Articles | Volume 24, issue 19
https://doi.org/10.5194/acp-24-11081-2024
© 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-24-11081-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
02 Oct 2024
Research article |
| 02 Oct 2024
| 02 Oct 2024
Satellite-observed relationships between land cover, burned area, and atmospheric composition over the southern Amazon
School of Geosciences, University of Edinburgh, Edinburgh, United Kingdom
Richard J. Pope
School of Earth and Environment, University of Leeds, Leeds, United Kingdom
National Centre for Earth Observation, University of Leeds, Leeds, United Kingdom
Ruth M. Doherty
School of Geosciences, University of Edinburgh, Edinburgh, United Kingdom
Fiona M. O'Connor
Met Office, Exeter, United Kingdom
Department of Mathematics and Statistics, Global Systems Institute, University of Exeter, Exeter, United Kingdom
Chris Wilson
School of Earth and Environment, University of Leeds, Leeds, United Kingdom
National Centre for Earth Observation, University of Leeds, Leeds, United Kingdom
Hugh Pumphrey
School of Geosciences, University of Edinburgh, Edinburgh, United Kingdom
Related authors
Emma Sands, Ruth M. Doherty, Fiona M. O'Connor, Richard J. Pope, James Weber, and Daniel P. Grosvenor
Atmos. Chem. Phys., 25, 7269–7297, https://doi.org/10.5194/acp-25-7269-2025, https://doi.org/10.5194/acp-25-7269-2025, 2025
Short summary
Short summary
We perform a detailed satellite–model comparison for isoprene, formaldehyde and aerosol optical depth in an Earth system model. We quantify the impacts of several processes that affect how biosphere–atmosphere interactions influence atmospheric chemistry and aerosols. Our findings highlight that the aerosol direct effect is sensitive to the processes studied. These results can inform future investigations of how the biosphere can affect atmospheric composition and climate.
William J. Collins, Fiona M. O'Connor, Rachael E. Byrom, Øivind Hodnebrog, Patrick Jöckel, Mariano Mertens, Gunnar Myhre, Matthias Nützel, Dirk Olivié, Ragnhild Bieltvedt Skeie, Laura Stecher, Larry W. Horowitz, Vaishali Naik, Gregory Faluvegi, Ulas Im, Lee T. Murray, Drew Shindell, Kostas Tsigaridis, Nathan Luke Abraham, and James Keeble
Atmos. Chem. Phys., 25, 9031–9060, https://doi.org/10.5194/acp-25-9031-2025, https://doi.org/10.5194/acp-25-9031-2025, 2025
Short summary
Short summary
We used 7 climate models that include atmospheric chemistry and find that in a scenario with weak controls on air quality, the warming effects (over 2015 to 2050) of decreases in ozone-depleting substances and increases in air quality pollutants are approximately equal and would make ozone the second highest contributor to warming over this period. We find that for stratospheric ozone recovery, the standard measure of climate effects underestimates a more comprehensive measure.
Maria P. Veláquez-García, Richard J. Pope, Steven T. Turnock, Chetan Deva, David P. Moore, Guilherme Mataveli, Steve R. Arnold, Ruth M. Doherty, and Martyn P. Chiperffield
EGUsphere, https://doi.org/10.5194/egusphere-2025-3579, https://doi.org/10.5194/egusphere-2025-3579, 2025
This preprint is open for discussion and under review for Biogeosciences (BG).
Short summary
Short summary
Incorporating fire simulation into climate models is crucial for accurately representing the interactions between fires, ecosystems, and climate, thereby enhancing climate projections. In South America, the INFERNO fire model captures active fire zones, e.g. the Amazon Arc of Deforestation, but it overestimates emissions in other areas (mainly in tree-rich ecosystems). The model errors capturing seasonal emission cycles relate to the effects of soil moisture on plant flammability and growth.
Paul T. Griffiths, Laura J. Wilcox, Robert J. Allen, Vaishali Naik, Fiona M. O'Connor, Michael Prather, Alex Archibald, Florence Brown, Makoto Deushi, William Collins, Stephanie Fiedler, Naga Oshima, Lee T. Murray, Bjørn H. Samset, Chris Smith, Steven Turnock, Duncan Watson-Parris, and Paul J. Young
Atmos. Chem. Phys., 25, 8289–8328, https://doi.org/10.5194/acp-25-8289-2025, https://doi.org/10.5194/acp-25-8289-2025, 2025
Short summary
Short summary
The Aerosol Chemistry Model Intercomparison Project (AerChemMIP) aimed to quantify the climate and air quality impacts of aerosols and chemically reactive gases. We review its contribution to AR6 (Sixth Assessment Report of the Intergovernmental Panel on Climate Change) and the wider understanding of the role of these species in climate and climate change. We identify challenges and provide recommendations to improve the utility and uptake of climate model data, detailed summary tables of CMIP6 models, experiments, and emergent diagnostics.
Suvarna Fadnavis, Yasin Elshorbany, Jerald Ziemke, Brice Barret, Alexandru Rap, P. R. Satheesh Chandran, Richard J. Pope, Vijay Sagar, Domenico Taraborrelli, Eric Le Flochmoen, Juan Cuesta, Catherine Wespes, Folkert Boersma, Isolde Glissenaar, Isabelle De Smedt, Michel Van Roozendael, Hervé Petetin, and Isidora Anglou
Atmos. Chem. Phys., 25, 8229–8254, https://doi.org/10.5194/acp-25-8229-2025, https://doi.org/10.5194/acp-25-8229-2025, 2025
Short summary
Short summary
Satellites and model simulations show enhancement in tropospheric ozone, which is highly impacted by human-produced nitrous oxides compared to volatile organic compounds. The increased amount of ozone enhances ozone radiative forcing. The ozone enhancement and associated radiative forcing are the highest over South and East Asia. The emissions of nitrous oxides show a higher influence on shifting ozone photochemical regimes than volatile organic compounds.
Megan A. J. Brown, Nicola J . Warwick, Nathan Luke Abraham, Paul T. Griffiths, Steve T. Rumbold, Gerd A. Folberth, Fiona M. O'Connor, and Alex T. Archibald
EGUsphere, https://doi.org/10.5194/egusphere-2025-2676, https://doi.org/10.5194/egusphere-2025-2676, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Short summary
Hydrogen (H2) is an indirect greenhouse gas by increasing methane (CH4) lifetime. Interaction between H2 and CH4 is important for hydrogen’s global warming potential (GWP). Global models do not represent this interaction well; H2 or CH4 are prescribed at the surface. We implement an interactive H2 scheme into a global model coupled with interactive CH4. We simulate scenarios demonstrating its capability, improving model performance and more accurately representing H2-CH4 interaction.
Emma Sands, Ruth M. Doherty, Fiona M. O'Connor, Richard J. Pope, James Weber, and Daniel P. Grosvenor
Atmos. Chem. Phys., 25, 7269–7297, https://doi.org/10.5194/acp-25-7269-2025, https://doi.org/10.5194/acp-25-7269-2025, 2025
Short summary
Short summary
We perform a detailed satellite–model comparison for isoprene, formaldehyde and aerosol optical depth in an Earth system model. We quantify the impacts of several processes that affect how biosphere–atmosphere interactions influence atmospheric chemistry and aerosols. Our findings highlight that the aerosol direct effect is sensitive to the processes studied. These results can inform future investigations of how the biosphere can affect atmospheric composition and climate.
Beth Dingley, James A. Anstey, Marta Abalos, Carsten Abraham, Tommi Bergman, Lisa Bock, Sonya Fiddes, Birgit Hassler, Ryan J. Kramer, Fei Luo, Fiona M. O'Connor, Petr Šácha, Isla R. Simpson, Laura J. Wilcox, and Mark D. Zelinka
EGUsphere, https://doi.org/10.5194/egusphere-2025-3189, https://doi.org/10.5194/egusphere-2025-3189, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Short summary
This manuscript defines as a list of variables and scientific opportunities which are requested from the CMIP7 Assessment Fast Track to address open atmospheric science questions. The list reflects the output of a large public community engagement effort, coordinated across autumn 2025 through to summer 2025.
Steven T. Turnock, Dimitris Akritidis, Larry Horowitz, Mariano Mertens, Andrea Pozzer, Carly L. Reddington, Hantao Wang, Putian Zhou, and Fiona O'Connor
Atmos. Chem. Phys., 25, 7111–7136, https://doi.org/10.5194/acp-25-7111-2025, https://doi.org/10.5194/acp-25-7111-2025, 2025
Short summary
Short summary
We assess the drivers behind changes in peak-season surface ozone concentrations and risks to human health between 1850 and 2014. Substantial increases in surface ozone have occurred over this period, resulting in an increased risk to human health, driven mainly by increases in anthropogenic NOx emissions and global CH4 concentrations. Fixing anthropogenic NOx emissions at 1850 values in the near-present-day period can eliminate the risk to human health associated with exposure to surface ozone.
Joao C. M. Teixeira, Chantelle Burton, Douglas I. Kelley, Gerd A. Folberth, Fiona M. O'Connor, Richard A. Betts, and Apostolos Voulgarakis
EGUsphere, https://doi.org/10.5194/egusphere-2025-3066, https://doi.org/10.5194/egusphere-2025-3066, 2025
This preprint is open for discussion and under review for Earth System Dynamics (ESD).
Short summary
Short summary
Burnt areas produced by wildfires around the world are decreasing, especially in tropical regions, but many climate models fail to show this trend. Our study looks at whether adding a measure of human development to a fire model could improve its representation of these processes. We found that including these factors helped the model better match observations in many regions. This shows that human activity plays a key role in shaping fire trends.
Zhenze Liu, Ke Li, Oliver Wild, Ruth M. Doherty, Fiona M. O’Connor, and Steven T. Turnock
EGUsphere, https://doi.org/10.5194/egusphere-2025-1250, https://doi.org/10.5194/egusphere-2025-1250, 2025
Short summary
Short summary
Our research aimed to enhance predictions of ozone levels in the atmosphere, a gas that influences air quality and climate. We used a computer model called UKESM1 to simulate ozone, but its estimates were often inaccurate. By applying deep learning, we improved the accuracy of these predictions. This advance helps us understand how ozone might shift as the climate warms. Better predictions are vital for shaping policies on air quality and climate.
Alok K. Pandey, David S. Stevenson, Alcide Zhao, Richard J. Pope, Ryan Hossaini, Krishan Kumar, and Martyn P. Chipperfield
Atmos. Chem. Phys., 25, 4785–4802, https://doi.org/10.5194/acp-25-4785-2025, https://doi.org/10.5194/acp-25-4785-2025, 2025
Short summary
Short summary
Nitrogen dioxide is an air pollutant largely controlled by human activity that affects ozone, methane, and aerosols. Satellite instruments can quantify column NO2 and, by carefully matching the time and location of measurements, enable evaluation of model simulations. NO2 over south and east Asia is assessed, showing that the model captures not only many features of the measurements, but also important differences that suggest model deficiencies in representing several aspects of the atmospheric chemistry of NO2.
