Articles | Volume 22, issue 4
https://doi.org/10.5194/nhess-22-1335-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-22-1335-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
13 Apr 2022
Research article |
| 13 Apr 2022
| 13 Apr 2022
Forecasting the regional fire radiative power for regularly ignited vegetation fires
Tero M. Partanen
CORRESPONDING AUTHOR
Finnish Meteorological Institute, Erik Palménin aukio 1, 00560 Helsinki, Finland
Mikhail Sofiev
Finnish Meteorological Institute, Erik Palménin aukio 1, 00560 Helsinki, Finland
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Rostislav Kouznetsov, Mikhail Sofiev, Andreas Uppstu, and Risto Hänninen
EGUsphere, https://doi.org/10.5194/egusphere-2025-2364, https://doi.org/10.5194/egusphere-2025-2364, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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The paper addresses a two-order-of-magnitude discrepancy in measured deposition velocities of accumulation-mode aerosols from different methods. This uncertainty affects current atmospheric deposition models. By explicitly accounting for gas-particle transition, we could reproduce the observations. Resolving the discrepancy, reduces uncertainties in simulated concentrations and fallout.
Marc Guevara, Augustin Colette, Antoine Guion, Valentin Petiot, Mario Adani, Joaquim Arteta, Anna Benedictow, Robert Bergström, Andrea Bolignano, Paula Camps, Ana C. Carvalho, Jesper Heile Christensen, Florian Couvidat, Ilia D’Elia, Hugo Denier van der Gon, Gaël Descombes, John Douros, Hilde Fagerli, Yalda Fatahi, Elmar Friese, Lise Frohn, Michael Gauss, Camilla Geels, Risto Hänninen, Kaj Hansen, Oriol Jorba, Jacek W. Kaminski, Rostislav Kouznetsov, Richard Kranenburg, Jeroen Kuenen, Victor Lannuque, Frédérik Meleux, Agnes Nyíri, Yuliia Palamarchuk, Carlos Pérez García-Pando, Lennard Robertson, Felicita Russo, Arjo Segers, Mikhail Sofiev, Joanna Struzewska, Renske Timmermans, Andreas Uppstu, Alvaro Valdebenito, and Zhuyun Ye
EGUsphere, https://doi.org/10.5194/egusphere-2025-1287, https://doi.org/10.5194/egusphere-2025-1287, 2025
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Air quality models require hourly emissions to accurately represent dispersion and physico-chemical processes in the atmosphere. Since emission inventories are typically provided at the annual level, emissions are downscaled to a refined temporal resolution using temporal profiles. This study quantifies the impact of using new anthropogenic temporal profiles on the performance of an European air quality multi-model ensemble. Overall, the findings indicate an improvement of the modelling results.
Augustin Colette, Gaëlle Collin, François Besson, Etienne Blot, Vincent Guidard, Frederik Meleux, Adrien Royer, Valentin Petiot, Claire Miller, Oihana Fermond, Alizé Jeant, Mario Adani, Joaquim Arteta, Anna Benedictow, Robert Bergström, Dene Bowdalo, Jorgen Brandt, Gino Briganti, Ana C. Carvalho, Jesper Heile Christensen, Florian Couvidat, Ilia D’Elia, Massimo D’Isidoro, Hugo Denier van der Gon, Gaël Descombes, Enza Di Tomaso, John Douros, Jeronimo Escribano, Henk Eskes, Hilde Fagerli, Yalda Fatahi, Johannes Flemming, Elmar Friese, Lise Frohn, Michael Gauss, Camilla Geels, Guido Guarnieri, Marc Guevara, Antoine Guion, Jonathan Guth, Risto Hänninen, Kaj Hansen, Ulas Im, Ruud Janssen, Marine Jeoffrion, Mathieu Joly, Luke Jones, Oriol Jorba, Evgeni Kadantsev, Michael Kahnert, Jacek W. Kaminski, Rostislav Kouznetsov, Richard Kranenburg, Jeroen Kuenen, Anne Caroline Lange, Joachim Langner, Victor Lannuque, Francesca Macchia, Astrid Manders, Mihaela Mircea, Agnes Nyiri, Miriam Olid, Carlos Pérez García-Pando, Yuliia Palamarchuk, Antonio Piersanti, Blandine Raux, Miha Razinger, Lennard Robertson, Arjo Segers, Martijn Schaap, Pilvi Siljamo, David Simpson, Mikhail Sofiev, Anders Stangel, Joanna Struzewska, Carles Tena, Renske Timmermans, Thanos Tsikerdekis, Svetlana Tsyro, Svyatoslav Tyuryakov, Anthony Ung, Andreas Uppstu, Alvaro Valdebenito, Peter van Velthoven, Lina Vitali, Zhuyun Ye, Vincent-Henri Peuch, and Laurence Rouïl
EGUsphere, https://doi.org/10.5194/egusphere-2024-3744, https://doi.org/10.5194/egusphere-2024-3744, 2024
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The Copernicus Atmosphere Monitoring Service – Regional Production delivers daily forecasts, analyses, and reanalyses of air quality in Europe. The Service relies on a distributed modelling production by eleven leading European modelling teams following stringent requirements with an operational design which has no equivalent in the world. All the products are full, free, open and quality assured and disseminated with a high level of reliability.
