JOURNAL OF GEOPHYSICALRESEARCH,VOL. 104,NO. D8, PAGES9423-9444,APRIL 27, 1999
Incorporation of mineralogicalcompositioninto models
of the radiative properties of mineral aerosol
from UV to IR wavelengths
Irina N. Sokolik and Owen B. Toon
Atmospheric
andOceanic
Sciences
Department
andLaboratory
forAtmospheric
andSpace
Physics,
Universityof Coloradoat Boulder
Abstract. We describea techniqueto modeltheradiativeproperties
of mineralaerosolswhichaccounts
for
theircomposition.
We compilea datasetof refractiveindicesof majormineralsandemployit, alongwith
dataon mineralogical
composition
of dustfromvariouslocations,
to calculatespectralopticalandradiative
properties
of mineralaerosolmixtures.
Suchradiativeproperties
areneeded
for climatemodelingand
remotesensing
applications.
We consider
externalmixturesof individualminerals,aswell asmixturesof
aggregates.
We demonstrate
thatanexternalmixtureof individualmineralsmustcontainunrealistically
high
amountsof hematiteto havea singlescattering
albedolowerthan0.9 at 500 nm wavelength.In contrast,
aggregation
of hematitewithquartzor clayscanstrongly
enhance
absorption
by dustat solarwavelengths.
We alsosimulatethedaily meannet(solar+ infrared)forcingby dustof varyingcompositions.
We found
that,for a givencomposition
andundersimilaratmospheric
conditions,
a mixtureof aggregates
cancause
thepositiveradiativeforcingwhilea mixtureof individualmineralsgivesthenegativeforcing.
1.
Introduction
2. The data were measured for dust samples which
Proper treatmentof optical propertiesfrom the ultraviolet to
infrared wavelengthsis a major concern in modeling the net
(solar+infrared)radiative forcing by dust [Sokolik and Toon,
1996]. The optical propertiesof dust are also necessaryfor
remote sensingretrievalsby channelsoperatingat wavelengths
from UV to IR [Kaufman et al., 1997]. Thereforedust optical
propertiesmust be quantifiedover a range of wavelengthsfrom
about0.2 to 30 gm.
The mineral aerosol is a complicated mixture of various
minerals whose optical constantsvary widely from mineral to
mineral.Thus the opticalpropertiesof the aerosolare determined
by the relative abundanceof various minerals and the details of
how the mineralsare mixed together.Furthermore,the abundance
of eachmineral, and how it is mixed with others,dependson dust
origin, dust mobilization processes,and on dust chemicaland
physicaltransformation
duringtransportin the atmosphere.
A commonapproachused in modelingdust radiativeeffects
relies on refractiveindicesmeasuredfor bulk dust samples(of
unknown mineralogical composition) collected at a few
geographicallocations.Previous studiesdemonstratedthat this
approachhas seriouslimitations [Bohrenand Huffinan, 1983;
Sokoliket al,. 1993, 1998; Sokolikand Toon, 1996]. The major
drawbacks
as follows.
1. The available data are rather poor in quality (since the
measurement
techniquesusedto obtainthe refractiveindicesare
poorly justified; since the dust samples are not related to
mineralogicalcomposition;and sincethe dataare limited in terms
of representativeness
of variousdustsources).
Copyright1999by the AmericanGeophysical
Union.
experiencedspecific atmosphericconditionsand specific
transformations
duringtheirtransportfrom the dustsourceto the
place where they were collected.Therefore, these optical
constantsare not adequatefor the purposeof modelingthe time
and spacevaryingaerosolopticalproperties.
3. The
data were
obtained
for mineral
mixtures.
Due
to
nonlinear dependenciesof aerosol optical properties on the
refractive indices, it remains a question if refractive indices
measuredas an averagefor a mixture are appropriateto use for
modelingthe mineral aerosoloptical characteristics.
Moreover,
particles of different sizes may have different chemical
compositions.
Therefore,it is incorrectto attributea singlesetof
valuesfor real and imaginarypartsof the refractiveindex to a
mixtureof variousparticles.
In this paperwe discussan alternativeapproachto modelthe
dust radiative properties. This approach employs dust
mineralogical
composition
andtherefractiveindicesof individual
mineral constituents.In this manner we are able to relate light
absorption
by dustto its mineralogyandsourceregion.
In section 2 we examine available data on mineralogical
compositionof dustfrom variousgeographical
locations.Then,
we selectthe major mineralswhi'chshouldbe takeninto account
to correctlyrepresentspectralopticalpropertiesof dustfrom UV
wavelengths
to far infraredwavelengths
(seesection3). Next, in
section4 we discussopticalpropertiescalculatedfor an external
mixture of individual mineralsas opposedto thosecomputedfor
a mixtureof aggregates.
Finally, in section5 we employour dust
spectralopticalmodelsto estimatethe potentialdirectnet (solar
plusIR) forcingby mineralaerosolsof variouscompositions.
2. Mineralogical Compositionof Dust
Papernumber1998JD200048
at Various Locations
Minerals are generallydefinedas naturallyoccurringelements
0148-0227/99/1998JD200048509.00
or compoundsformedby inorganicprocesses.
The majorityof
9423
9424
SOKOLIK
AND TOON: DtJST RADIATIVE
dust particlesare lofted into the atmosphereby eolian (wind)
erosion
of
arid
and
semi-arid
lands.
Human
activities
(agriculture,industry,construction,
deforestation,
etc.) canextend
the geographicalarea of dust sourcesand increasedustloading
into the atmosphere.
This portionof dustis calledanthropogenic
dust, and it is of special interest in climate change studies.
Becauseof the diversity of dust sources,the propertiesof dust
originatingfrom various types of land surfacesneeds to be
studied.
There is a large body of data on mineralogicaland elemental
(or chemical) compositionof the Earth's soils. These data
demonstrate
the complexspatialvariabilityof soil composition.
The observed variability is the result of the history of soil
formationand weatheringprocesses.
It is commonto compareelementalcompositionof soilsfrom
different parts of the world with the average compositionof
Earth's crust or of sedimentaryrocks [Pye, 1987]. For instance,
averagesedimentaryrockshave a Si/A1ratio of 4.04. It turn, the
Si/A1 ratio for dust from Sahelianregion is 3.18-3.6, while for
dust from northern Morocco is about 2.67-2.87 [Bergamettiet
MODELS
The main constituents found in dust derived from surface soils
are quartz,feldspars,
calcite,dolomite,gypsum,mica,kaolinite,
illite, montmorillonite,palygorskite,
chloriteand organicmatter
(suchasbacteria,fungalspores,pollengrains,seeds,stemtissue,
and ash) [Pye, 1987]. Althoughthe chemicaland mineralogical
compositionof airbornedust mimics the compositionof the
parentsurface,it alsodepends
on dustmobilizationprocesses
and
compositionalseparationduring dust transport.Changesin
compositionduring dust transporthave been reportedby the
numerousinvestigators.For instance,Rahn et al. [1979]
demonstratedthat the Si/A1 ratio changesduring the long-range
transport
of mineralparticles.A studyby Prosperoet al. [1981]
showed the changesin mineralogyof Saharandust samples
collectedat various distancesoff the coast of Africa along the
dustplumetransported
overthe AtlanticOcean.Chestereta!.
[1972] reportedthe variationsof clay mineralswith latitudein
dustsamplescollectedoff thewestcoastof Africa.
In turn, dustmobilizationprocesses
partlydeterminethe initial
particle size distributionof airborneminerals as well as the
degreeof particleaggregation,
and,therefore,influenceairborne
dustcomposition.
At the sametime, surfacecharacteristics
(such
al., 1989]. In contrast,dust in Arizona has the Si/A1 ratio of 4.02,
particle size distribution,
and dust from Tadzhikistan (central Asia) has a ratio of about as composition,particle aggregation,
3.06 [Gomes and Gillette, 1993]. Petrov [1976] showedthat the etc.) are crucial for dust mobilization processes.In fact, fine
mineral particlesare often presentin the form of aggregates
in
Gobi desert contains 0.74-1.36% less Fe, but 5-12% more A1 and
8.4% more Ca that the averageearth crust composition.These surface soils, rather than in the form of loose grains. This
is explainedby stronginterparticle
cohesive
forces,
data are in agreementwith measurements
by Parungo et al. phenomenon
which decreasewith increasingparticle size. Aggregateshave
[1995] conductedat severallocationsin China.