Matilda A. Pimlott, Richard J. Pope, Brian J. Kerridge, Richard Siddans, Barry G. Latter, Lucy J. Ventress, Wuhu Feng, and Martyn P. Chipperfield
Atmos. Chem. Phys., 25, 4391–4401, https://doi.org/10.5194/acp-25-4391-2025, https://doi.org/10.5194/acp-25-4391-2025, 2025
Short summary
Short summary
Globally, lockdowns were implemented to limit the spread of COVID-19, leading to a decrease in emissions of key air pollutants. Here, we use novel satellite data and a chemistry model to investigate the impact of the pandemic on tropospheric ozone (O3), a key pollutant, in 2020. Overall, we found substantial decreases of up to 20 %, two-thirds of which came from emission reductions, while one-third was due to a decrease in the stratospheric O3 flux into the troposphere.
Michael P. Cartwright, Jeremy J. Harrison, David P. Moore, Richard J. Pope, Martyn P. Chipperfield, Chris Wilson, and Wuhu Feng
EGUsphere, https://doi.org/10.5194/egusphere-2025-1073, https://doi.org/10.5194/egusphere-2025-1073, 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.
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.
Matilda A. Pimlott, Richard J. Pope, Brian J. Kerridge, Richard Siddans, Barry G. Latter, Wuhu Feng, and Martyn P. Chipperfield
EGUsphere, https://doi.org/10.5194/egusphere-2024-3717, https://doi.org/10.5194/egusphere-2024-3717, 2024
Short summary
Short summary
Tropospheric ozone (O3) is a harmful secondary atmospheric pollutant and an important greenhouse gas. Here, we present an in-depth analysis of lower-tropospheric sub-column O3 (LTCO3, surface – 6 km) records from three satellite products produced by the Rutherford Appleton Laboratory (RAL) over Europe between 1996 and 2017. Overall, we detect moderate negative trends in the satellite records, but corresponding model simulations and ozonesonde measurements show negligible trends.
Maria P. Velásquez-García, K. Santiago Hernández, James A. Vergara-Correa, Richard J. Pope, Miriam Gómez-Marín, and Angela M. Rendón
Atmos. Chem. Phys., 24, 11497–11520, https://doi.org/10.5194/acp-24-11497-2024, https://doi.org/10.5194/acp-24-11497-2024, 2024
Short summary
Short summary
In the Aburrá Valley, northern South America, local emissions determine air quality conditions. However, we found that external sources, such as regional fires, Saharan dust, and volcanic emissions, increase particulate concentrations and worsen chemical composition by introducing elements like heavy metals. Dry winds and source variability contribute to seasonal influences on these events. This study assesses the air quality risks posed by such events, which can affect broad regions worldwide.
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.
Richard J. Pope, Fiona M. O'Connor, Mohit Dalvi, Brian J. Kerridge, Richard Siddans, Barry G. Latter, Brice Barret, Eric Le Flochmoen, Anne Boynard, Martyn P. Chipperfield, Wuhu Feng, Matilda A. Pimlott, Sandip S. Dhomse, Christian Retscher, Catherine Wespes, and Richard Rigby
Atmos. Chem. Phys., 24, 9177–9195, https://doi.org/10.5194/acp-24-9177-2024, https://doi.org/10.5194/acp-24-9177-2024, 2024
Short summary
Short summary
Ozone is a potent air pollutant in the lower troposphere, with adverse impacts on human health. Satellite records of tropospheric ozone currently show large-scale inconsistencies in long-term trends. Our detailed study of the potential factors (e.g. satellite errors, where the satellite can observe ozone) potentially driving these inconsistencies found that, in North America, Europe, and East Asia, the underlying trends are typically small with large uncertainties.
Hanqin Tian, Naiqing Pan, Rona L. Thompson, Josep G. Canadell, Parvadha Suntharalingam, Pierre Regnier, Eric A. Davidson, Michael Prather, Philippe Ciais, Marilena Muntean, Shufen Pan, Wilfried Winiwarter, Sönke Zaehle, Feng Zhou, Robert B. Jackson, Hermann W. Bange, Sarah Berthet, Zihao Bian, Daniele Bianchi, Alexander F. Bouwman, Erik T. Buitenhuis, Geoffrey Dutton, Minpeng Hu, Akihiko Ito, Atul K. Jain, Aurich Jeltsch-Thömmes, Fortunat Joos, Sian Kou-Giesbrecht, Paul B. Krummel, Xin Lan, Angela Landolfi, Ronny Lauerwald, Ya Li, Chaoqun Lu, Taylor Maavara, Manfredi Manizza, Dylan B. Millet, Jens Mühle, Prabir K. Patra, Glen P. Peters, Xiaoyu Qin, Peter Raymond, Laure Resplandy, Judith A. Rosentreter, Hao Shi, Qing Sun, Daniele Tonina, Francesco N. Tubiello, Guido R. van der Werf, Nicolas Vuichard, Junjie Wang, Kelley C. Wells, Luke M. Western, Chris Wilson, Jia Yang, Yuanzhi Yao, Yongfa You, and Qing Zhu
Earth Syst. Sci. Data, 16, 2543–2604, https://doi.org/10.5194/essd-16-2543-2024, https://doi.org/10.5194/essd-16-2543-2024, 2024
Short summary
Short summary
Atmospheric concentrations of nitrous oxide (N2O), a greenhouse gas 273 times more potent than carbon dioxide, have increased by 25 % since the preindustrial period, with the highest observed growth rate in 2020 and 2021. This rapid growth rate has primarily been due to a 40 % increase in anthropogenic emissions since 1980. Observed atmospheric N2O concentrations in recent years have exceeded the worst-case climate scenario, underscoring the importance of reducing anthropogenic N2O emissions.
Stephanie Fiedler, Vaishali Naik, Fiona M. O'Connor, Christopher J. Smith, Paul Griffiths, Ryan J. Kramer, Toshihiko Takemura, Robert J. Allen, Ulas Im, Matthew Kasoar, Angshuman Modak, Steven Turnock, Apostolos Voulgarakis, Duncan Watson-Parris, Daniel M. Westervelt, Laura J. Wilcox, Alcide Zhao, William J. Collins, Michael Schulz, Gunnar Myhre, and Piers M. Forster
Geosci. Model Dev., 17, 2387–2417, https://doi.org/10.5194/gmd-17-2387-2024, https://doi.org/10.5194/gmd-17-2387-2024, 2024
Short summary
Short summary
Climate scientists want to better understand modern climate change. Thus, climate model experiments are performed and compared. The results of climate model experiments differ, as assessed in the latest Intergovernmental Panel on Climate Change (IPCC) assessment report. This article gives insights into the challenges and outlines opportunities for further improving the understanding of climate change. It is based on views of a group of experts in atmospheric composition–climate interactions.
Richard J. Pope, Alexandru Rap, Matilda A. Pimlott, Brice Barret, Eric Le Flochmoen, Brian J. Kerridge, Richard Siddans, Barry G. Latter, Lucy J. Ventress, Anne Boynard, Christian Retscher, Wuhu Feng, Richard Rigby, Sandip S. Dhomse, Catherine Wespes, and Martyn P. Chipperfield
Atmos. Chem. Phys., 24, 3613–3626, https://doi.org/10.5194/acp-24-3613-2024, https://doi.org/10.5194/acp-24-3613-2024, 2024
Short summary
Short summary
Tropospheric ozone is an important short-lived climate forcer which influences the incoming solar short-wave radiation and the outgoing long-wave radiation in the atmosphere (8–15 km) where the balance between the two yields a net positive (i.e. warming) effect at the surface. Overall, we find that the tropospheric ozone radiative effect ranges between 1.21 and 1.26 W m−2 with a negligible trend (2008–2017), suggesting that tropospheric ozone influences on climate have remained stable with time.
Emily Dowd, Alistair J. Manning, Bryn Orth-Lashley, Marianne Girard, James France, Rebecca E. Fisher, Dave Lowry, Mathias Lanoisellé, Joseph R. Pitt, Kieran M. Stanley, Simon O'Doherty, Dickon Young, Glen Thistlethwaite, Martyn P. Chipperfield, Emanuel Gloor, and Chris Wilson
Atmos. Meas. Tech., 17, 1599–1615, https://doi.org/10.5194/amt-17-1599-2024, https://doi.org/10.5194/amt-17-1599-2024, 2024
Short summary
Short summary
We provide the first validation of the satellite-derived emission estimates using surface-based mobile greenhouse gas surveys of an active gas leak detected near Cheltenham, UK. GHGSat’s emission estimates broadly agree with the surface-based mobile survey and steps were taken to fix the leak, highlighting the importance of satellite data in identifying emissions and helping to reduce our human impact on climate change.
Ross Noel Bannister and Chris Wilson
EGUsphere, https://doi.org/10.5194/egusphere-2024-655, https://doi.org/10.5194/egusphere-2024-655, 2024
Preprint archived
Short summary
Short summary
Prior information is essential for the top-down estimation of CH4 surface fluxes. Errors in the prior are correlated in time/space, but accounting for correlations can be costly. We report on an efficient scheme to represent correlations in the inverse modelling system, INVICAT. The method is tested by assimilating CH4 observations using the scheme. Our findings show that accounting for spatio-temporal correlations improve CH4 flux estimates, demonstrating that the method should be further used.
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.
Richard J. Pope, Brian J. Kerridge, Richard Siddans, Barry G. Latter, Martyn P. Chipperfield, Wuhu Feng, Matilda A. Pimlott, Sandip S. Dhomse, Christian Retscher, and Richard Rigby
Atmos. Chem. Phys., 23, 14933–14947, https://doi.org/10.5194/acp-23-14933-2023, https://doi.org/10.5194/acp-23-14933-2023, 2023
Short summary
Short summary
Ozone is a potent air pollutant, and we present the first study to investigate long-term changes in lower tropospheric column ozone (LTCO3) from space. We have constructed a merged LTCO3 dataset from GOME-1, SCIAMACHY and OMI between 1996 and 2017. Comparing LTCO3 between the 1996–2000 and 2013–2017 5-year averages, we find significant positive increases in the tropics/sub-tropics, while in the northern mid-latitudes, we find small-scale differences.
Zhenze Liu, Oliver Wild, Ruth M. Doherty, Fiona M. O'Connor, and Steven T. Turnock
Atmos. Chem. Phys., 23, 13755–13768, https://doi.org/10.5194/acp-23-13755-2023, https://doi.org/10.5194/acp-23-13755-2023, 2023
Short summary
Short summary
We investigate the impact of net-zero policies on surface ozone pollution in China. A chemistry–climate model is used to simulate ozone changes driven by local and external emissions, methane, and warmer climates. A deep learning model is applied to generate more robust ozone projection, and we find that the benefits of net-zero policies may be overestimated with the chemistry–climate model. Nevertheless, it is clear that the policies can still substantially reduce ozone pollution in future.
Nicola J. Warwick, Alex T. Archibald, Paul T. Griffiths, James Keeble, Fiona M. O'Connor, John A. Pyle, and Keith P. Shine
Atmos. Chem. Phys., 23, 13451–13467, https://doi.org/10.5194/acp-23-13451-2023, https://doi.org/10.5194/acp-23-13451-2023, 2023
Short summary
Short summary
A chemistry–climate model has been used to explore the atmospheric response to changes in emissions of hydrogen and other species associated with a shift from fossil fuel to hydrogen use. Leakage of hydrogen results in indirect global warming, offsetting greenhouse gas emission reductions from reduced fossil fuel use. To maximise the benefit of hydrogen as an energy source, hydrogen leakage and emissions of methane, carbon monoxide and nitrogen oxides should be minimised.
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.
