Articles | Volume 17, issue 21
https://doi.org/10.5194/gmd-17-7713-2024
© 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/gmd-17-7713-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
05 Nov 2024
Model description paper |
| 05 Nov 2024
| 05 Nov 2024
The Global Forest Fire Emissions Prediction System version 1.0
Kerry Anderson
CORRESPONDING AUTHOR
Air Quality Research Division, Environment and Climate Change Canada, Toronto, Ontario, Canada
formerly at: Natural Resources Canada, Edmonton, Alberta, Canada
retired
Jack Chen
Air Quality Research Division, Environment and Climate Change Canada, Toronto, Ontario, Canada
Peter Englefield
Natural Resources Canada, Edmonton, Alberta, Canada
Debora Griffin
Air Quality Research Division, Environment and Climate Change Canada, Toronto, Ontario, Canada
Paul A. Makar
Air Quality Research Division, Environment and Climate Change Canada, Toronto, Ontario, Canada
Dan Thompson
Natural Resources Canada, Sault Ste. Marie, Ontario, Canada
Related authors
Sina Voshtani, Dylan B. A. Jones, Debra Wunch, Drew C. Pendergrass, Paul O. Wennberg, David F. Pollard, Isamu Morino, Hirofumi Ohyama, Nicholas M. Deutscher, Frank Hase, Ralf Sussmann, Damien Weidmann, Rigel Kivi, Omaira García, Yao Té, Jack Chen, Kerry Anderson, Robin Stevens, Shobha Kondragunta, Aihua Zhu, Douglas Worthy, Senen Racki, Kathryn McKain, Maria V. Makarova, Nicholas Jones, Emmanuel Mahieu, Andrea Cadena-Caicedo, Paolo Cristofanelli, Casper Labuschagne, Elena Kozlova, Thomas Seitz, Martin Steinbacher, Reza Mahdi, and Isao Murata
EGUsphere, https://doi.org/10.5194/egusphere-2025-858, https://doi.org/10.5194/egusphere-2025-858, 2025
Short summary
Short summary
We assess the complementarity of the greater temporal coverage provided by ground-based remote sensing data with the spatial coverage of satellite observations when these data are used together to quantify CO emissions from extreme wildfires in 2023. Our results reveal that the commonly used biomass burning emission inventories significantly underestimate the fire emissions and emphasize the importance of the ground-based remote sensing data in reducing uncertainties in the estimated emissions.
Debora Griffin, Jack Chen, Kerry Anderson, Paul Makar, Chris A. McLinden, Enrico Dammers, and Andre Fogal
Atmos. Chem. Phys., 24, 10159–10186, https://doi.org/10.5194/acp-24-10159-2024, https://doi.org/10.5194/acp-24-10159-2024, 2024
Short summary
Short summary
Satellite-derived CO emissions provide new insights into the understanding of global CO emission rates from wildfires. We use TROPOMI satellite data to create a global inventory database of wildfire CO emissions. These satellite-derived wildfire emissions are used for the evaluation and improvement of existing fire emission inventories and to examine how the wildfire CO emissions have changed over the past 2 decades.
Paul A. Makar, Ayodeji Akingunola, Jack Chen, Balbir Pabla, Wanmin Gong, Craig Stroud, Christopher Sioris, Kerry Anderson, Philip Cheung, Junhua Zhang, and Jason Milbrandt
Atmos. Chem. Phys., 21, 10557–10587, https://doi.org/10.5194/acp-21-10557-2021, https://doi.org/10.5194/acp-21-10557-2021, 2021
Short summary
Short summary
We have examined the effects of airborne particles on absorption and scattering of incoming sunlight by the particles themselves via cloud formation. We used an advanced, combined high-resolution weather forecast and chemical transport computer model, for western North America, and simulations with and without the connections between particles and weather enabled. Feedbacks improved weather and air pollution forecasts and changed cloud behaviour and forest-fire pollutant amount and height.
Chris A. McLinden, Debora Griffin, Vitali Fioletov, Junhua Zhang, Enrico Dammers, Cristen Adams, Mallory Loria, Nickolay Krotkov, and Lok N. Lamsal
Atmos. Chem. Phys., 25, 6093–6120, https://doi.org/10.5194/acp-25-6093-2025, https://doi.org/10.5194/acp-25-6093-2025, 2025
Short summary
Short summary
The Ozone Monitoring Instrument (OMI) was used to understand the evolution of NOx emissions from the Canadian oil sands. OMI NO2 combined with winds and reported stack emissions found emissions from the heavy-hauler mine fleet have remained flat since 2005, whereas the total oil sands mined have more than doubled. This difference is a result of emissions standards that limit NOx emissions becoming more stringent over this period, confirming the efficacy of the policy enacting these standards.
Ramina Alwarda, Kristof Bognar, Xiaoyi Zhao, Vitali Fioletov, Jonathan Davies, Sum Chi Lee, Debora Griffin, Alexandru Lupu, Udo Frieß, Alexander Cede, Yushan Su, and Kimberly Strong
Atmos. Meas. Tech., 18, 2397–2423, https://doi.org/10.5194/amt-18-2397-2025, https://doi.org/10.5194/amt-18-2397-2025, 2025
Short summary
Short summary
Nitrogen dioxide (NO2) is a pollutant with a short lifetime and large variability, but there are limited measurements of its distribution in the lower atmosphere. We present a new 3-year dataset of NO2 vertical profiles in Toronto, Canada, and evaluate it using NO2 from satellite and surface monitoring networks and simulations by an air quality forecast model. We quantify and explain the differences among the datasets to provide information that can be used to understand NO2 variability.
Chi-Tsan Wang, Patrick C. Campbell, Paul Makar, Siqi Ma, Irena Ivanova, Bok H. Baek, Wei-Ting Hung, Zachary Moon, Youhua Tang, Barry Baker, Rick Saylor, and Daniel Tong
EGUsphere, https://doi.org/10.5194/egusphere-2025-485, https://doi.org/10.5194/egusphere-2025-485, 2025
Short summary
Short summary
Forests influence air quality by altering ozone levels, but most air pollution models overlook canopy effects. Our study improves ozone predictions by incorporating forest canopy shading and turbulence into a widely used model. We found that tree cover reduces near-surface ozone by decreasing photolysis rates and diffusion inside canopy, resulting in lower ozone concentrations in densely forested areas. These findings enhance ozone surface prediction accuracy and improve air quality modeling.
Debora Griffin, Colin Hempel, Chris McLinden, Shailesh Kumar Kharol, Colin Lee, Andre Fogal, Christopher Sioris, Mark Shephard, and Yuan You
EGUsphere, https://doi.org/10.5194/egusphere-2025-1681, https://doi.org/10.5194/egusphere-2025-1681, 2025
Short summary
Short summary
Surface NO2 concentrations are obtained across North America using satellite data and machine learning, and compared to traditional approaches to determine surface NO2 from satellite observations.
Ioannis Kioutsioukis, Christian Hogrefe, Paul A. Makar, Ummugulsun Alyuz, Jessy O. Bash, Roberto Bellasio, Roberto Bianconi, Tim Buttler, Olivia E. Clifton, Philippe Cheung, Alma Hodzic, Richard Kranenburg, Aurelia Lupascu, Kester Momoh, Juan Luis Perez-Camaño, John Pleim, Young-Hee Ryu, Robero San Jose, Donna Schwede, Ranjeet Sokhi, and Stefano Galmarini
EGUsphere, https://doi.org/10.5194/egusphere-2025-1091, https://doi.org/10.5194/egusphere-2025-1091, 2025
Short summary
Short summary
Deposition is a key in air quality modelling. An evaluation of the AQMEII4 models is performed prior to analysing the different deposition schemes in relation to the LULC used. Such analysis is unprecedented. Among the results, LULC masks have to be harmonised and up-to-date information used in place of outdated and too course masks. Alternatively LULC masks should be evaluated and intercom pared when multiple model results are analysed.
Paul A. Makar, Philip Cheung, Christian Hogrefe, Ayodeji Akingunola, Ummugulsum Alyuz, Jesse O. Bash, Michael D. Bell, Roberto Bellasio, Roberto Bianconi, Tim Butler, Hazel Cathcart, Olivia E. Clifton, Alma Hodzic, Ioannis Kioutsioukis, Richard Kranenburg, Aurelia Lupascu, Jason A. Lynch, Kester Momoh, Juan L. Perez-Camanyo, Jonathan Pleim, Young-Hee Ryu, Roberto San Jose, Donna Schwede, Thomas Scheuschner, Mark W. Shephard, Ranjeet S. Sokhi, and Stefano Galmarini
Atmos. Chem. Phys., 25, 3049–3107, https://doi.org/10.5194/acp-25-3049-2025, https://doi.org/10.5194/acp-25-3049-2025, 2025
Short summary
Short summary
The large range of sulfur and nitrogen deposition estimates from air quality models results in a large range of predicted impacts. We used models and deposition diagnostics to identify the processes controlling atmospheric sulfur and nitrogen deposition variability. Controlling factors included the uptake of gases and aerosols by hydrometeors, aerosol inorganic chemistry, particle dry deposition, ammonia bidirectional fluxes, gas deposition via plant cuticles and soil, and land use data.