Jorge E. Pachón, Mariel A. Opazo, Pablo Lichtig, Nicolas Huneeus, Idir Bouarar, Guy Brasseur, Cathy W. Y. Li, Johannes Flemming, Laurent Menut, Camilo Menares, Laura Gallardo, Michael Gauss, Mikhail Sofiev, Rostislav Kouznetsov, Julia Palamarchuk, Andreas Uppstu, Laura Dawidowski, Nestor Y. Rojas, María de Fátima Andrade, Mario E. Gavidia-Calderón, Alejandro H. Delgado Peralta, and Daniel Schuch
Geosci. Model Dev., 17, 7467–7512, https://doi.org/10.5194/gmd-17-7467-2024, https://doi.org/10.5194/gmd-17-7467-2024, 2024
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Latin America (LAC) has some of the most populated urban areas in the world, with high levels of air pollution. Air quality management in LAC has been traditionally focused on surveillance and building emission inventories. This study performed the first intercomparison and model evaluation in LAC, with interesting and insightful findings for the region. A multiscale modeling ensemble chain was assembled as a first step towards an air quality forecasting system.
Branko Sikoparija, Predrag Matavulj, Isidora Simovic, Predrag Radisic, Sanja Brdar, Vladan Minic, Danijela Tesendic, Evgeny Kadantsev, Julia Palamarchuk, and Mikhail Sofiev
Atmos. Meas. Tech., 17, 5051–5070, https://doi.org/10.5194/amt-17-5051-2024, https://doi.org/10.5194/amt-17-5051-2024, 2024
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We assess the suitability of a Rapid-E+ particle counter for use in pollen monitoring networks. The criterion was the ability of different devices to provide the same signal for the same pollen type, which would allow for unified reference libraries and recognition algorithms for Rapid-E+. We tested three devices and found notable differences between their fluorescence measurements. Each one showed potential for pollen identification, but the large variability between them needs to be addressed.
Rostislav Kouznetsov, Risto Hänninen, Andreas Uppstu, Evgeny Kadantsev, Yalda Fatahi, Marje Prank, Dmitrii Kouznetsov, Steffen Manfred Noe, Heikki Junninen, and Mikhail Sofiev
Atmos. Chem. Phys., 24, 4675–4691, https://doi.org/10.5194/acp-24-4675-2024, https://doi.org/10.5194/acp-24-4675-2024, 2024
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By relying solely on publicly available media reports, we were able to infer the temporal evolution and the injection height for the Nord Stream gas leaks in September 2022. The inventory specifies locations, vertical distributions, and temporal evolution of the methane sources. The inventory can be used to simulate the event with atmospheric transport models. The inventory is supplemented with a set of observational data tailored to evaluate the results of the simulated atmospheric dispersion.
Leena Kangas, Jaakko Kukkonen, Mari Kauhaniemi, Kari Riikonen, Mikhail Sofiev, Anu Kousa, Jarkko V. Niemi, and Ari Karppinen
Atmos. Chem. Phys., 24, 1489–1507, https://doi.org/10.5194/acp-24-1489-2024, https://doi.org/10.5194/acp-24-1489-2024, 2024
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Residential wood combustion is a major source of fine particulate matter. This study has evaluated the contribution of residential wood combustion to fine particle concentrations and its year-to-year and seasonal variation in te Helsinki metropolitan area. The average concentrations attributed to wood combustion in winter were up to 10- or 15-fold compared to summer. Wood combustion caused 12 % to 14 % of annual fine particle concentrations. In winter, the contribution ranged from 16 % to 21 %.
