Articles | Volume 23, issue 13
https://doi.org/10.5194/acp-23-7781-2023
© Author(s) 2023. 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-23-7781-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
14 Jul 2023
Research article |
| 14 Jul 2023
| 14 Jul 2023
Spatiotemporal variation characteristics of global fires and their emissions
State Key Joint Laboratory of Environmental Simulation and Pollution
Control, School of Environment, Beijing Normal University, Beijing, 100875,
China
Xingchuan Yang
College of Resource Environment and Tourism, Capital Normal
University, Beijing 100048, China
Laboratory for Climate and Ocean-Atmospheric Studies, Department of
Atmospheric and Oceanic Sciences, School of Physics, Peking University,
Beijing 100871, China
Yikun Yang
Laboratory for Climate and Ocean-Atmospheric Studies, Department of
Atmospheric and Oceanic Sciences, School of Physics, Peking University,
Beijing 100871, China
Zhenyao Shen
State Key Joint Laboratory of Environmental Simulation and Pollution
Control, School of Environment, Beijing Normal University, Beijing, 100875,
China
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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.
Albergel, C., Dutra, E., Munier, S., Calvet, J.-C., Munoz-Sabater, J., de Rosnay, P., and Balsamo, G.: ERA-5 and ERA-Interim driven ISBA land surface model simulations: which one performs better?, Hydrol. Earth Syst. Sci., 22, 3515–3532, https://doi.org/10.5194/hess-22-3515-2018, 2018.
Andela, N. and van der Werf, G.: Recent trends in African fires driven by
cropland expansion and El Niño to La Niña transition, Nat. Clim.
Change, 4, 791–795, https://doi.org/10.1038/nclimate2313, 2014.
Andela, N., Morton, D. C., Giglio, L., Chen, Y., van der Werf, G. R., Kasibhatla,
P. S., DeFries, R. S., Collatz, G. J., Hantson, S., Kloster, S., Bachelet, D.,
Forrest, M., Lasslop, G., Li, F., Mangeon, S., Melton, J. R., Yue, C., and
Randerson, J. T.: A human-driven decline in global burned area, Science, 356,
1356–1362, https://doi.org/10.1126/science.aal4108, 2017.
Archibald, S., Lehmann, C. E. R., Gómez-Dans, J. L., and Bradstock, R. A.:
Defining pyromes and global syndromes of fire regimes, P. Natl. Acad. Sci.
USA, 110, 6442–6447, https://doi.org/10.1073/pnas.1211466110, 2013.
Bian, H., Chin, M., Kawa, R., Duncan, B., Arellano Jr., A., and Kasibhatla,
R.: Uncertainty of global CO simulations constraint by biomass burning
emissions, J. Geophys. Res., 112,
D23308, https://doi.org/10.1029/2006JD008376, 2007.
Bian, Q., Jathar, S. H., Kodros, J. K., Barsanti, K. C., Hatch, L. E., May, A. A., Kreidenweis, S. M., and Pierce, J. R.: Secondary organic aerosol formation in biomass-burning plumes: theoretical analysis of lab studies and ambient plumes, Atmos. Chem. Phys., 17, 5459–5475, https://doi.org/10.5194/acp-17-5459-2017, 2017.
Bistinas, I., Harrison, S. P., Prentice, I. C., and Pereira, J. M. C.: Causal relationships versus emergent patterns in the global controls of fire frequency, Biogeosciences, 11, 5087–5101, https://doi.org/10.5194/bg-11-5087-2014, 2014.
Bowman, D., Williamson, G., Yebra, M., Lizundia-Loiola, J., Pettinari, M. L.,
Shah, S., Bradstock, R., and Chuvieco, E.: Wildfires: Australia needs national
monitoring agency, Nature, 584, 188–191,
https://doi.org/10.1038/d41586-020-02306-4, 2020.
Brandt, M., Rasmussen, K., Peñuelas, J., Tian, F., Schurgers, G.,
Verger, A., Mertz, O., Palmer, J. R. B., and Fensholt, R.: Human population growth
offsets climate-driven increase in woody vegetation in sub-Saharan Africa,
Nat. Ecol. Evol., 1, 0081, https://doi.org/10.1038/s41559-017-0081, 2017.