Sina Voshtani, Dylan B. A. Jones, Debra Wunch, Drew C. Pendergrass, Paul O. Wennberg, David F. Pollard, Isamu Morino, Hirofumi Ohyama, Nicholas M. Deutscher, Frank Hase, Ralf Sussmann, Damien Weidmann, Rigel Kivi, Omaira García, Yao Té, Jack Chen, Kerry Anderson, Robin Stevens, Shobha Kondragunta, Aihua Zhu, Douglas Worthy, Senen Racki, Kathryn McKain, Maria V. Makarova, Nicholas Jones, Emmanuel Mahieu, Andrea Cadena-Caicedo, Paolo Cristofanelli, Casper Labuschagne, Elena Kozlova, Thomas Seitz, Martin Steinbacher, Reza Mahdi, and Isao Murata
EGUsphere, https://doi.org/10.5194/egusphere-2025-858, https://doi.org/10.5194/egusphere-2025-858, 2025
Short summary
Short summary
We assess the complementarity of the greater temporal coverage provided by ground-based remote sensing data with the spatial coverage of satellite observations when these data are used together to quantify CO emissions from extreme wildfires in 2023. Our results reveal that the commonly used biomass burning emission inventories significantly underestimate the fire emissions and emphasize the importance of the ground-based remote sensing data in reducing uncertainties in the estimated emissions.
Sepehr Fathi, Paul Makar, Wanmin Gong, Junhua Zhang, Katherine Hayden, and Mark Gordon
Atmos. Chem. Phys., 25, 2385–2405, https://doi.org/10.5194/acp-25-2385-2025, https://doi.org/10.5194/acp-25-2385-2025, 2025
Short summary
Short summary
Our study explores the influence of water phase changes in plumes from industrial sources on atmospheric dispersion of emitted pollutants and air quality. Employing PRISM (Plume-Rise-Iterative-Stratified-Moist), a new method, we found that considering these effects significantly improves predictions of pollutant dispersion. This insight enhances our understanding of environmental impacts, enabling more accurate air quality modelling and fostering more effective pollution management strategies.
Dane Blanchard, Mark Gordon, Duc Huy Dang, Paul Andrew Makar, and Julian Aherne
Atmos. Chem. Phys., 25, 2423–2442, https://doi.org/10.5194/acp-25-2423-2025, https://doi.org/10.5194/acp-25-2423-2025, 2025
Short summary
Short summary
This study offers the first known evaluation of water-soluble brown carbon aerosols in the Athabasca oil sands region (AOSR), Canada. Fluorescence spectroscopy analysis of aerosol samples from five regional sites (collected during the summer of 2021) identified oil sands operations as a measurable brown carbon source. Industrial aerosol emissions were unlikely to impact regional radiative forcing. These findings show that fluorescence spectroscopy can be used to monitor brown carbon in the AOSR.
Christian Hogrefe, Stefano Galmarini, Paul A. Makar, Ioannis Kioutsioukis, Olivia E. Clifton, Ummugulsum Alyuz, Jesse O. Bash, Roberto Bellasio, Roberto Bianconi, Tim Butler, Philip Cheung, Alma Hodzic, Richard Kranenburg, Aurelia Lupascu, Kester Momoh, Juan Luis Perez-Camanyo, Jonathan E. Pleim, Young-Hee Ryu, Roberto San Jose, Martijn Schaap, Donna B. Schwede, and Ranjeet Sokhi
EGUsphere, https://doi.org/10.5194/egusphere-2025-225, https://doi.org/10.5194/egusphere-2025-225, 2025
Short summary
Short summary
Performed under the umbrella of the fourth phase of the Air Quality Model Evaluation International Initiative (AQMEII4), this study applies AQMEII4 diagnostic tools to better characterize how dry deposition removes pollutants from the atmosphere in regional-scale models. The results also strongly suggest that improvement and harmonization of the representation of land use in these models would serve the community in their future development efforts.
Hazel Cathcart, Julian Aherne, Michael D. Moran, Verica Savic-Jovcic, Paul A. Makar, and Amanda Cole
Biogeosciences, 22, 535–554, https://doi.org/10.5194/bg-22-535-2025, https://doi.org/10.5194/bg-22-535-2025, 2025
Short summary
Short summary
Deposition from sulfur and nitrogen pollution can harm ecosystems, and recovery from this type of pollution can take decades or longer. To identify risk to Canadian soils, we created maps showing sensitivity to sulfur and nitrogen pollution. Results show that some ecosystems are at risk from acid and nutrient nitrogen deposition: 10 % of protected areas are receiving acid deposition beyond their damage threshold, and 70 % may be receiving nitrogen deposition that could cause biodiversity loss.
Vitali Fioletov, Chris A. McLinden, Debora Griffin, Xiaoyi Zhao, and Henk Eskes
Atmos. Chem. Phys., 25, 575–596, https://doi.org/10.5194/acp-25-575-2025, https://doi.org/10.5194/acp-25-575-2025, 2025
Short summary
Short summary
Satellite data were used to estimate urban per capita emissions for 261 major cities worldwide. Three components in tropospheric NO2 data (background NO2, NO2 from urban sources, and NO2 from industrial point sources) were isolated, and then each of these components was analyzed separately. The largest per capita emissions were found in the Middle East and the smallest in India and southern Africa. Urban weekend emissions are 20 %–50 % less than workday emissions for all regions except China.
Xiaoyi Zhao, Vitali Fioletov, Debora Griffin, Chris McLinden, Ralf Staebler, Cristian Mihele, Kevin Strawbridge, Jonathan Davies, Ihab Abboud, Sum Chi Lee, Alexander Cede, Martin Tiefengraber, and Robert Swap
Atmos. Meas. Tech., 17, 6889–6912, https://doi.org/10.5194/amt-17-6889-2024, https://doi.org/10.5194/amt-17-6889-2024, 2024
Short summary
Short summary
This study explores differences between remote sensing and in situ instruments in terms of their vertical, horizontal, and temporal sampling differences. Understanding and resolving these differences are critical for future analyses linking satellite, ground-based remote sensing, and in situ observations in air quality monitoring. It shows that the meteorological conditions (wind directions, speed, and boundary layer conditions) will strongly affect the agreement between the two measurements.
Can Li, Nickolay A. Krotkov, Joanna Joiner, Vitali Fioletov, Chris McLinden, Debora Griffin, Peter J. T. Leonard, Simon Carn, Colin Seftor, and Alexander Vasilkov
Earth Syst. Sci. Data, 16, 4291–4309, https://doi.org/10.5194/essd-16-4291-2024, https://doi.org/10.5194/essd-16-4291-2024, 2024
Short summary
Short summary
Sulfur dioxide (SO2), a poisonous gas from human activities and volcanoes, causes air pollution, acid rain, and changes to climate and the ozone layer. Satellites have been used to monitor SO2 globally, including remote areas. Here we describe a new satellite SO2 dataset from the OMPS instrument that flies on the N20 satellite. Results show that the new dataset agrees well with the existing ones from other satellites and can help to continue the global monitoring of SO2 from space.
Debora Griffin, Jack Chen, Kerry Anderson, Paul Makar, Chris A. McLinden, Enrico Dammers, and Andre Fogal
Atmos. Chem. Phys., 24, 10159–10186, https://doi.org/10.5194/acp-24-10159-2024, https://doi.org/10.5194/acp-24-10159-2024, 2024
Short summary
Short summary
Satellite-derived CO emissions provide new insights into the understanding of global CO emission rates from wildfires. We use TROPOMI satellite data to create a global inventory database of wildfire CO emissions. These satellite-derived wildfire emissions are used for the evaluation and improvement of existing fire emission inventories and to examine how the wildfire CO emissions have changed over the past 2 decades.
Enrico Dammers, Janot Tokaya, Christian Mielke, Kevin Hausmann, Debora Griffin, Chris McLinden, Henk Eskes, and Renske Timmermans
Geosci. Model Dev., 17, 4983–5007, https://doi.org/10.5194/gmd-17-4983-2024, https://doi.org/10.5194/gmd-17-4983-2024, 2024
Short summary
Short summary
Nitrogen dioxide (NOx) is produced by sources such as industry and traffic and is directly linked to negative impacts on health and the environment. The current construction of emission inventories to keep track of NOx emissions is slow and time-consuming. Satellite measurements provide a way to quickly and independently estimate emissions. In this study, we apply a consistent methodology to derive NOx emissions over Germany and illustrate the value of having such a method for fast projections.
