Articles | Volume 24, issue 6
https://doi.org/10.5194/acp-24-3699-2024
© Author(s) 2024. 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-24-3699-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
25 Mar 2024
Research article |
| 25 Mar 2024
| 25 Mar 2024
Uncertainties from biomass burning aerosols in air quality models obscure public health impacts in Southeast Asia
Margaret R. Marvin
CORRESPONDING AUTHOR
National Centre for Earth Observation, University of Edinburgh, Edinburgh, UK
now at: Air Resources Laboratory, National Oceanic and Atmospheric Administration, College Park, MD, USA
now at: Center for Spatial Information Science and Systems, George Mason University, Fairfax, VA, USA
Paul I. Palmer
National Centre for Earth Observation, University of Edinburgh, Edinburgh, UK
School of GeoSciences, University of Edinburgh, Edinburgh, UK
National Centre for Earth Observation, University of Edinburgh, Edinburgh, UK
School of GeoSciences, University of Edinburgh, Edinburgh, UK
Mohd Talib Latif
Department of Earth Sciences and Environment, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, Bangi, Malaysia
Md Firoz Khan
Department of Chemistry, Faculty of Science, Universiti Malaya, Kuala Lumpur, Malaysia
now at: Department of Environmental Science and Management, North South University, Dhaka, Bangladesh
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Chlöe N. Schooling, Liang Feng, A. Jerome P. Woodwark, and Paul I. Palmer
EGUsphere, https://doi.org/10.5194/egusphere-2026-812, https://doi.org/10.5194/egusphere-2026-812, 2026
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
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Methane is a powerful greenhouse gas, but monitoring it in tropical regions is difficult due to clouds and air pollution. We explore a new high-resolution satellite mission concept that could see between clouds and improve observations over tropical Africa. Using simulations with cloud and aerosol data, we show that this satellite could provide much more complete and reliable measurements, helping to better estimate methane emissions and support global climate monitoring efforts.
Petri Clusius, Metin Baykara, Carlton Xavier, Putian Zhou, Juniper Tyree, Benjamin Foreback, Mikko Äijälä, Frans Graeffe, Tuukka Petäjä, Markku Kulmala, Pauli Paasonen, Paul I. Palmer, and Michael Boy
Atmos. Chem. Phys., 26, 1967–1992, https://doi.org/10.5194/acp-26-1967-2026, https://doi.org/10.5194/acp-26-1967-2026, 2026
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Cloud condensation nuclei are necessary to form clouds, and their size distribution affects cloud properties and therefore Earth’s energy budget. This study modelled the origins of cloud condensation nuclei at SMEAR II, Hyytiälä, Finland, and found that primary emissions and new particle formation separately contribute to more than half of the condensation nuclei, but they suppress each other, leading to current concentrations. Largest condensation nuclei originated mostly from emissions.
Douglas P. Finch and Paul I. Palmer
EGUsphere, https://doi.org/10.5194/egusphere-2025-5900, https://doi.org/10.5194/egusphere-2025-5900, 2026
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We have developed a machine learning tool to find emission plumes of sulphur dioxide (SO2) observed in satellite data. SO2 is an atmospheric pollutant from fuel combustion, metal smelting, and volcanic degassing, impacting health, acid deposition, and climate forcing. Over 6 years we find over 50,000 plumes, most of which are clustered around known sources (e.g. volcanoes or industrial hotspots). We show how this tool can be used to give near real-time estimates of emissions across the globe.
Gerrit Kuhlmann, Erik Franciscus Maria Koene, Chloe Natasha Schooling, Paul Ian Palmer, Òscar Collado López, and Marc Guevara
EGUsphere, https://doi.org/10.5194/egusphere-2025-6057, https://doi.org/10.5194/egusphere-2025-6057, 2026
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We used satellite measurements of nitrogen dioxide (NO2) to estimate top-down nitrogen oxide (NOx) emissions from power plants in Europe and the United States. Our study shows that these observations can track seasonal and short-term changes in emissions and agree well with bottom-up estimates. This approach offers a promising way to monitor NOx and indirectly carbon dioxide (CO2) emissions, supporting anthropogenic emissions monitoring systems.
Alexander Kurganskiy, Liang Feng, Neil Humpage, Paul I. Palmer, A. Jerome P. Woodwark, Stamatia Doniki, and Damien Weidmann
Atmos. Meas. Tech., 18, 7525–7563, https://doi.org/10.5194/amt-18-7525-2025, https://doi.org/10.5194/amt-18-7525-2025, 2025
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This study introduces GEMINI-UK (Greenhouse gas Emissions Monitoring network to Inform Net-zero Initiatives for the UK), the first UK-wide network using ground-based instruments to monitor net fluxes of CO2 and methane. By simulating its performance, we show that GEMINI-UK will significantly reduce uncertainties in these flux estimates, complementing data from existing tall towers and future satellite missions. The network will strengthen the UK's ability to track greenhouse gases, evaluate climate policies, and meet net-zero goals.
Haolin Wang, William Maslanka, Paul I. Palmer, Martin J. Wooster, Haofan Wang, Fei Yao, Liang Feng, Kai Wu, Xiao Lu, and Shaojia Fan
Atmos. Chem. Phys., 25, 17501–17526, https://doi.org/10.5194/acp-25-17501-2025, https://doi.org/10.5194/acp-25-17501-2025, 2025
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We examine the impact of diurnally varying African biomass burning (BB) emissions on tropospheric ozone using GEOS-Chem simulations with a high-resolution satellite-derived emission inventory. Compared to coarser temporal resolutions, incorporating diurnal variations leads to significant changes in surface ozone and atmospheric oxidation capacity. Our findings highlight the importance of accurately representing BB emission timing in chemical transport models to improve ozone predictions.
Samantha Petch, Liang Feng, Paul I. Palmer, Robert P. King, Tristan Quaife, and Keith Haines
Biogeosciences, 22, 7031–7051, https://doi.org/10.5194/bg-22-7031-2025, https://doi.org/10.5194/bg-22-7031-2025, 2025
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The growth rate of atmospheric CO2 varies year to year, mainly due to land ecosystems. Understanding factors controlling the land carbon uptake is crucial. Our study examines the link between terrestrial water storage and the CO2 growth rate from 2002–2023, revealing a strong negative correlation. We highlight the key role of tropical forests, especially in tropical America, and assess how regional contributions shift over time.