Burke, M., Driscoll, A., Heft-Neal, S., Xue, J., Burney, J., and Wara, M.:
The changing risk and burden of wildfire in the United States, P. Natl.
Acad. Sci. USA, 118, e2011048118, https://doi.org/10.1073/pnas.2011048118,
2021.
Cascio, W. E.: Wildland fire smoke and human health, Sci. Total Environ.,
624, 586–595, https://doi.org/10.1016/j.scitotenv.2017.12.086, 2018.
Chan, L. K., Nguyen, K. Q., Karim, N., Yang, Y., Rice, R. H., He, G., Denison, M. S., and Nguyen, T. B.: Relationship between the molecular composition, visible light absorption, and health-related properties of smoldering woodsmoke aerosols, Atmos. Chem. Phys., 20, 539–559, https://doi.org/10.5194/acp-20-539-2020, 2020.
Chen, J., Budisulistiorini, S. H., Miyakawa, T., Komazaki, Y., and Kuwata, M.: Secondary aerosol formation promotes water uptake by organic-rich wildfire haze particles in equatorial Asia, Atmos. Chem. Phys., 18, 7781–7798, https://doi.org/10.5194/acp-18-7781-2018, 2018.
Chen, S., Wu, R., Chen, W., Yao, S., and Yu, B.: Coherent interannual
variations of springtime surface temperature and temperature extremes
between central-northern Europe and Northeast Asia, J. Geophys. Res.-Atmos.,
125, e2019JD032226, https://doi.org/10.1029/2019JD032226, 2020.
Damoah, R., Spichtinger, N., Forster, C., James, P., Mattis, I., Wandinger, U., Beirle, S., Wagner, T., and Stohl, A.: Around the world in 17 days – hemispheric-scale transport of forest fire smoke from Russia in May 2003, Atmos. Chem. Phys., 4, 1311–1321, https://doi.org/10.5194/acp-4-1311-2004, 2004.
Ding, K., Huang, X., Ding, A. Wang, M., Su, H., Kerminen, V.-M.,
Petäjä, T., Tan, Z., Wang, Z., Zhou, D., Sun, J., Liao, H., Wang,
H., Carslaw, K., Wood, R., Zuidema, P., Rosenfeld, D., Kulmala, M., Fu, C.,
Pöschl, U., Cheng Y., and Andreae, M. O.: Aerosol-boundary-layer-monsoon
interactions amplify semi-direct effect of biomass smoke on low cloud
formation in Southeast Asia, Nat. Commun., 12, 6416,
https://doi.org/10.1038/s41467-021-26728-4, 2021.
Engelmann, R., Ansmann, A., Ohneiser, K., Griesche, H., Radenz, M., Hofer, J., Althausen, D., Dahlke, S., Maturilli, M., Veselovskii, I., Jimenez, C., Wiesen, R., Baars, H., Bühl, J., Gebauer, H., Haarig, M., Seifert, P., Wandinger, U., and Macke, A.: Wildfire smoke, Arctic haze, and aerosol effects on mixed-phase and cirrus clouds over the North Pole region during MOSAiC: an introduction, Atmos. Chem. Phys., 21, 13397–13423, https://doi.org/10.5194/acp-21-13397-2021, 2021.
Evangeliou, N., Shevchenko, V. P., Yttri, K. E., Eckhardt, S., Sollum, E., Pokrovsky, O. S., Kobelev, V. O., Korobov, V. B., Lobanov, A. A., Starodymova, D. P., Vorobiev, S. N., Thompson, R. L., and Stohl, A.: Origin of elemental carbon in snow from western Siberia and northwestern European Russia during winter–spring 2014, 2015 and 2016, Atmos. Chem. Phys., 18, 963–977, https://doi.org/10.5194/acp-18-963-2018, 2018.
Fan, H., Wang, Y., Zhao, C., Yang, Y., Yang, X., Sun, Y., and Jiang, S.: The
role of primary emission and transboundary trans-port in the air quality
changes during and after the COVID-19 lockdown in China, Geophys. Res.