Joao Carlos Martins Teixeira, Chantelle Burton, Douglas I. Kelly, Gerd A. Folberth, Fiona M. O'Connor, Richard A. Betts, and Apostolos Voulgarakis
Biogeosciences Discuss., https://doi.org/10.5194/bg-2023-136, https://doi.org/10.5194/bg-2023-136, 2023
Revised manuscript not accepted
Short summary
Short summary
Representing socio-economic impacts on fires is crucial to underpin the confidence in global fire models. Introducing these into INFERNO, reduces biases and improves the modelled burnt area (BA) trends when compared to observations. Including socio-economic factors in the representation of fires in Earth System Models is important for realistically simulating BA, quantifying trends in the recent past, and for understanding the main drivers of those at regional scales.
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.
Luana S. Basso, Chris Wilson, Martyn P. Chipperfield, Graciela Tejada, Henrique L. G. Cassol, Egídio Arai, Mathew Williams, T. Luke Smallman, Wouter Peters, Stijn Naus, John B. Miller, and Manuel Gloor
Atmos. Chem. Phys., 23, 9685–9723, https://doi.org/10.5194/acp-23-9685-2023, https://doi.org/10.5194/acp-23-9685-2023, 2023
Short summary
Short summary
The Amazon’s carbon balance may have changed due to forest degradation, deforestation and warmer climate. We used an atmospheric model and atmospheric CO2 observations to quantify Amazonian carbon emissions (2010–2018). The region was a small carbon source to the atmosphere, mostly due to fire emissions. Forest uptake compensated for ~ 50 % of the fire emissions, meaning that the remaining forest is still a small carbon sink. We found no clear evidence of weakening carbon uptake over the period.
Emily Dowd, Chris Wilson, Martyn P. Chipperfield, Emanuel Gloor, Alistair Manning, and Ruth Doherty
Atmos. Chem. Phys., 23, 7363–7382, https://doi.org/10.5194/acp-23-7363-2023, https://doi.org/10.5194/acp-23-7363-2023, 2023
Short summary
Short summary
Surface observations of methane show that the seasonal cycle amplitude (SCA) of methane is decreasing in the northern high latitudes (NHLs) but increased globally (1995–2020). The NHL decrease is counterintuitive, as we expect the SCA to increase with increasing concentrations. We use a chemical transport model to investigate changes in SCA in the NHLs. We find well-mixed methane and changes in emissions from Canada, the Middle East, and Europe are the largest contributors to the SCA in NHLs.
Peter Joyce, Cristina Ruiz Villena, Yahui Huang, Alex Webb, Manuel Gloor, Fabien H. Wagner, Martyn P. Chipperfield, Rocío Barrio Guilló, Chris Wilson, and Hartmut Boesch
Atmos. Meas. Tech., 16, 2627–2640, https://doi.org/10.5194/amt-16-2627-2023, https://doi.org/10.5194/amt-16-2627-2023, 2023
Short summary
Short summary
Methane emissions are responsible for a lot of the warming caused by the greenhouse effect, much of which comes from a small number of point sources. We can identify methane point sources by analysing satellite data, but it requires a lot of time invested by experts and is prone to very high errors. Here, we produce a neural network that can automatically identify methane point sources and estimate the mass of methane that is being released per hour and are able to do so with far smaller errors.
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.
Ana Maria Roxana Petrescu, Chunjing Qiu, Matthew J. McGrath, Philippe Peylin, Glen P. Peters, Philippe Ciais, Rona L. Thompson, Aki Tsuruta, Dominik Brunner, Matthias Kuhnert, Bradley Matthews, Paul I. Palmer, Oksana Tarasova, Pierre Regnier, Ronny Lauerwald, David Bastviken, Lena Höglund-Isaksson, Wilfried Winiwarter, Giuseppe Etiope, Tuula Aalto, Gianpaolo Balsamo, Vladislav Bastrikov, Antoine Berchet, Patrick Brockmann, Giancarlo Ciotoli, Giulia Conchedda, Monica Crippa, Frank Dentener, Christine D. Groot Zwaaftink, Diego Guizzardi, Dirk Günther, Jean-Matthieu Haussaire, Sander Houweling, Greet Janssens-Maenhout, Massaer Kouyate, Adrian Leip, Antti Leppänen, Emanuele Lugato, Manon Maisonnier, Alistair J. Manning, Tiina Markkanen, Joe McNorton, Marilena Muntean, Gabriel D. Oreggioni, Prabir K. Patra, Lucia Perugini, Isabelle Pison, Maarit T. Raivonen, Marielle Saunois, Arjo J. Segers, Pete Smith, Efisio Solazzo, Hanqin Tian, Francesco N. Tubiello, Timo Vesala, Guido R. van der Werf, Chris Wilson, and Sönke Zaehle
Earth Syst. Sci. Data, 15, 1197–1268, https://doi.org/10.5194/essd-15-1197-2023, https://doi.org/10.5194/essd-15-1197-2023, 2023
Short summary
Short summary
This study updates the state-of-the-art scientific overview of CH4 and N2O emissions in the EU27 and UK in Petrescu et al. (2021a). Yearly updates are needed to improve the different respective approaches and to inform on the development of formal verification systems. It integrates the most recent emission inventories, process-based model and regional/global inversions, comparing them with UNFCCC national GHG inventories, in support to policy to facilitate real-time verification procedures.
Zixuan Jia, Carlos Ordóñez, Ruth M. Doherty, Oliver Wild, Steven T. Turnock, and Fiona M. O'Connor
Atmos. Chem. Phys., 23, 2829–2842, https://doi.org/10.5194/acp-23-2829-2023, https://doi.org/10.5194/acp-23-2829-2023, 2023
Short summary
Short summary
This study investigates the influence of the winter large-scale circulation on daily concentrations of PM2.5 and their sensitivity to emissions. The new proposed circulation index can effectively distinguish different levels of air pollution and explain changes in PM2.5 sensitivity to emissions from local and surrounding regions. We then project future changes in PM2.5 concentrations using this index and find an increase in PM2.5 concentrations over the region due to climate change.
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
Short summary
Short summary
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.
Ville Leinonen, Harri Kokkola, Taina Yli-Juuti, Tero Mielonen, Thomas Kühn, Tuomo Nieminen, Simo Heikkinen, Tuuli Miinalainen, Tommi Bergman, Ken Carslaw, Stefano Decesari, Markus Fiebig, Tareq Hussein, Niku Kivekäs, Radovan Krejci, Markku Kulmala, Ari Leskinen, Andreas Massling, Nikos Mihalopoulos, Jane P. Mulcahy, Steffen M. Noe, Twan van Noije, Fiona M. O'Connor, Colin O'Dowd, Dirk Olivie, Jakob B. Pernov, Tuukka Petäjä, Øyvind Seland, Michael Schulz, Catherine E. Scott, Henrik Skov, Erik Swietlicki, Thomas Tuch, Alfred Wiedensohler, Annele Virtanen, and Santtu Mikkonen
Atmos. Chem. Phys., 22, 12873–12905, https://doi.org/10.5194/acp-22-12873-2022, https://doi.org/10.5194/acp-22-12873-2022, 2022
Short summary
Short summary
We provide the first extensive comparison of detailed aerosol size distribution trends between in situ observations from Europe and five different earth system models. We investigated aerosol modes (nucleation, Aitken, and accumulation) separately and were able to show the differences between measured and modeled trends and especially their seasonal patterns. The differences in model results are likely due to complex effects of several processes instead of certain specific model features.
Zhenze Liu, Ruth M. Doherty, Oliver Wild, Fiona M. O'Connor, and Steven T. Turnock
Atmos. Chem. Phys., 22, 12543–12557, https://doi.org/10.5194/acp-22-12543-2022, https://doi.org/10.5194/acp-22-12543-2022, 2022
Short summary
Short summary
Weaknesses in process representation in chemistry–climate models lead to biases in simulating surface ozone and to uncertainty in projections of future ozone change. We develop a deep learning model to demonstrate the feasibility of ozone bias correction and show its capability in providing improved assessments of the impacts of climate and emission changes on future air quality, along with valuable information to guide future model development.
Flossie Brown, Gerd A. Folberth, Stephen Sitch, Susanne Bauer, Marijn Bauters, Pascal Boeckx, Alexander W. Cheesman, Makoto Deushi, Inês Dos Santos Vieira, Corinne Galy-Lacaux, James Haywood, James Keeble, Lina M. Mercado, Fiona M. O'Connor, Naga Oshima, Kostas Tsigaridis, and Hans Verbeeck
Atmos. Chem. Phys., 22, 12331–12352, https://doi.org/10.5194/acp-22-12331-2022, https://doi.org/10.5194/acp-22-12331-2022, 2022
Short summary
Short summary
Surface ozone can decrease plant productivity and impair human health. In this study, we evaluate the change in surface ozone due to climate change over South America and Africa using Earth system models. We find that if the climate were to change according to the worst-case scenario used here, models predict that forested areas in biomass burning locations and urban populations will be at increasing risk of ozone exposure, but other areas will experience a climate benefit.
Matilda A. Pimlott, Richard J. Pope, Brian J. Kerridge, Barry G. Latter, Diane S. Knappett, Dwayne E. Heard, Lucy J. Ventress, Richard Siddans, Wuhu Feng, and Martyn P. Chipperfield
Atmos. Chem. Phys., 22, 10467–10488, https://doi.org/10.5194/acp-22-10467-2022, https://doi.org/10.5194/acp-22-10467-2022, 2022
Short summary
Short summary
We present a new method to derive global information of the hydroxyl radical (OH), an important atmospheric oxidant. OH controls the lifetime of trace gases important to air quality and climate. We use satellite observations of ozone, carbon monoxide, methane and water vapour in a simple expression to derive OH around 3–4 km altitude. The derived OH compares well to model and aircraft OH data. We then apply the method to 10 years of satellite data to study the inter-annual variability of OH.
Shipra Jain, Ruth M. Doherty, David Sexton, Steven Turnock, Chaofan Li, Zixuan Jia, Zongbo Shi, and Lin Pei
Atmos. Chem. Phys., 22, 7443–7460, https://doi.org/10.5194/acp-22-7443-2022, https://doi.org/10.5194/acp-22-7443-2022, 2022
Short summary
Short summary
We provide a range of future projections of winter haze and clear conditions over the North China Plain (NCP) using multiple simulations from a climate model for the high-emission scenario (RCP8.5). The frequency of haze conducive weather is likely to increase whereas the frequency of clear weather is likely to decrease in future. The total number of hazy days for a given winter can be as much as ˜3.5 times higher than the number of clear days over the NCP.
Zixuan Jia, Ruth M. Doherty, Carlos Ordóñez, Chaofan Li, Oliver Wild, Shipra Jain, and Xiao Tang
Atmos. Chem. Phys., 22, 6471–6487, https://doi.org/10.5194/acp-22-6471-2022, https://doi.org/10.5194/acp-22-6471-2022, 2022
Short summary
Short summary
This study investigates the modulation of daily PM2.5 over three major populated regions in China by regional meteorology and large-scale circulation during winter. These results demonstrate the benefits of considering the large-scale circulation for air quality studies. The novel circulation indices proposed here can explain a considerable fraction of the day-to-day variability of PM2.5 and can be combined with regional meteorology to improve our capability to predict the variability of PM2.5.
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%.