They
Variable elemental ratios reflect variable mineralogical sizesfrom about 80 gm to severalhundredsmicrometers.
compositionof parent soils. For instance,dust in the Sahelian can be made of particlesof the samemineralor of particlesof
(clays,quartz,hematite,salts,
regionis characterized
by a high Fe/A1ratio due to the abundance variousmineralogicalcompositions
can
of ferralitic soils in the Sahelianregion. In contrastsoils in the etc.) [Chatenetet al., 1996,Alfaro et al., 1997]. Aggregation
composition
of parentsoils.For
semi-aridregionsof central Asia containlesserFe. The variable also dependon mineralogical
compositionof soilsproducestheir variablecolor which is often instance,dust in Australiais more aggregatedthat Saharandust
[Kiefert et al., 1996].
used as a criteria in soil classification.
Soil color can be
Dust mobilization mechanismscan cause the complete or
controlledby organicmaterial(the carboncontentgivesit a dark
partial
breakdown
of aggregates
to particlesof sizeof about20color) or by the inorganic compounds.The most important
by winds.
inorganic coloring agent is iron. Iron oxides occur, at least in 50 gm and smaller,which can then be transported
small amounts,in nearly all soils (51 g/kg Fe in Earth's crustat Thereforeairbornedust may exist as an externalmixture of
average).However, large variationsare observed.For instance, individual mineralsor/and as a mixture of aggregatedparticles.
of the size-dependent
the soil of the Gobi is chieflygrayishbrown,while dustcollected We are nor awareof any parameterization
in the Negev desertis typicallylight brown or tan, and Sahelian dust flux with resolved mineralogicalcomposition.However
there are severalparameterizations
of size-dependent
dust flux
dustis brightred.
Despite the wealth of disperseddata on soil chemical and accountingfor varioussurfacesoil features[ Gillette 1979,
mineralogicalcompositionthere is no readily availabledata set Marticorenaand Bergametti,1995,Marticorenaet al., 1997].In
surfacemineralogy
on the compositionof parentsoils on a global scale.Existing particular,morerecentstudiesincorporated
into dustemissionschemeto simulatethe
global data setsof soil propertiescurrentlyinclude soil texture and surfaceroughness
(threesize classes:"clay", "silt" and "sand")and soil typeswith a size-resolved dust vertical flux. Such schemes can be extended to
dustfluxes.
resolution
1øxlø buttheydo notprovide
information
on size- simulatesize- andcomposition-resolved
Summarizingthe abovediscussion,
thereare severalprocesses
resolvedmineralogicalcompositionof the parentsoil [Webb et
al., 1991]. There are severalsystemsof soil classification
based leading to the variabilityof dust composition:(1) variable
of
on different criteria (type, composition, texture, etc.). For compositionof bed surfaces(supportedby measurements
elementaland mineralogicalcomposition;
by varioussoil colors;
instance, the Food and Agriculture Organization (FAO)
/UNESCO systemand U.S. Soil Taxonomy are two often used by varioussoil types);(2) spatiallyand temporallyvaryingdust
mechanisms
(selective
liftingof the mineralsfromthe
classificationsof soil types. The Soil Taxonomy system production
recognizes11 orders and five categoriesbelow the order [Soil bed surface);and (3) spaceand time varying compositional
duringdust
SurveyStaff, 1996]. They are: suborder,great group,subgroup, separationdue to physicaland chemicalprocesses
family and series.Elevenorders,47 suborders,
about195 groups, transport.
Sincemineralogical
dataon dustcomposition
arenot currently
about 1200 subgroups,about 5000 families, and about 12,000
seriesare presentlyin the Soil Taxonomysystemof the USA. It is availableon the global scale,to performour modelingwe use
measurements
of dustcomposition
at various
at the family level that mineralogyentersinto the classification somerepresentative
is oftenreportedfor a total
for soils,althoughit is usedas a criterionin a highercategoryfor locations.Mineralogicalcomposition
some soils. However, quantitativeinformationon mineralogical (bulk) dustsampleor for a clay-sizefraction(massradii < l gm).
the averagecomposition
of theclay-sizefraction
compositionof surface soils can not be extractedfrom these Table 1 presents
of dust which originatedin Chad,Egypt, SaudiArabia [Ganor
classificationsystems.There is a clear need for a new data set to
and Foner, 1996], AustraliaandMali [Kiefertet al., 1996], and
provide information on mineralogicalcompositionneeded for
the Sahara[Delanyet al., 1967]. Samplesanalyzedby Ganorand
dustmodelingon globalandregionalscales.
SOKOLIK
ANDTOON:
DUSTRADIATIVE
MODELS
9425
.
•
.litire
i•ao!!nlte
Montmonllon•te
-•
Hematite
b-rav
Hematite:
(.J-ra•,
•'
,.._}[l•rr•, ß •-.rc•
•
Quartz; O-ra
...Catch:
•
c•ypsum
6
5
4
3
0
0.001
5
10
5
10
Plate 1.
15
wavelength
15
wavelength
20
25
20
Same
asFigure
1,except
attheinfrared
wavelengths.
25
30
30
9426
SOKOLIK
AND TOON'
DUST RADIATIVE
MODELS
Illite
Kaolinite
Montmori!!onite
Hematite
Quartz
Calclte
0.01
+e-x-•
Gypsum -•-
.
0.001
,
,.
o.oool
ß
"
I
,,I
I
lO
o.1
L
15
wavelength
20
25
30
I
I!!ite
Kaolinite
Montmorillonite
Hematite
Quartz
Calcite
-+•.x
-•-•-
Gypsum+.
0.01
'k
.
.
%'ß
ß
o. ool
o.oool
I
_
! ..........
10
I
15
I
'
wavelength
20
Plate 2. Sameas Figure 2, exceptat IR wavelengths.
3O
SOKOLIK AND TOON: DUST RADIATIVE
MODELS
9427
Table 1. MineralogicalComposition
of Clay-SizeMode ParticlesWhich
OriginatedFrom VariousGeographicalSources
Chad Egypt SaudiArabia Mali
Barbados
Australia
(Saharan Dust)
Illite
87
15
5
26.4
41
Kaolinite
11
30
55*
67.8
32
61.8
2
55
40
2.7
16
0
Montmorillonite
38.2
* Kaoliniteandpalygorskite.
Valuesarein units% by weight.
Foner were collectedover Israel, but they showeddifferentclay
minerals according to their geographical sources, namely,
AhaggarMassif (Chad and Libya), Tibesti Mountains(Egyptian,
Libyan, and Negev deserts),and Saudi Arabia (Jordanand Dead
Theminerals
withtheimaginary
partsmaller
thatlx10-5cause
Sea deserts)(see first three columns in Table 1). Saharandust was
and Plate 1). Thereforedata setsmustbe interpolatedaround2.5
gm (for instance,montmorillonite,illite, kaolinite).Also, dataon
spectraloptical constantsin the visible are missingfor some
minerals (for instance, chlorite, calcite, gypsum). For these
specieswe usethe realpartof refractiveindicesasthe averagein
the visible from Ivlev and Popova [1973], ignoring possible
spectral dependencies.Moreover, some minerals (such as,
hematite, quartz, calcite, gypsum) can have amorphousand
collected at Barbados [Delany et al., 1967]. Dust which
originatedfrom the Ahaggar Massif is characterizedby a high
abundance of illite, while dust from the Tibesti Mountains has
moderate concentrations of illite, kaolinite and montmorillonite.
In contrast, dust from Australia has high concentrationsof
kaolinite.
Table 2 presentsthe averagecompositionof total dustsamples
negligiblelight absorption.
For some minerals there are independentmeasurementsof
opticalconstantsat visible and infraredwavelengths(Figure 1
collected
at SalIsland,Barbados
and Miami [Glaccum,
1978], . crystallineforms.Further,somecrystalsare anithotropic,
southern New Mexico [Hoidale and Blanco, 1969], Sudan
[Sharif, 1995], and Nigeria [Adedokun et al., 1989]. Table 2
showslargevariationsof mineralcomposition
with location.For
instance,the amountof quartzcan vary from 6% (southernNew
Mexico) to about83% (Nigeria,sample4). Anotherfeaturewhich
can be seenin Table 2 is that differentstudiesreporteddifferent
setsof dust mineral constituentsextremelyentanglingmodeling
and comparisonthe dust radiative properties.Also, only a few
studiesreported hematite (a major sourceof light absorption)
along with other minerals. To some extent this variation in
mineralsreportedis explained by problemswith identification
andquantificationof individualminerals.
showing different optical constantsin the directionsof their
principalopticalaxes[EganandHilgeman,1979].
fromTable3 areillustrated
in Figure1 andPlate1, whichpresent
Quartz is often dominant in terms of mass and has strong
It would be a difficult task to incorporateall the numerous
mineralsoccurringin nature into modelsof the dust radiative
propertiesrelevantfor climateand remotesensingapplications.