Lett., 48, e2020GL091065, https://doi.org/10.1029/2020GL091065, 2021.
Fan, H.: Wildfire CODE AND DATA, Zenodo [code/data set], https://doi.org/10.5281/zenodo.7997467, 2023.
Feng, Y., Ziegler, A. D., Elsen, P. R. Liu, Y., He, X., Spracklen, D. V.,
Holden, J., Jiang, X., Zheng, C., and Zeng, Z.: Upward expansion and
acceleration of forest clearance in the mountains of Southeast Asia, Nat.
Sustain., 4, 892–899, https://doi.org/10.1038/s41893-021-00738-y, 2021.
Giglio, L., Loboda, T., Roy, D. P., Quayle, B., and Justice, C. O.: An
active-fire based burned area mapping algorithm for the MODIS sensor, Remote
Sens. Environ., 113, 408–420, https://doi.org/10.1016/j.rse.2008.10.006,
2009.
Giglio, L., Randerson, J. T., van der Werf, G. R., Kasibhatla, P. S., Collatz, G. J., Morton, D. C., and DeFries, R. S.: Assessing variability and long-term trends in burned area by merging multiple satellite fire products, Biogeosciences, 7, 1171–1186, https://doi.org/10.5194/bg-7-1171-2010, 2010.
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.
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,
https://doi.org/10.1016/j.rse.2016.02.054, 2016 (data available at: https://firms.modaps.eosdis.nasa.gov/download/, last access: 25 February 2022).
Giglio, L., Boschetti, L., Roy, D. P., Humber, M. L., and Justice, C. O.: The
Collection 6 MODIS burned area mapping algorithm and product, Remote Sens.
Environ., 217, 72–85, https://doi.org/10.1016/j.rse.2018.08.005, 2018 (data available at: https://modis-fire.umd.edu/ba.html, last access: 23 February 2022).
Govender, N., Trollope, W. S. W., and Van Wilgen, B. W.: The effect of fire
season, fire frequency, rainfall and management on fire intensity in savanna
vegetation in South Africa, J. Appl. Ecol., 43, 748–758,
https://doi.org/10.1111/j.1365-2664.2006.01184.x, 2006.
Grillakis, M., Voulgarakis, A., Rovithakis, A., Seiradakis, K. D.,
Koutroulis, A., Field, R. D., Kasoar, M., Papadopoulos, A., and Lazaridis,
M.: Climate drivers of global wildfire burned area, Environ. Res. Lett., 17,
045021, https://doi.org/10.1088/1748-9326/ac5fa1, 2022.
Gui, K., Che, H., Li, Lei, Zheng, Y., Zhang, L., Zhao, H., Zhong, J., Yao,
W., Liang, Y., Wang, Y., and Zhang, X.: The significant contribution of
small-sized and spherical aerosol particles to the decreasing trend in total
aerosol optical depth over land from 2003 to 2018, Engineering, 16, 82–92,
https://doi.org/10.1016/j.eng.2021.05.017, 2021.
Guo, J., Zhang, J., Yang, K., Liao, H., Zhang, S., Huang, K., Lv, Y., Shao, J., Yu, T., Tong, B., Li, J., Su, T., Yim, S. H. L., Stoffelen, A., Zhai, P., and Xu, X.: Investigation of near-global daytime boundary layer height using high-resolution radiosondes: first results and comparison with ERA5, MERRA-2, JRA-55, and NCEP-2 reanalyses, Atmos. Chem. Phys., 21, 17079–17097, https://doi.org/10.5194/acp-21-17079-2021, 2021.
Hao, W. M., Reeves, M. C., Baggett, L. S., Balkanski, Y., Ciais, P., Nordgren, B. L., Petkov, A., Corley, R. E., Mouillot, F., Urbanski, S. P., and Yue, C.: Wetter environment and increased grazing reduced the area burned in northern Eurasia from 2002 to 2016, Biogeosciences, 18, 2559–2572, https://doi.org/10.5194/bg-18-2559-2021, 2021.