Shihan Sun, Paul I. Palmer, Richard Siddans, Brian J. Kerridge, Lucy Ventress, Achim Edtbauer, Akima Ringsdorf, Eva Y. Pfannerstill, and Jonathan Williams
Atmos. Chem. Phys., 25, 15801–15818, https://doi.org/10.5194/acp-25-15801-2025, https://doi.org/10.5194/acp-25-15801-2025, 2025
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Isoprene released by plants can impact atmospheric chemistry and climate. The Amazon rainforest is a major source of isoprene. We derived isoprene emissions using satellite retrievals of isoprene columns and a chemical transport model. We evaluated our isoprene emission estimates using ground-based isoprene observations and satellite retrievals of formaldehyde. We found that using satellite retrievals of isoprene can help us better understand isoprene emissions over the Amazon.
Chlöe N. Schooling, Paul I. Palmer, Auke Visser, and Nicolas Bousserez
Atmos. Chem. Phys., 25, 15631–15652, https://doi.org/10.5194/acp-25-15631-2025, https://doi.org/10.5194/acp-25-15631-2025, 2025
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This study presents a new method to estimate fossil fuel CO2 (ffCO2) emissions by modelling NOx chemistry. Our regression models predict NOx chemical rates and NO2 : NO ratios with R² values above 0.95 using meteorological inputs. Incorporating these regressions reduces computational time compared to traditional methods and enables integration into model inversion frameworks. This scalable approach supports global emissions monitoring and climate change mitigation efforts.
Liang Feng, Paul I. Palmer, Luke Smallman, Jingfeng Xiao, Paolo Cristofanelli, Ove Hermansen, John Lee, Casper Labuschagne, Simonetta Montaguti, Steffen M. Noe, Stephen M. Platt, Xinrong Ren, Martin Steinbacher, and Irène Xueref-Remy
Atmos. Chem. Phys., 25, 13053–13076, https://doi.org/10.5194/acp-25-13053-2025, https://doi.org/10.5194/acp-25-13053-2025, 2025
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The year 2023 saw unexpectedly large global atmospheric CO2 growth. Satellite data reveal a role for increased tropical emissions. Larger emissions over eastern Brazil can be explained by warmer temperatures, which has led to exceptional drought, while hydrological changes play more of a role in emission increases elsewhere in the tropics. Broadly, we find that this situation continues into 2024.
Ke Li, Rong Tan, Wenhao Qiao, Taegyung Lee, Yufen Wang, Danyuting Zhang, Minglong Tang, Wenqing Zhao, Yixuan Gu, Shaojia Fan, Jinqiang Zhang, Xiaopu Lyu, Likun Xue, Jianming Xu, Zhiqiang Ma, Mohd Talib Latif, Teerachai Amnuaylojaroen, Junsu Gil, Mee-Hye Lee, Juseon Bak, Joowan Kim, Hong Liao, Yugo Kanaya, Xiao Lu, Tatsuya Nagashima, and Ja-Ho Koo
Atmos. Chem. Phys., 25, 11575–11596, https://doi.org/10.5194/acp-25-11575-2025, https://doi.org/10.5194/acp-25-11575-2025, 2025
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East Asia and Southeast Asia have been identified as a global hot spot, with the fastest ozone increase. This paper presents the most comprehensive observational review of ozone distributions and evolution over East Asia and Southeast Asia across different spatiotemporal scales in the past two decades, which will have important implications for assessing ozone impacts on public health and crop yields and for developing future ozone control strategies.
Xiao Lu, Yiming Liu, Jiayin Su, Xiang Weng, Tabish Ansari, Yuqiang Zhang, Guowen He, Yuqi Zhu, Haolin Wang, Ganquan Zeng, Jingyu Li, Cheng He, Shuai Li, Teerachai Amnuaylojaroen, Tim Butler, Qi Fan, Shaojia Fan, Grant L. Forster, Meng Gao, Jianlin Hu, Yugo Kanaya, Mohd Talib Latif, Keding Lu, Philippe Nédélec, Peer Nowack, Bastien Sauvage, Xiaobin Xu, Lin Zhang, Ke Li, Ja-Ho Koo, and Tatsuya Nagashima
Atmos. Chem. Phys., 25, 7991–8028, https://doi.org/10.5194/acp-25-7991-2025, https://doi.org/10.5194/acp-25-7991-2025, 2025
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This study analyzes summertime ozone trends in East and Southeast Asia derived from a comprehensive observational database spanning from 1995 to 2019, incorporating aircraft observations, ozonesonde data, and measurements from 2500 surface sites. Multiple models are applied to attribute to changes in anthropogenic emissions and climate. The results highlight that increases in anthropogenic emissions are the primary driver of ozone increases both in the free troposphere and at the surface.
