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Simulation of Distributions andRadiative Impacts of Biomass-burning Aerosols
Toshihiko TAKEMURA
Research Institute for Applied Mechanics, Kyushu University,
6-1 Kasuga-koen, Kasuga, Fukuoka 816-8580, Japane-mail: toshi@riam.kyushu-u.ac.jp

Abstract
Distributions and climate impacts of biomass-burning aerosols were simulated by a global aerosol climate model, SPRINTARS, which was fully coupled to a general circulation model. The model included
calculations of the direct, semi-direct and indirect effects of aerosols. Seasonal variations of mass concentrations of the main biomass-burning aerosols in the atmosphere, i.e., black carbon, organic matter and sulfate,
were simulated well around burned regions. The global annual mean radiative forcing by biomass-burning
aerosols was thereby calculated to be – 0.07 W m-2 at the top of the atmosphere (TOA) and – 0.23 W m-2 at thesurface through the direct effects. The results indicate that aerosols have sufficient effects to change regional
climates through strong, negative direct radiative forcing over biomass-burning regions. The global mean
radiative forcing of the indirect effects due to biomass-burning aerosols is estimated to be nearly 0 W m-2.
This implies cancellation between the cooling effect of reducing cloud droplet size and warming effect ofpromoting conversion from supercooled water to ice crystals. A weekly aerosol forecasting system withSPRINTARS <http://sprintars.net/forecastj.html> includes information on daily aerosol emissions frombiomass burning retrieved from MODIS hotspot data.
Key words: aerosol, biomass burning, climate change, climate model, radiative forcing

1. Introduction
Aerosol particles, suspended particle matter in theatmosphere, may have not only a harmful influence onhuman health, e.g., respiratory and allergic diseases, butalso may lead to climate change through several processes. One such process is a direct effect in whichaerosols scatter and absorb solar and thermal radiation.
Another is an indirect effect in which they alter cloud
albedo through changes in the particle size and lifetimesof cloud droplets and ice crystals acting as cloud condensation nuclei and ice nuclei, respectively. Semi-direct
effects are secondary effects to the direct ones in whichaerosols, e.g., black carbon (BC) and mineral dust,absorb light. The Fourth Assessment Report (AR4) of theIntergovernmental Panel on Climate Change (IPCC)(Intergovernmental Panel on Climate Change, 2007)
concluded by assessing past refereed papers that theglobal annual mean radiative forcings due to anthropogenic aerosols were –0.5 W m-2 for the direct effects and–0.7 W m-2 for the indirect effects. There were, however,still large uncertainties in the evaluations of these radiative forcings from –0.1 to –0.9 W m-2 for the direct
effects and from –0.3 to –1.8 W m-2 for the indirect
effects. Therefore we need to make more efforts at
Global Environmental Research
15/2011: 77-81
printed in Japan

reducing these uncertainties through observational andmodeling studies to achieve more reliable evaluations ofpast, present, and future climate change.
Biomass burning is one of the main emission sourcesof black carbon (BC) and organic matter (OM) aerosols.
It is estimated that about 40% of global total BC emissions are from biomass burning (Bond et al., 2004). Theyoccur as a result of both natural (e.g., lightning) andanthropogenic causes (e.g., slash-and-burn farming, development of plantations, and burning of agricultural
wastes). In this study, the distributions and climaticeffects of biomass-burning aerosols were simulated by aglobal aerosol climate model, SPRINTARS (Spectral
Radiation-Transport Model for Aerosol Species).

2. Model Description
SPRINTARS was coupled to an atmosphere-ocean
general circulation model (GCM), MIROC (Model forInterdisciplinary Research on Climate), developed by theAtmosphere and Ocean Research Institute (AORI) /University of Tokyo, National Institute for Environmental Studies (NIES), and Japan Agency for MarineEarth Science and Technology (JAMSTEC) (K-1 ModelDevelopers, 2004). The horizontal resolution was T106
©2011 AIRIES

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T. TAKEMURA(approximately 1.1◦ by 1.1◦ in latitude and longitude) andthe vertical resolution was 56 layers. The maximum of
the time step was 8 min, which became shorter whenatmospheric conditions were unstable. MIROC was used
as an atmospheric GCM in this study, and the monthly
mean sea surface temperature and sea ice data were thoseprescribed by the Hadley Centre Sea Ice and Sea SurfaceTemperature data set (HadISST) (Rayner et al., 2003).
The present study used the National Centers forEnvironmental Prediction (NECP)/National Center for
Atmospheric Research (NCAR) reanalysis data produced
every six hours for nudging the temperature andhorizontal wind (Kalnay et al., 1996).
SPRINTARS includes the transport (emission,advection, diffusion, sulfur chemistry, wet deposition,
dry deposition and gravitational settling), radiation,
cloud, and precipitation processes of all main tropospheric aerosols (BC, OM, sulfate, soil dust and sea salt).
The radiation scheme in MIROC adopting the twostream discrete ordinate and adding method (Nakajimaet al., 2000) includes calculation of the aerosol directeffect. The scattering and absorption coefficients depending on the wavelength, size distributions andhygroscopic growth are considered for each type ofaerosol. The refractive indices of dry aerosols areaccording to Deepak and Gerber (1983). The model treats
not only the aerosol mass mixing ratios but also the cloud
droplet and ice crystal number concentrations as