Hennigan, C. J., Westervelt, D. M., Riipinen, I., Engelhart, G. J., Lee, T.,
Collett, J. L., Pandis, S. N., Adams, P. J., and Robinson, A. L.: New
particle formation and growth in biomass burning plumes: An important source
of cloud condensation nuclei, Geophys. Res. Lett., 39,
L09805, https://doi.org/10.1029/2012GL050930, 2012.
Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., and Thépaut, J.-N.: ERA5 monthly averaged data on single levels from 1979 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set], https://doi.org/10.24381/cds.f17050d7, 2019.
Hooghiem, J. J. D., Popa, M. E., Röckmann, T., Grooß, J.-U., Tritscher, I., Müller, R., Kivi, R., and Chen, H.: Wildfire smoke in the lower stratosphere identified by in situ CO observations, Atmos. Chem. Phys., 20, 13985–14003, https://doi.org/10.5194/acp-20-13985-2020, 2020.
Huang, X., Ding, K., Liu, J., Wang, Z., Tang, R., Xue, L., Wang, H., Zhang,
Q., Tan, Z., Fu, C., Davis, S. J., Andreae M. O., and Ding, A.: Smoke-weather
interaction affects extreme wildfires in diverse coastal regions, Science,
379, 457–461, https://doi.org/10.1126/science.add9843, 2023.
Huangfu, Y., Yuan, B., Wang, S., Wu, C., He, X., Qi, J., deGouw, J.,
Warneke, C., Gilman, J. B., Wistahler, A., Karl, T., Graus, M., Jobson, B.
T., and Shao, M.: Revisiting acetonitrile as tracer of biomass burning in
anthropogenic-influenced environments, Geophys. Res. Lett., 48,
e2020GL092322, https://doi.org/10.1029/2020GL092322, 2021.
Jaffe, D. A., Bertschi, I., Jaegle, L., Novelli, P., Reid, J. S., Tanimoto,
H., Vingarzan, R., and Westphal, D. L.: Long-range transport of Siberian
biomass burning emissions and impact on surface ozone in western North
America, Geophys. Res. Lett., 31,
L16106, https://doi.org/10.1029/2004GL020093, 2004.
Jolly, W., Cochrane, M., Freeborn, P. Holden, Z. A., Brown, T. J.,
Williamson G. J., and Bowman, D. M. J. S.: Climate-induced variations in
global wildfire danger from 1979 to 2013, Nat. Commun., 6, 7537,
https://doi.org/10.1038/ncomms8537, 2015.
Junghenn Noyes, K. T., Kahn, R. A., Limbacher, J. A., and Li, Z.: Canadian and Alaskan wildfire smoke particle properties, their evolution, and controlling factors, from satellite observations, Atmos. Chem. Phys., 22, 10267–10290, https://doi.org/10.5194/acp-22-10267-2022, 2022.
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 (data available at: https://atmosphere.copernicus.eu/global-fire-emissions, last access: 10 July 2023).
Kaulfus, A. S., Nair, U., Jaffe, D., Christopher, S. A., and Goodrick, S.:
Biomass burning smoke climatology of the United States: implications for
particulate matter air quality, Environ. Sci. Technol., 51,
11731–11741, https://doi.org/10.1021/acs.est.7b03292, 2017.
Kloss, C., Berthet, G., Sellitto, P., Ploeger, F., Bucci, S., Khaykin, S., Jégou, F., Taha, G., Thomason, L. W., Barret, B., Le Flochmoen, E., von Hobe, M., Bossolasco, A., Bègue, N., and Legras, B.: Transport of the 2017 Canadian wildfire plume to the tropics via the Asian monsoon circulation, Atmos. Chem. Phys., 19, 13547–13567, https://doi.org/10.5194/acp-19-13547-2019, 2019.
Konovalov, I. B., Golovushkin, N. A., Beekmann, M., and Andreae, M. O.: Insights into the aging of biomass burning aerosol from satellite observations and 3D atmospheric modeling: evolution of the aerosol optical properties in Siberian wildfire plumes, Atmos. Chem. Phys., 21, 357–392, https://doi.org/10.5194/acp-21-357-2021, 2021.