Instead,one can try to define the major mineralcomponentsof
aerosolswhich should be taken into considerationto correctly
representthe spectraldust optical propertiesover a range of
wavelengthsfrom 0.2 to 30 gin. We selectmineralswith the
followingtwo characteristics
to be usedfurtherin our modeling:
minerals which are a minor mass fraction but have specific
absorbingbands with a relatively high imaginarypart of the
refractive index, or minerals with a large mass fraction of the
3. Refractive Indicesof Major Minerals
aerosol.From analysesof dataon mineralogicalcompositionand
We compiled a data set of publishedrefractiveindices for
on spectralrefractiveindices (seeFigure 1 andPlate 1), we limit
major mineralsfrom UV to IR wavelengths.
Table 3 provides ourselvesto seven minerals when exploring the spectraldust
referencesfor some available data along with the range of
radiative properties:quartz, hematite, montmorillonite,illite,
wavelengthswhere optical constantswere measured.Some data kaolinite, calcite,and gypsum.
the spectralreal and imaginaryparts of the refractiveindices,
respectively.Figure lb and Plate lb show those mineralsfrom
Table 1 which have an imaginarypart of their refractiveindices
absorptionbandsin the IR atmospheric
window,althoughit does
not have noticeableabsorptionat UV and visible wavelengths.
Clays (montmorillonite,illite, kaolinite)are abundantin termsof
larger
thanlxl 0-5in solar
andinfrared
wavelengths,
respectively.massand have strongabsorptionin the IR. Multiple types of
Table 2. MineralogicalCompositionof Bulk Dust SamplesCollectedat VariousLocations
Sal Island
Barbados Miami
Southern Sudan
New
Sample
Mexico
Illite
Kaolinite
64.3
62.9
19.0
3.8
1.17
5.6
6.6
8.3
6.3
20.0
N/R
12.0
22.6
35.0
N/R
N/R
N/R
Quartz
19.6
13.8
14.2
Gypsum
Calcite
Hematite
Others
2/KH/83
53.8
Montmorillonite
Chlorite
Nigeria
Nigeria
Sample4 Sample9
6.0
N/R
N/R
N/R
56.3
83.3
67.4
N/R
4.3
4.1
4.2
N/R
N/R
N/R
N/R
N/R
N/R
N/R
5.0
N/R
N/R
8.2
3.9
6.9
16.0
7.3
N/R
N/R
N/R
7.5
N/R
5.4
N/R
5.5
N/R
4.0
6.23
21.4
N/R
3.5
N/R
4.4
N/R, datawerenotreported.Valuesarein unitsof % by weight.
9428
SOKOLIK
AND TOON:
D[JST RADIATIVE
MODELS
Table 3. RefractiveIndicesof Major Constituents
of theAirborneMineralAerosols
Constituent
Wavelength,[tin
Reference
Quartz
Amorphousform
Crystallineform
Montmorillonite
7.14-50.0
7.14-25.0
Popovaet al.[ 1972]
Steyeret al.[ 1974]
0.736-36.0
Petersonand Weinman [ 1969]
0.185-2.6
Eganand Hilgeman [ 1979]
5.0-40.0
Toon et al. [1977]
2.5-200
Illire
Kaolinire
Querry[ 1987]
0.185-2.6
2.5-200
EganandHilgeman [1979]
Querry [ 1987]
0.185-2.6
Eganand Hilgeman [1979]
5-25
Roushet al.[ 1991]
Calcite
Amorphousform
Crystallineform
2-32.8
2.5-300
Querryet al.[ 1978]
Longet al. [ 1993]
Gypsum
Crystallineform
2.5-300
Long et al. [ 1993]
Mica
0.185-2.6
Egan andHilgeman [ 1979]
Feldspar
0.185-2.6
Eganand Hilgeman [ 1979]
Chlorite
2.5-50
Serpentine
2.5-50
Mooneyand Knacke[ 1985]
Mooneyand Knacke[ 1985]
5-25
Hematite
Roushet al.[ 1991]
0.2 -50
Querry [ 1978]
Popovaet al. [ 1973]
8.3-50.0
clays are consideredbecausethere are specificfeaturesin their
spectra(such as band shapesand positions)which distinguish
them from quartz and from each other. Moreover, clays absorbat
solar wavelengths,showing an increasingimaginary part of the
refractiveindex toward UV wavelengths(seeFigure 1). Hematite
has the largest absorptionat UV and visible wavelengthsof the
mineralswe haveconsidered.Also hematitehasstrongabsorption
bandsin the IR around8 gm and 25 [tm. In contrast,calciteand
gypsumshow almostno absorptionin the UV and visible,but
Aggregationof dust particlescould be importantfor their
ability to scatterand absorbradiation.The availablestudieson
aggregationof other types of atmosphericaerosols have
demonstrated
that inclusionof small amountof highly absorbing
material(suchas soot) in a transparenthost(suchas sulfatesor
cloud droplets) can cause an absorptionenhancementby
aggregates
[Ackerman
and Toon,1981;ChylekandHallet, 1992;
Fuller et al., 1999]. In the case of dust, hematite (a strong
absorberat solar wavelengths)can be aggregated
with claysor
at solarwavelengths),
resultingin
they do have strong absorptionbands in the IR with band quartz(relativelytransparent
of solar absorptionby
positionsthat are quite differentfrom thoseof quartzand clays higher absorption.A correctassessment
dust is a crucialproblemin modelingthe impactof dustupon
(seeFigure 1 and Plate 1).
climate.
4. Modeling the Dust Radiative Properties
As we discussedin section2, dependingon the production
mechanisms and transformation processesduring transport,
mineral particlescan be in aggregatedor in disaggregated
forms.
First, we considerradiativepropertiesof an externaldustmixture
assumingthat it consistsof individual minerals,then we will
addressmodeling the radiative propertiesof dust particles in
aggregatedforms (in other words, an internalmixtures).Sincethe
latter problemcannotbe solvedin a generalway, we will explore
severalapproximationsto model optical propertiesof composite
particles.
We focus here on modeling the mineral aerosolspectral
optical propertieswhich are neededfor climatemodeling:the
extinction coefficient Kext (which is the sum of scatteringand
absorptioncoefficients),single scatteringalbedo 00o, and
asymmetry parameter(a cosine weighted integral of the
scatteringphase function) g. This set of parametersallows
calculationof radiativeforcingin the two-streamapproximation,
which is often used in climate models.
4.1. Optical Propertiesof a Mixture of Individual Minerals
Individualmineralswhichcomposean externalmixtureof the
airborne mineral particles can have the same particle size
SOKOLIK
AND TOON:
DUST RADIATIVE
MODELS
9429
3.5
'
•
a
.. ,•
4c
.•
'
'
•
•
'•.
•.
•' .__,,•x,.•
%
Illite- 1
Kaolinite
-+- I
Hematite,E-ray..x. •
Hematite,
O-ray-•- I
'•
•.•' •
'
Montmodllonite
.•-- ]
Quartz,
E-ray.•- _J
Quartz,O-ray-,-- /
•
Calcite
'+'/
&x
1.5
1
x
•o
0'.5
[
•
2.5
wavelength
[
i
[
Illite --
b
Kaolinite
•
Hematite, E-ray -xMontmorillonite
.•-
ß
O.Ol
c•0.001
0.0001
-
le'050'
OJ.
5
{
wavelength
115
•'
2.5
Figure 1. Spectral(a) realpart,n, and(b) imaginarypart,k, of therefractiveindicesof somemineralsfromTable 3
at solarwavelengths.
distribution or different size spectra.The shape of the size
spectrumand its variation in time depend on the initial size
distributionresulting from particle mobilization,as well as on
transformationprocesses
duringdusttransport.