Henry Bowman, Steven Turnock, Susanne E. Bauer, Kostas Tsigaridis, Makoto Deushi, Naga Oshima, Fiona M. O'Connor, Larry Horowitz, Tongwen Wu, Jie Zhang, Dagmar Kubistin, and David D. Parrish
Atmos. Chem. Phys., 22, 3507–3524, https://doi.org/10.5194/acp-22-3507-2022, https://doi.org/10.5194/acp-22-3507-2022, 2022
Short summary
Short summary
A full understanding of ozone in the troposphere requires investigation of its temporal variability over all timescales. Model simulations show that the northern midlatitude ozone seasonal cycle shifted with industrial development (1850–2014), with an increasing magnitude and a later summer peak. That shift reached a maximum in the mid-1980s, followed by a reversal toward the preindustrial cycle. The few available observations, beginning in the 1970s, are consistent with the model simulations.
Zhenze Liu, Ruth M. Doherty, Oliver Wild, Fiona M. O'Connor, and Steven T. Turnock
Atmos. Chem. Phys., 22, 1209–1227, https://doi.org/10.5194/acp-22-1209-2022, https://doi.org/10.5194/acp-22-1209-2022, 2022
Short summary
Short summary
Tropospheric ozone is important to future air quality and climate, and changing emissions and climate influence ozone. We investigate the evolution of ozone and ozone sensitivity from the present day (2004–2014) to the future (2045–2055) and explore the main drivers of ozone changes from global and regional perspectives. This helps guide suitable emission control strategies to mitigate ozone pollution.
Catherine Hardacre, Jane P. Mulcahy, Richard J. Pope, Colin G. Jones, Steven T. Rumbold, Can Li, Colin Johnson, and Steven T. Turnock
Atmos. Chem. Phys., 21, 18465–18497, https://doi.org/10.5194/acp-21-18465-2021, https://doi.org/10.5194/acp-21-18465-2021, 2021
Short summary
Short summary
We investigate UKESM1's ability to represent the sulfur (S) cycle in the recent historical period. The S cycle is a key driver of historical radiative forcing. Earth system models such as UKESM1 should represent the S cycle well so that we can have confidence in their projections of future climate. We compare UKESM1 to observations of sulfur compounds, finding that the model generally performs well. We also identify areas for UKESM1’s development, focussing on how SO2 is removed from the air.
Hugh C. Pumphrey, Michael J. Schwartz, Michelle L. Santee, George P. Kablick III, Michael D. Fromm, and Nathaniel J. Livesey
Atmos. Chem. Phys., 21, 16645–16659, https://doi.org/10.5194/acp-21-16645-2021, https://doi.org/10.5194/acp-21-16645-2021, 2021
Short summary
Short summary
Forest fires in British Columbia in August 2017 caused an unusual phenomonon: smoke and gases from the fires rose quickly to a height of 10 km. From there, the pollution continued to rise more slowly for many weeks, travelling around the world as it did so. In this paper, we describe how we used data from a satellite instrument to observe this polluted volume of air. The satellite has now been working for 16 years but has observed only three events of this type.
João C. Teixeira, Gerd A. Folberth, Fiona M. O'Connor, Nadine Unger, and Apostolos Voulgarakis
Geosci. Model Dev., 14, 6515–6539, https://doi.org/10.5194/gmd-14-6515-2021, https://doi.org/10.5194/gmd-14-6515-2021, 2021
Short summary
Short summary
Fire constitutes a key process in the Earth system, being driven by climate as well as affecting climate. However, studies on the effects of fires on atmospheric composition and climate have been limited to date. This work implements and assesses the coupling of an interactive fire model with atmospheric composition, comparing it to an offline approach. This approach shows good performance at a global scale. However, regional-scale limitations lead to a bias in modelling fire emissions.
Michael Biggart, Jenny Stocker, Ruth M. Doherty, Oliver Wild, David Carruthers, Sue Grimmond, Yiqun Han, Pingqing Fu, and Simone Kotthaus
Atmos. Chem. Phys., 21, 13687–13711, https://doi.org/10.5194/acp-21-13687-2021, https://doi.org/10.5194/acp-21-13687-2021, 2021
Short summary
Short summary
Heat-related illnesses are of increasing concern in China given its rapid urbanisation and our ever-warming climate. We examine the relative impacts that land surface properties and anthropogenic heat have on the urban heat island (UHI) in Beijing using ADMS-Urban. Air temperature measurements and satellite-derived land surface temperatures provide valuable means of evaluating modelled spatiotemporal variations. This work provides critical information for urban planners and UHI mitigation.
Johannes de Leeuw, Anja Schmidt, Claire S. Witham, Nicolas Theys, Isabelle A. Taylor, Roy G. Grainger, Richard J. Pope, Jim Haywood, Martin Osborne, and Nina I. Kristiansen
Atmos. Chem. Phys., 21, 10851–10879, https://doi.org/10.5194/acp-21-10851-2021, https://doi.org/10.5194/acp-21-10851-2021, 2021
Short summary
Short summary
Using the NAME dispersion model in combination with high-resolution SO2 satellite data from TROPOMI, we investigate the dispersion of volcanic SO2 from the 2019 Raikoke eruption. NAME accurately simulates the dispersion of SO2 during the first 2–3 weeks after the eruption and illustrates the potential of using high-resolution satellite data to identify potential limitations in dispersion models, which will ultimately help to improve efforts to forecast the dispersion of volcanic clouds.
Chris Wilson, Martyn P. Chipperfield, Manuel Gloor, Robert J. Parker, Hartmut Boesch, Joey McNorton, Luciana V. Gatti, John B. Miller, Luana S. Basso, and Sarah A. Monks
Atmos. Chem. Phys., 21, 10643–10669, https://doi.org/10.5194/acp-21-10643-2021, https://doi.org/10.5194/acp-21-10643-2021, 2021
Short summary
Short summary
Methane (CH4) is an important greenhouse gas emitted from wetlands like those found in the basin of the Amazon River. Using an atmospheric model and observations from GOSAT, we quantified CH4 emissions from Amazonia during the previous decade. We found that the largest emissions came from a region in the eastern basin and that emissions there were rising faster than in other areas of South America. This finding was supported by CH4 observations made on aircraft within the basin.
Zhenze Liu, Ruth M. Doherty, Oliver Wild, Michael Hollaway, and Fiona M. O’Connor
Atmos. Chem. Phys., 21, 10689–10706, https://doi.org/10.5194/acp-21-10689-2021, https://doi.org/10.5194/acp-21-10689-2021, 2021
Short summary
Short summary
Surface ozone (O3) has become the main cause of atmospheric pollution in the summertime in China since 2013. We find that 70 % reductions in NOx emissions are required to reduce O3 pollution in most of industrial regions of China, and controls in VOC emissions are very important. The new chemical scheme developed for a global chemistry–climate model not only captures the regional air pollution but also benefits the future studies of regional air-quality–climate interactions.
Ramiro Checa-Garcia, Yves Balkanski, Samuel Albani, Tommi Bergman, Ken Carslaw, Anne Cozic, Chris Dearden, Beatrice Marticorena, Martine Michou, Twan van Noije, Pierre Nabat, Fiona M. O'Connor, Dirk Olivié, Joseph M. Prospero, Philippe Le Sager, Michael Schulz, and Catherine Scott
Atmos. Chem. Phys., 21, 10295–10335, https://doi.org/10.5194/acp-21-10295-2021, https://doi.org/10.5194/acp-21-10295-2021, 2021
Short summary
Short summary
Thousands of tons of dust are emitted into the atmosphere every year, producing important impacts on the Earth system. However, current global climate models are not yet able to reproduce dust emissions, transport and depositions with the desirable accuracy. Our study analyses five different Earth system models to report aspects to be improved to reproduce better available observations, increase the consistency between models and therefore decrease the current uncertainties.
David D. Parrish, Richard G. Derwent, Steven T. Turnock, Fiona M. O'Connor, Johannes Staehelin, Susanne E. Bauer, Makoto Deushi, Naga Oshima, Kostas Tsigaridis, Tongwen Wu, and Jie Zhang
Atmos. Chem. Phys., 21, 9669–9679, https://doi.org/10.5194/acp-21-9669-2021, https://doi.org/10.5194/acp-21-9669-2021, 2021
Short summary
Short summary
The few ozone measurements made before the 1980s indicate that industrial development increased ozone concentrations by a factor of ~ 2 at northern midlatitudes, which are now larger than at southern midlatitudes. This difference was much smaller, and likely reversed, in the pre-industrial atmosphere. Earth system models find similar increases, but not higher pre-industrial ozone in the south. This disagreement may indicate that modeled natural ozone sources and/or deposition loss are inadequate.
Ana Maria Roxana Petrescu, Chunjing Qiu, Philippe Ciais, Rona L. Thompson, Philippe Peylin, Matthew J. McGrath, Efisio Solazzo, Greet Janssens-Maenhout, Francesco N. Tubiello, Peter Bergamaschi, Dominik Brunner, Glen P. Peters, Lena Höglund-Isaksson, Pierre Regnier, Ronny Lauerwald, David Bastviken, Aki Tsuruta, Wilfried Winiwarter, Prabir K. Patra, Matthias Kuhnert, Gabriel D. Oreggioni, Monica Crippa, Marielle Saunois, Lucia Perugini, Tiina Markkanen, Tuula Aalto, Christine D. Groot Zwaaftink, Hanqin Tian, Yuanzhi Yao, Chris Wilson, Giulia Conchedda, Dirk Günther, Adrian Leip, Pete Smith, Jean-Matthieu Haussaire, Antti Leppänen, Alistair J. Manning, Joe McNorton, Patrick Brockmann, and Albertus Johannes Dolman
Earth Syst. Sci. Data, 13, 2307–2362, https://doi.org/10.5194/essd-13-2307-2021, https://doi.org/10.5194/essd-13-2307-2021, 2021
Short summary
Short summary
This study is topical and provides a state-of-the-art scientific overview of data availability from bottom-up and top-down CH4 and N2O emissions in the EU27 and UK. The data integrate recent emission inventories with process-based model data and regional/global inversions for the European domain, aiming at reconciling them with official country-level UNFCCC national GHG inventories in support to policy and to facilitate real-time verification procedures.
Akash Biswal, Vikas Singh, Shweta Singh, Amit P. Kesarkar, Khaiwal Ravindra, Ranjeet S. Sokhi, Martyn P. Chipperfield, Sandip S. Dhomse, Richard J. Pope, Tanbir Singh, and Suman Mor
Atmos. Chem. Phys., 21, 5235–5251, https://doi.org/10.5194/acp-21-5235-2021, https://doi.org/10.5194/acp-21-5235-2021, 2021
Short summary
Short summary
Satellite and surface observations show a reduction in NO2 levels over India during the lockdown compared to business-as-usual years. A substantial reduction, proportional to the population, was observed over the urban areas. The changes in NO2 levels at the surface during the lockdown appear to be present in the satellite observations. However, TROPOMI showed a better correlation with surface NO2 and was more sensitive to the changes than OMI because of the finer resolution.