Risto Matias Hänninen, Rostislav Kouznetsov, and Mikhail Sofiev
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-3, https://doi.org/10.5194/gmd-2023-3, 2023
Preprint withdrawn
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Chemistry transport models describe the motion of particles and gases in atmosphere, containing chemistry equations that allow reaction between different species. The widely used carbon-bond chemistry schemes are originally written in a numerically problematic form that drives some concentrations to unphysical negative values. Here the chemistry equations are re-written in a form where this problem is absent, allowing an easier integration of the equations into any chemistry transport model.
Yunyao Li, Daniel Tong, Siqi Ma, Saulo R. Freitas, Ravan Ahmadov, Mikhail Sofiev, Xiaoyang Zhang, Shobha Kondragunta, Ralph Kahn, Youhua Tang, Barry Baker, Patrick Campbell, Rick Saylor, Georg Grell, and Fangjun Li
Atmos. Chem. Phys., 23, 3083–3101, https://doi.org/10.5194/acp-23-3083-2023, https://doi.org/10.5194/acp-23-3083-2023, 2023
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Plume height is important in wildfire smoke dispersion and affects air quality and human health. We assess the impact of plume height on wildfire smoke dispersion and the exceedances of the National Ambient Air Quality Standards. A higher plume height predicts lower pollution near the source region, but higher pollution in downwind regions, due to the faster spread of the smoke once ejected, affects pollution exceedance forecasts and the early warning of extreme air pollution events.
Svetlana Sofieva, Eija Asmi, Nina S. Atanasova, Aino E. Heikkinen, Emeline Vidal, Jonathan Duplissy, Martin Romantschuk, Rostislav Kouznetsov, Jaakko Kukkonen, Dennis H. Bamford, Antti-Pekka Hyvärinen, and Mikhail Sofiev
Atmos. Meas. Tech., 15, 6201–6219, https://doi.org/10.5194/amt-15-6201-2022, https://doi.org/10.5194/amt-15-6201-2022, 2022
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A new bubble-generating glass chamber design with an extensive set of aerosol production experiments is presented to re-evaluate bubble-bursting-mediated aerosol production as a function of water parameters: bubbling air flow, water salinity, and temperature. Our main findings suggest modest dependence of aerosol production on the water salinity and a strong dependence on temperature below ~ 10 °C.
Outi Meinander, Pavla Dagsson-Waldhauserova, Pavel Amosov, Elena Aseyeva, Cliff Atkins, Alexander Baklanov, Clarissa Baldo, Sarah L. Barr, Barbara Barzycka, Liane G. Benning, Bojan Cvetkovic, Polina Enchilik, Denis Frolov, Santiago Gassó, Konrad Kandler, Nikolay Kasimov, Jan Kavan, James King, Tatyana Koroleva, Viktoria Krupskaya, Markku Kulmala, Monika Kusiak, Hanna K. Lappalainen, Michał Laska, Jerome Lasne, Marek Lewandowski, Bartłomiej Luks, James B. McQuaid, Beatrice Moroni, Benjamin Murray, Ottmar Möhler, Adam Nawrot, Slobodan Nickovic, Norman T. O’Neill, Goran Pejanovic, Olga Popovicheva, Keyvan Ranjbar, Manolis Romanias, Olga Samonova, Alberto Sanchez-Marroquin, Kerstin Schepanski, Ivan Semenkov, Anna Sharapova, Elena Shevnina, Zongbo Shi, Mikhail Sofiev, Frédéric Thevenet, Throstur Thorsteinsson, Mikhail Timofeev, Nsikanabasi Silas Umo, Andreas Uppstu, Darya Urupina, György Varga, Tomasz Werner, Olafur Arnalds, and Ana Vukovic Vimic
Atmos. Chem. Phys., 22, 11889–11930, https://doi.org/10.5194/acp-22-11889-2022, https://doi.org/10.5194/acp-22-11889-2022, 2022
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High-latitude dust (HLD) is a short-lived climate forcer, air pollutant, and nutrient source. Our results suggest a northern HLD belt at 50–58° N in Eurasia and 50–55° N in Canada and at >60° N in Eurasia and >58° N in Canada. Our addition to the previously identified global dust belt (GDB) provides crucially needed information on the extent of active HLD sources with both direct and indirect impacts on climate and environment in remote regions, which are often poorly understood and predicted.