To model the optical propertiesof individual mineralswe
assumethat their size distributionsmay be represented
by several
lognormalfunctionsas
N (r)=I; Nj ((2/I;)
1/2ln(oj)r )-Iexp[ - ln(droj)
2/ 2ln(oj)
2],
where N (r) is the particle number concentrationof a given
respectively).The particlesizemodeshaver0=0.5 (Figure2a and
Plate 2a), and 0.7 gm (Figure 2b andPlate 2b), and 6=2. The size
mode with r0=0.5 gm is believed to be representativeof the
particle size distribution of the long-lived, distant-transport
accumulation mode of airborne dust [Patterson and Gillette,
1977, Arimoto et al., 1997]. The larger r0 is representativefor a
particlesizemodewhichoccursnearthe dustsource[Gomesand
Gillette, 1993]. In reality, particle size spectracan have one or
severalmodes,characterizedby a specificcomposition.
Figure 2 and Plate 2 demonstratehow the normalizedspectral
extinction
coefficient
varies
due
to
the
differences
in
the
mineral,Nj is particlenumberconcentration
of thej-th sizemode refractiveindicesof the minerals.As shownin Figure 2, Kext*of
from that
with its medianradiusroj,andgeometric
standard
deviationoj. hematitehasa spectrumwhichis clearlydistinguishable
The lognormal function is often used to model aerosol size of other minerals at solar wavelengths.Some minerals have
distributions[e.g., D'Almeida et al., 1991]. We will calculate noticeable differencesin Kext* for wavelengthslarger than a
optical properties of individual minerals using a variety of specificwavelengthwhich dependson r0. For instance,for r0=0.5
observedparticlesize spectrato representthe complextemporal gm the mineralsconsideredhave differencesin their Kext*spectra
andspatialvariationof the sizedistribution.
for wavelengths
largerthanabout)• = 0.6 gm.
First,we calculateopticalpropertiesof mineralsassuming
that
In the IR region,Plate 2 showsvariousspecificfeaturesin the
theyhaveonesizemodebut varyingmedianradius.Figure2 and Kext* spectrumof the individual minerals.For a given mineral,
Plate2 showcalculatednormalizedextinctioncoefficients,Kext* the spectralfeaturesin rext* mimic the featuresin the mineral's
(cm3/km)
(normalized
forN=I cm-3),forindividual
minerals
at refractive index spectrum, although the magnitude of Kext*
the solar and infrared wavelengths(Figure 2 and Plate 2, dependson the parametersof the particlesize distribution.Plate
9430
SOKOLIK AND TOON: DUST RADIATIVE
MODELS
0.0065
Illite
Kaolinire
Montmorillonite
Hematite
Quartz
Calcite
a
m
-+x
-•-
Gypsum
0.006
",.•.
'"•,, -'.-<
0.0055
0.005
O.OO45
o
0.5
1
wavelength
1.5
2
2.5
Kaolinite -+Montmorillonite
Hematite
0.012
Calcite -•-
Gypsum
0.0115
I
0.0105
0.01
0.0095
0.009
0
0'.5
•
wavelength
1.
1•
2.5
Figure2. Normalized
spectral
extinction
coefficient
Kext*of individual
minerals
calculated
fora lognormal
particle
sizedistribution
with(a) ro=0.5 gm and(b) ro=0.7 gm for o =2 at thesolarwavelengths.
2a and 2b canbe comparedto Figures2a and 3a from Sokoliket
In the IR region,movariesin a wide rangefrom aboutalmost0 to
al. [1998] to demonstrate
the differences
in the rext* spectra 1 (Plate 4), and has a complex spectralbehavior which varies
calculatedfor individualmineralsandcalculated
usingrefractive greatly betweenthe mineralsconsidered.
indicesof mixeddustsamplesof unknowncomposition
collected
Plate 5 comparesthe asymmetryparameterof somemineralsat
at variouslocations.The mixed dust sampleshave relatively UV and visible wavelengthswith size modeshavingr0=0.25,0.5,
smoothspectrawhichreflecttheirspectralrefractiveindices.
Plate3 illustrates
the singlescattering
albedoof the minerals
whichhavesignificant
absorption
at UV andvisiblewavelengths
for particlesize distributionwith r0=0.25,0.5, and 0.7 gm.
Quartz, calcite and gypsumsingle scatteringalbedosare not
shownin Plate3 because
theirm0is closeto 1 in thiswavelength
region.For hematite,we showm0for boththeE-rayandO-rayto
illustratethe differences.In turn, Plate 4 presentscalculated
single scatteringalbedosat infraredwavelengthsfor the same
particlesizedistributions:
(a) r0=0.25gm, (b) r0=0.5gm, and(c)
r0=0.7 gm.
The single scatteringalbedo for hematite is about 0.6 for
wavelengths
X,< 0.6 gm andvarieslittlewithr0 or raytype.In
contrast,clayshave m0in a rangefrom about0.8 to 1 for X,< 0.6
gm, showing strong spectraldependenceat UV and visible
wavelengths.
For X, > 0.6 gm, clayshavem0of about0.95 to 1,
whilehematite
haslargevariations
of m0depending
on raytype.
and 0.7 gm. The magnitudesof g are in a rangefrom 0.65 to 0.75
with a few exceptions(Plate 5). Namely, hematitecan haveg =
0.35-0.85, dependingon the wavelength.All mineralsconsidered
have larger magnitudesof g for shorter wavelengths.In the
infrared,g decreases
whenX,is increasing,
although
somespectral
featuresin g for the individualmineralscan be seen.
Employing calculated optical characteristicsof individual
minerals(Figure 2 and Plates2-5) one can modelthe optical
propertiesof externalmixturesof minerals.The large variations
in the optical propertiesof individual mineralsillustratedabove
suggestthat the radiativepropertiesof a mixturewouldstrongly
depend on the relative abundance of individual minerals.
However, the minerals have unequal importance in their
contributionto the mixtureopticalpropertiesat solarandinfrared
wavelengths.To explore the importanceof the abundanceof
individual mineralsfor the effectiveoptical propertiesof their
mixture, we use availablemeasurements
of the compositionof
dust samplescollected at various geographicallocationsand
SOKOLIK AND TOON: DUST RADIATIVE
MODELS
9431
0.9
0.8
0.7
Iltite, ro=0.25 •--.
Kaolinite, ro=0.25 -+Montmoriilonite, ro=0.25
0.6
Hematite, O-ray, ro=0.25 -xHematite, E-ray, ro=0.25
Illite, ro=0.5
Kaolinite, ro=0.5 -e-Montmori!lonite, ro=0.5 +-
0.5
Hematite, E-ray, ro=0.5
Hematite, O-ray, ro=0.5
Illite, ro=0.7
Kaoli.nite, ro=0.7
Montmorillonite, ro=0.7
0.4
Hematite, E-ray, ro=0.7 -+Hematite,O-ray, ro=0.7
0
0.5
I
I
i
1.5
2
,
2.5
wavelength
Plate 3. Singlescattering
albedoof somemineralsat solarwavelengths
calculatedfor ro=0.25, 0.5, and0.7 gm.
measured(if available) or assumedlognormalparticle size usedto model its opticalproperties(in this case,kaolinite).Thus
distributions.As we discussedin section2, mineralogical we have
compositionis often reportedas a weight fractionof individual
AKex
t = Kext
m•x-Ke,,(kaolinite).
mineralsin thetotalsampleor asa fractionwithinsomerangeof
ß
particlediameters(seeTables1 and2). In particular,we usedata
from Table 1 to calculatethe opticalpropertiesof dustwith a
clay-sizeparticlemode(with massradius< 1 gm).
Figure 3 shows AI•xt calculatedin the solar and infrared
wavelengths.
We assumeM=10gg/m
3 anda lognormal
size
Calculations
wereperformed
as follows.If Kext
mix(km-1) distributionwith ro=0.5 !.tm.For variousmixtures,the calculated
denotes the extinction coefficient of a mixture of individual
AKex
t (km-•) is in a rangefrom-8x10
-s to 5x10-5 at visible
minerals, it can be written as
wavelengths,
andin therange
from-3x10
'4to about1.5x10
'4at
infraredwavelengths.
To understandhow importantthe differencesin AI%xtare, one
can translate them into differencesin optical depth. For a
where Ni is the particle number concentrationof the i-th
homogeneousdust layer locatedin the four lowest kilometersof
individualmineraland Kext*
i is its normalized
extinction the atmosphere(H=4 km) the differencesin opticaldepthsversus
Kext
re'x=Z (Kext*
i Ni),
coefficientcalculatedabovefor individualminerals.If Wi is the
weight fraction of the i-th mineral in a mixture with a total
particlemassconcentration
M, we have
Ni= M Wi / [Pi4/3n (ro)
3exp(9 ln((J)
2/2)],
wherePiis thedensityof thei-th mineral.Consequently,
Kext
m•x
is
Kext
mix
= Z (Kext*
i M Wi/ Pi) / [4/3•:(r0)3exp(9ln(c92/2)].