Thomas Thorp, Stephen R. Arnold, Richard J. Pope, Dominick V. Spracklen, Luke Conibear, Christoph Knote, Mikhail Arshinov, Boris Belan, Eija Asmi, Tuomas Laurila, Andrei I. Skorokhod, Tuomo Nieminen, and Tuukka Petäjä
Atmos. Chem. Phys., 21, 4677–4697, https://doi.org/10.5194/acp-21-4677-2021, https://doi.org/10.5194/acp-21-4677-2021, 2021
Short summary
Short summary
We compare modelled near-surface pollutants with surface and satellite observations to better understand the controls on the regional concentrations of pollution in western Siberia for late spring and summer in 2011. We find two commonly used emission inventories underestimate human emissions when compared to observations. Transport emissions are the main source of pollutants within the region during this period, whilst fire emissions peak during June and are only significant south of 60° N.
Paul T. Griffiths, Lee T. Murray, Guang Zeng, Youngsub Matthew Shin, N. Luke Abraham, Alexander T. Archibald, Makoto Deushi, Louisa K. Emmons, Ian E. Galbally, Birgit Hassler, Larry W. Horowitz, James Keeble, Jane Liu, Omid Moeini, Vaishali Naik, Fiona M. O'Connor, Naga Oshima, David Tarasick, Simone Tilmes, Steven T. Turnock, Oliver Wild, Paul J. Young, and Prodromos Zanis
Atmos. Chem. Phys., 21, 4187–4218, https://doi.org/10.5194/acp-21-4187-2021, https://doi.org/10.5194/acp-21-4187-2021, 2021
Short summary
Short summary
We analyse the CMIP6 Historical and future simulations for tropospheric ozone, a species which is important for many aspects of atmospheric chemistry. We show that the current generation of models agrees well with observations, being particularly successful in capturing trends in surface ozone and its vertical distribution in the troposphere. We analyse the factors that control ozone and show that they evolve over the period of the CMIP6 experiments.
Chaim I. Garfinkel, Ohad Harari, Shlomi Ziskin Ziv, Jian Rao, Olaf Morgenstern, Guang Zeng, Simone Tilmes, Douglas Kinnison, Fiona M. O'Connor, Neal Butchart, Makoto Deushi, Patrick Jöckel, Andrea Pozzer, and Sean Davis
Atmos. Chem. Phys., 21, 3725–3740, https://doi.org/10.5194/acp-21-3725-2021, https://doi.org/10.5194/acp-21-3725-2021, 2021
Short summary
Short summary
Water vapor is the dominant greenhouse gas in the atmosphere, and El Niño is the dominant mode of variability in the ocean–atmosphere system. The connection between El Niño and water vapor above ~ 17 km is unclear, with single-model studies reaching a range of conclusions. This study examines this connection in 12 different models. While there are substantial differences among the models, all models appear to capture the fundamental physical processes correctly.
Fiona M. O'Connor, N. Luke Abraham, Mohit Dalvi, Gerd A. Folberth, Paul T. Griffiths, Catherine Hardacre, Ben T. Johnson, Ron Kahana, James Keeble, Byeonghyeon Kim, Olaf Morgenstern, Jane P. Mulcahy, Mark Richardson, Eddy Robertson, Jeongbyn Seo, Sungbo Shim, João C. Teixeira, Steven T. Turnock, Jonny Williams, Andrew J. Wiltshire, Stephanie Woodward, and Guang Zeng
Atmos. Chem. Phys., 21, 1211–1243, https://doi.org/10.5194/acp-21-1211-2021, https://doi.org/10.5194/acp-21-1211-2021, 2021
Short summary
Short summary
This paper calculates how changes in emissions and/or concentrations of different atmospheric constituents since the pre-industrial era have altered the Earth's energy budget at the present day using a metric called effective radiative forcing. The impact of land use change is also assessed. We find that individual contributions do not add linearly, and different Earth system interactions can affect the magnitude of the calculated effective radiative forcing.
Gillian Thornhill, William Collins, Dirk Olivié, Ragnhild B. Skeie, Alex Archibald, Susanne Bauer, Ramiro Checa-Garcia, Stephanie Fiedler, Gerd Folberth, Ada Gjermundsen, Larry Horowitz, Jean-Francois Lamarque, Martine Michou, Jane Mulcahy, Pierre Nabat, Vaishali Naik, Fiona M. O'Connor, Fabien Paulot, Michael Schulz, Catherine E. Scott, Roland Séférian, Chris Smith, Toshihiko Takemura, Simone Tilmes, Kostas Tsigaridis, and James Weber
Atmos. Chem. Phys., 21, 1105–1126, https://doi.org/10.5194/acp-21-1105-2021, https://doi.org/10.5194/acp-21-1105-2021, 2021
Short summary
Short summary
We find that increased temperatures affect aerosols and reactive gases by changing natural emissions and their rates of removal from the atmosphere. Changing the composition of these species in the atmosphere affects the radiative budget of the climate system and therefore amplifies or dampens the climate response of climate models of the Earth system. This study found that the largest effect is a dampening of climate change as warmer temperatures increase the emissions of cooling aerosols.
Gillian D. Thornhill, William J. Collins, Ryan J. Kramer, Dirk Olivié, Ragnhild B. Skeie, Fiona M. O'Connor, Nathan Luke Abraham, Ramiro Checa-Garcia, Susanne E. Bauer, Makoto Deushi, Louisa K. Emmons, Piers M. Forster, Larry W. Horowitz, Ben Johnson, James Keeble, Jean-Francois Lamarque, Martine Michou, Michael J. Mills, Jane P. Mulcahy, Gunnar Myhre, Pierre Nabat, Vaishali Naik, Naga Oshima, Michael Schulz, Christopher J. Smith, Toshihiko Takemura, Simone Tilmes, Tongwen Wu, Guang Zeng, and Jie Zhang
Atmos. Chem. Phys., 21, 853–874, https://doi.org/10.5194/acp-21-853-2021, https://doi.org/10.5194/acp-21-853-2021, 2021
Short summary
Short summary
This paper is a study of how different constituents in the atmosphere, such as aerosols and gases like methane and ozone, affect the energy balance in the atmosphere. Different climate models were run using the same inputs to allow an easy comparison of the results and to understand where the models differ. We found the effect of aerosols is to reduce warming in the atmosphere, but this effect varies between models. Reactions between gases are also important in affecting climate.
Jane P. Mulcahy, Colin Johnson, Colin G. Jones, Adam C. Povey, Catherine E. Scott, Alistair Sellar, Steven T. Turnock, Matthew T. Woodhouse, Nathan Luke Abraham, Martin B. Andrews, Nicolas Bellouin, Jo Browse, Ken S. Carslaw, Mohit Dalvi, Gerd A. Folberth, Matthew Glover, Daniel P. Grosvenor, Catherine Hardacre, Richard Hill, Ben Johnson, Andy Jones, Zak Kipling, Graham Mann, James Mollard, Fiona M. O'Connor, Julien Palmiéri, Carly Reddington, Steven T. Rumbold, Mark Richardson, Nick A. J. Schutgens, Philip Stier, Marc Stringer, Yongming Tang, Jeremy Walton, Stephanie Woodward, and Andrew Yool
Geosci. Model Dev., 13, 6383–6423, https://doi.org/10.5194/gmd-13-6383-2020, https://doi.org/10.5194/gmd-13-6383-2020, 2020
Short summary
Short summary
Aerosols are an important component of the Earth system. Here, we comprehensively document and evaluate the aerosol schemes as implemented in the physical and Earth system models, HadGEM3-GC3.1 and UKESM1. This study provides a useful characterisation of the aerosol climatology in both models, facilitating the understanding of the numerous aerosol–climate interaction studies that will be conducted for CMIP6 and beyond.
Steven T. Turnock, Robert J. Allen, Martin Andrews, Susanne E. Bauer, Makoto Deushi, Louisa Emmons, Peter Good, Larry Horowitz, Jasmin G. John, Martine Michou, Pierre Nabat, Vaishali Naik, David Neubauer, Fiona M. O'Connor, Dirk Olivié, Naga Oshima, Michael Schulz, Alistair Sellar, Sungbo Shim, Toshihiko Takemura, Simone Tilmes, Kostas Tsigaridis, Tongwen Wu, and Jie Zhang
Atmos. Chem. Phys., 20, 14547–14579, https://doi.org/10.5194/acp-20-14547-2020, https://doi.org/10.5194/acp-20-14547-2020, 2020
Short summary
Short summary
A first assessment is made of the historical and future changes in air pollutants from models participating in the 6th Coupled Model Intercomparison Project (CMIP6). Substantial benefits to future air quality can be achieved in future scenarios that implement measures to mitigate climate and involve reductions in air pollutant emissions, particularly methane. However, important differences are shown between models in the future regional projection of air pollutants under the same scenario.
Robert J. Parker, Chris Wilson, A. Anthony Bloom, Edward Comyn-Platt, Garry Hayman, Joe McNorton, Hartmut Boesch, and Martyn P. Chipperfield
Biogeosciences, 17, 5669–5691, https://doi.org/10.5194/bg-17-5669-2020, https://doi.org/10.5194/bg-17-5669-2020, 2020
Short summary
Short summary
Wetlands contribute the largest uncertainty to the atmospheric methane budget. WetCHARTs is a simple, data-driven model that estimates wetland emissions using observations of precipitation and temperature. We perform the first detailed evaluation of WetCHARTs against satellite data and find it performs well in reproducing the observed wetland methane seasonal cycle for the majority of wetland regions. In regions where it performs poorly, we highlight incorrect wetland extent as a key reason.
David S. Stevenson, Alcide Zhao, Vaishali Naik, Fiona M. O'Connor, Simone Tilmes, Guang Zeng, Lee T. Murray, William J. Collins, Paul T. Griffiths, Sungbo Shim, Larry W. Horowitz, Lori T. Sentman, and Louisa Emmons
Atmos. Chem. Phys., 20, 12905–12920, https://doi.org/10.5194/acp-20-12905-2020, https://doi.org/10.5194/acp-20-12905-2020, 2020
Short summary
Short summary
We present historical trends in atmospheric oxidizing capacity (OC) since 1850 from the latest generation of global climate models and compare these with estimates from measurements. OC controls levels of many key reactive gases, including methane (CH4). We find small model trends up to 1980, then increases of about 9 % up to 2014, disagreeing with (uncertain) measurement-based trends. Major drivers of OC trends are emissions of CH4, NOx, and CO; these will be important for future CH4 trends.
Benjamin Birner, Martyn P. Chipperfield, Eric J. Morgan, Britton B. Stephens, Marianna Linz, Wuhu Feng, Chris Wilson, Jonathan D. Bent, Steven C. Wofsy, Jeffrey Severinghaus, and Ralph F. Keeling
Atmos. Chem. Phys., 20, 12391–12408, https://doi.org/10.5194/acp-20-12391-2020, https://doi.org/10.5194/acp-20-12391-2020, 2020
Short summary
Short summary
With new high-precision observations from nine aircraft campaigns and 3-D chemical transport modeling, we show that the argon-to-nitrogen ratio (Ar / N2) in the lowermost stratosphere provides a useful constraint on the “age of air” (the time elapsed since entry of an air parcel into the stratosphere). Therefore, Ar / N2 in combination with traditional age-of-air indicators, such as CO2 and N2O, could provide new insights into atmospheric mixing and transport.
Francesco Grieco, Kristell Pérot, Donal Murtagh, Patrick Eriksson, Peter Forkman, Bengt Rydberg, Bernd Funke, Kaley A. Walker, and Hugh C. Pumphrey
Atmos. Meas. Tech., 13, 5013–5031, https://doi.org/10.5194/amt-13-5013-2020, https://doi.org/10.5194/amt-13-5013-2020, 2020
Short summary
Short summary
We present a unique – by time extension and geographical coverage – dataset of satellite observations of carbon monoxide (CO) in the mesosphere which will allow us to study dynamical processes, since CO is a very good tracer of circulation in the mesosphere. Previously, the dataset was unusable due to instrumental artefacts that affected the measurements. We identify the cause of the artefacts, eliminate them and prove the quality of the results by comparing with other instrument measurements.