Zhu Deng, Philippe Ciais, Liting Hu, Adrien Martinez, Marielle Saunois, Rona L. Thompson, Kushal Tibrewal, Wouter Peters, Brendan Byrne, Giacomo Grassi, Paul I. Palmer, Ingrid T. Luijkx, Zhu Liu, Junjie Liu, Xuekun Fang, Tengjiao Wang, Hanqin Tian, Katsumasa Tanaka, Ana Bastos, Stephen Sitch, Benjamin Poulter, Clément Albergel, Aki Tsuruta, Shamil Maksyutov, Rajesh Janardanan, Yosuke Niwa, Bo Zheng, Joël Thanwerdas, Dmitry Belikov, Arjo Segers, and Frédéric Chevallier
Earth Syst. Sci. Data, 17, 1121–1152, https://doi.org/10.5194/essd-17-1121-2025, https://doi.org/10.5194/essd-17-1121-2025, 2025
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This study reconciles national greenhouse gas (GHG) inventories with updated atmospheric inversion results to evaluate discrepancies for three principal GHG fluxes at the national level. Compared to our previous study, new satellite-based CO2 inversions were included and an updated mask of managed lands was used, improving agreement for Brazil and Canada. The proposed methodology can be regularly applied as a check to assess the gap between top-down inversions and bottom-up inventories.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Judith Hauck, Peter Landschützer, Corinne Le Quéré, Hongmei Li, Ingrid T. Luijkx, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Almut Arneth, Vivek Arora, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Carla F. Berghoff, Henry C. Bittig, Laurent Bopp, Patricia Cadule, Katie Campbell, Matthew A. Chamberlain, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Thomas Colligan, Jeanne Decayeux, Laique M. Djeutchouang, Xinyu Dou, Carolina Duran Rojas, Kazutaka Enyo, Wiley Evans, Amanda R. Fay, Richard A. Feely, Daniel J. Ford, Adrianna Foster, Thomas Gasser, Marion Gehlen, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Jens Heinke, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Andrew R. Jacobson, Atul K. Jain, Tereza Jarníková, Annika Jersild, Fei Jiang, Zhe Jin, Etsushi Kato, Ralph F. Keeling, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Xin Lan, Siv K. Lauvset, Nathalie Lefèvre, Zhu Liu, Junjie Liu, Lei Ma, Shamil Maksyutov, Gregg Marland, Nicolas Mayot, Patrick C. McGuire, Nicolas Metzl, Natalie M. Monacci, Eric J. Morgan, Shin-Ichiro Nakaoka, Craig Neill, Yosuke Niwa, Tobias Nützel, Lea Olivier, Tsuneo Ono, Paul I. Palmer, Denis Pierrot, Zhangcai Qin, Laure Resplandy, Alizée Roobaert, Thais M. Rosan, Christian Rödenbeck, Jörg Schwinger, T. Luke Smallman, Stephen M. Smith, Reinel Sospedra-Alfonso, Tobias Steinhoff, Qing Sun, Adrienne J. Sutton, Roland Séférian, Shintaro Takao, Hiroaki Tatebe, Hanqin Tian, Bronte Tilbrook, Olivier Torres, Etienne Tourigny, Hiroyuki Tsujino, Francesco Tubiello, Guido van der Werf, Rik Wanninkhof, Xuhui Wang, Dongxu Yang, Xiaojuan Yang, Zhen Yu, Wenping Yuan, Xu Yue, Sönke Zaehle, Ning Zeng, and Jiye Zeng
Earth Syst. Sci. Data, 17, 965–1039, https://doi.org/10.5194/essd-17-965-2025, https://doi.org/10.5194/essd-17-965-2025, 2025
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The Global Carbon Budget 2024 describes the methodology, main results, and datasets used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, land ecosystems, and the ocean over the historical period (1750–2024). These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Ingrid Super, Tia Scarpelli, Arjan Droste, and Paul I. Palmer
Geosci. Model Dev., 17, 7263–7284, https://doi.org/10.5194/gmd-17-7263-2024, https://doi.org/10.5194/gmd-17-7263-2024, 2024
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Monitoring greenhouse gas emission reductions requires a combination of models and observations, as well as an initial emission estimate. Each component provides information with a certain level of certainty and is weighted to yield the most reliable estimate of actual emissions. We describe efforts for estimating the uncertainty in the initial emission estimate, which significantly impacts the outcome. Hence, a good uncertainty estimate is key for obtaining reliable information on emissions.
Neil Humpage, Hartmut Boesch, William Okello, Jia Chen, Florian Dietrich, Mark F. Lunt, Liang Feng, Paul I. Palmer, and Frank Hase
Atmos. Meas. Tech., 17, 5679–5707, https://doi.org/10.5194/amt-17-5679-2024, https://doi.org/10.5194/amt-17-5679-2024, 2024
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We used a Bruker EM27/SUN spectrometer within an automated weatherproof enclosure to measure greenhouse gas column concentrations over a 3-month period in Jinja, Uganda. The portability of the EM27/SUN allows us to evaluate satellite and model data in locations not covered by traditional validation networks. This is of particular value in tropical Africa, where extensive terrestrial ecosystems are a significant store of carbon and play a key role in the atmospheric budgets of CO2 and CH4.
Tia R. Scarpelli, Paul I. Palmer, Mark Lunt, Ingrid Super, and Arjan Droste
Atmos. Chem. Phys., 24, 10773–10791, https://doi.org/10.5194/acp-24-10773-2024, https://doi.org/10.5194/acp-24-10773-2024, 2024
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Under the Paris Agreement, countries must track their anthropogenic greenhouse gas emissions. This study describes a method to determine self-consistent estimates for combustion emissions and natural fluxes of CO2 from atmospheric data. We report consistent estimates inferred using this approach from satellite data and ground-based data over Europe, suggesting that satellite data can be used to determine national anthropogenic CO2 emissions for countries where ground-based CO2 data are absent.
Hossain Mohammed Syedul Hoque, Kengo Sudo, Hitoshi Irie, Yanfeng He, and Md Firoz Khan
Geosci. Model Dev., 17, 5545–5571, https://doi.org/10.5194/gmd-17-5545-2024, https://doi.org/10.5194/gmd-17-5545-2024, 2024
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Using multi-platform observations, we validated global formaldehyde (HCHO) simulations from a chemistry transport model. HCHO is a crucial intermediate in the chemical catalytic cycle that governs the ozone formation in the troposphere. The model was capable of replicating the observed spatiotemporal variability in HCHO. In a few cases, the model's capability was limited. This is attributed to the uncertainties in the observations and the model parameters.
Dien Wu, Joshua L. Laughner, Junjie Liu, Paul I. Palmer, John C. Lin, and Paul O. Wennberg
Geosci. Model Dev., 16, 6161–6185, https://doi.org/10.5194/gmd-16-6161-2023, https://doi.org/10.5194/gmd-16-6161-2023, 2023
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To balance computational expenses and chemical complexity in extracting emission signals from tropospheric NO2 columns, we propose a simplified non-linear Lagrangian chemistry transport model and assess its performance against TROPOMI v2 over power plants and cities. Using this model, we then discuss how NOx chemistry affects the relationship between NOx and CO2 emissions and how studying NO2 columns helps quantify modeled biases in wind directions and prior emissions.