For purposesof illustration we calculate AI%xt as the
differencebetweenthe extinctioncoefficientof a given clay
mineral mixture from Table 1 and the extinction coefficient of
kaolinite. The latter extinction represents a case when
composition
of clay-sizemodeis ignoredandonlyonemineralis
mass concentration
are
AX=
AK•xt H M,
whereAK,,xt
is for M =1 .gg/m
3. As an illustration,
Figure4
presentsA'r calculatedat 0.5 and 9.5 !.tm(wavelengthsused in
remote sensing)versusmassconcentrationfor the dust samples
from Table 1. Figures3 and 4 showthat the uncertaintiesin the
extinctioncoefficients(or opticaldepth)of a clay mixturedue to
ßcompositionchangeare largerat the infraredwavelengths
thanat
visible wavelengths.However,for a heavydustloadingof about
M=10,000!.tg/m
3 , whichcorresponds
to a well-developed
dust
storm,the differencesat visible wavelengthsbecomeimportant.
Although the clay mixtures can have more complicated
compositions,illite, kaolinite and montmorilloniteare known to
9432
SOKOLIK AND TOON: DUST RADIATIVE MODELS
ß
I
i
i
I'
Illit•
Kaolinit•
Montmorillonite
Hematite
Quartz
Calcite
fi
•
-+••
•
Gypsum.e-0.8
.\
0.2
:
" ."
•"
, 7,
•
..
Iliite
Kaohmte
Montmoritlonite
Hematite •<Quartz •
Calcit• x-
Gypsum.e.-
/
,i
0.4
0.2
0
lb
....
lv•5
velength
20-
25
ao
titire.
KaolJnlte
Montmorillonite •Hematite
Quartz
Calcite
. t
Gypsum .e0.8
0.2
15
wavelength
Plate4. Singlescattering
albedoof someminerals
at IR wavelengths
calculated
for (a) ro=0.25 gm, (b) ro=0.5 gm,
and (c) ro= 0.7 gm.
SOKOLIK
ANDTOON'
DUST
RADIATIVE
MODELS
,9
.....
I
......
I ...........
I
9433
I
0.8
.6- Illite,
ro=0.25•, •-•.•,.
•..,•,
• '.- ••.•
Kaolinire, r=0.25
Montmorillonite, r=0.25
Hematite, ro=0.25
ro=0.25
I!l•e, r•0.5
0.5 -
KaolinRe,•0.5
Montmoriltonite, r=0.5
Hematite, to=0.5
Quadz, to=0.5
!11ite,to=0.7
Kaolinire, r=0.7
.e-•
•
•
0.4
-Montmorillonite,
r=0.7-•
0
Hematite, to=0.7 •
._Qua•z, roF0.7 D
0.5
•
•
...........
I wavelenCh
1.5
•
2
........
J
2.5
Plate
5. Asymmctry
parameter
ofsome
minerals
atthesolar
wavelengths
calculated
for•=0.25,
0.5and
0.7pro.
forthesizedistribution
assumed.
Thesingle
scattering
albedo
of
the
mixtures
decreases
with
increase
of
hematite
at
solar
kaolinitcis usedto modelopticalproperties
of claymixture,one
while
it generally
increases
atmost
IRwavelengths.
can expectto underestimate
or overestimate
the extinction wavelengths,
of individual
minerals
musthavea hematite
coefficient
(and opticaldepth)for a givenmassloadingas Notethata mixture
amount
ofmorethan20%tohaveco0
smaller
than0.9at•, = 0.5
illustratedin Figures3 and4.
gm.
This
hematite
amount
is
high,
since
on
average
hematite
is
Thesinglescattering
albedo
of a mixture
doesnotdepend
on
5-10%.
Inturn,forthesame
sizedistribution,
to0
calculated
total dust concentration,
but dependsinsteadon the relative about
be the mostabundantin termsof theirmassfraction.Thusif only
dustusing
refractive
indices
fromPatterson
et al.
abundance
of absorbing
constituents.
In particular,
iron oxides for Sahara
0.8[see
Sokolik
etal.,1997].
Thislowsingle
enhance
absorption
at UV andvisiblewavelengths,
andquartz, [1977]isabout
albedo
implies
thateither
Patterson's
refractive
indices
calciteandgypsum
changethe spectral
absorption
features
at scattering
areincorrect
or hematite
is notpresent
in anexternal
mixture
as
infraredwavelengths.
As we discussed
in section2, thereareverylimiteddataon the
amountof iron oxidesspeciesin dustsamples.
Thereforewe
we haveconsidered.
In particular,
we demonstrate
belowin
section
4.2thataggregation
ofhematite
withquartz
orclays
can
modelthe opticalproperties
for a rangeof possible
weight causemuchhigherabsorption.
fractions
of hematitein the clay-sizemodewhilethe remaining
Quartz,
calcite,
orgypsum
results
inanincrease
ofto0atsolar
For thesecases,we alsocalculated
the singlescattering
albedo,
expected,
the largest
differences
in the calculated
optical
whenexternally
mixedwithclays.
Also,these
masswas equallydistributed
amongillitc, kaolinitcand wavelengths
canstrongly
influence
thedustmixture
properties
atIR
montmorillonite.
Figure5 showsthe differences
betweenthe minerals
because
quartz,
calcite,
or gypsum
oftenoccuras
normalizedextinctioncoefficientcalculatedfor the mixtureof wavelengths
sized
particles
andeach
hasstrong
absorption
features.
three
clays
andhematite
andthenormalized
extinction
coefficientlarger
We modeled
theopticalproperties
of a mixedaerosol
with
calculatedfor a mixtureof threeclaysat visibleand infrared
particle
sizes
byassuming
ro=0.7gmandc5=2.
Weallowed
wavelengths.
Figure5 presents
thecases
of 1%,10%,and20% large
ofquartz,
calcite,
andgypsum
tovary.Aswas
hematite
byweight.
Thetotal
mass
concentration
isM=10
l.tg/m
3. therelativeamount
wereobserved
atIR wavelengths.
Asanillustration,
whichis shownin Figure6. We assumed
a lognormal
size properties
7 presents
thedifferences
in theextinction
coefficients,
distributionwith r0=0.5 l.tm and o= 2. For comparison,
m0 Figure
calculatedfor a mixtureof threeclayswithouthematiteis also
shownin Figure 6.
Figures
5a and5b showthatanincrease
in theamount
of
AKext,
between
threetypesof mixtures
andthe extinction
coefficient
calculated
for quartz.
Type1 is for a mixture
of the
equal
weight
fraction
ofquartz,
calcite,
andgypsum,
type2 isfor
hematitecausesa decreasein Kextat wavelengths
smallerthan
a mixture
of 80%quartz,
10%calcite,
and10%gypsum;
andtype
about
2 l.tm,andanincrease
atmost
wavelength
regions
intheIR
3 is for a mixtureof 50%quartz,30%calcite,and20%gypsum.
9434
SOKOLIK
AND TOON: DUST RADIATIVE
MODELS
6.0E-05
4.0E-05
•[
Lm
;
m m m m m m• m m ---- m 'j
m mm
2.0E-05
•
Kchad-Kkaol
--12-- Kegypt-Kkaol
0.0E+00
ß
,,
Kbarba-Kkaol
,,,
-2.0E-05
Ksau.arab-Kkaol
--0--
Kaus-Kkaol
Kmali-Kkaol
-4.0E-05
-6.0E-05
-8.0E-05
0
0.5
1
1.5
2
2.5
wavelength
1.5E-04
1.0E-04
5.0E-05
O.OE+00
•
Kchad-Kkaol
--12-- Kegypt-Kkaol
-5.0E-05
ß
,,
-1.0E-04
,,,
--0--
Ksau.arab-Kkaol
Kbarba-Kkaol
Kaus-Kkaol
Kmali-Kkaol
-1.5E-04
-2.0E-04
-2.5E-04
-3.0E-04
2.5
4.5
6.5
8.5
10.5
12.5
14.5
wavelength
Figure 3. The differenceAI•x t betweenthe extinctioncoefficientof a givenclay mineralmixturefrom Table 1 and
the extinction coefficient of kaolinitc (scc text).
