干旱区生态环境知识资源中心(Arid): Historical (1700-2012) global multi-model estimates of the fire emissions from the Fire Modeling Intercomparison Project (FireMIP)

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DOI	10.5194/acp-19-12545-2019
	Historical (1700-2012) global multi-model estimates of the fire emissions from the Fire Modeling Intercomparison Project (FireMIP)
	Li, Fang 1; Martin, Maria Val 2; Andreae, Meinrat O.3,4; Arneth, Almut 5; Hantson, Stijn 5,6; Kaiser, Johannes W.3,7; Lasslop, Gitta 8; Yue, Chao 9,10; Bachelet, Dominique 11; Forrest, Matthew 8; Kluzek, Erik 12; Liu, Xiaohong 13; Mangeon, Stephane 14,24; Melton, Joe R.15; Ward, Daniel S.16; Darmenov, Anton 17; Hickler, Thomas 8,18; Ichoku, Charles 19; Magi, Brian, I 20; Sitch, Stephen 21; van der Werf, Guido R.22; Wiedinmyer, Christine 23; Rabin, Sam S.5
通讯作者	Li, Fang
来源期刊	ATMOSPHERIC CHEMISTRY AND PHYSICS
ISSN	1680-7316
EISSN	1680-7324
出版年	2019
卷号	19 期号:19 页码:12545-12567
英文摘要	Fire emissions are a critical component of carbon and nutrient cycles and strongly affect climate and air quality. Dynamic global vegetation models (DGVMs) with interactive fire modeling provide important estimates for long-term and large-scale changes in fire emissions. Here we present the first multi-model estimates of global gridded historical fire emissions for 1700-2012, including carbon and 33 species of trace gases and aerosols. The dataset is based on simulations of nine DGVMs with different state-of-the-art global fire models that participated in the Fire Modeling Intercomparison Project (FireMIP), using the same and standardized protocols and forcing data, and the most up-to-date fire emission factor table based on field and laboratory studies in various land cover types. We evaluate the simulations of present-day fire emissions by comparing them with satellite-based products. The evaluation results show that most DGVMs simulate present-day global fire emission totals within the range of satellite-based products. They can capture the high emissions over the tropical savannas and low emissions over the arid and sparsely vegetated regions, and the main features of seasonality. However, most models fail to simulate the interannual variability, partly due to a lack of modeling peat fires and tropical deforestation fires. Before the 1850s, all models show only a weak trend in global fire emissions, which is consistent with the multi-source merged historical reconstructions used as input data for CMIP6. On the other hand, the trends are quite different among DGVMs for the 20th century, with some models showing an increase and others a decrease in fire emissions, mainly as a result of the discrepancy in their simulated responses to human population density change and land use and land cover change (LULCC). Our study provides an important dataset for further development of regional and global multi-source merged historical reconstructions, analyses of the historical changes in fire emissions and their uncertainties, and quantification of the role of fire emissions in the Earth system. It also highlights the importance of accurately modeling the responses of fire emissions to LULCC and population density change in reducing uncertainties in historical reconstructions of fire emissions and providing more reliable future projections.
类型	Article
语种	英语
国家	Peoples R China ; England ; Germany ; Saudi Arabia ; USA ; France ; Canada ; Netherlands ; Australia
开放获取类型	Green Accepted, Green Published, gold
收录类别	SCI-E
WOS记录号	WOS:000489689500002
WOS关键词	BIOMASS BURNING EMISSIONS ; ENVIRONMENT SIMULATOR JULES ; TERRESTRIAL CARBON BALANCE ; LAND-USE ; SATELLITE-OBSERVATIONS ; TRACE GASES ; PART 1 ; AEROSOL EMISSIONS ; VEGETATION MODEL ; INTERANNUAL VARIABILITY
WOS类目	Environmental Sciences ; Meteorology & Atmospheric Sciences
WOS研究方向	Environmental Sciences & Ecology ; Meteorology & Atmospheric Sciences
来源机构	西北农林科技大学 ; 中国科学院大气物理研究所 ; Commonwealth Scientific and Industrial Research Organisation ; King Saud University
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/214485
作者单位	1.Chinese Acad Sci, Int Ctr Climate & Environm Sci, Inst Atmospher Phys, Beijing, Peoples R China; 2.Univ Sheffield, Leverhulme Ctr Climate Change Mitigat, Dept Anim & Plant Sci, Sheffield, S Yorkshire, England; 3.Max Planck Inst Chem, Biogeochem Dept, Mainz, Germany; 4.King Saud Univ, Dept Geol & Geophys, Riyadh, Saudi Arabia; 5.KIT, Inst Meteorol & Climate Res, Atmospher Environm Res, Garmisch Partenkirchen, Germany; 6.Univ Calif Irvine, Geospatial Data Solut Ctr, Irvine, CA USA; 7.Deutsch Wetterdienst, Offenbach, Germany; 8.Senckenberg Biodivers & Climate Res Inst BiK F, Senckenberganlage, Germany; 9.Northwest A&F Univ, State Key Lab Soil Eros & Dryland Farming Loess P, Yangling, Shanxi, Peoples R China; 10.Univ Paris Saclay, LSCE, IPSL, CEA,CNRS,UVSQ, Gif Sur Yvette, France; 11.Oregon State Univ, Biol & Ecol Engn, Corvallis, OR 97331 USA; 12.Natl Ctr Atmospher Res, POB 3000, Boulder, CO 80307 USA; 13.Univ Wyoming, Dept Atmospher Sci, Laramie, WY 82071 USA; 14.Imperial Coll London, Dept Phys, London, England; 15.Environm & Climate Change Canada, Climate Res Div, Victoria, BC, Canada; 16.Karen Clark & Co, Boston, MA USA; 17.NASA, Goddard Space Flight Ctr, Global Modeling & Assimilat Off, Greenbelt, MD USA; 18.Goethe Univ, Dept Phys Geog, Frankfurt, Germany; 19.Howard Univ, Dept Interdisciplinary Studies, Washington, DC 20059 USA; 20.Univ North Carolina Charlotte, Dept Geog & Earth Sci, Charlotte, NC USA; 21.Univ Exeter, Coll Life & Environm Sci, Exeter, Devon, England; 22.Vrije Univ, Fac Sci, Amsterdam, Netherlands; 23.Univ Colorado, Cooperat Inst Res Environm Sci, Boulder, CO 80309 USA; 24.CSIRO, Data61, Brisbane, Qld, Australia
推荐引用方式 GB/T 7714	Li, Fang,Martin, Maria Val,Andreae, Meinrat O.,et al. Historical (1700-2012) global multi-model estimates of the fire emissions from the Fire Modeling Intercomparison Project (FireMIP)[J]. 西北农林科技大学, 中国科学院大气物理研究所, Commonwealth Scientific and Industrial Research Organisation, King Saud University,2019,19(19):12545-12567.
APA	Li, Fang.,Martin, Maria Val.,Andreae, Meinrat O..,Arneth, Almut.,Hantson, Stijn.,...&Rabin, Sam S..(2019).Historical (1700-2012) global multi-model estimates of the fire emissions from the Fire Modeling Intercomparison Project (FireMIP).ATMOSPHERIC CHEMISTRY AND PHYSICS,19(19),12545-12567.
MLA	Li, Fang,et al."Historical (1700-2012) global multi-model estimates of the fire emissions from the Fire Modeling Intercomparison Project (FireMIP)".ATMOSPHERIC CHEMISTRY AND PHYSICS 19.19(2019):12545-12567.