Matthew J. McGrath, Ana Maria Roxana Petrescu, Philippe Peylin, Robbie M. Andrew, Bradley Matthews, Frank Dentener, Juraj Balkovič, Vladislav Bastrikov, Meike Becker, Gregoire Broquet, Philippe Ciais, Audrey Fortems-Cheiney, Raphael Ganzenmüller, Giacomo Grassi, Ian Harris, Matthew Jones, Jürgen Knauer, Matthias Kuhnert, Guillaume Monteil, Saqr Munassar, Paul I. Palmer, Glen P. Peters, Chunjing Qiu, Mart-Jan Schelhaas, Oksana Tarasova, Matteo Vizzarri, Karina Winkler, Gianpaolo Balsamo, Antoine Berchet, Peter Briggs, Patrick Brockmann, Frédéric Chevallier, Giulia Conchedda, Monica Crippa, Stijn N. C. Dellaert, Hugo A. C. Denier van der Gon, Sara Filipek, Pierre Friedlingstein, Richard Fuchs, Michael Gauss, Christoph Gerbig, Diego Guizzardi, Dirk Günther, Richard A. Houghton, Greet Janssens-Maenhout, Ronny Lauerwald, Bas Lerink, Ingrid T. Luijkx, Géraud Moulas, Marilena Muntean, Gert-Jan Nabuurs, Aurélie Paquirissamy, Lucia Perugini, Wouter Peters, Roberto Pilli, Julia Pongratz, Pierre Regnier, Marko Scholze, Yusuf Serengil, Pete Smith, Efisio Solazzo, Rona L. Thompson, Francesco N. Tubiello, Timo Vesala, and Sophia Walther
Earth Syst. Sci. Data, 15, 4295–4370, https://doi.org/10.5194/essd-15-4295-2023, https://doi.org/10.5194/essd-15-4295-2023, 2023
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Accurate estimation of fluxes of carbon dioxide from the land surface is essential for understanding future impacts of greenhouse gas emissions on the climate system. A wide variety of methods currently exist to estimate these sources and sinks. We are continuing work to develop annual comparisons of these diverse methods in order to clarify what they all actually calculate and to resolve apparent disagreement, in addition to highlighting opportunities for increased understanding.
Alice Drinkwater, Paul I. Palmer, Liang Feng, Tim Arnold, Xin Lan, Sylvia E. Michel, Robert Parker, and Hartmut Boesch
Atmos. Chem. Phys., 23, 8429–8452, https://doi.org/10.5194/acp-23-8429-2023, https://doi.org/10.5194/acp-23-8429-2023, 2023
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Changes in atmospheric methane over the last few decades are largely unexplained. Previous studies have proposed different hypotheses to explain short-term changes in atmospheric methane. We interpret observed changes in atmospheric methane and stable isotope source signatures (2004–2020). We argue that changes over this period are part of a large-scale shift from high-northern-latitude thermogenic energy emissions to tropical biogenic emissions, particularly from North Africa and South America.
Thomas E. Taylor, Christopher W. O'Dell, David Baker, Carol Bruegge, Albert Chang, Lars Chapsky, Abhishek Chatterjee, Cecilia Cheng, Frédéric Chevallier, David Crisp, Lan Dang, Brian Drouin, Annmarie Eldering, Liang Feng, Brendan Fisher, Dejian Fu, Michael Gunson, Vance Haemmerle, Graziela R. Keller, Matthäus Kiel, Le Kuai, Thomas Kurosu, Alyn Lambert, Joshua Laughner, Richard Lee, Junjie Liu, Lucas Mandrake, Yuliya Marchetti, Gregory McGarragh, Aronne Merrelli, Robert R. Nelson, Greg Osterman, Fabiano Oyafuso, Paul I. Palmer, Vivienne H. Payne, Robert Rosenberg, Peter Somkuti, Gary Spiers, Cathy To, Brad Weir, Paul O. Wennberg, Shanshan Yu, and Jia Zong
Atmos. Meas. Tech., 16, 3173–3209, https://doi.org/10.5194/amt-16-3173-2023, https://doi.org/10.5194/amt-16-3173-2023, 2023
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NASA's Orbiting Carbon Observatory 2 and 3 (OCO-2 and OCO-3, respectively) provide complementary spatiotemporal coverage from a sun-synchronous and precession orbit, respectively. Estimates of total column carbon dioxide (XCO2) derived from the two sensors using the same retrieval algorithm show broad consistency over a 2.5-year overlapping time record. This suggests that data from the two satellites may be used together for scientific analysis.
Liang Feng, Paul I. Palmer, Robert J. Parker, Mark F. Lunt, and Hartmut Bösch
Atmos. Chem. Phys., 23, 4863–4880, https://doi.org/10.5194/acp-23-4863-2023, https://doi.org/10.5194/acp-23-4863-2023, 2023
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Our understanding of recent changes in atmospheric methane has defied explanation. Since 2007, the atmospheric growth of methane has accelerated to record-breaking values in 2020 and 2021. We use satellite observations of methane to show that (1) increasing emissions over the tropics are mostly responsible for these recent atmospheric changes, and (2) changes in the OH sink during the 2020 Covid-19 lockdown can explain up to 34% of changes in atmospheric methane for that year.
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.
Kai Wu, Paul I. Palmer, Dien Wu, Denis Jouglet, Liang Feng, and Tom Oda
Atmos. Meas. Tech., 16, 581–602, https://doi.org/10.5194/amt-16-581-2023, https://doi.org/10.5194/amt-16-581-2023, 2023
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We evaluate the theoretical ability of the upcoming MicroCarb satellite to estimate urban CO2 emissions over Paris and London. We explore the relative performance of alternative two-sweep and three-sweep city observing modes and take into account the impacts of cloud cover and urban biological CO2 fluxes. Our results find both the two-sweep and three-sweep observing modes are able to reduce prior flux errors by 20 %–40 % depending on the prevailing wind direction and cloud coverage.