Stefan J. Miller, Paul A. Makar, and Colin J. Lee
Geosci. Model Dev., 17, 2197–2219, https://doi.org/10.5194/gmd-17-2197-2024, https://doi.org/10.5194/gmd-17-2197-2024, 2024
Short summary
Short summary
This work outlines a new solver written in Fortran to calculate the partitioning of metastable aerosols at thermodynamic equilibrium based on the forward algorithms of ISORROPIA II. The new code includes numerical improvements that decrease the computational speed (compared to ISORROPIA II) while improving the accuracy of the partitioning solution.
Roya Ghahreman, Wanmin Gong, Paul A. Makar, Alexandru Lupu, Amanda Cole, Kulbir Banwait, Colin Lee, and Ayodeji Akingunola
Geosci. Model Dev., 17, 685–707, https://doi.org/10.5194/gmd-17-685-2024, https://doi.org/10.5194/gmd-17-685-2024, 2024
Short summary
Short summary
The article explores the impact of different representations of below-cloud scavenging on model biases. A new scavenging scheme and precipitation-phase partitioning improve the model's performance, with better SO42- scavenging and wet deposition of NO3- and NH4+.
Lukas Fehr, Chris McLinden, Debora Griffin, Daniel Zawada, Doug Degenstein, and Adam Bourassa
Geosci. Model Dev., 16, 7491–7507, https://doi.org/10.5194/gmd-16-7491-2023, https://doi.org/10.5194/gmd-16-7491-2023, 2023
Short summary
Short summary
This work highlights upgrades to SASKTRAN, a model that simulates sunlight interacting with the atmosphere to help measure trace gases. The upgrades were verified by detailed comparisons between different numerical methods. A case study was performed using SASKTRAN’s multidimensional capabilities, which found that ignoring horizontal variation in the atmosphere (a common practice in the field) can introduce non-negligible errors where there is snow or high pollution.
Vitali E. Fioletov, Chris A. McLinden, Debora Griffin, Nickolay A. Krotkov, Can Li, Joanna Joiner, Nicolas Theys, and Simon Carn
Atmos. Meas. Tech., 16, 5575–5592, https://doi.org/10.5194/amt-16-5575-2023, https://doi.org/10.5194/amt-16-5575-2023, 2023
Short summary
Short summary
Snow-covered terrain, with its high reflectance in the UV, typically enhances satellite sensitivity to boundary layer pollution. However, a significant fraction of high-quality cloud-free measurements over snow is currently excluded from analyses. In this study, we investigated how satellite SO2 measurements over snow-covered surfaces can be used to improve estimations of annual SO2 emissions.
Colin J. Lee, Paul A. Makar, and Joana Soares
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-185, https://doi.org/10.5194/gmd-2023-185, 2023
Publication in GMD not foreseen
Short summary
Short summary
Clustering is an analysis technique for finding similarities within datasets. We present a new implementation of the hierarchical clustering algorithm that is able to process much larger datasets than was previously possible, by spreading the program out over many connected computers in a high-performance computing system. We show airshed maps of a high-resolution regional model output domain, and find related air pollution profiles at monitoring stations separated by thousands of kilometers.
Xuanyi Zhang, Mark Gordon, Paul A. Makar, Timothy Jiang, Jonathan Davies, and David Tarasick
Atmos. Chem. Phys., 23, 13647–13664, https://doi.org/10.5194/acp-23-13647-2023, https://doi.org/10.5194/acp-23-13647-2023, 2023
Short summary
Short summary
Measurements of ozone in the atmosphere were made in a forest downwind of oil sands mining and production facilities in northern Alberta. These measurements show that the emissions of other pollutants from oil sands production and processing reduce the amount of ozone in the forest. By using an atmospheric model combined with measurements, we find that the rate at which ozone is absorbed by the forest is lower than typical rates from similar measurements in other forests.
Olivia E. Clifton, Donna Schwede, Christian Hogrefe, Jesse O. Bash, Sam Bland, Philip Cheung, Mhairi Coyle, Lisa Emberson, Johannes Flemming, Erick Fredj, Stefano Galmarini, Laurens Ganzeveld, Orestis Gazetas, Ignacio Goded, Christopher D. Holmes, László Horváth, Vincent Huijnen, Qian Li, Paul A. Makar, Ivan Mammarella, Giovanni Manca, J. William Munger, Juan L. Pérez-Camanyo, Jonathan Pleim, Limei Ran, Roberto San Jose, Sam J. Silva, Ralf Staebler, Shihan Sun, Amos P. K. Tai, Eran Tas, Timo Vesala, Tamás Weidinger, Zhiyong Wu, and Leiming Zhang
Atmos. Chem. Phys., 23, 9911–9961, https://doi.org/10.5194/acp-23-9911-2023, https://doi.org/10.5194/acp-23-9911-2023, 2023
Short summary
Short summary
A primary sink of air pollutants is dry deposition. Dry deposition estimates differ across the models used to simulate atmospheric chemistry. Here, we introduce an effort to examine dry deposition schemes from atmospheric chemistry models. We provide our approach’s rationale, document the schemes, and describe datasets used to drive and evaluate the schemes. We also launch the analysis of results by evaluating against observations and identifying the processes leading to model–model differences.
Mark Gordon, Dane Blanchard, Timothy Jiang, Paul A. Makar, Ralf M. Staebler, Julian Aherne, Cris Mihele, and Xuanyi Zhang
Atmos. Chem. Phys., 23, 7241–7255, https://doi.org/10.5194/acp-23-7241-2023, https://doi.org/10.5194/acp-23-7241-2023, 2023
Short summary
Short summary
Measurements of the gas sulfur dioxide (SO2) were made in a forest downwind of oil sands mining and production facilities in northern Alberta. These measurements tell us the rate at which SO2 is absorbed by the forest. The measured rate is much higher than what is currently used by air quality models, which is supported by a previous study in this region. This suggests that SO2 may have a much shorter lifetime in the atmosphere at this location than currently predicted by models.
Timothy Jiang, Mark Gordon, Paul A. Makar, Ralf M. Staebler, and Michael Wheeler
Atmos. Chem. Phys., 23, 4361–4372, https://doi.org/10.5194/acp-23-4361-2023, https://doi.org/10.5194/acp-23-4361-2023, 2023
Short summary
Short summary
Measurements of submicron aerosols (particles smaller than 1 / 1000 of a millimeter) were made in a forest downwind of oil sands mining and production facilities in northern Alberta. These measurements tell us how quickly aerosols are absorbed by the forest (known as deposition rate) and how the deposition rate depends on the size of the aerosol. The measurements show good agreement with a parameterization developed from a recent study for deposition of aerosols to a similar pine forest.
Vitali E. Fioletov, Chris A. McLinden, Debora Griffin, Ihab Abboud, Nickolay Krotkov, Peter J. T. Leonard, Can Li, Joanna Joiner, Nicolas Theys, and Simon Carn
Earth Syst. Sci. Data, 15, 75–93, https://doi.org/10.5194/essd-15-75-2023, https://doi.org/10.5194/essd-15-75-2023, 2023
Short summary
Short summary
Sulfur dioxide (SO2) measurements from three satellite instruments were used to update and extend the previously developed global catalogue of large SO2 emission sources. This version 2 of the global catalogue covers the period of 2005–2021 and includes a total of 759 continuously emitting point sources. The catalogue data show an approximate 50 % decline in global SO2 emissions between 2005 and 2021, although emissions were relatively stable during the last 3 years.
Katherine L. Hayden, Shao-Meng Li, John Liggio, Michael J. Wheeler, Jeremy J. B. Wentzell, Amy Leithead, Peter Brickell, Richard L. Mittermeier, Zachary Oldham, Cristian M. Mihele, Ralf M. Staebler, Samar G. Moussa, Andrea Darlington, Mengistu Wolde, Daniel Thompson, Jack Chen, Debora Griffin, Ellen Eckert, Jenna C. Ditto, Megan He, and Drew R. Gentner
Atmos. Chem. Phys., 22, 12493–12523, https://doi.org/10.5194/acp-22-12493-2022, https://doi.org/10.5194/acp-22-12493-2022, 2022
Short summary
Short summary
In this study, airborne measurements provided the most detailed characterization, to date, of boreal forest wildfire emissions. Measurements showed a large diversity of air pollutants expanding the volatility range typically reported. A large portion of organic species was unidentified, likely comprised of complex organic compounds. Aircraft-derived emissions improve wildfire chemical speciation and can support reliable model predictions of pollution from boreal forest wildfires.