Kumar, A., Pierce, R. B., Ahmadov, R., Pereira, G., Freitas, S., Grell, G., Schmidt, C., Lenzen, A., Schwarz, J. P., Perring, A. E., Katich, J. M., Hair, J., Jimenez, J. L., Campuzano-Jost, P., and Guo, H.: Simulating wildfire emissions and plume rise using geostationary satellite fire radiative power measurements: a case study of the 2019 Williams Flats fire, Atmos. Chem. Phys., 22, 10195–10219, https://doi.org/10.5194/acp-22-10195-2022, 2022.
Lee, K. H., Kim, J. E., Kim, Y. J., Kim, J., and von Hoyningen-Huene, W.: Impact of
the smoke aerosol from Russian forest fires on the atmospheric environment
over Korea during May 2003, Atmos. Environ., 39, 85–99,
https://doi.org/10.1016/j.atmosenv.2004.09.032, 2005.
Li, Y., Tong, D. Q., Ngan, F., Cohen, M. D., Stein, A. F., Kondragunta, S.,
Zhang, X., Ichoku, C., Hyer, E. J., and Kahn, R. A.: Ensemble
PM2.5 forecasting during the 2018 camp fire event using the HYSPLIT
transport and dispersion model, J. Geophys. Res.-Atmos., 125,
e2020JD032768, https://doi.org/10.1029/2020JD032768, 2020.
Li, Y., Tong, D., Ma, S., Zhang, X., Kondragunta, S., Li, F., and Saylor,
R.: Dominance of wildfires impact on air quality exceedances during the 2020
record-breaking wildfire season in the United States, Geophys. Res.
Lett., 48, e2021GL094908, https://doi.org/10.1029/2021GL094908, 2021.
Liang, Y., Stamatis, C., Fortner, E. C., Wernis, R. A., Van Rooy, P., Majluf, F., Yacovitch, T. I., Daube, C., Herndon, S. C., Kreisberg, N. M., Barsanti, K. C., and Goldstein, A. H.: Emissions of organic compounds from western US wildfires and their near-fire transformations, Atmos. Chem. Phys., 22, 9877–9893, https://doi.org/10.5194/acp-22-9877-2022, 2022.
Liu, X., Huey, G., Yokelson, R. J., Selimovic, V., Simpson, I. J.,
Müller, M., Jimenez, J. L., Campuzano-Jost, P., Beyersdorf, A. J.,
Blake, D. R., Butterfield, Z., Choi, Y., Crounse, J. D., Day, D. A., Diskin,
G. S., Dubey, M. K., Fortner, E., Hanisco, T. F., Hu, W., King, L. E.,
Kleinman, L., Meinardi, S., Mikoviny, T., Onasch, T. B., Palm, B. B.,
Peischl, J., Pollack, I. B., Ryerson, T. B., Sachse, G. W., Sedlacek, A. J.,
Shilling, J. E., Springston, S., St. Clair, J. M., Tanner, D. J., Teng, A.
P., Wennberg, P. O., Wisthaler, A., and Wolfe, G. M.: Airborne measurements
of western U.S. wildfire emissions: Comparison with prescribed burning and
air quality implications, J. Geophys. Res.-Atmos., 122,
6108–6129, https://doi.org/10.1002/2016JD026315, 2017.
Liu, Y., Austin, E., Xiang, J., Gould, T., Larson, T., and Seto, E.: Health
impact assessment of the 2020 Washington State wildfire smoke episode:
Excess health burden attributable to increased PM2.5 exposures and potential
exposure reductions, GeoHealth, 5, e2020GH000359, https://doi.org/10.1029/2020GH000359, 2021.
Lizundia-Loiola, J., Otón, G., Ramo, R., and Chuvieco, E.: A spatio-temporal
active-fire clustering approach for global burned area mapping at 250 m from
MODIS data, Remote Sens. Environ., 236, 111493,
https://doi.org/10.1016/j.rse.2019.111493, 2020 (data available at: https://climate.esa.int/en/projects/fire/data/, last access: 12 February 2022).
Lu, X., Zhang, L., Yue, X., Zhang, J., Jaffe, D. A., Stohl, A., Zhao, Y., and Shao, J.: Wildfire influences on the variability and trend of summer surface ozone in the mountainous western United States, Atmos. Chem. Phys., 16, 14687–14702, https://doi.org/10.5194/acp-16-14687-2016, 2016.