Matthew J. Rowlinson, Alexandru Rap, Douglas S. Hamilton, Richard J. Pope, Stijn Hantson, Steve R. Arnold, Jed O. Kaplan, Almut Arneth, Martyn P. Chipperfield, Piers M. Forster, and Lars Nieradzik
Atmos. Chem. Phys., 20, 10937–10951, https://doi.org/10.5194/acp-20-10937-2020, https://doi.org/10.5194/acp-20-10937-2020, 2020
Short summary
Short summary
Tropospheric ozone is an important greenhouse gas which contributes to anthropogenic climate change; however, the effect of human emissions is uncertain because pre-industrial ozone concentrations are not well understood. We use revised inventories of pre-industrial natural emissions to estimate the human contribution to changes in tropospheric ozone. We find that tropospheric ozone radiative forcing is up to 34 % lower when using improved pre-industrial biomass burning and vegetation emissions.
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
Arneth, A., Schurgers, G., Lathiere, J., Duhl, T., Beerling, D. J., Hewitt, C. N., Martin, M., and Guenther, A.: Global terrestrial isoprene emission models: sensitivity to variability in climate and vegetation, Atmos. Chem. Phys., 11, 8037–8052, https://doi.org/10.5194/acp-11-8037-2011, 2011. a
Artaxo, P., Rizzo, L. V., Brito, J. F., Barbosa, H. M. J., Arana, A., Sena, E. T., Cirino, G. G., Bastos, W., Martin, S. T., and Andreae, M. O.: Atmospheric aerosols in Amazonia and land use change: from natural biogenic to biomass burning conditions, Faraday Discuss., 165, 203–235, https://doi.org/10.1039/C3FD00052D, 2013. a
Artaxo, P., Hansson, H.-C., Andreae, M. O., Bäck, J., Alves, E. G., Barbosa, H. M. J., Bender, F., Bourtsoukidis, E., Carbone, S., Chi, J., Decesari, S., Després, V. R., Ditas, F., Ezhova, E., Fuzzi, S., Hasselquist, N. J., Heintzenberg, J., Holanda, B. A., Guenther, A., Hakola, H., Heikkinen, L., Kerminen, V.-M., Kontkanen, J., Krejci, R., Kulmala, M., Lavric, J. V., de Leeuw, G., Lehtipalo, K., Machado, L. A. T., McFiggans, G., Franco, M. A. M., Meller, B. B., Morais, F. G., Mohr, C., Morgan, W., Nilsson, M. B., Peichl, M., Petäjä, T., Praß, M., Pöhlker, C., Pöhlker, M. L., Pöschl, U., Von Randow, C., Riipinen, I., Rinne, J., Rizzo, L. V., Rosenfeld, D., Silva Dias, M. A. F., Sogacheva, L., Stier, P., Swietlicki, E., Sörgel, M., Tunved, P., Virkkula, A., Wang, J., Weber, B., Yáñez-Serrano, A. M., Zieger, P., Mikhailov, E., Smith, J. N., and Kesselmeier, J.: Tropical and Boreal Forest – Atmosphere Interactions: A Review, Tellus B, 74, 24–163, https://doi.org/10.16993/tellusb.34, 2022. a, b, c, d, e
Badr, O. and Probert, S. D.: Sources of atmospheric carbon monoxide, Appl. Energ., 49, 145–195, https://doi.org/10.1016/0306-2619(94)90036-1, 1994. a
Barkley, M. P., Palmer, P. I., De Smedt, I., Karl, T., Guenther, A., and Van Roozendael, M.: Regulated large-scale annual shutdown of Amazonian isoprene emissions?, Geophys. Res. Lett., 36, L04803, https://doi.org/10.1029/2008GL036843, 2009. a, b, c
Bates, K. H., Jacob, D. J., Wang, S., Hornbrook, R. S., Apel, E. C., Kim, M. J., Millet, D. B., Wells, K. C., Chen, X., Brewer, J. F., Ray, E. A., Commane, R., Diskin, G. S., and Wofsy, S. C.: The global budget of atmospheric methanol: New constraints on secondary, oceanic, and terrestrial sources, J. Geophys. Res.-Atmos., 126, e2020JD033439, https://doi.org/10.1029/2020JD033439, 2021. a, b, c, d
Bela, M. M., Longo, K. M., Freitas, S. R., Moreira, D. S., Beck, V., Wofsy, S. C., Gerbig, C., Wiedemann, K., Andreae, M. O., and Artaxo, P.: Ozone production and transport over the Amazon Basin during the dry-to-wet and wet-to-dry transition seasons, Atmos. Chem. Phys., 15, 757–782, https://doi.org/10.5194/acp-15-757-2015, 2015. a
Boersma, K. F., Eskes, H. J., Dirksen, R. J., van der A, R. J., Veefkind, J. P., Stammes, P., Huijnen, V., Kleipool, Q. L., Sneep, M., Claas, J., Leitão, J., Richter, A., Zhou, Y., and Brunner, D.: An improved tropospheric NO2 column retrieval algorithm for the Ozone Monitoring Instrument, Atmos. Meas. Tech., 4, 1905–1928, https://doi.org/10.5194/amt-4-1905-2011, 2011. a, b
Cao, Y., Yue, X., Lei, Y., Zhou, H., Liao, H., Song, Y., Bai, J., Yang, Y., Chen, L., Zhu, J., Ma, Y., and Tian, C.: Identifying the drivers of modeling uncertainties in isoprene emissions: Schemes versus meteorological forcings, J. Geophys. Res.-Atmos., 126, e2020JD034242, https://doi.org/10.1029/2020JD034242, 2021. a
Chance, K.: OMI/Aura Formaldehyde (HCHO) Total Column 1-orbit L2 Swath 13x24 km V003, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set], Greenbelt, MD, USA, https://doi.org/10.5067/Aura/OMI/DATA2015, 2007. a, b
Chen, Y., Hall, J., van Wees, D., Andela, N., Hantson, S., Giglio, L., van der Werf, G. R., Morton, D. C., and Randerson, J. T.: Global Fire Emissions Database (GFED5) Burned Area, Version 0.1, Zenodo [data set], https://doi.org/10.5281/zenodo.7668424, 2023. a
Ciccioli, P., Centritto, M., and Loreto, F.: Biogenic volatile organic compound emissions from vegetation fires, Plant Cell Environ., 37, 1810–1825, https://doi.org/10.1111/pce.12336, 2014. a
Danielson, J. and Gesch, D.: Global Multi-resolution Terrain Elevation Data 2010 (GMTED2010), US Geological Survey [data set], https://doi.org/10.5066/F7J38R2N, 2011. a, b, c
Deeter, M. N., Edwards, D. P., Francis, G. L., Gille, J. C., Martínez-Alonso, S., Worden, H. M., and Sweeney, C.: A climate-scale satellite record for carbon monoxide: the MOPITT Version 7 product, Atmos. Meas. Tech., 10, 2533–2555, https://doi.org/10.5194/amt-10-2533-2017, 2017. a
Devadiga, S. and Nickeson, J.: Status for: LAI/FPAR (MOD15), https://modis-land.gsfc.nasa.gov/ValStatus.php?ProductID= MOD15&_gl=1*y1py41*_ga*MTA1Njk2MDM5MC4xNzE0 NTU0MDQz*_ga_0YWDZEJ295*MTcxNjk3NTA1OC4yLj EuMTcxNjk3NTA2OS4wLjAuMA.. (last access: 28 June 2024), 2023. a
Dodge, Y.: Spearman Rank Correlation Coefficient, in: The Concise Encyclopedia of Statistics, Springer New York, 502–505, https://doi.org/10.1007/978-0-387-32833-1_379, 2008. a
dos Santos, A. M., da Silva, C. F. A., de Almeida Junior, P. M., Rudke, A. P., and de Melo, S. N.: Deforestation drivers in the Brazilian Amazon: assessing new spatial predictors, J. Environ. Manage., 294, 113020, https://doi.org/10.1016/j.jenvman.2021.113020, 2021. a, b
ESA: TEMIS (Tropospheric Emission Monitoring Internet Service), https://www.temis.nl/, last access: 25 September 2024. a
European Commission: EDGARv6.1, https://edgar.jrc.ec.europa.eu/index.php/dataset_ap61, last access: 22 December 2023. a
Fang, H., Jiang, C., Li, W., Wei, S., Baret, F., Chen, J. M., Garcia-Haro, J., Liang, S., Liu, R., Myneni, R. B., Pinty, B., Xiao, Z., and Zhu, Z.: Characterization and intercomparison of global moderate resolution leaf area index (LAI) products: Analysis of climatologies and theoretical uncertainties, J. Geophys. Res.-Biogeo., 118, 529–548, https://doi.org/10.1002/jgrg.20051, 2013. a
Fernandes, R. and Leblanc, S. G.: Parametric (modified least squares) and non-parametric (Theil–Sen) linear regressions for predicting biophysical parameters in the presence of measurement errors, Remote Sens. Environ., 95, 303–316, https://doi.org/10.1016/j.rse.2005.01.005, 2005. a
Fowler, D., Pilegaard, K., Sutton, M. A., Ambus, P., Raivonen, M., Duyzer, J., Simpson, D., Fagerli, H., Fuzzi, S., Schjoerring, J. K., Granier, C., Neftel, A., Isaksen, I. S. A., Laj, P., Maione, M., Monks, P. S., Burkhardt, J., Daemmgen, U., Neirynck, J., Personne, E., Wichink-Kruit, R., Butterbach-Bahl, K., Flechard, C., Tuovinen, J. P., Coyle, M., Gerosa, G., Loubet, B., Altimir, N., Gruenhage, L., Ammann, C., Cieslik, S., Paoletti, E., Mikkelsen, T. N., Ro-Poulsen, H., Cellier, P., Cape, J. N., Horváth, L., Loreto, F., Niinemets, Ü., Palmer, P. I., Rinne, J., Misztal, P., Nemitz, E., Nilsson, D., Pryor, S., Gallagher, M. W., Vesala, T., Skiba, U., Brüggemann, N., Zechmeister-Boltenstern, S., Williams, J., O'Dowd, C., Facchini, M. C., Leeuw, G. d., Flossman, A., Chaumerliac, N., and Erisman, J. W.: Atmospheric composition change: Ecosystems–Atmosphere interactions, Atmos. Environ., 43, 5193–5267, https://doi.org/10.1016/j.atmosenv.2009.07.068, 2009. a
Freitas, A. D. and Fornaro, A.: Atmospheric Formaldehyde Monitored by TROPOMI Satellite Instrument throughout 2020 over São Paulo State, Brazil, Remote Sens.-Basel, 14, 3032, https://doi.org/10.3390/rs14133032, 2022. a, b, c
Friedl, M. and Sulla-Menashe, D.: MCD12C1 MODIS/Terra+Aqua Land Cover Type Yearly L3 Global 0.05Deg CMG V006, NASA EOSDIS Land Processes Distributed Active Archive Center [data set], https://doi.org/10.5067/MODIS/MCD12C1.006, 2015. a
Fu, D., Millet, D. B., Wells, K. C., Payne, V. H., Yu, S., Guenther, A., and Eldering, A.: Direct retrieval of isoprene from satellite-based infrared measurements, Nat. Commun., 10, 3811, https://doi.org/10.1038/s41467-019-11835-0, 2019. a, b
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
Gorelick, N., Hancher, M., Dixon, M., Ilyushchenko, S., Thau, D., and Moore, R.: Google Earth Engine: Planetary-scale geospatial analysis for everyone, Remote Sens. Environ., 202, 18–27, https://doi.org/10.1016/j.rse.2017.06.031, 2017. a