Vitali Fioletov, Chris A. McLinden, Debora Griffin, Nickolay Krotkov, Fei Liu, and Henk Eskes
Atmos. Chem. Phys., 22, 4201–4236, https://doi.org/10.5194/acp-22-4201-2022, https://doi.org/10.5194/acp-22-4201-2022, 2022
Short summary
Short summary
The COVID-19 lockdown had a large impact on anthropogenic emissions and particularly on nitrogen dioxide (NO2). A new method of isolation of background, urban, and industrial components in NO2 is applied to estimate the lockdown impact on each of them. From 16 March to 15 June 2020, urban NO2 declined by −18 % to −28 % in most regions of the world, while background NO2 typically declined by less than −10 %.
Mahtab Majdzadeh, Craig A. Stroud, Christopher Sioris, Paul A. Makar, Ayodeji Akingunola, Chris McLinden, Xiaoyi Zhao, Michael D. Moran, Ihab Abboud, and Jack Chen
Geosci. Model Dev., 15, 219–249, https://doi.org/10.5194/gmd-15-219-2022, https://doi.org/10.5194/gmd-15-219-2022, 2022
Short summary
Short summary
A new lookup table for aerosol optical properties based on a Mie scattering code was calculated and adopted within an improved version of the photolysis module in the GEM-MACH in-line chemical transport model. The modified version of the photolysis module makes use of online interactive aerosol feedback and applies core-shell parameterizations to the black carbon absorption efficiency based on Bond et al. (2006) to the size bins with black carbon mass fraction of less than 40 %.
Debora Griffin, Chris A. McLinden, Enrico Dammers, Cristen Adams, Chelsea E. Stockwell, Carsten Warneke, Ilann Bourgeois, Jeff Peischl, Thomas B. Ryerson, Kyle J. Zarzana, Jake P. Rowe, Rainer Volkamer, Christoph Knote, Natalie Kille, Theodore K. Koenig, Christopher F. Lee, Drew Rollins, Pamela S. Rickly, Jack Chen, Lukas Fehr, Adam Bourassa, Doug Degenstein, Katherine Hayden, Cristian Mihele, Sumi N. Wren, John Liggio, Ayodeji Akingunola, and Paul Makar
Atmos. Meas. Tech., 14, 7929–7957, https://doi.org/10.5194/amt-14-7929-2021, https://doi.org/10.5194/amt-14-7929-2021, 2021
Short summary
Short summary
Satellite-derived NOx emissions from biomass burning are estimated with TROPOMI observations. Two common emission estimation methods are applied, and sensitivity tests with model output were performed to determine the accuracy of these methods. The effect of smoke aerosols on TROPOMI NO2 columns is estimated and compared to aircraft observations from four different aircraft campaigns measuring biomass burning plumes in 2018 and 2019 in North America.
Nicolas Theys, Vitali Fioletov, Can Li, Isabelle De Smedt, Christophe Lerot, Chris McLinden, Nickolay Krotkov, Debora Griffin, Lieven Clarisse, Pascal Hedelt, Diego Loyola, Thomas Wagner, Vinod Kumar, Antje Innes, Roberto Ribas, François Hendrick, Jonas Vlietinck, Hugues Brenot, and Michel Van Roozendael
Atmos. Chem. Phys., 21, 16727–16744, https://doi.org/10.5194/acp-21-16727-2021, https://doi.org/10.5194/acp-21-16727-2021, 2021
Short summary
Short summary
We present a new algorithm to retrieve sulfur dioxide from space UV measurements. We apply the technique to high-resolution TROPOMI measurements and demonstrate the high sensitivity of the approach to weak SO2 emissions worldwide with an unprecedented limit of detection of 8 kt yr−1. This result has broad implications for atmospheric science studies dealing with improving emission inventories and identifying and quantifying missing sources, in the context of air quality and climate.
Stefano Galmarini, Paul Makar, Olivia E. Clifton, Christian Hogrefe, Jesse O. Bash, Roberto Bellasio, Roberto Bianconi, Johannes Bieser, Tim Butler, Jason Ducker, Johannes Flemming, Alma Hodzic, Christopher D. Holmes, Ioannis Kioutsioukis, Richard Kranenburg, Aurelia Lupascu, Juan Luis Perez-Camanyo, Jonathan Pleim, Young-Hee Ryu, Roberto San Jose, Donna Schwede, Sam Silva, and Ralf Wolke
Atmos. Chem. Phys., 21, 15663–15697, https://doi.org/10.5194/acp-21-15663-2021, https://doi.org/10.5194/acp-21-15663-2021, 2021
Short summary
Short summary
This technical note presents the research protocols for phase 4 of the Air Quality Model Evaluation International Initiative (AQMEII4). This initiative has three goals: (i) to define the state of wet and dry deposition in regional models, (ii) to evaluate how dry deposition influences air concentration and flux predictions, and (iii) to identify the causes for prediction differences. The evaluation compares LULC-specific dry deposition and effective conductances and fluxes.
Sepehr Fathi, Mark Gordon, Paul A. Makar, Ayodeji Akingunola, Andrea Darlington, John Liggio, Katherine Hayden, and Shao-Meng Li
Atmos. Chem. Phys., 21, 15461–15491, https://doi.org/10.5194/acp-21-15461-2021, https://doi.org/10.5194/acp-21-15461-2021, 2021
Short summary
Short summary
We have investigated the accuracy of aircraft-based mass balance methodologies through computer model simulations of the atmosphere and air quality at a regional high-resolution scale. We have defined new quantitative metrics to reduce emission retrieval uncertainty by evaluating top-down mass balance estimates against the known simulated meteorology and input emissions. We also recommend methodologies and flight strategies for improved retrievals in future aircraft-based studies.
Xinxin Ye, Pargoal Arab, Ravan Ahmadov, Eric James, Georg A. Grell, Bradley Pierce, Aditya Kumar, Paul Makar, Jack Chen, Didier Davignon, Greg R. Carmichael, Gonzalo Ferrada, Jeff McQueen, Jianping Huang, Rajesh Kumar, Louisa Emmons, Farren L. Herron-Thorpe, Mark Parrington, Richard Engelen, Vincent-Henri Peuch, Arlindo da Silva, Amber Soja, Emily Gargulinski, Elizabeth Wiggins, Johnathan W. Hair, Marta Fenn, Taylor Shingler, Shobha Kondragunta, Alexei Lyapustin, Yujie Wang, Brent Holben, David M. Giles, and Pablo E. Saide
Atmos. Chem. Phys., 21, 14427–14469, https://doi.org/10.5194/acp-21-14427-2021, https://doi.org/10.5194/acp-21-14427-2021, 2021
Short summary
Short summary
Wildfire smoke has crucial impacts on air quality, while uncertainties in the numerical forecasts remain significant. We present an evaluation of 12 real-time forecasting systems. Comparison of predicted smoke emissions suggests a large spread in magnitudes, with temporal patterns deviating from satellite detections. The performance for AOD and surface PM2.5 and their discrepancies highlighted the role of accurately represented spatiotemporal emission profiles in improving smoke forecasts.
Paul A. Makar, Craig Stroud, Ayodeji Akingunola, Junhua Zhang, Shuzhan Ren, Philip Cheung, and Qiong Zheng
Atmos. Chem. Phys., 21, 12291–12316, https://doi.org/10.5194/acp-21-12291-2021, https://doi.org/10.5194/acp-21-12291-2021, 2021
Short summary
Short summary
Vehicle pollutant emissions occur in an environment where upward transport can be enhanced due to the turbulence created by the vehicles as they move through the atmosphere. An approach for including these turbulence effects in regional air pollution forecast models has been derived from theoretical, observation, and higher-resolution modeling. The enhanced mixing, which occurs in the immediate vicinity of roadways, changes pollutant concentrations on the regional to continental scale.
Zhiyong Wu, Leiming Zhang, John T. Walker, Paul A. Makar, Judith A. Perlinger, and Xuemei Wang
Geosci. Model Dev., 14, 5093–5105, https://doi.org/10.5194/gmd-14-5093-2021, https://doi.org/10.5194/gmd-14-5093-2021, 2021
Short summary
Short summary
A community dry deposition algorithm for modeling the gaseous dry deposition process in chemistry transport models was extended to include an additional 12 oxidized volatile organic compounds and hydrogen cyanide based on their physicochemical properties and was then evaluated using field flux measurements over a mixed forest. This study provides a useful tool that is needed in chemistry transport models with increasing complexity for simulating an important atmospheric process.