Robert J. Parker, Chris Wilson, Edward Comyn-Platt, Garry Hayman, Toby R. Marthews, A. Anthony Bloom, Mark F. Lunt, Nicola Gedney, Simon J. Dadson, Joe McNorton, Neil Humpage, Hartmut Boesch, Martyn P. Chipperfield, Paul I. Palmer, and Dai Yamazaki
Biogeosciences, 19, 5779–5805, https://doi.org/10.5194/bg-19-5779-2022, https://doi.org/10.5194/bg-19-5779-2022, 2022
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Wetlands are the largest natural source of methane, one of the most important climate gases. The JULES land surface model simulates these emissions. We use satellite data to evaluate how well JULES reproduces the methane seasonal cycle over different tropical wetlands. It performs well for most regions; however, it struggles for some African wetlands influenced heavily by river flooding. We explain the reasons for these deficiencies and highlight how future development will improve these areas.
Dien Wu, Junjie Liu, Paul O. Wennberg, Paul I. Palmer, Robert R. Nelson, Matthäus Kiel, and Annmarie Eldering
Atmos. Chem. Phys., 22, 14547–14570, https://doi.org/10.5194/acp-22-14547-2022, https://doi.org/10.5194/acp-22-14547-2022, 2022
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Prior studies have derived the combustion efficiency for a region/city using observed CO2 and CO. We further zoomed into the urban domain and accounted for factors affecting the calculation of spatially resolved combustion efficiency from two satellites. The intra-city variability in combustion efficiency was linked to heavy industry within Shanghai and LA without relying on emission inventories. Such an approach can be applied when analyzing data from future geostationary satellites.
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.
Selena Georgiou, Edward T. A. Mitchard, Bart Crezee, Paul I. Palmer, Greta C. Dargie, Sofie Sjögersten, Corneille E. N. Ewango, Ovide B. Emba, Joseph T. Kanyama, Pierre Bola, Jean-Bosco N. Ndjango, Nicholas T. Girkin, Yannick E. Bocko, Suspense A. Ifo, and Simon L. Lewis
EGUsphere, https://doi.org/10.5194/egusphere-2022-580, https://doi.org/10.5194/egusphere-2022-580, 2022
Preprint archived
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Two major vegetation types, hardwood trees and palms, overlay the Central Congo Basin peatland complex, each dominant in different locations. We investigated the influence of terrain and climatological variables on their distribution, using a regression model, and found elevation and seasonal rainfall and temperature contribute significantly. There are indications of an optimal range of net water input for palm swamp to dominate, above and below which hardwood swamp dominates.
Carlos Alberti, Frank Hase, Matthias Frey, Darko Dubravica, Thomas Blumenstock, Angelika Dehn, Paolo Castracane, Gregor Surawicz, Roland Harig, Bianca C. Baier, Caroline Bès, Jianrong Bi, Hartmut Boesch, André Butz, Zhaonan Cai, Jia Chen, Sean M. Crowell, Nicholas M. Deutscher, Dragos Ene, Jonathan E. Franklin, Omaira García, David Griffith, Bruno Grouiez, Michel Grutter, Abdelhamid Hamdouni, Sander Houweling, Neil Humpage, Nicole Jacobs, Sujong Jeong, Lilian Joly, Nicholas B. Jones, Denis Jouglet, Rigel Kivi, Ralph Kleinschek, Morgan Lopez, Diogo J. Medeiros, Isamu Morino, Nasrin Mostafavipak, Astrid Müller, Hirofumi Ohyama, Paul I. Palmer, Mahesh Pathakoti, David F. Pollard, Uwe Raffalski, Michel Ramonet, Robbie Ramsay, Mahesh Kumar Sha, Kei Shiomi, William Simpson, Wolfgang Stremme, Youwen Sun, Hiroshi Tanimoto, Yao Té, Gizaw Mengistu Tsidu, Voltaire A. Velazco, Felix Vogel, Masataka Watanabe, Chong Wei, Debra Wunch, Marcia Yamasoe, Lu Zhang, and Johannes Orphal
Atmos. Meas. Tech., 15, 2433–2463, https://doi.org/10.5194/amt-15-2433-2022, https://doi.org/10.5194/amt-15-2433-2022, 2022
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Space-borne greenhouse gas missions require ground-based validation networks capable of providing fiducial reference measurements. Here, considerable refinements of the calibration procedures for the COllaborative Carbon Column Observing Network (COCCON) are presented. Laboratory and solar side-by-side procedures for the characterization of the spectrometers have been refined and extended. Revised calibration factors for XCO2, XCO and XCH4 are provided, incorporating 47 new spectrometers.
Zhu Deng, Philippe Ciais, Zitely A. Tzompa-Sosa, Marielle Saunois, Chunjing Qiu, Chang Tan, Taochun Sun, Piyu Ke, Yanan Cui, Katsumasa Tanaka, Xin Lin, Rona L. Thompson, Hanqin Tian, Yuanzhi Yao, Yuanyuan Huang, Ronny Lauerwald, Atul K. Jain, Xiaoming Xu, Ana Bastos, Stephen Sitch, Paul I. Palmer, Thomas Lauvaux, Alexandre d'Aspremont, Clément Giron, Antoine Benoit, Benjamin Poulter, Jinfeng Chang, Ana Maria Roxana Petrescu, Steven J. Davis, Zhu Liu, Giacomo Grassi, Clément Albergel, Francesco N. Tubiello, Lucia Perugini, Wouter Peters, and Frédéric Chevallier
Earth Syst. Sci. Data, 14, 1639–1675, https://doi.org/10.5194/essd-14-1639-2022, https://doi.org/10.5194/essd-14-1639-2022, 2022
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In support of the global stocktake of the Paris Agreement on climate change, we proposed a method for reconciling the results of global atmospheric inversions with data from UNFCCC national greenhouse gas inventories (NGHGIs). Here, based on a new global harmonized database that we compiled from the UNFCCC NGHGIs and a comprehensive framework presented in this study to process the results of inversions, we compared their results of carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O).
Douglas P. Finch, Paul I. Palmer, and Tianran Zhang
Atmos. Meas. Tech., 15, 721–733, https://doi.org/10.5194/amt-15-721-2022, https://doi.org/10.5194/amt-15-721-2022, 2022
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We developed a machine learning model to detect plumes of nitrogen dioxide satellite observations over 2 years. We find over 310 000 plumes, mainly over cities, industrial regions, and areas of oil and gas production. Our model performs well in comparison to other datasets and in some cases finds emissions that are not included in other datasets. This method could be used to help locate and measure emission hotspots across the globe and help inform climate policies.