Gu, D., Guenther, A. B., Shilling, J. E., Yu, H., Huang, M., Zhao, C., Yang, Q., Martin, S. T., Artaxo, P., Kim, S., Seco, R., Stavrakou, T., Longo, K. M., Tóta, J., de Souza, R. A. F., Vega, O., Liu, Y., Shrivastava, M., Alves, E. G., Santos, F. C., Leng, G., and Hu, Z.: Airborne observations reveal elevational gradient in tropical forest isoprene emissions, Nat. Commun., 8, 15541, https://doi.org/10.1038/ncomms15541, 2017. a
Guenther, A., Hewitt, C. N., Erickson, D., Fall, R., Geron, C., Graedel, T., Harley, P., Klinger, L., Lerdau, M., Mckay, W. A., Pierce, T., Scholes, B., Steinbrecher, R., Tallamraju, R., Taylor, J., and Zimmerman, P.: A global model of natural volatile organic compound emissions, J. Geophys. Res.-Atmos., 100, 8873–8892, https://doi.org/10.1029/94JD02950, 1995. 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, b
Heald, C. L. and Spracklen, D. V.: Land Use Change Impacts on Air Quality and Climate, Chem. Rev., 115, 4476–4496, https://doi.org/10.1021/cr500446g, 2015. a
Helas, G., Lobert, J., Scharffe, D., Schäfer, L., Goldammer, J., Baudet, J., Ahoua, B., Ajavon, A.-L., Lacaux, J.-P., Delmas, R., and Andreae, M. O.: Ozone production due to emissions from vegetation burning, J. Atmos. Chem., 22, 163–174, https://doi.org/10.1007/BF00708187, 1995. a
Hodzic, A., Kasibhatla, P. S., Jo, D. S., Cappa, C. D., Jimenez, J. L., Madronich, S., and Park, R. J.: Rethinking the global secondary organic aerosol (SOA) budget: stronger production, faster removal, shorter lifetime, Atmos. Chem. Phys., 16, 7917–7941, https://doi.org/10.5194/acp-16-7917-2016, 2016. a, b
Holloway, T., Levy II, H., and Kasibhatla, P.: Global distribution of carbon monoxide, J. Geophys. Res.-Atmos., 105, 12123–12147, https://doi.org/10.1029/1999JD901173, 2000. a, b
Kang, R., Huang, K., Gao, T., Mulder, J., Duan, L., Wang, C., Ke, P., Yao, M., Su, C., Li, J., Zhu, W., Zhu, J., and Fang, Y.: Forest Canopy Acts as an atmospheric NOx sink: Results from micrometeorological flux measurements, J. Geophys. Res.-Atmos., 128, e2022JD037729, https://doi.org/10.1029/2022JD037729, 2023. a
Kefauver, S. C., Filella, I., and Peñuelas, J.: Remote Sensing of atmospheric biogenic volatile organic compounds (BVOCs) via satellite-based formaldehyde vertical column assessments, Int. J. Remote Sens., 35, 7519–7542, https://doi.org/10.1080/01431161.2014.968690, 2014. a
Kim, K.-H., Kabir, E., and Kabir, S.: A review on the human health impact of airborne particulate matter, Environ. Int., 74, 136–143, https://doi.org/10.1016/j.envint.2014.10.005, 2015. a
Kuhn, U., Ganzeveld, L., Thielmann, A., Dindorf, T., Schebeske, G., Welling, M., Sciare, J., Roberts, G., Meixner, F. X., Kesselmeier, J., Lelieveld, J., Kolle, O., Ciccioli, P., Lloyd, J., Trentmann, J., Artaxo, P., and Andreae, M. O.: Impact of Manaus City on the Amazon Green Ocean atmosphere: ozone production, precursor sensitivity and aerosol load, Atmos. Chem. Phys., 10, 9251–9282, https://doi.org/10.5194/acp-10-9251-2010, 2010. a
Langford, B., House, E., Valach, A., Hewitt, C. N., Artaxo, P., Barkley, M. P., Brito, J., Carnell, E., Davison, B., MacKenzie, A. R., Marais, E. A., Newland, M. J., Rickard, A. R., Shaw, M. D., Yáñez-Serrano, A. M., and Nemitz, E.: Seasonality of isoprene emissions and oxidation products above the remote Amazon, Environ. Sci.: Atmos., 2, 230–240, https://doi.org/10.1039/D1EA00057H, 2022. a
Levy, R. C., Mattoo, S., Munchak, L. A., Remer, L. A., Sayer, A. M., Patadia, F., and Hsu, N. C.: The Collection 6 MODIS aerosol products over land and ocean, Atmos. Meas. Tech., 6, 2989–3034, https://doi.org/10.5194/amt-6-2989-2013, 2013. a
Loreto, F. and Fares, S.: Biogenic Volatile Organic Compounds and Their Impacts on Biosphere–Atmosphere Interactions, Dev. Environm. Sci., 13, 57–75, https://doi.org/10.1016/B978-0-08-098349-3.00004-9, 2013. a
Loveland, T. R. and Belward, A. S.: The IGBP-DIS global 1km land cover data set, DISCover: First results, Int. J. Remote Sens., 18, 3289–3295, https://doi.org/10.1080/014311697217099, 1997. a
Marais, E. A., Jacob, D. J., Kurosu, T. P., Chance, K., Murphy, J. G., Reeves, C., Mills, G., Casadio, S., Millet, D. B., Barkley, M. P., Paulot, F., and Mao, J.: Isoprene emissions in Africa inferred from OMI observations of formaldehyde columns, Atmos. Chem. Phys., 12, 6219–6235, https://doi.org/10.5194/acp-12-6219-2012, 2012. a
Millet, D. B., Jacob, D. J., Custer, T. G., de Gouw, J. A., Goldstein, A. H., Karl, T., Singh, H. B., Sive, B. C., Talbot, R. W., Warneke, C., and Williams, J.: New constraints on terrestrial and oceanic sources of atmospheric methanol, Atmos. Chem. Phys., 8, 6887–6905, https://doi.org/10.5194/acp-8-6887-2008, 2008. a
Morellato, L. P. C., Camargo, M. G. G., and Gressler, E.: A Review of Plant Phenology in South and Central America, in: Phenology: An Integrative Environmental Science, edited by: Schwartz, M. D., Springer Netherlands, Dordrecht, 91–113, https://doi.org/10.1007/978-94-007-6925-0_6, ISBN 978-94-007-6925-0, 2013. a
Myneni, R., Knyazikhin, Y., and Park, T.: MODIS/Terra Leaf Area Index/FPAR 8-Day L4 Global 500m SIN Grid V061, NASA EOSDIS Land Processes Distributed Active Archive Center [data set], https://doi.org/10.5067/MODIS/MOD15A2H.061, 2021. a
Myneni, R. B., Yang, W., Nemani, R. R., Huete, A. R., Dickinson, R. E., Knyazikhin, Y., Didan, K., Fu, R., Juárez, R. I. N., Saatchi, S. S., Hashimoto, H., Ichii, K., Shabanov, N. V., Tan, B., Ratana, P., Privette, J. L., Morisette, J. T., Vermote, E. F., Roy, D. P., Wolfe, R. E., Friedl, M. A., Running, S. W., Votava, P., El-Saleous, N., Devadiga, S., Su, Y., and Salomonson, V. V.: Large seasonal swings in leaf area of Amazon rainforests, P. Natl. Acad. Sci. USA, 104, 4820–4823, https://doi.org/10.1073/pnas.0611338104, 2007. a
NASA/LARC/SD/ASDC: MOPITT Derived CO (Near and Thermal Infrared Radiances) V007, Atmospheric Science Data Center (ASDC) [data set], https://doi.org/10.5067/TERRA/MOPITT/MOP02J_L2.007, 2000. a, b
OMI Team: Ozone Monitoring Instrument (OMI) Data User's Guide, https://docserver.gesdisc.eosdis.nasa.gov/repository/Mission/OMI/3.3_ScienceDataProductDocumentation/3.3.2_ProductRequirements_Designs/README.OMI_DUG.pdf (last access: 28 June 2024), 2012. a
Pacifico, F., Harrison, S. P., Jones, C. D., and Sitch, S.: Isoprene emissions and climate, Atmos. Environ., 43, 6121–6135, https://doi.org/10.1016/j.atmosenv.2009.09.002, 2009. a, b, c
Pacifico, F., Harrison, S. P., Jones, C. D., Arneth, A., Sitch, S., Weedon, G. P., Barkley, M. P., Palmer, P. I., Serça, D., Potosnak, M., Fu, T.-M., Goldstein, A., Bai, J., and Schurgers, G.: Evaluation of a photosynthesis-based biogenic isoprene emission scheme in JULES and simulation of isoprene emissions under present-day climate conditions, Atmos. Chem. Phys., 11, 4371–4389, https://doi.org/10.5194/acp-11-4371-2011, 2011. a
Pacifico, F., Folberth, G. A., Jones, C. D., Harrison, S. P., and Collins, W. J.: Sensitivity of biogenic isoprene emissions to past, present, and future environmental conditions and implications for atmospheric chemistry, J. Geophys. Res., 117, D22302, https://doi.org/10.1029/2012JD018276, 2012. a
Padilla, M., Stehman, S. V., Ramo, R., Corti, D., Hantson, S., Oliva, P., Alonso-Canas, I., Bradley, A. V., Tansey, K., Mota, B., Pereira, J. M., and Chuvieco, E.: Comparing the accuracies of remote sensing global burned area products using stratified random sampling and estimation, Remote Sens. Environ., 160, 114–121, https://doi.org/10.1016/j.rse.2015.01.005, 2015. a
Palmer, P. I., Abbot, D. S., Fu, T.-M., Jacob, D. J., Chance, K., Kurosu, T. P., Guenther, A., Wiedinmyer, C., Stanton, J. C., Pilling, M. J., Pressley, S. N., Lamb, B., and Sumner, A. L.: Quantifying the seasonal and interannual variability of North American isoprene emissions using satellite observations of the formaldehyde column, J. Geophys. Res.-Atmos., 111, D12315, https://doi.org/10.1029/2005JD006689, 2006. a
Palmer, P. I., Barkley, M. P., Kurosu, T. P., Lewis, A. C., Saxton, J. E., Chance, K., and Gatti, L. V.: Interpreting satellite column observations of formaldehyde over tropical South America, Philos. T. Roy. Soc. A, 365, 1741–1751, https://doi.org/10.1098/rsta.2007.2042, 2007. a, b
Palmer, P. I., Marvin, M. R., Siddans, R., Kerridge, B. J., and Moore, D. P.: Nocturnal survival of isoprene linked to formation of upper tropospheric organic aerosol, Science, 375, 562–566, https://doi.org/10.1126/science.abg4506, 2022. a
Panisset, J. S., Libonati, R., Gouveia, C. M. P., Machado-Silva, F., Franca, D. A., Franca, J. R. A., and Peres, L. F.: Contrasting patterns of the extreme drought episodes of 2005, 2010 and 2015 in the Amazon Basin, Int. J. Climatol., 38, 1096–1104, https://doi.org/10.1002/joc.5224, 2018. a
Park, K., Emmons, L. K., Wang, Z., and Mak, J. E.: Joint Application of Concentration and δ18O to Investigate the Global Atmospheric CO Budget, Atmosphere, 6, 547–578, https://doi.org/10.3390/atmos6050547, 2015. a