Paul A. Makar, Ayodeji Akingunola, Jack Chen, Balbir Pabla, Wanmin Gong, Craig Stroud, Christopher Sioris, Kerry Anderson, Philip Cheung, Junhua Zhang, and Jason Milbrandt
Atmos. Chem. Phys., 21, 10557–10587, https://doi.org/10.5194/acp-21-10557-2021, https://doi.org/10.5194/acp-21-10557-2021, 2021
Short summary
Short summary
We have examined the effects of airborne particles on absorption and scattering of incoming sunlight by the particles themselves via cloud formation. We used an advanced, combined high-resolution weather forecast and chemical transport computer model, for western North America, and simulations with and without the connections between particles and weather enabled. Feedbacks improved weather and air pollution forecasts and changed cloud behaviour and forest-fire pollutant amount and height.
Katherine Hayden, Shao-Meng Li, Paul Makar, John Liggio, Samar G. Moussa, Ayodeji Akingunola, Robert McLaren, Ralf M. Staebler, Andrea Darlington, Jason O'Brien, Junhua Zhang, Mengistu Wolde, and Leiming Zhang
Atmos. Chem. Phys., 21, 8377–8392, https://doi.org/10.5194/acp-21-8377-2021, https://doi.org/10.5194/acp-21-8377-2021, 2021
Short summary
Short summary
We developed a method using aircraft measurements to determine lifetimes with respect to dry deposition for oxidized sulfur and nitrogen compounds over the boreal forest in Alberta, Canada. Atmospheric lifetimes were significantly shorter than derived from chemical transport models with differences related to modelled dry deposition velocities. The shorter lifetimes suggest models need to reassess dry deposition treatment and predictions of sulfur and nitrogen in the atmosphere and ecosystems.
Xiaoyi Zhao, Vitali Fioletov, Michael Brohart, Volodya Savastiouk, Ihab Abboud, Akira Ogyu, Jonathan Davies, Reno Sit, Sum Chi Lee, Alexander Cede, Martin Tiefengraber, Moritz Müller, Debora Griffin, and Chris McLinden
Atmos. Meas. Tech., 14, 2261–2283, https://doi.org/10.5194/amt-14-2261-2021, https://doi.org/10.5194/amt-14-2261-2021, 2021
Short summary
Short summary
The Brewer spectrophotometer is one of the main instruments for measurements of atmospheric total column ozone. The global Brewer network largely relies on the world reference instruments (the Brewer triad) operated by Environment and Climate Change Canada since the early 1980s. This study provides an updated assessment (1999–2019) of the reference instrument performance, in terms of random uncertainties and long-term stability.
Dan K. Thompson and Kimberly Morrison
Nat. Hazards Earth Syst. Sci., 20, 3439–3454, https://doi.org/10.5194/nhess-20-3439-2020, https://doi.org/10.5194/nhess-20-3439-2020, 2020
Short summary
Short summary
We describe critically low relative humidity and high wind speeds above which only documented wildfires were seen to occur and where no agricultural fires were documented in southern Canada. We then applied these thresholds to the much larger satellite record from 2002–2018 to quantify regional differences in both the rate of observed burning and the number of days with critical weather conditions to sustain a wildfire in this grassland and agricultural region.
Cited articles
Abram, N. J., Henley, B. J., Sen Gupta, A., Lippmann, T. J., Clarke, H., Dowdy, A. J., Sharples, J. J., Nolan, R. H., Zhang, T., Wooster, M. J., and Wurtzel, J. B.: Connections of climate change and variability to large and extreme forest fires in southeast Australia, Commun. Earth Environ., 2, 8, https://doi.org/10.1038/s43247-020-00065-8, 2021.
Adams, C., McLinden, C. A., Shephard, M. W., Dickson, N., Dammers, E., Chen, J., Makar, P., Cady-Pereira, K. E., Tam, N., Kharol, S. K., Lamsal, L. N., and Krotkov, N. A.: Satellite-derived emissions of carbon monoxide, ammonia, and nitrogen dioxide from the 2016 Horse River wildfire in the Fort McMurray area, Atmos. Chem. Phys., 19, 2577–2599, https://doi.org/10.5194/acp-19-2577-2019, 2019.
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.
Alexander, M. E.: Foliar moisture content input in the Canadian Forest Fire Behavior Prediction System for areas outside of Canada, VI International Conference on Forest Fire Research, 15–18 November 2010, Coimbra, Portugal, 15–18, 2010a.
Alexander, M. E.: Surface fire spread potential in trembling aspen during summer in the Boreal Forest Region of Canada, The Forestry Chronicle, 86, 200–212, 2010b.
Alexander, M. E., Stocks, B. J., and Lawson, B. D.: Fire behavior in black spruce-lichen woodland: the Porter Lake project (No. NOR-X-310), Forestry Canada-Northwest Region, 1990.
Anderson, K.: Global Forest Fire Emissions Prediction System (GFFEPS) (v1.0), Zenodo [code and data set], https://doi.org/10.5281/zenodo.10710453, 2024.
Anderson, K. R.: January. Incorporating smoldering into fire growth modelling, Third Symposium on Fire and Forest Meteorology, 9–14 January 2000, Long Beach, CA, 9–14, 2000.
Anderson, K. R., Englefield, P., Little, J. M., and Reuter, G.: An approach to operational forest fire growth predictions for Canada, Int. J. Wildland Fire, 18, 893–905, 2009.
Ban, Y., Zhang, P., Nascetti, A., Bevington, A. R., and Wulder, M. A.: Near real-time wildfire progression monitoring with Sentinel-1 SAR time series and deep learning, Sci. Rep.-UK, 10, 1322, https://doi.org/10.1038/s41598-019-56967-x, 2020.
Barros, B., Oliveira, M., and Morais, S.: Continent-based systematic review of the short-term health impacts of wildfire emissions, J. Toxicol. Environ. He. B, 26, 387–415, 2023.
Bartholome, E. and Belward, A. S.: GLC2000: a new approach to global land cover mapping from Earth observation data, Int. J. Remote Sens., 26, 1959–1977, 2005.
Bond, T. C., Doherty, S. J., Fahey, D. W., Forster, P. M., Berntsen, T., DeAngelo, B. J., Flanner, M. G., Ghan, S., Kärcher, B., Koch, D., and Kinne, S.: Bounding the role of black carbon in the climate system: A scientific assessment, J. Geophys. Res.-Atmos., 118, 5380–5552, 2013.
Budd, G. M., Brotherhood, J. R., Hendrie, A. L., Jeffery, S. E., Beasley, F. A., Costin, B. P., Zhien, W., Baker, M. M., Cheney, N. P., and Dawson, M. P.: Project Aquarius 1. Stress, strain, and productivity in men suppressing Australian summer bushfires with hand tools: background, objectives, and methods, Int. J. Wildland Fire, 7, 69–76, 1997.
Burrows, N., Ward, B., Wills, A., Williams, M., and Cranfield, R.: Fine-scale temporal turnover of jarrah forest understory vegetation assemblages is independent of fire regime, Fire Ecol., 15, 1–18, 2019.
Carvalho Jr., J. A., Santos, J. M., Santos, J. C. D., Leitão, M. M., and Higuchi, N.: A tropical rainforest clearing experiment by biomass burning in the Manaus region, Atmos. Environ., 29, 2301–2309, 1995.
Cassou, E.: Field Burning (English), Agricultural Pollution, World Bank Group, Washington, DC, 2018.
Chen, G., Guo, Y., Yue, X., Tong, S., Gasparrini, A., Bell, M. L., Armstrong, B., Schwartz, J., Jaakkola, J. J., Zanobetti, A., and Lavigne, E.: Mortality risk attributable to wildfire-related PM2.5 pollution: a global time series study in 749 locations, The Lancet Planetary Health, 5, e579–e587, 2021.
Chen, J., Anderson, K., Pavlovic, R., Moran, M. D., Englefield, P., Thompson, D. K., Munoz-Alpizar, R., and Landry, H.: The FireWork v2.0 air quality forecast system with biomass burning emissions from the Canadian Forest Fire Emissions Prediction System v2.03, Geosci. Model Dev., 12, 3283–3310, https://doi.org/10.5194/gmd-12-3283-2019, 2019.
Chen, Y., Hall, J., van Wees, D., Andela, N., Hantson, S., Giglio, L., van der Werf, G. R., Morton, D. C., and Randerson, J. T.: Multi-decadal trends and variability in burned area from the fifth version of the Global Fire Emissions Database (GFED5), Earth Syst. Sci. Data, 15, 5227–5259, https://doi.org/10.5194/essd-15-5227-2023, 2023.
Cheney, N. P., Gould, J. S., McCaw, W. L., and Anderson, W. R.: Predicting fire behaviour in dry eucalypt forest in southern Australia, Forest Ecol. Manage., 280, 120–131, 2012.
Cheney, P. and Sullivan, A.: Grassfires: fuel, weather and fire behaviour, Csiro Publishin, https://doi.org/10.1071/9780643096493, 2008.
Countryman, C. M.: The fire environment concept, Pacific Southwest Forest and Range Experiment Station, 1972.