SOKOLIK AND TOON: DUST RADIATIVE
MODELS
9435
'"
Kchad-Kkaol
"
•
Kegupt Kkaol
,&
Ksau.arab-Kkaol
X
Kbarba-Kkaol
,,,,
Kaus-Kkaol
,,,
Kmali-Kkaol
-
- - -•. - - Kchad-Kkaol
- - E} - - Kegupt-Kkaol
- - -•
- - Ksau.arab-Kkaol
- - -X. - - Kbarba-Kkaol
- - -Z. - - Kaus-Kkaol
- - -O. - - Kmali-Kkaol
-1-
-1.2
0 '
2000
4000
6000
8000
10000
M, gg/m3
Figure4. Ax calculated
at 0.5 gm (solidlines) and 9.5 gm (dashed
lines)wavelengths
versus
particlemass
concentration
M.
We assume
M=I 0 gg/m
3.Quartzgiveshigherspectral
extinction different set of approximations[Bohren and Huffman, 1983;
coefficients(or optical depth) at infrared wavelengthsthan the
mixturesexcepta few smallwavelengthregions(seeFigure 7). In
particular,Kext of quartz is larger than thosecalculatedfor the
mixtures in wavelengthregions centeredat 8.5 and 12.5 gm.
Both thesewavelengthregionsare usedin satelliteobservations.
Summarizing the results of our modeling discussedabove,
somegeneralizationscan be made aboutthe opticalpropertiesof
the mixtures of individual
Chyleket al., 1988]. We comparethe refractiveindicescalculated
from these approximationsto refractive indices obtained by
volume or massmixing.
The simplestway to calculatean effectiverefractiveindex of a
compositeparticle is to sum up the refractive indices of its
individual constituentsweighted by their volume (or mass)
fractions:
minerals.
1. At solarwavelengthsthe extinctioncoefficientscalculated
for mixtures of varying compositionhave relatively similar
spectra,except for hematite.At infrared wavelengthssignificant
differencesare readily seen between the extinction coefficient
spectraof individual mineralsand their mixturesdue to specific
absorptionbands.
2. At solar wavelengthsthe singlescatteringalbedois more
sensitiveto the presenceof hematitethanto otherminerals.Clays
have singlescatteringalbedofrom about0.85 to 1, showingthe
smallestmagnitudesat UV wavelengths.At infraredwavelengths
the single scatteringalbedo varies from about 0 to 1 due to
specificabsorptionfeaturesin eachmineral.
3. At solar wavelengthsthe asymmetryparameteris in the
rangefrom about0.65 to about0.75 for the mixturesconsidered.
At infrared wavelengths,despite some specific featurestied to
absorption bands, the asymmetry parameter decreaseswith
increasingwavelength.
4.2. Optical Properties of a Mixture of Mineral Particles
in Aggregated Form
Airborne dust particlesoften occur in an aggregatedform of
two or more minerals.Moreover compositioncan vary with the
sizeof aggregates
andcanundergovariouschemicalandphysical
transformations
duringthe particlelife-cycle.There is no general
technique for modeling the optical properties of composite
particles. We consider two effective medium approximations,
referredto as Maxwell-Garnet and Bruggemanapproximations.
Both Maxwell-Garnet and Bruggeman approximations are
derived from the same integral equation for propagation of
electromagneticwaves in inhomogeneousmedium but under a
Illeft= • Vi mi,
where mot•is the effective refractive index of the composite
particle,mi is therefractiveindexof thei-th constituent,
andvi is
the volume fraction of the i-th constituent.
The Maxwell-Garnet approximation gives an effective
dielectricconstant,œeff,
of a two-component
mixturecomposedof'
inclusions embedded in homogeneousmatrix [Bohren and
Huffman, 1983]. The inclusions should be identical in
compositionbut may be different in volume, shape and
orientation.If all inclusionsare spherical,it can be shownunder
someadditionalassumptions
that
eeff=em{1 + [3 v• (e - em)/(e+2 em)]/[1- v• (e- em)/(e+2 em)]},
whereemande arecomplexdielectricconstants
of the matrixand
inclusion, respectively. However, the Maxwell-Garnet
approximationis not invariantwith respectto interchangingthe
matrix and inclusions.It impliesthat a decisionmustbe madeas
to whichcomponentis the matrixandwhichis an inclusion.
In contrast, the Bruggeman approximation allows for
calculation
of
an
effective
dielectric
constant
of
the
multicomponentmixtureswithout distinguishingbetweenmatrix
and inclusions.In otherwords,this approximationcanbe applied
for a random.inhomogeneousmedium. For a two-component
mixture the Bruggemanapproximationcan be written in the
following way:
V1(E1 - ecff)/(E1+2 ecff)+ (1-v•) (e2 - ecff)/(e2+2 eeff) = 0,
9436
SOKOLIK
AND TOON: DUST RADIATIVE
MODELS
0.0001
0.00005
-- -- -......
1%Hem
10%Hem
20%Hem
-0.00005
-0.0001
-0.00015
0
0.5
1
1.5
2
2.5
wavelength
0.0012
0.0007
-- -- -......
1%Hem
10%Hem
20%Hem
0.0002
-0.0003
-0.0008
................
2.5
: ..............
7.5
: ....................... :
12.5
17.5
',
22.5
:
27.5
wavelength
Figure5. Thedifferences
between
thenormalized
extinction
coefficient
calculated
fora mixture
of threeclaysand
hematite
andthenormalized
extinction
coefficient
'calculated
for a mixtureof threeclaysat (a) visibleand(b)
infraredwavelengths(seetext).
SOKOLIK
ANDTOON:DUSTRADIATIVE
MODELS
9437
0.98
0.96
0
•
0.94
'
1%HemE
01 0.92
-.-B--
10%HemE
ß
--•--
20%HemE
•
0.9
,",
0%HemE
*
1%HemE
0.88
c- 0.86
0.84
0.82
0.8
0
0.5
1.5
1
2
2.5
wavelength
0.8
0.7
0.6
,--,B-- 10%HemE
0.5
0.4
0.3
0.2
0.1
0
2.5
7.5
12.5
17.5
22.5
27.5
wavelength
Figure
6. Same
asFigure
5,except
forthesingle
scattering
albedo
(see
text).
'"-
20%HemE
""'
0%HemE
9438
SOKOLIK
AND TOON'
DUST RADIATIVE
MODELS
2.00E-03
1.00E-03
O.00E+00
-1.00E-03
......
Type 1
-- -- -- Type 2
½ -2.00E-03
Type 3
-3.00E-03
-4.00E-03
-5.00E-03
-6.00E-03
•i
r....................
',.................
I...................
',................
;...................
:.....................
',................
1.....................
:.....................
',.................
',.....................
',...................
•....................
;..............
2.5
4.5
6.5
8.5
10.5
12.5
14.5
16.5
18.5 20.5
22.5
24.5
26.5
28.5
wavelength
Figure 7. Differencesbetweenthe extinctioncoefficientscalculatedfor three types of mixturesand extinction
coefficientcalculatedfor quartz.Type 1 is for a mixtureof equalweightfractionof quartz,calcite,andgypsum;type
2 is for a mixtureof 80% quartz, 10% calcite,and 10% gypsum;and type 3 is for a mixtureof 50% quartz, 30%
calcite, and 20% gypsum.
where œ• and œ2
are dielectric constants of the mixture
components.Also both approximationscan be easily extended
from a two-componentto a multicomponentmixture. After
effective dielectric constants are calculated by one of the
approximations,the effective optical constantsare given by
equation:
various possible mineralogical composition of composite
particlesbasedon reported measurements
(seesection2).
The calculatedeffectiveindicesof the aggregates
madeof clays
(kaolinite, montmorillonite, and illite) give similar results for
approximationsconsidereddue to the relatively small differences
in the refractive
indices
of these minerals.
The
fact that the
Bruggemanapproximationand volumemean approximationgive
close results,and that theseresultsare in a good agreementwith
meff
= (œerr)
'•
measurements
of refractiveindicesfor a mixtureof theseclaysby
Querry [1987] is encouragingfor using the effective medium
(note that both meff and •:effare complexnumbers).
approximations
for dustaggregates.
