stocker, E., Bolvin, D., Nelkin, E., and Tan, J.: GPM IMERG Final Precipitation L3 1 day 0.1° × 0.1° V07, Geoscience Data Exchange [data set], https://doi.org/10.5065/7DE2-M746, 2024. a
Huijnen, V., Wooster, M. J., Kaiser, J. W., Gaveau, D. L., Flemming, J., Parrington, M., Inness, A., Murdiyarso, D., Main, B., and van Weele, M.: Fire carbon emissions over maritime southeast Asia in 2015 largest since 1997, Sci. Rep., 6, 26886, https://doi.org/10.1038/srep26886, 2016. a, b
Illingworth, S. M., Remedios, J. J., Boesch, H., Ho, S.-P., Edwards, D. P., Palmer, P. I., and Gonzi, S.: A comparison of OEM CO retrievals from the IASI and MOPITT instruments, Atmos. Meas. Tech., 4, 775–793, https://doi.org/10.5194/amt-4-775-2011, 2011a. a, b, c
Illingworth, S. M., Remedios, J. J., Boesch, H., Moore, D. P., Sembhi, H., Dudhia, A., and Walker, J. C.: ULIRS, an optimal estimation retrieval scheme for carbon monoxide using IASI spectral radiances: sensitivity analysis, error budget and simulations, Atmos. Meas. Tech., 4, 269–288, https://doi.org/10.5194/amt-4-269-2011, 2011b. a
Kerzenmacher, T., Dils, B., Kumps, N., Blumenstock, T., Clerbaux, C., Coheur, P.-F., Demoulin, P., García, O., George, M., Griffith, D. W. T., Hase, F., Hadji-Lazaro, J., Hurtmans, D., Jones, N., Mahieu, E., Notholt, J., Paton-Walsh, C., Raffalski, U., Ridder, T., Schneider, M., Servais, C., and De Mazière, M.: Validation of IASI FORLI carbon monoxide retrievals using FTIR data from NDACC, Atmos. Meas. Tech., 5, 2751–2761, https://doi.org/10.5194/amt-5-2751-2012, 2012. a
Kiely, L., Spracklen, D. V., Wiedinmyer, C., Conibear, L., Reddington, C. L., Archer-Nicholls, S., Lowe, D., Arnold, S. R., Knote, C., Khan, M. F., Latif, M. T., Kuwata, M., Budisulistiorini, S. H., and Syaufina, L.: New estimate of particulate emissions from Indonesian peat fires in 2015, Atmos. Chem. Phys., 19, 111051–1121, https://doi.org/10.5194/acp-19-11105-2019, 2019. a, b, c, d, e, f, g, h, i
Kleinböhl, A., Toon, G. C., Sen, B., Blavier, J.-F. L., Weisenstein, D. K., Strekowski, R. S., Nicovich, J. M., Wine, P. H., and Wennberg, P. O.: On the stratospheric chemistry of hydrogen cyanide, Geophys. Res. Lett., 33, https://doi.org/10.1029/2006GL026015, 2006. a
Krol, M., de Bruine, M., Killaars, L., Ouwersloot, H., Pozzer, A., Yin, Y., Chevallier, F., Bousquet, P., Patra, P., Belikov, D., Maksyutov, S., Dhomse, S., Feng, W., and Chipperfield, M. P.: Age of air as a diagnostic for transport timescales in global models, Geosci. Model Dev., 11, 3109–3130, https://doi.org/10.5194/gmd-11-3109-2018, 2018. a
Li, Q., Jacob, D. J., Bey, I., Yantosca, R. M., Zhao, Y., Kondo, Y., and Notholt, J.: Atmospheric hydrogen cyanide (HCN): Biomass burning source, ocean sink?, Geophys. Res. Lett., 27, 357–360, https://doi.org/10.1029/1999GL010935, 2000. a
Lohberger, S., Stängel, M., Atwood, E. C., and Siegert, F.: Spatial evaluation of Indonesia's 2015 fire‐affected area and estimated carbon emissions using Sentinel‐1, Glob. Change Biol., 24, 644–654, https://doi.org/10.1111/gcb.13841, 2018. a
Ma, J., Remaud, M., Peylin, P., Patra, P., Niwa, Y., Rodenbeck, C., Cartwright, M., Harrison, J. J., Chipperfield, M. P., Pope, R. J., Wilson, C., Belviso, S., Montzka, S. A., Vimont, I., Moore, F., Atlas, E. L., Schwartz, E., and Krol, M. C.: Intercomparison of Atmospheric Carbonyl Sulfide (TransCom-COS): 2. Evaluation of Optimized Fluxes Using Ground-Based and Aircraft Observations, J. Geophys. Res.: Atmos., 128, e2023JD039198, https://doi.org/10.1029/2023JD039198, 2023. a