Viktoria F. Sofieva, Risto Hänninen, Mikhail Sofiev, Monika Szeląg, Hei Shing Lee, Johanna Tamminen, and Christian Retscher
Atmos. Meas. Tech., 15, 3193–3212, https://doi.org/10.5194/amt-15-3193-2022, https://doi.org/10.5194/amt-15-3193-2022, 2022
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We present tropospheric ozone column datasets that have been created using combinations of total ozone column from OMI and TROPOMI with stratospheric ozone column datasets from several available limb-viewing instruments (MLS, OSIRIS, MIPAS, SCIAMACHY, OMPS-LP, GOMOS). The main results are (i) several methodological developments, (ii) new tropospheric ozone column datasets from OMI and TROPOMI, and (iii) a new high-resolution dataset of ozone profiles from limb satellite instruments.
Karol Kuliński, Gregor Rehder, Eero Asmala, Alena Bartosova, Jacob Carstensen, Bo Gustafsson, Per O. J. Hall, Christoph Humborg, Tom Jilbert, Klaus Jürgens, H. E. Markus Meier, Bärbel Müller-Karulis, Michael Naumann, Jørgen E. Olesen, Oleg Savchuk, Andreas Schramm, Caroline P. Slomp, Mikhail Sofiev, Anna Sobek, Beata Szymczycha, and Emma Undeman
Earth Syst. Dynam., 13, 633–685, https://doi.org/10.5194/esd-13-633-2022, https://doi.org/10.5194/esd-13-633-2022, 2022
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The paper covers the aspects related to changes in carbon, nitrogen, and phosphorus (C, N, P) external loads; their transformations in the coastal zone; changes in organic matter production (eutrophication) and remineralization (oxygen availability); and the role of sediments in burial and turnover of C, N, and P. Furthermore, this paper also focuses on changes in the marine CO2 system, the structure of the microbial community, and the role of contaminants for biogeochemical processes.
Yalda Fatahi, Rostislav Kouznetsov, and Mikhail Sofiev
Geosci. Model Dev., 14, 7459–7475, https://doi.org/10.5194/gmd-14-7459-2021, https://doi.org/10.5194/gmd-14-7459-2021, 2021
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Incorporating information on public holidays into anthropogenic sector emissions results in substantial short-term improvement of the chemistry transport model SILAM scores. The largest impact was found for NOx, which is controlled by the changes in the traffic intensity. Certain improvements were also found for other species, but the signal was weaker than that for NOx.
Hugues Brenot, Nicolas Theys, Lieven Clarisse, Jeroen van Gent, Daniel R. Hurtmans, Sophie Vandenbussche, Nikolaos Papagiannopoulos, Lucia Mona, Timo Virtanen, Andreas Uppstu, Mikhail Sofiev, Luca Bugliaro, Margarita Vázquez-Navarro, Pascal Hedelt, Michelle Maree Parks, Sara Barsotti, Mauro Coltelli, William Moreland, Simona Scollo, Giuseppe Salerno, Delia Arnold-Arias, Marcus Hirtl, Tuomas Peltonen, Juhani Lahtinen, Klaus Sievers, Florian Lipok, Rolf Rüfenacht, Alexander Haefele, Maxime Hervo, Saskia Wagenaar, Wim Som de Cerff, Jos de Laat, Arnoud Apituley, Piet Stammes, Quentin Laffineur, Andy Delcloo, Robertson Lennart, Carl-Herbert Rokitansky, Arturo Vargas, Markus Kerschbaum, Christian Resch, Raimund Zopp, Matthieu Plu, Vincent-Henri Peuch, Michel Van Roozendael, and Gerhard Wotawa
Nat. Hazards Earth Syst. Sci., 21, 3367–3405, https://doi.org/10.5194/nhess-21-3367-2021, https://doi.org/10.5194/nhess-21-3367-2021, 2021
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The purpose of the EUNADICS-AV (European Natural Airborne Disaster Information and Coordination System for Aviation) prototype early warning system (EWS) is to develop the combined use of harmonised data products from satellite, ground-based and in situ instruments to produce alerts of airborne hazards (volcanic, dust, smoke and radionuclide clouds), satisfying the requirement of aviation air traffic management (ATM) stakeholders (https://cordis.europa.eu/project/id/723986).