Thomas E. Taylor, Christopher W. O'Dell, David Crisp, Akhiko Kuze, Hannakaisa Lindqvist, Paul O. Wennberg, Abhishek Chatterjee, Michael Gunson, Annmarie Eldering, Brendan Fisher, Matthäus Kiel, Robert R. Nelson, Aronne Merrelli, Greg Osterman, Frédéric Chevallier, Paul I. Palmer, Liang Feng, Nicholas M. Deutscher, Manvendra K. Dubey, Dietrich G. Feist, Omaira E. García, David W. T. Griffith, Frank Hase, Laura T. Iraci, Rigel Kivi, Cheng Liu, Martine De Mazière, Isamu Morino, Justus Notholt, Young-Suk Oh, Hirofumi Ohyama, David F. Pollard, Markus Rettinger, Matthias Schneider, Coleen M. Roehl, Mahesh Kumar Sha, Kei Shiomi, Kimberly Strong, Ralf Sussmann, Yao Té, Voltaire A. Velazco, Mihalis Vrekoussis, Thorsten Warneke, and Debra Wunch
Earth Syst. Sci. Data, 14, 325–360, https://doi.org/10.5194/essd-14-325-2022, https://doi.org/10.5194/essd-14-325-2022, 2022
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We provide an analysis of an 11-year record of atmospheric carbon dioxide (CO2) concentrations derived using an optimal estimation retrieval algorithm on measurements made by the GOSAT satellite. The new product (version 9) shows improvement over the previous version (v7.3) as evaluated against independent estimates of CO2 from ground-based sensors and atmospheric inversion systems. We also compare the new GOSAT CO2 values to collocated estimates from NASA's Orbiting Carbon Observatory-2.
Mark F. Lunt, Alistair J. Manning, Grant Allen, Tim Arnold, Stéphane J.-B. Bauguitte, Hartmut Boesch, Anita L. Ganesan, Aoife Grant, Carole Helfter, Eiko Nemitz, Simon J. O'Doherty, Paul I. Palmer, Joseph R. Pitt, Chris Rennick, Daniel Say, Kieran M. Stanley, Ann R. Stavert, Dickon Young, and Matt Rigby
Atmos. Chem. Phys., 21, 16257–16276, https://doi.org/10.5194/acp-21-16257-2021, https://doi.org/10.5194/acp-21-16257-2021, 2021
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We present an evaluation of the UK's methane emissions between 2013 and 2020 using a network of tall tower measurement sites. We find emissions that are consistent in both magnitude and trend with the UK's reported emissions, with a declining trend driven by a decrease in emissions from England. The impact of various components of the modelling set-up on these findings are explored through a number of sensitivity studies.
Mehliyar Sadiq, Paul I. Palmer, Mark F. Lunt, Liang Feng, Ingrid Super, Stijn N. C. Dellaert, and Hugo A. C. Denier van der Gon
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-816, https://doi.org/10.5194/acp-2021-816, 2021
Publication in ACP not foreseen
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We make use of high-resolution emission inventory of CO2 and co-emitted tracers, satellite measurements, together with nested atmospheric transport model simulation, to investigate how reactive trace gases such as nitrogen dioxide and carbon monoxide can be used as proxies to determine the combustion contribution to atmospheric CO2 over Europe. We find stronger correlation in ratios of nitrogen dioxide and carbon dioxide between emission and satellite observed and modelled column concentration.
Antoine Berchet, Espen Sollum, Rona L. Thompson, Isabelle Pison, Joël Thanwerdas, Grégoire Broquet, Frédéric Chevallier, Tuula Aalto, Adrien Berchet, Peter Bergamaschi, Dominik Brunner, Richard Engelen, Audrey Fortems-Cheiney, Christoph Gerbig, Christine D. Groot Zwaaftink, Jean-Matthieu Haussaire, Stephan Henne, Sander Houweling, Ute Karstens, Werner L. Kutsch, Ingrid T. Luijkx, Guillaume Monteil, Paul I. Palmer, Jacob C. A. van Peet, Wouter Peters, Philippe Peylin, Elise Potier, Christian Rödenbeck, Marielle Saunois, Marko Scholze, Aki Tsuruta, and Yuanhong Zhao
Geosci. Model Dev., 14, 5331–5354, https://doi.org/10.5194/gmd-14-5331-2021, https://doi.org/10.5194/gmd-14-5331-2021, 2021
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We present here the Community Inversion Framework (CIF) to help rationalize development efforts and leverage the strengths of individual inversion systems into a comprehensive framework. The CIF is a programming protocol to allow various inversion bricks to be exchanged among researchers.
The ensemble of bricks makes a flexible, transparent and open-source Python-based tool. We describe the main structure and functionalities and demonstrate it in a simple academic case.
Caterina Mogno, Paul I. Palmer, Christoph Knote, Fei Yao, and Timothy J. Wallington
Atmos. Chem. Phys., 21, 10881–10909, https://doi.org/10.5194/acp-21-10881-2021, https://doi.org/10.5194/acp-21-10881-2021, 2021
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We use a 3-D atmospheric chemistry model to investigate how seasonal emissions sources and meteorological conditions affect the surface distribution of fine particulate matter (PM2.5) and organic aerosol (OA) over the Indo-Gangetic Plain. We find that all seasonal mean values of PM2.5 still exceed safe air quality levels, with human emissions contributing to PM2.5 all year round, open fires during post- and pre-monsoon, and biogenic emissions during monsoon. OA contributes up to 30 % to PM2.5.