Ma, H., Zeng, J., Zhang, X., Peng, J., Li, X., Fu, P., Cosh, M. H., Letu, H., Wang, S., Chen, N., and Wigneron, J.-P.: Surface soil moisture from combined active and passive microwave observations: Integrating ASCAT and SMAP observations based on machine learning approaches, Remote Sens. Environ., 308, 114 197, https://doi.org/10.1016/j.rse.2024.114197, 2024. a
Monks, S. A., Arnold, S. R., Hollaway, M. J., Pope, R. J., Wilson, C., Feng, W., Emmerson, K. M., Kerridge, B. J., Latter, B. L., Miles, G. M., Siddans, R., and Chipperfield, M. P.: The TOMCAT global chemical transport model v1.6: description of chemical mechanism and model evaluation, Geosci. Model Dev., 10, 3025–3057, https://doi.org/10.5194/gmd-10-3025-2017, 2017. a
Morgenstern, O., Hegglin, M. I., Rozanov, E., O'Connor, F. M., Abraham, N. L., Akiyoshi, H., Archibald, A. T., Bekki, S., Butchart, N., Chipperfield, M. P., Deushi, M., Dhomse, S. S., Garcia, R. R., Hardiman, S. C., Horowitz, L. W., Jöckel, P., Josse, B., Kinnison, D., Lin, M., Mancini, E., Manyin, M. E., Marchand, M., Marécal, V., Michou, M., Oman, L. D., Pitari, G., Plummer, D. A., Revell, L. E., Saint-Martin, D., Schofield, R., Stenke, A., Stone, K., Sudo, K., Tanaka, T. Y., Tilmes, S., Yamashita, Y., Yoshida, K., and Zeng, G.: Review of the global models used within phase 1 of the Chemistry–Climate Model Initiative (CCMI), Geosci. Model Dev., 10, 639–671, https://doi.org/10.5194/gmd-10-639-2017, 2017. a
Nayak, A. K., Xu, X., Frey, S. K., Khader, O., Erler, A. R., Lapen, D. R., Russell, H. A. J., and Sudicky, E. A.: Quantifying the potential of using Soil Moisture Active Passive (SMAP) soil moisture variability to predict subsurface water dynamics, Hydrol. Earth Syst. Sci., 29, 215–244, https://doi.org/10.5194/hess-29-215-2025, 2025. a
Nechita-Banda, N., Krol, M., van der Werf, G. R., Kaiser, J. W., Pandey, S., Huijnen, V., Clerbaux, C., Coheur, P., Deeter, M. N., and Röckmann, T.: Monitoring emissions from the 2015 Indonesian fires using CO satellite data, Phil. Trans. R. Soc. B, 373, 20170 307, https://doi.org/10.1098/rstb.2017.0307, 2018. a, b, c, d
NOAA Climate.gov: Climate Variability: Oceanic Niño Index, https://www.climate.gov/news-features/understanding-climate/climate-variability-oceanic-nino-index (last access: 1 October 2025), 2009. a
Nurdiati, S., Sopaheluwakan, A., and Septiawan, P.: Spatial and Temporal Analysis of El Niño Impact on Land and Forest Fire in Kalimantan and Sumatra, Agromet, 35, 1–10, https://doi.org/10.29244/j.agromet.35.1.1-10, 2021. a
ONeill, P., Chan, S., Njoku, E., Jackson, T., Bindlish, R., and Chaubell, J.: SMAP L3 Radiometer Global Daily 36 km EASE-Grid Soil Moisture, Version 8, https://doi.org/10.5067/OMHVSRGFX38O, 2021. a
Page, S. E. and Hooijer, A.: In the line of fire: the peatlands of Southeast Asia, Phil. Trans. R. Soc. B, 371, 20150176, https://doi.org/10.1098/rstb.2015.0176, 2016. a
Park, M., Worden, H. M., Kinnison, D. E., Gaubert, B., Tilmes, S., Emmons, L. K., Santee, M. L., Froidevaux, L., and Boone, C. D.: Fate of Pollution Emitted During the 2015 Indonesian Fire Season, J. Geophys. Res.: Atmos., 126, e2020JD033474, https://doi.org/10.1029/2020JD033474, 2021. a
Parker, R. J., Boesch, H., Wooster, M. J., Moore, D. P., Webb, A. J., Gaveau, D., and Murdiyarso, D.: Atmospheric CH4 and CO2 enhancements and biomass burning emission ratios derived from satellite observations of the 2015 Indonesian fire plumes, Atmos. Chem. Phys., 16, 10111–10131, https://doi.org/10.5194/acp-16-10111-2016, 2016. a