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
Alexander, M.: Computer calculation of the Keetch-Byram Drought Index - programmers beware!, Fire Management Notes 51, 23–25, 1990. a
Bond, W. J. and Midgley, G. F.: Carbon dioxide and the uneasy interactions of trees and savannah grasses, Philos. T. Roy. Soc. B, 367, 601–612, https://doi.org/10.1098/rstb.2011.0182, 2012. a
Coughlan, R., Di Giuseppe, F., Vitolo, C., Barnard, C., Lopez, P., and Drusch, M.: Using machine learning to predict fire-ignition occurrences from lightning forecasts, Meteorol. Appl., 28, e1973, https://doi.org/10.1002/met.1973, 2021. a
Di Giuseppe, F., Rémy, S., Pappenberger, F., and Wetterhall, F.: Improving Forecasts of Biomass Burning Emissions with the Fire Weather Index, J. Appl. Meteorol. Clim., 56, 2789–2799, https://doi.org/10.1175/JAMC-D-16-0405.1, 2017. a
Di Giuseppe, F., Rémy, S., Pappenberger, F., and Wetterhall, F.: Using the Fire Weather Index (FWI) to improve the estimation of fire emissions from fire radiative power (FRP) observations, Atmos. Chem. Phys., 18, 5359–5370, https://doi.org/10.5194/acp-18-5359-2018, 2018. a
ECMWF: ERA5, ECMWF [data set], https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era5, last access: April 2022. a
EUMETSAT: EUMETSAT data centre, https://www.eumetsat.int/eumetsat-data-centre, last access: April 2022. a
Huang, H., Xue, Y., Liu, Y., Li, F., and Okin, G. S.: Modeling the short-term fire effects on vegetation dynamics and surface energy in southern Africa using the improved SSiB4/TRIFFID-Fire model, Geosci. Model Dev., 14, 7639–7657, https://doi.org/10.5194/gmd-14-7639-2021, 2021. a
Jacobson, M.: Strong radiative heating due to the mixing state of black carbon in atmospheric aerosols, 409, 695–697, https://doi.org/10.1038/35055518, 2001. a
Johnston, F. H., Henderson, S. B., Chen, Y., Randerson, J. T., Marlier, M., Defries, R. S., Kinney, P., Bowman, D. M., and Brauer, M.: Estimated global mortality attributable to smoke from landscape fires, Environ. Health Persp., 120, 695–701, https://doi.org/10.1289/ehp.1104422, 2012. a, b
Keetch, J. J. and Byram, G. M.: A Drought Index for Forest Fire Control, Asheville, NC, U.S. Department of Agriculture, Forest Service, Southeastern Forest Experiment Station, Research Paper SE-38, 35 pp., 1968. a
King, M. D., Platnick, S., Menzel, W. P., Ackerman, S. A., and Hubanks, P. A.: Spatial and Temporal Distribution of Clouds Observed by MODIS Onboard the Terra and Aqua Satellites, IEEE T. Geosci. Remote, 51, 3826–3852, https://doi.org/10.1109/TGRS.2012.2227333, 2013. a
Kollanus, V., Prank, M., Gens, A., Soares, J., Vira, J., Kukkonen, J., Sofiev, M., Salonen, R. O., and Lanki, T.: Mortality due to Vegetation Fire-Originated PM2.5 Exposure in Europe–Assessment for the Years 2005 and 2008, Environ. Health Persp., 125, 30–37, https://doi.org/10.1289/EHP194, 2017. a, b
Lasslop, G., Hantson, S., Harrison, S. P., Bachelet, D., Burton, C., Forkel, M., Forrest, M., Li, F., Melton, J. R., Yue, C., Archibald, S., Scheiter, S., Arneth, A., Hickler, T., and Sitch, S.: Global ecosystems and fire: Multi-model assessment of fire-induced tree-cover and carbon storage reduction, Global Change Biol., 26, 5027–5041, https://doi.org/10.1111/gcb.15160, 2020. a
Lelieveld, J., Evans, J. S., Fnais, M., Giannadaki, D., and Pozzer, A.: The contribution of outdoor air pollution sources to premature mortality on a global scale, Nature, 525, 367–371, https://doi.org/10.1038/nature15371, 2015. a