Paton-Walsh, C., Emmerson, K. M., Garland, R. M., Keywood, M., Hoelzemann, J. J., Huneeus, N., Buchholz, R. R., Humphries, R. S., Altieri, K., Schmale, J., Wilson, S. R., Labuschagne, C., Kalisa, E., Fisher, J. A., Deutscher, N. M., van Zyl, P. G., Beukes, J. P., Joubert, W., Martin, L., Mkololo, T., Barbosa, C., de Fatima Andrade, M., Schofield, R., Mallet, M. D., Harvey, M. J., Formenti, P., Piketh, S. J., and Olivares, G.: Key challenges for tropospheric chemistry in the Southern Hemisphere, Elementa: Science of the Anthropocene, 10, 00050, https://doi.org/10.1525/elementa.2021.00050, 2022. a
Pivello, V. R.: The Use of Fire in the Cerrado and Amazonian Rainforests of Brazil: Past and Present, Fire Ecol., 7, 24–39, https://doi.org/10.4996/fireecology.0701024, 2011. a
Platnick, S., King, M., and Hubanks, P.: MODIS Atmosphere L3 Monthly Product, Goddard Space Flight Center [data set], USA, https://doi.org/10.5067/MODIS/MOD08_M3.061, 2015. a, b
Pommier, M.: Estimations of NOx emissions, NO2 lifetime and their temporal variation over three British urbanised regions in 2019 using TROPOMI NO2 observations, Environ. Sci.: Atmos., 3, 408–421, https://doi.org/10.1039/D2EA00086E, 2023. a, b
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
Pope, R. J., Kerridge, B. J., Siddans, R., Latter, B. G., Chipperfield, M. P., Arnold, S. R., Ventress, L. J., Pimlott, M. A., Graham, A. M., Knappett, D. S., and Rigby, R.: Large enhancements in Southern Hemisphere satellite-observed trace gases due to the 2019/2020 Australian wildfires, J. Geophys. Res.-Atmos., 126, e2021JD034892, https://doi.org/10.1029/2021JD034892, 2021. a, b
Ritchie, H. and Roser, M.: Forests and Deforestation, Our World in Data, https://ourworldindata.org/forests-and-deforestation (last access: 10 December 2023), 2021. a
Rutherford Appleton Laboratory: Infrared-microwave-sounding Methanol, Version v1, Zenodo [data set], https://doi.org/10.5281/zenodo.11472103, 2024. a
Sands, E. SouthernAmazon-code-figures, Zenodo [code], https://doi.org/10.5281/zenodo.13862510, 2024. a
Sayer, A. M., Munchak, L. A., Hsu, N. C., Levy, R. C., Bettenhausen, C., and Jeong, M.-J.: MODIS Collection 6 aerosol products: Comparison between Aqua's e-Deep Blue, Dark Target, and “merged” data sets, and usage recommendations, J. Geophys. Res.-Atmos., 119, 13965–13989, https://doi.org/10.1002/2014JD022453, 2014. a
Schreier, S. F., Richter, A., Kaiser, J. W., and Burrows, J. P.: The empirical relationship between satellite-derived tropospheric NO2 and fire radiative power and possible implications for fire emission rates of NOx, Atmos. Chem. Phys., 14, 2447–2466, https://doi.org/10.5194/acp-14-2447-2014, 2014. a
Shrivastava, M., Cappa, C. D., Fan, J., Goldstein, A. H., Guenther, A. B., Jimenez, J. L., Kuang, C., Laskin, A., Martin, S. T., Ng, N. L., Petaja, T., Pierce, J. R., Rasch, P. J., Roldin, P., Seinfeld, J. H., Shilling, J., Smith, J. N., Thornton, J. A., Volkamer, R., Wang, J., Worsnop, D. R., Zaveri, R. A., Zelenyuk, A., and Zhang, Q.: Recent advances in understanding secondary organic aerosol: Implications for global climate forcing, Rev. Geophys., 55, 509–559, https://doi.org/10.1002/2016RG000540, 2017. a
Silva Junior, C. H. L., Pessôa, A. C. M., Carvalho, N. S., Reis, J. B. C., Anderson, L. O., and Aragão, L. E. O. C.: The Brazilian Amazon deforestation rate in 2020 is the greatest of the decade, Nature Ecology & Evolution, 5, 144–145, https://doi.org/10.1038/s41559-020-01368-x, 2021. a
Stavrakou, T., Müller, J.-F., Bauwens, M., De Smedt, I., Van Roozendael, M., De Mazière, M., Vigouroux, C., Hendrick, F., George, M., Clerbaux, C., Coheur, P.-F., and Guenther, A.: How consistent are top-down hydrocarbon emissions based on formaldehyde observations from GOME-2 and OMI?, Atmos. Chem. Phys., 15, 11861–11884, https://doi.org/10.5194/acp-15-11861-2015, 2015. a
Strada, S., Fernández-Martínez, M., Peñuelas, J., Bauwens, M., Stavrakou, T., Verger, A., and Giorgi, F.: Disentangling temperature and water stress contributions to trends in isoprene emissions using satellite observations of formaldehyde, 2005–2016, Atmos. Environ., 295, 119530, https://doi.org/10.1016/j.atmosenv.2022.119530, 2023. a
Sulla-Menashe, D., Gray, J. M., Abercrombie, S. P., and Friedl, M. A.: Hierarchical mapping of annual global land cover 2001 to present: The MODIS Collection 6 Land Cover product, Remote Sens. Environ., 222, 183–194, https://doi.org/10.1016/j.rse.2018.12.013, 2019. a
Szopa, S., Naik, V., Adhikary, B., Artaxo, P., Berntsen, T., Collins, W. D., Fuzzi, S., Gallardo, L., Kiendler-Scharr, A., Klimont, Z., Liao, H., Unger, N., and Zanis, P.: Short-Lived Climate Forcers, in: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, 817–922, https://doi.org/10.1017/9781009157896.008, 2021. a, b
van der A, R. J., Eskes, H. J., Boersma, K. F., van Noije, T. P. C., Van Roozendael, M., De Smedt, I., Peters, D. H. M. U., and Meijer, E. W.: Trends, seasonal variability and dominant NOx source derived from a ten year record of NO2 measured from space, J. Geophys. Res.-Atmos., 113, D04302, https://doi.org/10.1029/2007JD009021, 2008. 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
Wang, P., Holloway, T., Bindl, M., Harkey, M., and De Smedt, I.: Ambient Formaldehyde over the United States from Ground-Based (AQS) and Satellite (OMI) Observations, Remote Sens.-Basel, 14, 2191, https://doi.org/10.3390/rs14092191, 2022. a
Wang, Y., Jiang, J. H., and Su, H.: Atmospheric responses to the redistribution of anthropogenic aerosols, J. Geophys. Res.-Atmos., 120, 9625–9641, https://doi.org/10.1002/2015JD023665, 2015. a
Weber, J., King, J. A., Sindelarova, K., and Val Martin, M.: Updated isoprene and terpene emission factors for the Interactive BVOC (iBVOC) emission scheme in the United Kingdom Earth System Model (UKESM1.0), Geosci. Model Dev., 16, 3083–3101, https://doi.org/10.5194/gmd-16-3083-2023, 2023. a
Wei, X., Chang, N. B., Bai, K., and Gao, W.: Satellite remote sensing of aerosol optical depth: advances, challenges, and perspectives, Crit. Rev. Env. Sci. Tec., 50, 1640–1725, https://doi.org/10.1080/10643389.2019.1665944, 2020. a
Wells, K. C., Millet, D. B., Payne, V. H., Deventer, M. J., Bates, K. H., de Gouw, J. A., Graus, M., Warneke, C., Wisthaler, A., and Fuentes, J. D.: Satellite isoprene retrievals constrain emissions and atmospheric oxidation, Nature, 585, 225–233, https://doi.org/10.1038/s41586-020-2664-3, 2020. a, b, c, d, e
Wells, K. C., Millet, D. B., Payne, V. H., Vigouroux, C., Aquino, C. A. B., De Mazière, M., de Gouw, J. A., Graus, M., Kurosu, T., Warneke, C., and Wisthaler, A.: Next-Generation Isoprene Measurements From Space: Detecting Daily Variability at High Resolution, J. Geophys. Res.-Atmos., 127, e2021JD036181, https://doi.org/10.1029/2021JD036181, 2022. a, b, c
Wiedinmyer, C., Kimura, Y., McDonald-Buller, E. C., Emmons, L. K., Buchholz, R. R., Tang, W., Seto, K., Joseph, M. B., Barsanti, K. C., Carlton, A. G., and Yokelson, R.: The Fire Inventory from NCAR version 2.5: an updated global fire emissions model for climate and chemistry applications, Geosci. Model Dev., 16, 3873–3891, https://doi.org/10.5194/gmd-16-3873-2023, 2023. a, b, c, d
Wohlfahrt, G., Amelynck, C., Ammann, C., Arneth, A., Bamberger, I., Goldstein, A. H., Gu, L., Guenther, A., Hansel, A., Heinesch, B., Holst, T., Hörtnagl, L., Karl, T., Laffineur, Q., Neftel, A., McKinney, K., Munger, J. W., Pallardy, S. G., Schade, G. W., Seco, R., and Schoon, N.: An ecosystem-scale perspective of the net land methanol flux: synthesis of micrometeorological flux measurements, Atmos. Chem. Phys., 15, 7413–7427, https://doi.org/10.5194/acp-15-7413-2015, 2015. a
Wong, A. Y. H. and Geddes, J. A.: Examining the competing effects of contemporary land management vs. land cover changes on global air quality, Atmos. Chem. Phys., 21, 16479–16497, https://doi.org/10.5194/acp-21-16479-2021, 2021. a
Yáñez-Serrano, A. M., Bourtsoukidis, E., Alves, E. G., Bauwens, M., Stavrakou, T., Llusià, J., Filella, I., Guenther, A., Williams, J., Artaxo, P., Sindelarova, K., Doubalova, J., Kesselmeier, J., and Peñuelas, J.: Amazonian biogenic volatile organic compounds under global change, Glob. Change Biol., 26, 4722–4751, https://doi.org/10.1111/gcb.15185, 2020. a, b, c
Short summary
Changes in vegetation alongside biomass burning impact regional atmospheric composition and air quality. Using satellite remote sensing, we find a clear linear relationship between forest cover and isoprene and a pronounced non-linear relationship between burned area and nitrogen dioxide in the southern Amazon, a region of substantial deforestation. These quantified relationships can be used for model evaluation and further exploration of biosphere-atmosphere interactions in Earth System Models.
Changes in vegetation alongside biomass burning impact regional atmospheric composition and air...
Altmetrics
Final-revised paper
Preprint