The Maxwell-Garnetapproximationwas previouslyappliedto
The refractive indices of hematite are quiet different from
dust by Longtin et al. [1988]. Longtin et al. consideredmineral
aerosolas a sandwhichcanconsistof two kindsof particles:pure those of other minerals. We considered various composite
quartz and quartz contaminatedwith a small amountof hematite. particles made of hematite and quartz or clays. Plates 6 and 7
The optical constantsof the latter particleswere calculatedby present the spectral real and imaginary parts of the effective
refractive indices calculated for the aggregatesby the both
usingthe Maxwell-Garnetapproximation
for hematitecontentsof
5% and 10% by weight. Our calculationsusing the Bruggeman Bruggemanand volume mean approximations.These refractive
approximationgive very similar effectiverefractiveindicesto indices are for compositeparticles made of 99% quartz or
thoseobtainedwith the Maxwell-Garnetapproximationfor these kaolinite and 1% hematite,and for the aggregatesmade of 90%
cases.However, we preferto use the Bruggemanapproximation quartz or kaolinite and 10% hematite.Plates 6a and 7a provide
becauseit seemsmore adequatefor modelingof multicomponent the effectiverefractiveindexat solarwavelengths,while Plates6b
(more than two components) mixtures with random and 7b show the effective refractive index at infrared
wavelengths.Examiningthesefigures,one can point out various
inhomogenitiessuchas mineralaerosolaggregates.
It is importantto stressthat due both to variousassumptions differencesbetween the refractiveindices of the four types of
involved in the effective medium approximationsand to poor compositeparticlesconsidered.For a given amountof hematiten
knowledge of dust particle aggregation,much effort will be calculated by two approximationsdiffers by a few percent.
required to justify the applicationsof these approximationsto However, aggregationof quartz and hematite and kaolinire and
mineral aerosols. Such studies have been conducted for cosmic
hematiteresultsin differentdependencies
of n versus•k at solar
dustgrains,but we are not awareof any studiesfor eolianduston wavelengths.The imaginarypart, k, of the refractiveindex hasthe
the Earth [e.g., Perrin and Lamy, 1990].
similar spectra shape for compositeparticles with the same
Using the Bruggemanapproximationwe calculatedeffective amountof hematite,althoughk calculatedby two approaches
refractiveindices of aggregatedparticlesand comparedto the differsby as much as 40%. This differenceis illustratedin Figure
refractiveindicescalculated
by volumemeanmixing.We explore 8, which shows the relative difference calculated as
SOKOLIKAND TeeN: DUSTRADIATIVEMODELS
1.7
a
'
.•
f'
'
99%Quartz+1%Hem,
99%Quartz+1%Hem,
Vol.meani-
ß '•
•,
, t;•l,,ff
' 99%Ouartz+1%H•m.
Brug
•tppr
' 99%Quartz•-løoH;rn,
Bfog
appr.
90OoQuartz+10%Hem, Vol mean
99%KaoL+1ø,.oHem,
Brugappr.
90%Quartz+10%Hem,
Vol.meat
99%Kaol.+1%Hem,
Brug.appr..•
,•. x,,.
99%K•ol
qgø/Kaoi.+1%Hem Vol mean ,
. •r, •
Vol.mean
90%Quartz+10%Hem,Brug.appr.
90%Quartz+10%Hem,
Brug.appr.
d• -• _ ,•,<
•
1.65
9439
-•Hem
X/oi.mean
90%Kaol.+10%Hem,Brug.•i•r.
90%Kaol.+10%Hem,
Brug.appr.
-e--
90%Kaol +10%Hem, Vol.mean
1.6
1.55
1.5
,
.
0•5
1.45
0
I
wayclenCh
1.5
2
o15
2.5
99OoOuartz+1øoHem.
Brugappr.
99%Quartz+ 1%Hem, Vol.mean -,90%Quartz+10%Hem, Brug.appr. e-
9gøoOuartz+1%Hem, Brug appr. ,99%Quartz+1%Hem, Vol.mean -+90%Quartz+10%Hem, Brug.appr. e90%Quar'tz+10%Hem.
Vol.mean
90%Ouartz • 10%Hem, Vol.mean
-•
99OoKaOl.+
1%Hem, Bmg.appr. •-
99%Kao1.+1%Hem, Brug.appr.
.oq%K•ol
1%Hem
99%Kaot.+ 1%Hem
Volmean
Vol mean -•
90%Kaol,+10%Hem,Brug.appr.-•-
90%Kaol.+10%Hem,
Brug.appr..e-
90%Kaol.+10%Hem,
Vol.mean -+-
90%Kaol.+ • O%Hem, Vol.mean -+-
o
0
5
10
lw5avelength
20
25
5
•0
30
-f13•
' th 20
waveleng
25
30
partof the
Plate6. Realpartof theeffective
refractive
indices
of aggregatesPlate7. SameasPlate6, exceptfor the imaginary
calculated
by theBruggeman
andvolumemeanapproximationseffective refractive indices.
for aggregates
madeof 99% quartzand 1% hematite
, 90%
quartzand10%hematite,
99%kaolinite
and1%hematite,
and
90% kaolinite and 10% hematite.
is apparentthat the volumemeanmixingpredictsgreater
absorption
by the bandsat the IR thandoesthe Bruggeman
approximation,
butthedifferences
arenotgreat.
[A(Bruggeman)A (volume
mean)]/A (Bruggeman),
Usingthe effectiverefractive
indicesdiscussed
abovewe
modelopticalproperties
of aggregates
in a similarmannerto
what we have donefor a mixtureof individualminerals.Plate 8
thenormalized
Kext*calculated
forcomposite
particles
wherethe variableA is n or k. Figure8 showsthatthe relative presents
difference
of n is negligiblysmall,whilethedifference
is high
for k. A maximumof the differences
is centeredat •, = 0.5 gm and
is about 60% to 80% dependingon composition
of the
aggregates.
Overall,for the aggregates
considered,
k calculated
by the
volumemeanapproximation
is largerthanthatcalculated
by the
madeof 90% quartzor kaoliniteand 10%hematite,
andfor
composite
particles
madeof 99%quartzor kaolinite
and1%
hematite.In turn,Plate9 showsthe singlescattering
albedoand
asymmetry
factor.The size distribution
of aggregates
was
lognormal
withro= 0.5gmand(5=2.Theoptical
characteristics
havesimilarfeaturesto what we pointedout for the imaginary
refractive
index.Fora givenamount
of
Bruggeman
approximation,
except
in a region
of about•, < 0.3 partof theeffective
hematite,
aggregation
with
quartz
or
kaolinite
has
spectral
optical
gm.Bothapproximations
showthataggregation
of evensmall
calculated
bya giveneffective
medium
approximation
amountof hematitewith the lessabsorbingconstituents
causesan properties
increaseof k by almostan order of magnitudeat solar
wavelengths.
similarto eachother.But theydifferfor the differenteffective
mediumapproximations.
optical
characteristics
presented
in Plates8 and9
We alsomodelaggregates
madeof quartzandcalcite,quartz to Comparing
those calculatedfor a mixture of individual minerals (see
andgypsum,
claysandcalcite,
andclaysandgypsum.
Wefound section4.1), one can notice that for a given mineralogical
goodagreement
between
refractive
indices
of thesecomposite
mixtures
of aggregates
arecharacterized
by much
particles
calculated
by bothapproaches
at solarwavelengths.composition,
lower
single
scattering
albedo
and
somewhat
different
Kext*
than
However,variousdiscrepancies
were observedin infrared
externalmixtures.For instance,
Figure6a andPlate9a showthat
wavelengths.
For instance,
Figure9 showsthe imaginary
part
an externalmixtureof kaoliniteand 1% hematitehasto0of 0.98 at
calculatedby the Bruggemanapproximation
for composite
to0.83or0.89calculated
foraggregates
by
particles
madeof 50% quartzand50% calcitealongwithits X=0.5gm,in contrast
In turn,aggregates
with10%hematite
differences
relativeto k calculated
by thevolumemeanmixing.It thetwoapproximations.
9440
SOKOLIK AND TOON: DlJST RADIATIVE MODELS
2O
o
-2o
•
90%Quartz,dn/n
--0--
90%Quartz, dk/k
•
90%Kaolinite, dn/n
-4o
.-.
90%Kaolinite, dk/k
.....
X-99%Quartz,
'"
dn/n, %
99%Quartz,dk/k, %
-6o
-80
i
-lOO
o
I
I
I
I
0.5
1
1.5
2
2.5
wavelength
Figure 8. Relativedifferences
of n andk calculated
for composite
particlesby theBruggeman
approximation
andby
the volumemeanapproximation(seetext).