De Castro, E. A. and Kauffman, J. B.: Ecosystem structure in the Brazilian Cerrado: a vegetation gradient of aboveground biomass, root mass and consumption by fire, J. Trop. Ecol., 14, 263–283, 1998.
Eyth, A., Vukovich, J., Farkas, C., and Godfrey, J.: Technical Support Document (TSD): Preparation of Emissions Inventories for the 2016v3 North American Emissions Modeling Platform. US Environmental Protection Agency, Office of Air Quality Planning and Standards, Air Quality Assessment Division, 2022.
Fearnside, P. M., Leal Jr., N., and Fernandes, F. M.: Rainforest burning and the global carbon budget: biomass, combustion efficiency, and charcoal formation in the Brazilian Amazon, J. Geophys. Res.-Atmos., 98, 16733–16743, 1993.
Fearnside, P. M., de Alencastro Graça, P. M. L., and Rodrigues, F. J. A.: Burning of Amazonian rainforests: burning efficiency and charcoal formation in forest cleared for cattle pasture near Manaus, Brazil, Forest Ecol. Manage., 146, 115–128, 2001.
Field, R. D., Wang, Y., and Roswintiarti, O.: A drought-based predictor of recent haze events in western Indonesia, Atmos. Environ., 38, 1869–1878, 2004.
Field, R. D., Van Der Werf, G. R., and Shen, S. S.: Human amplification of drought-induced biomass burning in Indonesia since 1960, Nat. Geosci., 2, 185–188, 2009.
Forestry Canada Fire Danger Group: Development and structure of the Canadian forest fire behavior prediction system (vol. 3), Forestry Canada, Science and Sustainable Development Directorate, 1992.
Fraser, R. H., Hall, R. J., Landry, R., Lynham, T. J., Lee, B. S., and Li, Z.: Validation and calibration of Canada-wide coarse-resolution satellite burned area maps, Photogramm. Eng. Remote Sens., 70, 451–460, 2004.
Gaveau, D. L. A., Descals, A., Salim, M. A., Sheil, D., and Sloan, S.: Refined burned-area mapping protocol using Sentinel-2 data increases estimate of 2019 Indonesian burning, Earth Syst. Sci. Data, 13, 5353–5368, https://doi.org/10.5194/essd-13-5353-2021, 2021.
Giglio, L., van der Werf, G. R., Randerson, J. T., Collatz, G. J., and Kasibhatla, P.: Global estimation of burned area using MODIS active fire observations, Atmos. Chem. Phys., 6, 957–974, https://doi.org/10.5194/acp-6-957-2006, 2006.
Giglio, L., Schroeder, W., and Justice, C. O.: The collection 6 MODIS active fire detection algorithm and fire products, Remote Sens. Environ., 178, 31–41, 2016.
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, 2018.
Goodenough, D. G., Chen, H., Richardson, A., Cloude, S., Hong, W., and Li, Y.: Mapping fire scars using Radarsat-2 polarimetric SAR data, Can. J. Remote Sens., 37, 500–509, 2011.
Graham, L. L., Applegate, G. B., Thomas, A., Ryan, K. C., Saharjo, B. H., and Cochrane, M. A.: A Field Study of Tropical Peat Fire Behaviour and Associated Carbon Emissions, Fire, 5, 62, https://doi.org/10.3390/fire5030062, 2022.
Griffin, D., Sioris, C., Chen, J., Dickson, N., Kovachik, A., de Graaf, M., Nanda, S., Veefkind, P., Dammers, E., McLinden, C. A., Makar, P., and Akingunola, A.: The 2018 fire season in North America as seen by TROPOMI: aerosol layer height intercomparisons and evaluation of model-derived plume heights, Atmos. Meas. Tech., 13, 1427–1445, https://doi.org/10.5194/amt-13-1427-2020, 2020.
Griffin, D., Chen, J., Anderson, K., Makar, P., McLinden, C. A., Dammers, E., and Fogal, A.: Biomass burning CO emissions: exploring insights through TROPOMI-derived emissions and emission coefficients, Atmos. Chem. Phys., 24, 10159–10186, https://doi.org/10.5194/acp-24-10159-2024, 2024.
Guild, L. S., Kauffman, J. B., Ellingson, L. J., Cummings, D. L., Castro, E. A., Babbitt, R. E., and Ward, D. E.: Dynamics associated with total aboveground biomass, C, nutrient pools, and biomass burning of primary forest and pasture in Rondonia, Brazil during SCAR-B, J. Geophys. Res.-Atmos., 103, 32091–32100, 1998.
Hall, J. V., Zibtsev, S. V., Giglio, L., Skakun, S., Myroniuk, V., Zhuravel, O., Goldammer, J. G., and Kussul, N.: Environmental and political implications of underestimated cropland burning in Ukraine, Environ. Res. Lett., 16, 064019, https://doi.org/10.1088/1748-9326/abfc04, 2021.
Hall, J. V., Argueta, F., Zubkova, M., Chen, Y., Randerson, J. T., and Giglio, L.: GloCAB: global cropland burned area from mid-2002 to 2020, Earth Syst. Sci. Data, 16, 867–885, https://doi.org/10.5194/essd-16-867-2024, 2024.
Hatch, L. E., Yokelson, R. J., Stockwell, C. E., Veres, P. R., Simpson, I. J., Blake, D. R., Orlando, J. J., and Barsanti, K. C.: Multi-instrument comparison and compilation of non-methane organic gas emissions from biomass burning and implications for smoke-derived secondary organic aerosol precursors, Atmos. Chem. Phys., 17, 1471–1489, https://doi.org/10.5194/acp-17-1471-2017, 2017.
Hayden, K. L., Li, S.-M., Liggio, J., Wheeler, M. J., Wentzell, J. J. B., Leithead, A., Brickell, P., Mittermeier, R. L., Oldham, Z., Mihele, C. M., Staebler, R. M., Moussa, S. G., Darlington, A., Wolde, M., Thompson, D., Chen, J., Griffin, D., Eckert, E., Ditto, J. C., He, M., and Gentner, D. R.: Reconciling the total carbon budget for boreal forest wildfire emissions using airborne observations, Atmos. Chem. Phys., 22, 12493–12523, https://doi.org/10.5194/acp-22-12493-2022, 2022.
Hoffa, E. A., Ward, D. E., Hao, W. M., Susott, R. A., and Wakimoto, R. H.: Seasonality of carbon emissions from biomass burning in a Zambian savanna, J. Geophys. Res.-Atmos., 104, 13841–13853, 1999.
Hollis, J. J., Matthews, S., Ottmar, R. D., Prichard, S. J., Slijepcevic, A., Burrows, N. D., Ward, B., Tolhurst, K. G., Anderson, W. R., and Gould, J. S.: Testing woody fuel consumption models for application in Australian southern eucalypt forest fires, Forest Ecol. Manage., 260, 948–964, 2010.
Huang, M., Carmichael, G. R., Pierce, R. B., Jo, D. S., Park, R. J., Flemming, J., Emmons, L. K., Bowman, K. W., Henze, D. K., Davila, Y., Sudo, K., Jonson, J. E., Tronstad Lund, M., Janssens-Maenhout, G., Dentener, F. J., Keating, T. J., Oetjen, H., and Payne, V. H.: Impact of intercontinental pollution transport on North American ozone air pollution: an HTAP phase 2 multi-model study, Atmos. Chem. Phys., 17, 5721–5750, https://doi.org/10.5194/acp-17-5721-2017, 2017.
Huijnen, V., Wooster, M. J., Kaiser, J. W., Gaveau, D. L., Flemming, J., Parrington, M., Inness, A., Murdiyarso, D., Main, B., and van Weele, M.: Fire carbon emissions over maritime southeast Asia in 2015 largest since 1997, Sci. Rep., 6, 26886, https://doi.org/10.1038/srep26886, 2016.
Jolly, W. M., Nemani, R., and Running, S. W.: A generalized, bioclimatic index to predict foliar phenology in response to climate, Global Change Biol., 11, 619–632, 2005.
Kaiser, J. W. and van der Werf, G. R.: Biomass burning, in: State of the Climate in 2021, B. Am. Meteorol. Soc., 104, S105–S107, https://doi.org/10.1175/2023BAMSStateoftheClimate.1, 2023.
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.
Kaiser, J. W., van der Werf, G. R., and Heil, A.: Biomass burning, B. Am. Meteorol. Soc., Spec. Suppl. “State of the Climate in 2015”, 97, S60–S62, 2016.
Kauffman, J. B., Sanford Jr., R. L., Cummings, D. L., Salcedo, I. H., and Sampaio, E. V. S. B.: Biomass and nutrient dynamics associated with slash fires in neotropical dry forests, Ecology, 74, 140–151, 1993.