Marlon, J. R., Bartlein, P. J., Daniau, A.-L., Harrison, S. P., Maezumi, S.
Y., Power, M. J., Tinner, W., and Vanniére, B.: Global biomass burning:
a synthesis and review of Holocene paleofifire records and their controls,
Quaternary Sci. Rev., 65, 5–25, https://doi.org/10.1016/j.quascirev.2012.11.029,
2013.
Ohneiser, K., Ansmann, A., Kaifler, B., Chudnovsky, A., Barja, B., Knopf, D. A., Kaifler, N., Baars, H., Seifert, P., Villanueva, D., Jimenez, C., Radenz, M., Engelmann, R., Veselovskii, I., and Zamorano, F.: Australian wildfire smoke in the stratosphere: the decay phase in 2020/2021 and impact on ozone depletion, Atmos. Chem. Phys., 22, 7417–7442, https://doi.org/10.5194/acp-22-7417-2022, 2022.
O’Neill, S. M., Diao, M., Raffuse, S., Al-Hamdan, M., Barik, M., Jia, Y., Reid, S., Zou, Y., Tong, D., West, J. J., Wilkins, J., Marsha, A., Freedman, F., Vargo, J., Larkin, N. K., Alvarado, E., and Loesche, P.: A multi-analysis approach for estimating regional health
impacts from the 2017 Northern California wildfires, JAPCA J. Air Waste Ma., 71, 791–814, https://doi.org/10.1080/10962247.2021.1891994, 2021.
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.
Permar, W., Wang, Q., Selimovic, V., Wielgasz, C., Yokelson, R. J.,
Hornbrook, R. S., Hills, A. J., Apel, E. C., Ku, I. T., Zhou, Y., Sive, B.
C., Sullivan, A. P., Collett, J. L., Campos, T. L., Palm, B. B., Peng, Q.,
Thornton, J. A., Garofalo, L. A., Farmer, D. K., Kreidenweis, S. M., Levin,
E. J. T., DeMott, P. J., Flocke, F., Fischer, E. V., and Hu, L.: Emissions
of Trace Organic Gases From Western U.S. Wildfires Based on WE-CAN Aircraft
Measurements, J. Geophys. Res.-Atmos., 126,
1–29, https://doi.org/10.1029/2020JD033838, 2021.
Rantanen, M., Karpechko, A.Y., Lipponen, A., Nordling, K., Hyvärinen,
O., Ruosteenoja, K., Vihma, T., and Laaksonen, A.: The Arctic has warmed
nearly four times faster than the globe since 1979, Commun. Earth Environ., 3,
168, https://doi.org/10.1038/s43247-022-00498-3, 2022.
Reid, C. E., Brauer, M., Johnston, F. H., Jerrett, M., Balmes, J. R., and Elliott,
C. T.: Critical review of health impacts of wildfire smoke exposure, Environ.
Health Persp., 124, 1334–1343, https://doi.org/10.1289/ehp.1409277,
2016.
Requia, W. J., Amini, H., Mukherjee, R., Gold, D. R., and Schwartz, J. D.: Health
impacts of wildfire-related air pollution in Brazil: a nationwide study of
more than 2 million hospital admissions between 2008 and 2018, Nat.
Commun., 12, 6555, https://doi.org/10.1038/s41467-021-26822-7, 2021.
Senande-Rivera, M., Insua-Costa, D., and Miguez-Macho, G.: Spatial and
temporal expansion of global wildland fire activity in response to climate
change, Nat. Commun., 13, 1208, https://doi.org/10.1038/s41467-022-28835-2,
2022.
Spracklen, D. V., Reddington, C. L., and Gaveau, D. L. A.: Industrial
concessions, fires and air pollution in Equatorial Asia, Environ. Res.
Lett., 10, 091001, https://doi.org/10.1088/1748-9326/10/9/091001, 2015.
Tian, C., Yue, X., Zhu, J., Liao, H., Yang, Y., Lei, Y., Zhou, X., Zhou, H., Ma, Y., and Cao, Y.: Fire–climate interactions through the aerosol radiative effect in a global chemistry–climate–vegetation model, Atmos. Chem. Phys., 22, 12353–12366, https://doi.org/10.5194/acp-22-12353-2022, 2022.