'
3
'
'
k(Bruggeman)-k(volumemean)
k(Bruggeman)
2.5
2
1.5
1
0.5
7.5 •,
-0.5
12.5
17.5
•,21•.5
27.5
•
-1
wavelength
Figure 9. Imaginarypart,k, of the effectiverefractiveindexof composite
particlesmadeof 50% quartzand 50%
calcitecalculated
by theBruggeman
approximations,
anditsdifferences,
Ak,relativeto onecalculated
by thevolume
meanmixing.
SOKOLIK
AND TOON: DUST RADIATIVE
MODELS
9441
1
0.95
0ø9
.85
0.8
0.0058
.75
0.7
•
•'
.65
•
0.6
•
0.0054
99%Qu•+1%Hem,
9•1.+
99%Quartz+1%Hem, Brug appr.
•
0.5
o'.•
•
'
'
99%Kaol.+1%Hem, Vol.mean w0.0•8
9r•%Guartz+10%Hem
Vol.mean
b
•-
90%Kaol
+10%Hem,
Volmean
wavelength
•
• ....
90%Kaol.+10%Hem,
99•ua•+l%Hem,
V•.mean •
99%Kaol+1%Hem, Brug.appr.•
0.95
Vol mean
99%KaoI
{ ' wavelength 4'.5
•
+1%•m,
90%Qua•+lO%H•,
9{•
015
2,5
Plate 8. NormalizedKext*calculatedfor aggregates
with the
effectiverefractiveindicesfromFigure7 andPlate6 assuming
a
lognormalsizedistributionwith r0=0.5pm and(5= 2 (seetext).
•
' •%Quadz+1%H•m,
Brag
appr.
•
90%Quartz+10%Hem,
Brug.appr.
90%Kao!.+10%Hem,Brug.appr.-e--
0'00"60
Vol.mean •
•%Kaol.+10%Hem,
Brug.appr.
•
•
1
em• vol,mean •-
90%Qua•z+10%Hem,
'.55
99%Quartz+1%Hem,Vol.mean -+99%Kaol.+1%Hem, Brug.appr.
Vol,mean •
1%Hem,Brug.appr.
•
99ø/•a•.+1%
,
0.0052
0.005
99%Quartz+l%Hem
Brugappr •--
I
J
• •a•+•
V•
m•n
Br•.a•r.
' Hem, Vol.mean
•-
90%•ol.+10%Hem, Brug.appr.•
0.9
90%Kaol.+10%Hem,
Vetmean
0.85
0.8
0.75
.
0.7
have t00of about0.57 and have quite differentsinglescattering
albedo spectra at visible wavelengthscompared to those
calculated for a mixture of individual
0.65
minerals.
.
Our explanationfor the differencesbetweenaggregatesand
externalmixturesis the following. Hematitehasa largeimaginary
partof therefractiveindex,but alsoa largereal part.Thereforeits
singlescatteringalbedois not extremelylow, and a largeamount
of hematite must be included in an external
0.%
l .....
0.•
•
'
•velen•
•:s
•
2.5
Plate
9.
Sameas Plate 8, exceptfor (a) singlescatteringalbedo
and (b) asymmetryparameter.
mixture with other
minerals to have an overall low single scattering albedo.
However,if hematiteaggregates
with lessabsorbingparticles,the
effectiverefractiveindex still hashigh k for all the particlesin the
mixture but a relatively low real part of the effective refractive
index. This combinationresultsin low single scatteringalbedo
for the mixture of aggregateswith a relatively small amount of
hematite.
5. Radiative Forcing by Mineral Aerosols
We usedthe dustopticalpropertiescalculatedaboveto explore
the importanceof varyingmineralogicalcomposition
and particle
aggregation for the assessmentof direct net (solar+infrared)
forcingby mineral aerosols.
In particular,we calculatedaily meannet radiativeforcingby a
mixtureof individual mineralswith varyingweight fraction,and
compare it to that by a mixture of aggregatedminerals. We
employ a one-dimensionalradiative transfercode, basedon the
correlated K distribution technique incorporatedinto a twostreamcode [Sokolik et al., 1998, Bergstromet al., 1998]. We
considera surface albedo of 0.2. Atmosphericcharacteristics
(water vapor profile, temperatureprofile, etc.) are from the
"midlatitude summer" standardatmosphere.The dust vertical
distributionwas homogeneous
up to 4 km, with a total particle
numberconcentrationof N=400 cm-3.
compositionof 90% clays,5% quartz,and 5% hematite(Figure
10a); 75% clays,20% quartz,and 5% hematite(Figure 10b); and
80% clays,0% quartzand 20% hematite(Figure 10c).In Figures
10a and 10b, radiativeforcingis negativeleadingto cooling.To
have positive forcing, the hematiteamountmust be increasedto
about15-20% whichseemsunrealisticallyhigh.
In contrast,Figure 10d demonstratesthat a small amount of
hematite(2% of a total mixture)aggregatedwith quartz,and then
externally mix with clays gives positive AF. We obtain similar
resultsfor a case when hematite is aggregatedwith one of the
clays, and then externally mixed with quartz. These studies
indicate that knowingwhetheror not hematiteis aggregatedwith
othermineralsis crucialfor modelingthe dustopticalproperties,
and for assessing
dustradiativeforcing.
6. Summary
In this paper we explored an alternative approach to
incorporate
the mineralogical
composition
of mineralaerosols'
into modelsof dustradiativeproperties.The approachconsidered
hasseveraladvantages.
1. Refractive
than refractive
indices for individual
minerals are better measured
indices of mixtures.
2. Mixing the optical propertiesof mineralsis more likely to
To illustrateFigure 10 shows the net radiativeforcing yield correctoptical propertiesthan using the optical constants
calculatedfor severalmixturesof varyingproportionof clays, for a mixtureof unknowncomposition.
quartz
andhematite.
Thefigureshows
dailymean
net•orcing,
AF
3. Refractive indices of individual minerals may be better
(W/m2),
calculated
forthemixtures
ofindividual
minerals
having relatedto specificsizemodesthanrefractiveindicesof mixtures.
9442
SOKOLIK AND TOON: DUST RADIATIVE MODELS
Clays Quartz Hematite
90%
5%
Quartz Hematite
5%
5%
5%
......
.•.... '"','%,,
•?
..-'•.•,-•-:•:•- •...•.•.•;.
•..••.......•
AF =-20.4
•?•.•--
W/m2
•.•
.'"-•'•
•' -•'"•
••••••.'
• • •'•':'•• • •5••:•-::----•:•
•.
Clays
90%
Clays
75%
Quartz Hematite
2O%
5%
Hematite
Quartz
5%
20%
.,::::.i•.•::.,,!i.i!::.:
:•,-:•
..
ß
AF = -27.9 W/m2
:.
.... .
::.
.......
Clays
75%
Clays
80%
Quartz Hematite
0%
20%
Hematite
2O%
AF = +7.2 W/m2
Clays
8O%
Aggregates
Clays Aggregates
(Quartz+Hem)
80%
20%
ß
20%
AF = +11.4 W/m2
.
.
......
Clays80%
Figure10. Dailymeannetradiative
forcing,AF,dueto various
mixtures
of minerals
(seetext)
The majordisadvantages
of thisapproachareasfollows.
1. There are not enoughdata on regionaland global scalesto
quantifythe size-resolved
composition
of dust at the moment.
2. There is no single welltestedtheory for modeling optical
constantsof the aggregatedparticles.
Nevertheless,we demonstrated
that the opticalpropertiesof a
mixturedependon the abundanceof individualmineralsand on
their aggregation.In particular,we have selectedsevenmajor
mineralsbasedon their abundanceand their absorptionspectra.
Using data on mineralogicalcompositionof dust collectedat
several locations we calculated dust optical characteristics
assuminga mixture of individual minerals or a mixture of
aggregates.To calculate the effective refractive indices of
aggregates,we employedthe Maxwell-Garnet,Bruggeman,and
volume mean. approximations.Despite the lack of rigorous
justificationfor theseapproximations,
theyindicatean absorption
enhancement
due to aggregationrelativeto an externalmixture.
Adequate treatment of particle aggregation is crucial for
assessmentof dust radiative effects because for a given
composition
andundersimilaratmospheric
conditions
a mixture
of aggregates
can causethe positiveradiativeforcingwhile a
mixtureof individualmineralsgivesthenegativeforcing.
Acknowledgments.This researchwas supportedby ONR grant
N00014-98-1-0121andNASA EOS-IDSgrantNAG 5-6504.The authors
would like to thank Ted Roushfor providingdigital data of refractive
indices for some minerals.
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