Pope, R. J., Arnold, S. R., Chipperfield, M. P., Reddington, C. L. S., Butt, E. W., Keslake, T. D., Feng, W., Latter, B. G., Kerridge, B. J., Siddans, R., Rizzo, L., Artaxo, P., Sadiq, M., and Tai, A. P. K.: Substantial Increases in Eastern Amazon and Cerrado Biomass Burning-Sourced Tropospheric Ozone, Geophys. Res. Lett., 47, e2019GL084143, https://doi.org/10.1029/2019GL084143, 2020. a
Pradhan, R. K., Markonis, Y., Vargas Godoy, M. R., Villalba-Pradas, A., Andreadis, K. M., Nikolopoulos, E. I., Papalexiou, S. M., Rahim, A., Tapiador, F. J., and Hanel, M.: Review of GPM IMERG performance: A global perspective, Remote Sens. Environ., 268, 112754, https://doi.org/10.1016/j.rse.2021.112754, 2022. a
Pumphrey, H. C., Glatthor, N., Bernath, P. F., Boone, C. D., Hannigan, J. W., Ortega, I., Livesey, N. J., and Read, W. G.: MLS measurements of stratospheric hydrogen cyanide during the 2015–2016 El Niño event, Atmos. Chem. Phys., 18, 691–703, https://doi.org/10.5194/acp-18-691-2018, 2018. a
Randerson, J., Van Der Werf, G., Giglio, L., Collatz, G., and Kasibhatla, P.: Global Fire Emissions Database, Version 4.1 (GFEDv4), EarthData [data set], https://doi.org/10.3334/ORNLDAAC/1293, 2017. a
Remaud, M., Ma, J., Krol, M., Abadie, C., Cartwright, M. P., Patra, P., Niwa, Y., Rodenbeck, C., Belviso, S., Kooijmans, L., Lennartz, S., Maignan, F., Chevallier, F., Chipperfield, M. P., Pope, R. J., Harrison, J. J., Vimont, I., Wilson, C., and Peylin, P.: Intercomparison of Atmospheric Carbonyl Sulfide (TransCom-COS; Part One): Evaluating the Impact of Transport and Emissions on Tropospheric Variability Using Ground-Based and Aircraft Data, J. Geophys. Res.: Atmospheres, 128, e2022JD037817, https://doi.org/10.1029/2022JD037817, 2023. a
Remedios, J. J., Leigh, R. J., Waterfall, A. M., Moore, D. P., Sembhi, H., Parkes, I., Greenhough, J., Chipperfield, M. P., and Hauglustaine, D.: MIPAS reference atmospheres and comparisons to V4.61/V4.62 MIPAS level 2 geophysical data sets, Atmos. Chem. Phys. Discuss., 7, 9973–10017, https://doi.org/10.5194/acpd-7-9973-2007, 2007. a, b
R'Honi, Y., Clarisse, L., Clerbaux, C., Hurtmans, D., Duflot, V., Turquety, S., Ngadi, Y., and Coheur, P.-F.: Exceptional emissions of NH3 and HCOOH in the 2010 Russian wildfires, Atmos. Chem. Phys., 13, 4171–4181, https://doi.org/10.5194/acp-13-4171-2013, 2013. a
Rodgers, C. D.: Inverse Methods for Atmospheric Sounding: Theory and Practice (Vol. 2), World Scientific, https://doi.org/10.1142/3171, 2000. a
Rodriguez Vasquez, M. J., Benoist, A., Roda, J.-M., and Fortin, M.: Estimating greenhouse gas emissions from peat combustion in wildfires on Indonesian peatlands, and their uncertainty, Glob. Biogeochem. Cycles, 35, e2019GB006218, https://doi.org/10.1029/2019GB006218, 2021. a, b
Rosanka, S., Franco, B., Clarisse, L., Coheur, P.-F., Pozzer, A., Wahner, A., and Taraborrelli, D.: The impact of organic pollutants from Indonesian peatland fires on the tropospheric and lower stratospheric composition, Atmos. Chem. Phys., 21, 11257–11288, https://doi.org/10.5194/acp-21-11257-2021, 2021. a
Santoso, A., Mcphaden, M. J., and Cai, W.: The Defining Characteristics of ENSO Extremes and the Strong 2015/2016 El Niño, Rev. Geophys., 55, 1079–1129, https://doi.org/10.1002/2017RG000560, 2017. a