Turetsky, M. R., Benscoter, B., Page, S., Rein, G., Van Der Werf, G. R., and
Watts, A.: Global vulnerability of peatlands to fire and carbon loss, Nat.
Geosci., 8, 11–14, https://doi.org/10.1038/ngeo2325, 2015.
van der Werf, G. R., Randerson, J. T., Giglio, L., Collatz, G. J., Kasibhatla, P. S., and Arellano Jr., A. F.: Interannual variability in global biomass burning emissions from 1997 to 2004, Atmos. Chem. Phys., 6, 3423–3441, https://doi.org/10.5194/acp-6-3423-2006, 2006.
van der Werf, G. R., Randerson, J. T., Giglio, L., Collatz, G. J., Mu, M., Kasibhatla, P. S., Morton, D. C., DeFries, R. S., Jin, Y., and van Leeuwen, T. T.: Global fire emissions and the contribution of deforestation, savanna, forest, agricultural, and peat fires (1997–2009), Atmos. Chem. Phys., 10, 11707–11735, https://doi.org/10.5194/acp-10-11707-2010, 2010.
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.
Wang, J. F., Li, X. H., Christakos, G., Liao, Y. L., Zhang, T., Gu, X., and
Zheng, X. Y.: Geographical detectors-based health risk assessment and its
application in the neural tube defects study of the Heshun region, China,
Int. J. Geogr. Inf. Sci., 24, 107–127,
https://doi.org/10.1080/13658810802443457, 2010.
Wang, J. F., Zhang, T. L., and Fu, B. J.: A measure of spatial stratified
heterogeneit, Ecol. Indic., 67, 250–256,
https://doi.org/10.1016/j.ecolind.2016.02.052, 2016.
Wu, C., Venevsky, S., Sitch, S., Mercado, L. M., Huntingford, C., and
Staver, A. C.: Historical and future global burned area with changing
climate and human demography, One Earth, 4, 517–530,
https://doi.org/10.1016/j.oneear.2021.03.002, 2021.
Wu, C., Sitch, S., Huntingford, C., Mercado, L. M., Venevsky, S., Lasslop,
G., Archibald, S., and Staver, A. C.: Reduced global fire activity due to
human demography slows global warming by enhanced land carbon uptake, P.
Natl. Acad. Sci. USA, 119, e2101186119,
https://doi.org/10.1073/pnas.2101186119, 2022.
Xu, Q., Westerling, A. L., and Baldwin, W. J.: Spatial and temporal patterns
of wildfire burn severity and biomass burning-induced emissions in
California, Environ. Res. Lett., 17, 115001,
https://doi.org/10.1088/1748-9326/ac9704, 2022.
Xue, Z., Gupta, P., and Christopher, S.: Satellite-based estimation of the impacts of summertime wildfires on PM2.5 concentration in the United States, Atmos. Chem. Phys., 21, 11243–11256, https://doi.org/10.5194/acp-21-11243-2021, 2021.
Yang, X., Zhao, C., Yang, Y., Yan, X., and Fan, H.: Statistical aerosol properties associated with fire events from 2002 to 2019 and a case analysis in 2019 over Australia, Atmos. Chem. Phys., 21, 3833–3853, https://doi.org/10.5194/acp-21-3833-2021, 2021.
Yu, P., Davis, S. M., Toon, O. B., Portmann, R. W., Bardeen, C. G., Barnes,
J. E., Telg, H., Maloney, C., and Rosenlof, K. H.: Persistent stratospheric
warming due to 2019–2020 Australian wildfire smoke, Geophys. Res. Lett.,
48, e2021GL092609, https://doi.org/10.1029/2021GL092609, 2021.
Yu, Y. and Ginoux, P.: Enhanced dust emission following large wildfires due
to vegetation disturbance, Nat. Geosci., 15, 878–884,
https://doi.org/10.1038/s41561-022-01046-6, 2022.