Cited articles
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Ahmad Mohtar, A. A., Latif, M. T., Dominick, D., Chel Gee Ooi, M., Azhari, A., Baharudin, N. H., Hanif, N. M., Chung, J. X., and Juneng, L.: Spatiotemporal variations of particulate matter and their association with criteria pollutants and meteorology in Malaysia, Aerosol Air Qual. Res., 22, 220124, https://doi.org/10.4209/aaqr.220124, 2022. a, b
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, c, d, e
Atkinson, R. W., Kang, S., Anderson, H. R., Mills, I. C., and Walton, H. A.: Epidemiological time series studies of PM2.5 and daily mortality and hospital admissions: A systematic review and meta-analysis, Thorax, 69, 660–665, https://doi.org/10.1136/THORAXJNL-2013-204492, 2014. a, b
Boys, B. L., Martin, R. V., van Donkelaar, A., MacDonell, R. J., Hsu, N. C., Cooper, M. J., Yantosca, R. M., Lu, Z., Streets, D. G., Zhang, Q., and Wang, S. W.: Fifteen-year global time series of satellite-derived fine particulate matter, Environ. Sci. Technol., 48, 11109–11118, https://doi.org/10.1021/es502113p, 2014. a, b
Budisulistiorini, S. H., Riva, M., Williams, M., Miyakawa, T., Chen, J., Itoh, M., Surratt, J. D., and Kuwata, M.: Dominant contribution of oxygenated organic aerosol to haze particles from real-time observation in Singapore during an Indonesian wildfire event in 2015, Atmos. Chem. Phys., 18, 16481–16498, https://doi.org/10.5194/acp-18-16481-2018, 2018. a, b, c
Chen, J., Budisulistiorini, S. H., Itoh, M., Lee, W.-C., Miyakawa, T., Komazaki, Y., Yang, L. D. Q., and Kuwata, M.: Water uptake by fresh Indonesian peat burning particles is limited by water-soluble organic matter, Atmos. Chem. Phys., 17, 11591–11604, https://doi.org/10.5194/acp-17-11591-2017, 2017. a
Chen, J., Lee, W. C., Itoh, M., and Kuwata, M.: A significant portion of water-soluble organic matter in fresh biomass burning particles does not contribute to hygroscopic growth: An application of polarity segregation by 1-octanol-water partitioning method, Environ. Sci. Technol., 53, 10034–10042, https://doi.org/10.1021/acs.est.9b01696, 2019. a
Chow, J. C., Cao, J., Chen, L.-W. A., Wang, X., Wang, Q., Tian, J., Ho, S. S. H., Watts, A. C., Carlson, T. B., Kohl, S. D., and Watson, J. G.: Changes in PM2.5 peat combustion source profiles with atmospheric aging in an oxidation flow reactor, Atmos. Meas. Tech., 12, 5475–5501, https://doi.org/10.5194/amt-12-5475-2019, 2019. a
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Crippa, P., Castruccio, S., Archer-Nicholls, S., Lebron, G. B., Kuwata, M., Thota, A., Sumin, S., Butt, E., Wiedinmyer, C., and Spracklen, D. V.: Population exposure to hazardous air quality due to the 2015 fires in Equatorial Asia, Sci. Rep., 6, 37074, https://doi.org/10.1038/srep37074, 2016. a
Csiszar, I., Denis, L., Giglio, L., Justice, C. O., and Hewson, J.: Global fire activity from two years of MODIS data, Int. J. Wildl. Fire, 14, 117–130, https://doi.org/10.1071/WF03078, 2005. a
Darmenov, A. S. and da Silva, A. M.: The Quick Fire Emissions Dataset (QFED): Documentation of versions 2.1, 2.2 and 2.4, Technical Report Series on Global Modeling and Data Assimilation, Vol. 38., NASA, http://gmao.gsfc.nasa.gov/pubs/docs/Darmenov796.pdf (last access: 20 March 2024), 2015. a
Duncan, B. N., Martin, R. V., Staudt, A. C., Yevich, R., and Logan, J. A.: Interannual and seasonal variability of biomass burning emissions constrained by satellite observations, J. Geophys. Res., 108, 4100, https://doi.org/10.1029/2002JD002378, 2003. a
Eastham, S. D., Weisenstein, D. K., and Barrett, S. R. H.: Development and evaluation of the unified tropospheric–stratospheric chemistry extension (UCX) for the global chemistry-transport model GEOS-Chem, Atmos. Environ., 89, 52–63, https://doi.org/10.1016/J.ATMOSENV.2014.02.001, 2014. a
Eck, T. F., Holben, B. N., Reid, J. S., Dubovik, O., Smirnov, A., O'Neill, N. T., Slutsker, I., and Kinne, S.: Wavelength dependence of the optical depth of biomass burning, urban, and desert dust aerosols, J. Geophys. Res.-Atmos., 104, 31333–31349, https://doi.org/10.1029/1999JD900923, 1999. a, b
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, P. Natl. Acad. Sci. USA, 113, 9204–9209, https://doi.org/10.1073/pnas.1524888113, 2016. a
Giglio, L., Randerson, J. T., and van der Werf, G. R.: Analysis of daily, monthly, and annual burned area using the fourth-generation global fire emissions database (GFED4), J. Geophys. Res.-Biogeo., 118, 317–328, https://doi.org/10.1002/jgrg.20042, 2013. a
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. a
Giles, D. M., Sinyuk, A., Sorokin, M. G., Schafer, J. S., Smirnov, A., Slutsker, I., Eck, T. F., Holben, B. N., Lewis, J. R., Campbell, J. R., Welton, E. J., Korkin, S. V., and Lyapustin, A. I.: Advancements in the Aerosol Robotic Network (AERONET) Version 3 database – automated near-real-time quality control algorithm with improved cloud screening for Sun photometer aerosol optical depth (AOD) measurements, Atmos. Meas. Tech., 12, 169–209, https://doi.org/10.5194/amt-12-169-2019, 2019. a
Guenther, A. B., Jiang, X., Heald, C. L., Sakulyanontvittaya, T., Duhl, T., Emmons, L. K., and Wang, X.: The Model of Emissions of Gases and Aerosols from Nature version 2.1 (MEGAN2.1): An extended and updated framework for modeling biogenic emissions, Geosci. Model Dev., 5, 1471–1492, https://doi.org/10.5194/gmd-5-1471-2012, 2012. a