Schroeder, W., Oliva, P., Giglio, L., and Csiszar, I. A.: The New VIIRS 375m active fire detection data product: Algorithm description and initial assessment, Remote. Sens. Environ., 143, 85–96, https://doi.org/10.1016/j.rse.2013.12.008, 2014. a
Sheese, P. E., Walker, K. A., and Boone, C. D.: A global enhancement of hydrogen cyanide in the lower stratosphere throughout 2016, Geophys. Res. Lett., 44, 5791–5797, https://doi.org/10.1002/2017GL073519, 2017. a
Singh, H. B., Brune, W. H., Crawford, J. H., Flocke, F., and Jacob, D. J.: Chemistry and transport of pollution over the Gulf of Mexico and the Pacific: spring 2006 INTEX-B campaign overview and first results, Atmos. Chem. Phys., 9, 2301–2318, https://doi.org/10.5194/acp-9-2301-2009, 2009. a
Stockwell, C. E., Yokelson, R. J., Kreidenweis, S. M., Robinson, A. L., DeMott, P. J., Sullivan, R. C., Reardon, J., Ryan, K. C., Griffith, D. W. T., and Stevens, L.: Trace gas emissions from combustion of peat, crop residue, domestic biofuels, grasses, and other fuels: configuration and Fourier transform infrared (FTIR) component of the fourth Fire Lab at Missoula Experiment (FLAME-4), Atmos. Chem. Phys., 14, 9727–9754, https://doi.org/10.5194/acp-14-9727-2014, 2014. a
Stockwell, C. E., Jayarathne, T., Cochrane, M. A., Ryan, K. C., Putra, E. I., Saharjo, B. H., Nurhayati, A. D., Albar, I., Blake, D. R., Simpson, I. J., et al.: Field measurements of trace gases and aerosols emitted by peat fires in Central Kalimantan, Indonesia, during the 2015 El Niño, Atmos. Chem. Phys., 16, 11711–11732, https://doi.org/10.5194/acp-16-11711-2016, 2016. a, b, c, d
Storch, H. V. and Zwiers, F. W.: Statistical Analysis in Climate Research, Cambridge University Press, 1 edn., https://doi.org/10.1017/CBO9780511612336, 1999. a
Thompson, R. L., Patra, P. K., Ishijima, K., Saikawa, E., Corazza, M., Karstens, U., Wilson, C., Bergamaschi, P., Dlugokencky, E., Sweeney, C., Prinn, R. G., Weiss, R. F., O'Doherty, S., Fraser, P. J., Steele, L. P., Krummel, P. B., Saunois, M., Chipperfield, M., and Bousquet, P.: TransCom N2O model inter-comparison – Part 1: Assessing the influence of transport and surface fluxes on tropospheric N2O variability, Atmos. Chem. Phys., 14, 4349–4368, https://doi.org/10.5194/acp-14-4349-2014, 2014. a
Usup, A., Hashimoto, Y., Takahashi, H., and Hayasaka, H.: Combustion and thermal characteristics of peat fire in tropical peatland in Central Kalimantan, Indonesia, Tropics, 14, 1–19, https://doi.org/10.3759/tropics.14.1, 2004. a
van der Werf, G. R., Randerson, J. T., Giglio, L., van Leeuwen, T. T., Chen, Y., Rogers, B. M., Mu, M., van Marle, M. J. E., Morton, D. C., Collatz, G. J., Yokelson, R. J., and Kasibhatla, P. S.: Global fire emissions estimates during 1997–2016, Earth Syst. Sci. Data, 9, 697–720, https://doi.org/10.5194/essd-9-697-2017, 2017. a, b
Vetrita, Y. and Cochrane, M. A.: Fire Frequency and Related Land-Use and Land-Cover Changes in Indonesia’s Peatlands, Remote Sens., 12, https://doi.org/10.3390/rs12010005, 2020. a
Vigouroux, C., Stavrakou, T., Whaley, C., Dils, B., Duflot, V., Hermans, C., Kumps, N., Metzger, J.-M., Scolas, F., Vanhaelewyn, G., Müller, J.-F., Jones, D. B. A., Li, Q., and De Mazière, M.: FTIR time-series of biomass burning products (HCN, C2H6, C2H2, CH3OH, and HCOOH) at Reunion Island (21° S, 55° E) and comparisons with model data, Atmos. Chem. Phys., 12, 10367–10385, https://doi.org/10.5194/acp-12-10367-2012, 2012. a, b, c, d, e, f