Levine, J. S., Bobbe, T., Ray, N., Singh, A., and Witt, R. G.: Wildland Fires and the Environment: a Global Synthesis, UNEP/DEIAEW/TR.99-1, United Nations Environment Programme (UNEP), Nairobi, Kenya, 1999. a
Li, F., Lawrence, D. M., and Bond-Lamberty, B.: Impact of fire on global land surface air temperature and energy budget for the 20th century due to changes within ecosystems, Environ. Res. Lett., 12, 044014, https://doi.org/10.1088/1748-9326/aa6685, 2017. a
Lindberg, H., Granström, A., Gromtsev, A., Levina, M., Shorohova, E., and Vanha-Majamaa, I.: The annually burnt forest area is relatively low in Fennoscandia, in: Climate change and forest management affect forest fire risk in Fennoscandia, edited by: Aalto, J. and Venäläinen, A., Finnish Meteorological Institute Reports 2021, 28–65, http://hdl.handle.net/10138/330898 (last access: April 2022), 2021. a
Lobert, J. M., Keene, W. C., Logan, J. A., and Yevich, R.: Global chlorine emissions from biomass burning: Reactive Chlorine Emissions Inventory, J. Geophys. Res.-Atmos., 104, 8373–8389, https://doi.org/10.1029/1998JD100077, 1999. a
McArthur, A.: Fire Behaviour in Eucalypt Forests, Department of National Development Forestry and Timber Bureau Leaflet 107, Canberra, Australia, 1967. a
Naeher, L. P., Brauer, M., Lipsett, M., Zelikoff, J. T., Simpson, C. D., Koenig, J. Q., and Smith, K. R.: Woodsmoke health effects: a review, Inhal. Toxicol., 19, 67–106, https://doi.org/10.1080/08958370600985875, 2007. a
Noble, I. R., Gill, A. M., and Bary, G. A. V.: McArthur's fire-danger meters expressed as equations, Aust. J. Ecol., 5, 201–203, https://doi.org/10.1111/j.1442-9993.1980.tb01243.x, 1980. a
Pechony, O. and Shindell, D. T.: Driving forces of global wildfires over the past millennium and the forthcoming century, 107, 19167–19170, https://doi.org/10.1073/pnas.1003669107, 2010. a
Pope III, C. A. and Dockery, D. W.: Health Effects of Fine Particulate Air Pollution: Lines that Connect, JAPCA J. Air Waste Ma., 56, 709–742, https://doi.org/10.1080/10473289.2006.10464485, 2006. a
Purton, C. M.: Equations for the McArthur Mark 4 grassland fire danger meter, Australia, Bureau of Meteorology, Meteorological note, 147, 1982. a
Roberts, G., Wooster, M. J., and Lagoudakis, E.: Annual and diurnal african biomass burning temporal dynamics, Biogeosciences, 6, 849–866, https://doi.org/10.5194/bg-6-849-2009, 2009. a
Roberts, G. J. and Wooster, M. J.: Fire Detection and Fire Characterization Over Africa Using Meteosat SEVIRI, IEEE T. Geosci. Remote, 46, 1200–1218, https://doi.org/10.1109/TGRS.2008.915751, 2008. a
Russell-Smith, J., Yates, C., Vernooij, R., Eames, T., van der Werf, G., Ribeiro, N., Edwards, A., Beatty, R., Lekoko, O., Mafoko, J., Monagle, C., and Johnston, S.: Opportunities and challenges for savanna burning emissions abatement in southern Africa, J. Environ. Manage., 288, 112414, https://doi.org/10.1016/j.jenvman.2021.112414, 2021. a
Seo, H. and Kim, Y.: Interactive impacts of fire and vegetation dynamics on global carbon and water budget using Community Land Model version 4.5, Geosci. Model Dev., 12, 457–472, https://doi.org/10.5194/gmd-12-457-2019, 2019. a
Sims, R., Gorsevski, V., and Anenberg, S.: Black Carbon Mitigation and the Role of the Global Environment Facility, A STAP Advisory Document, Global Environment Facility, Washington, DC, https://stapgef.org/sites/default/files/2020-02/Black-Carbon-Web-Single.pdf?null= (last access: April 2022), 2015. a
Soares, J., Sofiev, M., and Hakkarainen, J.: Uncertainties of wild-land fires emission in AQMEII phase 2 case study, Atmos. Environ., 115, 361–370, https://doi.org/10.1016/j.atmosenv.2015.01.068, 2015. a