Hammer, M. S., Martin, R. V., van Donkelaar, A., Buchard, V., Torres, O., Ridley, D. A., and Spurr, R. J. D.: Interpreting the ultraviolet aerosol index observed with the OMI satellite instrument to understand absorption by organic aerosols: Implications for atmospheric oxidation and direct radiative effects, Atmos. Chem. Phys., 16, 2507–2523, https://doi.org/10.5194/acp-16-2507-2016, 2016. a
Hammer, M. S., van Donkelaar, A., Li, C., Lyapustin, A., Sayer, A. M., Hsu, N. C., Levy, R. C., Garay, M. J., Kalashnikova, O. V., Kahn, R. A., Brauer, M., Apte, J. S., Henze, D. K., Zhang, L., Zhang, Q., Ford, B., Pierce, J. R., and Martin, R. V.: Global estimates and long-term trends of fine particulate matter concentrations (1998–2018), Environ. Sci. Technol., 54, 7879–7890, https://doi.org/10.1021/acs.est.0c01764, 2020. a, b
Hoesly, R. M., Smith, S. J., Feng, L., Klimont, Z., Janssens-Maenhout, G., Pitkanen, T., Seibert, J. J., Vu, L., Andres, R. J., Bolt, R. M., Bond, T. C., Dawidowski, L., Kholod, N., Kurokawa, J.-I., Li, M., Liu, L., Lu, Z., Cecilia, M., Moura, P., O'rourke, P. R., and Zhang, Q.: Historical (1750–2014) anthropogenic emissions of reactive gases and aerosols from the Community Emissions Data System (CEDS), Geosci. Model Dev., 11, 369–408, https://doi.org/10.5194/gmd-11-369-2018, 2018. a
Hudman, R. C., Moore, N. E., Mebust, A. K., Martin, R. V., Russell, A. R., Valin, L. C., and Cohen, R. C.: Steps towards a mechanistic model of global soil nitric oxide emissions: Implementation and space based-constraints, Atmos. Chem. Phys., 12, 7779–7795, https://doi.org/10.5194/acp-12-7779-2012, 2012. a
Huijnen, V., Wooster, M. J., Kaiser, J. W., Gaveau, D. L. A., 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
Jayarathne, T., Stockwell, C. E., Gilbert, A. A., Daugherty, K., Cochrane, M. A., Ryan, K. C., Putra, E. I., Saharjo, B. H., Nurhayati, A. D., Albar, I., Yokelson, R. J., and Stone, E. A.: Chemical characterization of fine particulate matter emitted by peat fires in Central Kalimantan, Indonesia, during the 2015 El Niño, Atmos. Chem. Phys., 18, 2585–2600, https://doi.org/10.5194/acp-18-2585-2018, 2018. a
Jo, D. S., Park, R. J., Lee, S., Kim, S. W., and Zhang, X.: A global simulation of brown carbon: Implications for photochemistry and direct radiative effect, Atmos. Chem. Phys., 16, 3413–3432, https://doi.org/10.5194/acp-16-3413-2016, 2016. a
Jo, D. S., Hodzic, A., Emmons, L. K., Marais, E. A., Peng, Z., Nault, B. A., Hu, W., Campuzano-Jost, P., and Jimenez, J. L.: A simplified parameterization of isoprene-epoxydiol-derived secondary organic aerosol (IEPOX-SOA) for global chemistry and climate models: A case study with GEOS-Chem v11-02-rc, Geosci. Model Dev., 12, 2983–3000, https://doi.org/10.5194/gmd-12-2983-2019, 2019. a
Kahn, R., Banerjee, P., McDonald, D., and Diner, D. J.: Sensitivity of multiangle imaging to aerosol optical depth and to pure-particle size distribution and composition over ocean, J. Geophys. Res.-Atmos., 103, 32195–32213, https://doi.org/10.1029/98JD01752, 1998. a
Kaiser, J. W., Heil, A., Andreae, M. O., Benedetti, A., Chubarova, N., Jones, L., Morcrette, J.-J., Razinger, M., Schultz, M. G., Suttie, M., and van der Werf, G. R.: Biomass burning emissions estimated with a global fire assimilation system based on observed fire radiative power, Biogeosciences, 9, 527–554, https://doi.org/10.5194/bg-9-527-2012, 2012. 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, 11105–11121, https://doi.org/10.5194/acp-19-11105-2019, 2019. a, b
Koplitz, S. N., Mickley, L. J., Marlier, M. E., Buonocore, J. J., Kim, P. S., Liu, T., Sulprizio, M. P., DeFries, R. S., Jacob, D. J., Schwartz, J., Pongsiri, M., and Myers, S. S.: Public health impacts of the severe haze in Equatorial Asia in September–October 2015: Demonstration of a new framework for informing fire management strategies to reduce downwind smoke exposure, Environ. Res. Lett., 11, 94023, https://doi.org/10.1088/1748-9326/11/9/094023, 2016. a
Latif, M. T., Dominick, D., Ahamad, F., Khan, M. F., Juneng, L., Hamzah, F. M., and Nadzir, M. S. M.: Long term assessment of air quality from a background station on the Malaysian Peninsula, Sci. Total Environ., 482–483, 336–348, https://doi.org/10.1016/J.SCITOTENV.2014.02.132, 2014. a
Levelt, P. F., van den Oord, G. H. J., Dobber, M. R., Malkki, A., Visser, H., de Vries, J., Stammes, P., Lundell, J. O. V., and Saari, H.: The Ozone Monitoring Instrument, IEEE T. Geosci. Remote, 44, 1093–1101, https://doi.org/10.1109/TGRS.2006.872333, 2006. a
Levy, R. C., Remer, L. A., Kleidman, R. G., Mattoo, S., Ichoku, C., Kahn, R., and Eck, T. F.: Global evaluation of the Collection 5 MODIS dark-target aerosol products over land, Atmos. Chem. Phys., 10, 10399–10420, https://doi.org/10.5194/acp-10-10399-2010, 2010. a
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Short summary
We use an atmospheric chemistry model to investigate aerosols emitted from fire activity across Southeast Asia. We find that the limited nature of measurements in this region leads to large uncertainties that significantly hinder the model representation of these aerosols and their impacts on air quality. As a result, the number of monthly attributable deaths is underestimated by as many as 4500, particularly in March at the peak of the mainland burning season.
We use an atmospheric chemistry model to investigate aerosols emitted from fire activity across...
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