Vincent, R. A. and Dudhia, A.: Fast radiative transfer using monochromatic look-up tables, J. Quant. Spectrosc. Radiat. Transfer, 186, 254–264, https://doi.org/10.1016/j.jqsrt.2016.04.011, 2017. a
Watson, J. G., Cao, J., Chen, L.-W. A., Wang, Q., Tian, J., Wang, X., Gronstal, S., Ho, S. S. H., Watts, A. C., and Chow, J. C.: Gaseous, PM2.5 mass, and speciated emission factors from laboratory chamber peat combustion, Atmos. Chem. Phys., 19, 14173–14193, https://doi.org/10.5194/acp-19-14173-2019, 2019. a
Wells, K. C., Millet, D. B., Brewer, J. F., Payne, V. H., Cady-Pereira, K. E., Pernak, R., Kulawik, S., Vigouroux, C., Jones, N., Mahieu, E., Makarova, M., Nagahama, T., Ortega, I., Palm, M., Strong, K., Schneider, M., Smale, D., Sussmann, R., and Zhou, M.: Global decadal measurements of methanol, ethene, ethyne, and HCN from the Cross-track Infrared Sounder, Atmos. Meas. Tech., 18, 695–716, https://doi.org/10.5194/amt-18-695-2025, 2025. a
Whitburn, S., Van Damme, M., Clarisse, L., Hurtmans, D., Clerbaux, C., and Coheur, P.-F.: IASI-derived NH3 enhancement ratios relative to CO for the tropical biomass burning regions, Atmos. Chem. Phys., 17, 12239–12252, https://doi.org/10.5194/acp-17-12239-2017, 2017. a, b, c, d
Wiedinmyer, C., Akagi, S. K., Yokelson, R. J., Emmons, L. K., Al-Saadi, J. A., Orlando, J. J., and Soja, A. J.: The Fire INventory from NCAR (FINN): a high resolution global model to estimate the emissions from open burning, Geosci. Model Dev., 4, 625–641, https://doi.org/10.5194/gmd-4-625-2011, 2011. a, b, c
Yokelson, R. J., Saharjo, B. H., Stockwell, C. E., Putra, E. I., Jayarathne, T., Akbar, A., Albar, I., Blake, D. R., Graham, L. L. B., Kurniawan, A., Meinardi, S., Ningrum, D., Nurhayati, A. D., Saad, A., Sakuntaladewi, N., Setianto, E., Simpson, I. J., Stone, E. A., Sutikno, S., Thomas, A., Ryan, K. C., and Cochrane, M. A.: Tropical peat fire emissions: 2019 field measurements in Sumatra and Borneo and synthesis with previous studies, Atmos. Chem. Phys., 22, 10173–10194, https://doi.org/10.5194/acp-22-10173-2022, 2022. a, b
Zhang, T., Wooster, M. J., and Xu, W.: Approaches for synergistically exploiting VIIRS I- and M-Band data in regional active fire detection and FRP assessment: A demonstration with respect to agricultural residue burning in Eastern China, Remote Sens. Environ., 198, 407–424, https://doi.org/10.1016/j.rse.2017.06.028, 2017. a
Zhou, M., Langerock, B., Vigouroux, C., Sha, M. K., Ramonet, M., Delmotte, M., Mahieu, E., Bader, W., Hermans, C., Kumps, N., Metzger, J.-M., Duflot, V., Wang, Z., Palm, M., and De Mazière, M.: Atmospheric CO and CH4 time series and seasonal variations on Reunion Island from ground-based in situ and FTIR (NDACC and TCCON) measurements, Atmos. Chem. Phys., 18, 13881–13901, https://doi.org/10.5194/acp-18-13881-2018, 2018. a
Short summary
Indonesian peatlands store vast carbon reserves, but can release large quantities of greenhouse gases and other species with significant environmental impacts, including hydrogen cyanide (HCN), when fires occur. Analyzing three major El Niño years with satellites and models, we found that emissions depend on local hydrological conditions, not just El Niño strength. Including soil moisture and burn depth can improve emission estimates and climate strategies.
Indonesian peatlands store vast carbon reserves, but can release large quantities of greenhouse...
Altmetrics
Final-revised paper
Preprint