Sofiev, M., Vankevich, R., Lotjonen, M., Prank, M., Petukhov, V., Ermakova, T., Koskinen, J., and Kukkonen, J.: An operational system for the assimilation of the satellite information on wild-land fires for the needs of air quality modelling and forecasting, Atmos. Chem. Phys., 9, 6833–6847, https://doi.org/10.5194/acp-9-6833-2009, 2009. a
Sofiev, M., Vankevich, R., Ermakova, T., and Hakkarainen, J.: Global mapping of maximum emission heights and resulting vertical profiles of wildfire emissions, Atmos. Chem. Phys., 13, 7039–7052, https://doi.org/10.5194/acp-13-7039-2013, 2013. a
Sofiev, M., Vira, J., Kouznetsov, R., Prank, M., Soares, J., and Genikhovich, E.: Construction of the SILAM Eulerian atmospheric dispersion model based on the advection algorithm of Michael Galperin, Geosci. Model Dev., 8, 3497–3522, https://doi.org/10.5194/gmd-8-3497-2015, 2015. a
Toll, V., Reis, K., Ots, R., Kaasik, M., Männik, A., Prank, M., and Sofiev, M.: SILAM and MACC reanalysis aerosol data used for simulating the aerosol direct radiative effect with the NWP model HARMONIE for summer 2010 wildfire case in Russia, Atmos. Environ., 121, 75–85, https://doi.org/10.1016/j.atmosenv.2015.06.007, 2015. a
Vajda, A., Venäläinen, A., Suomi, I., Junila, P., and Mäkelä, H. M.: Assessment of forest fire danger in a boreal forest environment: description and evaluation of the operational system applied in Finland, Meteorol. Appl., 21, 879–887, https://doi.org/10.1002/met.1425, 2014. a
van Wagner, C. E.: Development and structure of a Canadian forest fire weather index system, Canadian Forestry Service, Ottawa, Forestry Tech. Rep. 35, https://cfs.nrcan.gc.ca/publications?id=19927 (last access: April 2022), 1987. a
Vanha-Majamaa, I., Aalto, J., Lehtonen, I., Lindberg, H., Shorohova, E., and Venäläinen, A.: The occurrence of forest fires depends on characteristics of forest fuels, weather, and human activities, in: Climate change and forest management affect forest fire risk in Fennoscandia, edited by: Aalto, J. and Venäläinen, A., Finnish Meteorological Institute Reports 2021, 17–27, http://hdl.handle.net/10138/330898 (last access: April 2022), 2021. a
Venäläinen, A. and Heikinheimo, M.: The Finnish Forest Fire Index Calculation System, in: Early Warning Systems for Natural Disaster Reduction, edited by: Zschau, J. and Küppers, A., Springer, Berlin, 645–648, https://doi.org/10.1007/978-3-642-55903-7_88, 2003. a
WHO: Ambient (outdoor) air pollution, https://www.who.int/en/news-room/fact-sheets/detail/ambient-(outdoor)-air-quality-and-health (last access: 26 May 2021), 2018. a
Wooster, M. J., Roberts, G., Perry, G. L. W., and Kaufman, Y. J.: Retrieval of biomass combustion rates and totals from fire radiative power observations: FRP derivation and calibration relationships between biomass consumption and fire radiative energy release, J. Geophys. Res.-Atmos., 110, D24311, https://doi.org/10.1029/2005JD006318, 2005. a
Short summary
The presented method aims to forecast regional wildfire-emitted radiative power in a time-dependent manner several days in advance. The temporal fire radiative power can be converted to an emission production rate, which can be implemented in air quality forecasting simulations. It is shown that in areas with a high incidence of wildfires, the fire radiative power is quite predictable, but otherwise it is not.
The presented method aims to forecast regional wildfire-emitted radiative power in a...
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