prognostic variables, and the nucleation processes ofcloud droplets and ice crystals depend on the number
concentrations of each aerosol type. Changes in the cloud
droplet and ice crystal number concentrations affect thecloud radiation and precipitation processes in the model,
which is the aerosol indirect effect. Takemura et al. (2000,2002, 2005, 2009) give details on SPRINTARS.
The global distributions of BC, organic carbon (OC),i.e., the mass of carbon atoms in OM, and SO2 emissions
that are a precursor of sulfate aerosol from biomassburning in this study are delineated by the monthly meandata of the Global Fire Emissions Database version 2(GFEDv2) which are retrieved from hotspot dataobtained by the space-borne sensor MODIS (ModerateResolution Imaging Spectrometer) (Randerson et al.,2005). The global total emissions of BC, OC and SO2 in2006 were estimated to be 2.58, 21.4, and 4.09 Tg/year,
respectively. The distributions and climate effects ofbiomass burning aerosols in this study were analyzed
through differences between a standard simulation and
one excluding aerosol emissions from biomass burning in
2006.

3. Results and Discussion
Figure 1 shows the simulated seasonal mean distributions of OM mass column loading from biomassburning. The concentrations are high in central Africa(a) BB OM Mass column loading (DEC, JAN, FEB)(b) BB OM Mass column loading (MAR, APR, MAY)

(c) BB OM Mass column loading (JUN, JUL, AUG)(d) BB OM Mass column loading (SEP, OCT, NOV)

Fig. 1 Seasonal mean distribution of OM from biomass burning (a) from December to February, (b) from March toMay, (c) from June to August, and (d) from September to November, simulated by SPRINTARS.

Simulation of Distributions and Radiative Impacts of Biomass-burning Aerosols(December to February), southern Africa (July toSeptember), Central America (April to May), SouthAmerica (August to October), Siberia (May to August)and southern Australia (November to December). In
Southeast Asia, biomass-burning aerosols are emitted on
the Indochina Peninsula from January to April and inSumatra and Kalimantan Islands from July to December.
Biomass burning on the Indochina Peninsula, around
Thailand, is caused mainly by controlled traditionalslash-and-burn farming, so the amount of emitted aerosols is stable every year. On the other hand, most of thebiomass burnings in Sumatra and Kalimantan Islands areuncontrolled, and expand especially under El Niño
conditions. Figure 1 shows remarkable biomass-burning
aerosols around Sumatra and Kalimantan Islands becauseof the El Niño from the summer of 2006 to the spring of2007. Simulated distributions of BC and sulfate aerosols
originating from biomass burning are similar to that ofOM (not shown). SO2 emissions due to biomass burningfrom tropical Southeast Asia are larger than those fromthe savannas, because sulfur-rich peat bog is burned(Nichol, 1997). The simulated aerosol optical thickness
was confirmed to be in reasonable agreement withobservations, e.g., ground-based remote sensing
observations, AERONET (Aerosol Robotic Network)(Takemura et al., 2002; AeroCom (Aerosol Model Inter(a) BB aerosol direct radiative forcing (DEC, JAN, FEB) (TOA, all-sky)79

comparison Project).
Sulfate and OM scatter solar radiation because of
their white or colorless particles, therefore their direct
radiative forcing at the top of the atmosphere (TOA) isnegative. On the other hand, BC strongly absorbs solar
radiation and thus has a positive direct radiative forcing
at TOA. Figure 2 shows the seasonal mean direct radiative forcing at TOA due to biomass-burning aerosols. The
strong negative forcing primarily corresponds to the highaerosol concentrations shown in Fig. 1, which are over
–1 W m-2 in burned regions in their burning seasons. The
negative forcing is strong in central and southern Africa,
Amazon, Siberia and Southeast Asia. Figure 3 shows theannual mean direct radiative forcing by biomass-burning
aerosols at TOA and the surface. The forcing values arealmost the same between TOA and the surface for OM
and sulfate aerosols, while the sign is reversed frompositive at TOA to negative at the surface for BC becauseof strong attenuation by absorbing solar radiation. The
global annual mean forcing by biomass-burning aerosols
is calculated to be –0.07 W m-2 at TOA and –0.23 W m-2
at the surface. The monthly mean forcing over burned
areas is larger than –10 W m-2 at the surface, andfurthermore over –50 W m-2 around Sumatra andKalimantan Islands in 2006 (not shown). There was alarge uncertainty in the IPCC’s estimation of the direct(b) BB aerosol direct radiative forcing (MAR, APR, MAY) (TOA, all-sky)W/m2(c) BB aerosol direct radiative forcing (JUN, JUL, AUG) (TOA, all-sky)W/m2(d) BB aerosol direct radiative forcing (SEP, OCT, NOV) (TOA, all-sky)

W/m2

Fig. 2 Seasonal mean distribution of direct radiative forcing at TOA under all-sky conditions due to aerosols frombiomass burning (a) from December to February, (b) from March to May, (c) from June to August, and (d)from September to November, simulated by SPRINTARS.