Kauffman, J. B., Cummings, D. L., and Ward, D. E.: Fire in the Brazilian Amazon 2. Biomass, nutrient pools and losses in cattle pastures, Oecologia, 113, 415–427, 1998.
Keeley, J. E. and Syphard, A. D.: Large California wildfires: 2020 fires in historical context, Fire Ecol., 17, 1–11, 2021.
Knorr, W., Lehsten, V., and Arneth, A.: Determinants and predictability of global wildfire emissions, Atmos. Chem. Phys., 12, 6845–6861, https://doi.org/10.5194/acp-12-6845-2012, 2012.
Kolden, C. A., Abatzoglou, J. T., Jones, M. W., and Jain, P.: Wildfires in 2023, Nat. Rev. Earth Environ., 5, 238–240, 2024.
Lal, R.: World crop residues production and implications of its use as a biofuel, Environ. Int., 31, 575–584, 2005.
Lee, B. S., Alexander, M. E., Hawkes, B. C., Lynham, T. J., Stocks, B. J., and Englefield, P.: Information systems in support of wildland fire management decision making in Canada, Comput. Electron. Agr., 37, 185–198, 2002.
Liu, Y., Huang, Y., Liggio, J., Hayden, K., Mihele, C., Wentzell, J., Wheeler, M., Leithead, A., Moussa, S., Xie, C., and Yang, Y.: A newly developed Lagrangian chemical transport scheme: Part 1. Simulation of a boreal forest fire plume, Sci. Total Environ., 880, 163232, https://doi.org/10.1016/j.scitotenv.2023.163232, 2023.
Makar, P. A., Akingunola, A., Chen, J., Pabla, B., Gong, W., Stroud, C., Sioris, C., Anderson, K., Cheung, P., Zhang, J., and Milbrandt, J.: Forest-fire aerosol–weather feedbacks over western North America using a high-resolution, online coupled air-quality model, Atmos. Chem. Phys., 21, 10557–10587, https://doi.org/10.5194/acp-21-10557-2021, 2021.
Matz, C. J., Egyed, M., Xi, G., Racine, J., Pavlovic, R., Rittmaster, R., Henderson, S. B., and Stieb, D. M.: Health impact analysis of PM2.5 from wildfire smoke in Canada (2013–2015, 2017–2018), Sci. Total Environ., 725, 138506, https://doi.org/10.1016/j.scitotenv.2020.138506, 2020.
McCarty, J. L., Korontzi, S., Justice, C. O., and Loboda, T.: The spatial and temporal distribution of crop residue burning in the contiguous United States, Sci. Total Environ., 407, 5701–5712, 2009.
McElhinny, M., Beckers, J. F., Hanes, C., Flannigan, M., and Jain, P.: A high-resolution reanalysis of global fire weather from 1979 to 2018 – overwintering the Drought Code, Earth Syst. Sci. Data, 12, 1823–1833, https://doi.org/10.5194/essd-12-1823-2020, 2020.
McPhaden, M. J.: The 2020–22 triple-dip La Niña, in: State of the Climate in 2021, B. Am. Meteorol. Soc., 104, S157–S158, https://doi.org/10.1175/2023BAMSStateoftheClimate.1, 2023.
McRae, D. J., Conard, S. G., Ivanova, G. A., Sukhinin, A. I., Baker, S. P., Samsonov, Y. N., Blake, T. W., Ivanov, V. A., Ivanov, A. V., Churkina, T. V., and Hao, W.: Variability of fire behavior, fire effects, and emissions in Scotch pine forests of Central Siberia, Mitigation and Adaptation Strategies for Global Change, 11, 45–74, 2006.
Mota, B. and Wooster, M. J.: A new top-down approach for directly estimating biomass burning emissions and fuel consumption rates and totals from geostationary satellite fire radiative power (FRP), Remote Sens. Environ., 206, 45–62, 2018.
Nguyen, H. M. and Wooster, M. J.: Advances in the estimation of high Spatio-temporal resolution pan-African top-down biomass burning emissions made using geostationary fire radiative power (FRP) and MAIAC aerosol optical depth (AOD) data, Remote Sens. Environ., 248, 111971, https://doi.org/10.1016/j.rse.2020.111971, 2020.
Oliveira, S. L., Maier, S. W., Pereira, J. M., and Russell-Smith, J.: Seasonal differences in fire activity and intensity in tropical savannas of northern Australia using satellite measurements of fire radiative power, Int. J. Wildland Fire, 24, 249–260, 2015.
Quintilio, D., Alexander, M. E., and Ponto, R. L.: Spring fires in a semimature trembling aspen stand in central Alberta (No. NOR-X-323), Forestry Canada-Northwest Region, 1991.
Page, S. E. and Hooijer, A.: In the line of fire: the peatlands of Southeast Asia, Philos. T. Roy. Soc. B, 371, 20150176, https://doi.org/10.1098/rstb.2015.0176, 2016.
Pan, X., Ichoku, C., Chin, M., Bian, H., Darmenov, A., Colarco, P., Ellison, L., Kucsera, T., da Silva, A., Wang, J., Oda, T., and Cui, G.: Six global biomass burning emission datasets: intercomparison and application in one global aerosol model, Atmos. Chem. Phys., 20, 969–994, https://doi.org/10.5194/acp-20-969-2020, 2020.
Pearce, H. G., Anderson, S. A. J., and Clifford, V. R.: A manual for predicting fire behaviour in New Zealand fuels, Scion Rural Fire Research Group, 2008.
Pereira, G., Longo, K. M., Freitas, S. R., Mataveli, G., Oliveira, V. J., Santos, P. R., Rodrigues, L. F., and Cardozo, F. S.: Improving the south America wildfires smoke estimates: Integration of polar-orbiting and geostationary satellite fire products in the Brazilian biomass burning emission model (3BEM), Atmos. Environ., 273, 118954, https://doi.org/10.1016/j.atmosenv.2022.118954, 2022.
Pettorelli, N.: The normalized difference vegetation index, Oxford University Press, USA, 2013.
Pouliot, G., Rao, V., McCarty, J. L., and Soja, A.: Development of the crop residue and rangeland burning in the 2014 National Emissions Inventory using information from multiple sources, J. Air Waste Manag. A., 67, 613–622, 2017.
Ramo, R., Roteta, E., Bistinas, I., Van Wees, D., Bastarrika, A., Chuvieco, E., and Van der Werf, G. R.: African burned area and fire carbon emissions are strongly impacted by small fires undetected by coarse resolution satellite data, P. Natl. Acad. Sci. USA, 118, e2011160118, https://doi.org/10.1073/pnas.2011160118, 2021.
Randerson, J. T., Chen, Y., Van Der Werf, G. R., Rogers, B. M., and Morton, D. C.: Global burned area and biomass burning emissions from small fires, J. Geophys. Res.-Biogeo., 117, G04012, https://doi.org/10.1029/2012JG002128, 2012.
Roberts, G. and Wooster, M. J.: Global impact of landscape fire emissions on surface level PM2.5 concentrations, air quality exposure and population mortality, Atmos. Environ., 252, 118210, https://doi.org/10.1016/j.atmosenv.2021.118210, 2021.
Schmidt, I. B. and Eloy, L.: Fire regime in the Brazilian Savanna: Recent changes, policy and management, Flora, 268, 151613, https://doi.org/10.1016/j.flora.2020.151613, 2020.
Seiler, W. and Crutzen, P. J.: Estimates of gross and net fluxes of carbon between the biosphere and the atmosphere from biomass burning, Clim. Change, 2, 207–247, 1980.
Shea, R. W., Shea, B. W., Kauffman, J. B., Ward, D. E., Haskins, C. I., and Scholes, M. C.: Fuel biomass and combustion factors associated with fires in savanna ecosystems of South Africa and Zambia, J. Geophys. Res.-Atmos., 101, 23551–23568, 1996.
Stocks, B. J.: Fire behavior in immature jack pine, Can. J. Forest Res., 17, 80–86, 1987a.
Stocks, B. J.: Fire potential in the spruce budworm-damaged forests of Ontario, The Forestry Chronicle, 63, 8–14, 1987b.
Stocks, B. J.: Fire behavior in mature jack pine, Can. J. Forest Res., 19, 783–790, 1989.
Stocks, B. J., Lynham, T. J., Lawson, B. D., Alexander, M. E., Wagner, C. V., McAlpine, R. S., and Dube, D. E.: Canadian forest fire danger rating system: an overview, The Forestry Chronicle, 65, 258–265, 1989.
Stocks, B. J., Alexander, M. E., Wotton, B. M., Stefner, C. N., Flannigan, M. D., Taylor, S. W., Lavoie, N., Mason, J. A., Hartley, G. R., Maffey, M. E., and Dalrymple, G. N.: Crown fire behaviour in a northern jack pine black spruce forest, Can. J. Forest Res., 34, 1548–1560, 2004.