Yue, C., Ciais, P., Bastos, A., Chevallier, F., Yin, Y., Rödenbeck, C., and Park, T.: Vegetation greenness and land carbon-flux anomalies associated with climate variations: a focus on the year 2015, Atmos. Chem. Phys., 17, 13903–13919, https://doi.org/10.5194/acp-17-13903-2017, 2017.
Zhang, A., Liu, Y., Goodrick, S., and Williams, M. D.: Duff burning from wildfires in a moist region: different impacts on PM2.5 and ozone, Atmos. Chem. Phys., 22, 597–624, https://doi.org/10.5194/acp-22-597-2022, 2022.
Zhang, H., Yee, L. D., Lee, B. H., Curtis, M. P., Worton, D. R.,
Isaacman-VanWertz, G., Offenberg, J. H., Lewandowski, M., Kleindienst, T.
E., Beaver, M. R., Holder, A. L., Lonneman, W. A., Docherty, K. S., Jaoui,
M., Pye, H. O. T., Hu, W., Day, D. A., Campuzano-Jost, P., Jimenez, J. L.,
Guo, H., Weber, R. J., de Gouw, J., Koss, A. R., Edgerton, E. S., Brune, W.,
Mohr, C., Lopez-Hilfiker, F. D., Lutz, A., Kreisberg, N. M., Spielman, S.
R., Hering, S. V., Wilson, K. R., Thornton, J. A., and Goldstein, A. H.:
Monoterpenes are the largest source of summertime organic aerosol in the
southeastern United States, P. Natl. Acad. Sci. USA, 115,
2038–2043, https://doi.org/10.1073/pnas.1717513115, 2018.
Zhang, L., Wang, T., Zhang, Q., Zheng, J., Xu, Z., and Lv, M.: Potential
sources of nitrous acid (HONO) and their impacts on ozone: A WRF-Chem study
in a polluted subtropical region, J. Geophys. Res.-Atmos., 121,
3645–3662, https://doi.org/10.1002/2015JD024468, 2016.
Zhang, L., Liu, W., Hou, K., Lin, J., Song, C., Zhou, C., Huang, B., Tong,
X., Wang, J., Rhine, W., Jiao, Y., Wang, Z., Ni, R., Liu, M., Zhang, L.,
Wang, Z., Wang, Y., Li, X., Liu, S., and Wang, Y.: Air pollution exposure
associates with increased risk of neonatal jaundice, Nat. Commun., 10, 3741,
https://doi.org/10.1038/s41467-019-11387-3, 2019.
Zhang, Y., Piao, S., Sun, Y., Rogers, B. M., Li, X., Lian, X., Liu, Z.,
Chen, A., and Peñuelas, J.: Future reversal of warming-enhanced vegetation
productivity in the Northern Hemisphere, Nat. Clim. Change, 12, 581–586,
https://doi.org/10.1038/s41558-022-01374-w, 2022.
Zheng, B., Ciais, P., Chevallier, F., Chuvieco, E., Chen, Y., and Yang, H.:
Increasing forest fire emissions despite the decline in global burned area,
Sci. Adv., 7, eabh2646, https://doi.org/10.1126/sciadv.abh2646,
2021.
Zhu, X., Xu, X., and Jia, G.: Asymmetrical trends of burned area between
eastern and western Siberia regulated by atmospheric oscillation, Geophys.
Res. Lett., 48, e2021GL096095, https://doi.org/10.1029/2021GL096095, 2021.
Zhuang, Y., Fu, R., Santer, B. D., Dickinson, R. E., and Hall, A.:
Quantifying contributions of natural variability and anthropogenic forcings
on increased fire weather risk over the western United States, P. Natl.
Acad. Sci. USA, 118, e2111875118, https://doi.org/10.1073/pnas.2111875118,
2021.
Short summary
Using 20-year multi-source data, this study shows pronounced regional and seasonal variations in fire activities and emissions. Seasonal variability of fires is larger with increasing latitude. The increase in temperature in the Northern Hemisphere's middle- and high-latitude forest regions was primarily responsible for the increase in fires and emissions, while the changes in fire occurrence in tropical regions were more influenced by the decrease in precipitation and relative humidity.
Using 20-year multi-source data, this study shows pronounced regional and seasonal variations in...
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