W/m2

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T. TAKEMURA

radiative forcing (Intergovernmental Panel on Climate
Change, 2007) due to biomass burning aerosols, theglobal mean of which was +0.03±0.12 W m-2.
BC emitted from biomass burning may be responsible
for part of the semi-direct effect (e.g., Ackerman et al.,2000). It has been generally explained that absorption ofsolar radiation due to BC results in heating of the surrounding atmosphere, leading to an increase in the saturated water vapor pressure and stabilization of theatmosphere, with a subsequent decrease in cloudiness.
However, Takemura et al. (submitted to GeophysicalResearch Letters, 2011) indicate that BC can intensify
instability of the atmosphere and thereby increase cloudwater and precipitation if BC is concentrated near thesurface, which is mainly applicable to BC originatingfrom fuel consumption. BC from biomass burning is
injected into the free troposphere through the boundary
layer due to convection occurring due to the heat of thefires, and then it basically stabilizes the atmosphere.
Biomass-burning aerosols have an indirect effectthrough acting as cloud condensation nuclei (mainlysulfate and some species of OM) and as ice nuclei in the(a) BB aerosol direct radiative forcing (TOA, all-sky)case of BC. Figure 4 shows changes in cloud droplet andice crystal effective radii by biomass-burning aerosols.
There is a significant decrease in the cloud droplet effective radius over areas where the concentrations both ofbiomass-burning aerosols and liquid water content arelarge, i.e., the west coasts of South America and southern
Africa, leading to larger cloud albedo. Although there areno significant regional trends for changes in the ice crystal effective radius, it is increasing due to biomassburning aerosols over almost the entire globe. This may
be because aerosols transported to the middle and upper
troposphere act as ice nuclei and then promote conversion from supercooled water to ice crystals, which leads
to a decrease in cloud albedo for solar radiation and anincrease in absorption of thermal radiation by ice clouds.
The global annual mean radiative forcing of the indirect
effect due to biomass-burning aerosols is estimated to benearly 0 W m-2 because of cancellation between thecooling effect of reducing the cloud droplet size andwarming effect of promoting conversion from supercooled water to ice crystals.
(b) BB aerosol direct radiative forcing (survace, all-sky)Fig. 3 Annual mean distribution of direct radiative forcing at (a) TOA and (b) the surface under all-sky conditions due
to aerosols from biomass burning, simulated by SPRINTARS.

(a) ∆ could droplet effective radius (BB aerosols)(b) ∆ ice crystal effective radius (BB aerosols)

Fig. 4 Annual mean changes in the effective radii of (a) cloud droplets and (b) ice crystals at the cloud tops due toaerosols from biomass burning, simulated by SPRINTARS.

Simulation of Distributions and Radiative Impacts of Biomass-burning Aerosols

4. Summary
Distributions and climate forcing of BC, OM andsulfate aerosols from biomass burning were simulated ona global scale in this study. The results indicated thatbiomass-burning aerosols have sufficient effects tochange regional climate through strong, negative directradiative forcing. As a practical simulation of biomass-burning aerosols, a weekly aerosol forecasting
system with SPRINTARS (Takemura, 2009) includes
information on daily aerosol emissions from biomassburning retrieved from MODIS hotspot data.

Acknowledgments
We would like to thank those who contributed to thedevelopment of SPRINTARS and MIROC. The simulation in this study was performed on the NIES supercomputer system (NEC SX-8R). This study was partly
supported by the Global Environment Research Fund(RF-0901) of the Ministry of the Environment of Japan, aGrant-in-Aid for Young Scientists (21681001) of the
Ministry of Education, Culture, Sports, Science, andTechnology of Japan, and the Mitsui & Co., Ltd. Environment Fund (R08-D035).
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Toshihiko TAKEMURA
Toshihiko TAKEMURA is an Associate Professor atthe Research Institute for Applied Mechanics(RIAM), Kyushu University. He received his
Master of Science in 1999 and Doctor of Sciencein 2001 from the Graduate School of Science,
University of Tokyo. He was a research associate
at RIAM, Kyushu University from 2001 to 2006, and a visiting scientist at
the NASA Goddard Space Flight Center / University of Maryland
Baltimore County from 2004 to 2005. He has developed a global aerosol
radiation-transport model, SPRINTARS (http://sprintars.net/) to study
aerosol-cloud-climate interaction. He received the Yamamoto-ShonoAward for Outstanding Papers from the Meteorological Society of Japan in2002, Young Scientist Award from the International Radiation Commissionin 2004, Young Scientists’ Prize of the Commendation for Science andTechnology from the Minister of Education, Culture, Sports, Science andTechnology of Japan in 2008, Prize for Encouragement from the Japan
Association of Aerosol Science and Technology in 2009, and Asian YoungAerosol Scientist Award from the Asian Aerosol Research Assembly in2011. He was a contributing author of the 4th Assessment Report of theIntergovernmental Panel on Climate Change (IPCC) and a lead author ofthe 5th Assessment Report of the IPCC.

(Received 2 February 2011, Accepted 6 September 2011)