Stockwell, C. E., Bela, M. M., Coggon, M. M., Gkatzelis, G. I., Wiggins, E., Gargulinski, E. M., Shingler, T., Fenn, M., Griffin, D., Holmes, C. D., and Ye, X.: Airborne emission rate measurements validate remote sensing observations and emission inventories of western US wildfires, Environ. Sci. Technol., 56, 7564–7577, 2022.
Streets, D. G., Yarber, K. F., Woo, J. H., and Carmichael, G. R.: Biomass burning in Asia: Annual and seasonal estimates and atmospheric emissions, Global Biogeochem. Cycles, 17, 1099, https://doi.org/10.1029/2003GB002040, 2003.
Sullivan, A. L., McCaw, W., Cruz, M. G., Matthews, S., and Ellis, P. F.: Fuel, Fire Weather and Fire Behaviour in Australian Ecosystems, in: Fire Regimes, Biodiversity and Ecosystems in a Changing World, edited by: Williams, R. J., Gill, A. M., and Bradstock, R. A., 51–79, CSIRO Publishing, 2012.
Swart, N. C., Cole, J. N. S., Kharin, V. V., Lazare, M., Scinocca, J. F., Gillett, N. P., Anstey, J., Arora, V., Christian, J. R., Hanna, S., Jiao, Y., Lee, W. G., Majaess, F., Saenko, O. A., Seiler, C., Seinen, C., Shao, A., Sigmond, M., Solheim, L., von Salzen, K., Yang, D., and Winter, B.: The Canadian Earth System Model version 5 (CanESM5.0.3), Geosci. Model Dev., 12, 4823–4873, https://doi.org/10.5194/gmd-12-4823-2019, 2019.
Taylor, S. W. and Alexander, M. E.: Science, technology, and human factors in fire danger rating: the Canadian experience, Int. J. Wildland Fire, 15, 121–135, 2006.
Thomas, S. C. and Martin, A. R.: Carbon content of tree tissues: a synthesis, Forests, 3, 332–352, 2012.
Thompson, D. K., Simpson, B. N., Whitman, E., Barber, Q. E., and Parisien, M. A.: Peatland hydrological dynamics as a driver of landscape connectivity and fire activity in the boreal plain of Canada, Forests, 10, 534, https://doi.org/10.3390/f10070534, 2019.
Tubiello, F. N., Salvatore, M., Cóndor Golec, R. D., Ferrara, A., Rossi, S., Biancalani, R., Federici, S., Jacobs, H., and Flammini, A.: Agriculture, Forestry and Other Land Use Emissions by Sources and Removals by Sinks, ESS Working Paper No. 2, FAO: Rome, Italy, 2014.
Turn, S. Q., Jenkins, B. M., Chow, J. C., Pritchett, L. C., Campbell, D., Cahill, T., and Whalen, S. A.: Elemental characterization of particulate matter emitted from biomass burning: Wind tunnel derived source profiles for herbaceous and wood fuels, J. Geophys. Res.-Atmos., 102, 3683–3699, 1997.
Urbanski, S.: Wildland fire emissions, carbon, and climate: Emission factors, Forest Ecol. Manage., 317, 51–60, 2014.
van der Werf, G. R., Randerson, J. T., Giglio, L., van Leeuwen, T. T., Chen, Y., Rogers, B. M., Mu, M., van Marle, M. J. E., Morton, D. C., Collatz, G. J., Yokelson, R. J., and Kasibhatla, P. S.: Global fire emissions estimates during 1997–2016, Earth Syst. Sci. Data, 9, 697–720, https://doi.org/10.5194/essd-9-697-2017, 2017.
van Leeuwen, T. T., van der Werf, G. R., Hoffmann, A. A., Detmers, R. G., Rücker, G., French, N. H. F., Archibald, S., Carvalho Jr., J. A., Cook, G. D., de Groot, W. J., Hély, C., Kasischke, E. S., Kloster, S., McCarty, J. L., Pettinari, M. L., Savadogo, P., Alvarado, E. C., Boschetti, L., Manuri, S., Meyer, C. P., Siegert, F., Trollope, L. A., and Trollope, W. S. W.: Biomass burning fuel consumption rates: a field measurement database, Biogeosciences, 11, 7305–7329, https://doi.org/10.5194/bg-11-7305-2014, 2014.
Van Wagner, C. E.: Development and structure of the Canadian forest fire weather index system, Can. For. Serv. Tech. Rep., No. 35, 1987.
van Wees, D., van der Werf, G. R., Randerson, J. T., Rogers, B. M., Chen, Y., Veraverbeke, S., Giglio, L., and Morton, D. C.: Global biomass burning fuel consumption and emissions at 500 m spatial resolution based on the Global Fire Emissions Database (GFED), Geosci. Model Dev., 15, 8411–8437, https://doi.org/10.5194/gmd-15-8411-2022, 2022.
Vaughan, G., Draude, A. P., Ricketts, H. M. A., Schultz, D. M., Adam, M., Sugier, J., and Wareing, D. P.: Transport of Canadian forest fire smoke over the UK as observed by lidar, Atmos. Chem. Phys., 18, 11375–11388, https://doi.org/10.5194/acp-18-11375-2018, 2018.
Vitolo, C., Di Giuseppe, F., Barnard, C., Coughlan, R., San-Miguel-Ayanz, J., Libertá, G., and Krzeminski, B.: ERA5-based global meteorological wildfire danger maps, Sci. Data, 7, 216, https://doi.org/10.1038/s41597-020-0554-z, 2020.
von Salzen, K., Scinocca, J. F., McFarlane, N. A., Li, J., Cole, J. N., Plummer, D., Verseghy, D., Reader, M. C., Ma, X., Lazare, M., and Solheim, L.: The Canadian Fourth Generation Atmospheric Global Climate Model (CanAM4). Part I: Representation of Physical Processes, Atmosphere-Ocean, 51, 104–125, https://doi.org/10.1080/07055900.2012.755610, 2013.
Ward, D. E., Susott, R., Kauffman, J. B., Babbitt, R. E., Cummings, D. L., Dias, B., Holben, B. N., Kaufman, Y. J., Rasmussen, R. A., and Setzer, A. W.: Smoke and fire characteristics for cerrado and deforestation burns in Brazil: BASE-B experiment, J. Geophys. Res.-Atmos., 97, 14601–14619, 1992.
Wentworth, G. R., Aklilu, Y. A., Landis, M. S., and Hsu, Y. M.: Impacts of a large boreal wildfire on ground level atmospheric concentrations of PAHs, VOCs and ozone, Atmos. Environ., 178, 19–30, 2018.
Wiedinmyer, C., Akagi, S. K., Yokelson, R. J., Emmons, L. K., Al-Saadi, J. A., Orlando, J. J., and Soja, A. J.: The Fire INventory from NCAR (FINN): a high resolution global model to estimate the emissions from open burning, Geosci. Model Dev., 4, 625–641, https://doi.org/10.5194/gmd-4-625-2011, 2011.
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.
Withey, K., Berenguer, E., Palmeira, A. F., Espírito-Santo, F. D., Lennox, G. D., Silva, C. V., Aragão, L. E., Ferreira, J., França, F., Malhi, Y., and Rossi, L. C.: Quantifying immediate carbon emissions from El Niño-mediated wildfires in humid tropical forests, Philos. T. Roy. Soc. B, 373, 20170312, https://doi.org/10.1098/rstb.2017.0312, 2018.
Wotton, B. M., Alexander, M. E., and Taylor, S. W.: Updates and revisions to the 1992 Canadian forest fire behavior prediction system, Great Lakes Forestry Centre, 2009.
Wu, Y., Peña, W., Gross, B., and Moshary, F.: Wildfire smoke transport and impact on air quality observed by a mullti-wavelength elastic-raman lidar and ceilometer in New York city, in: EPJ Web of Conferences, vol. 176, p. 05044, EDP Sciences, 2018.
Zhang, T., Wooster, M. J., De Jong, M. C., and Xu, W.: How well does the “small fire boost” methodology used within the GFED4. 1s fire emissions database represent the timing, location and magnitude of agricultural burning?, Remote Sens., 10, 823, https://doi.org/10.3390/rs10060823, 2018.
Short summary
The Global Forest Fire Emissions Prediction System (GFFEPS) is a model that predicts smoke and carbon emissions from wildland fires. The model calculates emissions from the ground up based on satellite-detected fires, modelled weather and fire characteristics. Unlike other global models, GFFEPS uses daily weather conditions to capture changing burning conditions on a day-to-day basis. GFFEPS produced lower carbon emissions due to the changing weather not captured by the other models.
The Global Forest Fire Emissions Prediction System (GFFEPS) is a model that predicts smoke and...
