Variability of Absorption and Optical Properties of Key ...web.gps.caltech.edu/~vijay/Papers/Aerosol/Dubovik_et_al._(2002).pdf · Variability of Absorption and Optical Properties

590 VOLUME 59J O U R N A L O F T H E A T M O S P H E R I C S C I E N C E S

q 2002 American Meteorological Society

Variability of Absorption and Optical Properties of Key Aerosol Types Observed inWorldwide Locations

OLEG DUBOVIK,*,1 BRENT HOLBEN,* THOMAS F. ECK,*,# ALEXANDER SMIRNOV,*,1

YORAM J. KAUFMAN,@ MICHAEL D. KING,& DIDIER TANRE,** AND ILYA SLUTSKER*,1

*Laboratory for Terrestrial Physics, NASA Goddard Space Flight Center, Greenbelt, Maryland1Science Systems and Applications, Inc., Lanham, Maryland

#Goddard Earth Sciences and Technology Center, University of Maryland Baltimore County, Baltimore, Maryland@Laboratory for Atmospheres, NASA Goddard Space Flight Center, Greenbelt, Maryland&Earth Science Directorate, NASA Goddard Space Flight Center, Greenbelt, Maryland

**Universite de Sciences et Techniques de Lille, Lille, France

(Manuscript received 21 December 2000, in final form 14 May 2001)

ABSTRACT

Aerosol radiative forcing is a critical, though variable and uncertain, component of the global climate. Yetclimate models rely on sparse information of the aerosol optical properties. In situ measurements, thoughimportant in many respects, seldom provide measurements of the undisturbed aerosol in the entire atmosphericcolumn. Here, 8 yr of worldwide distributed data from the AERONET network of ground-based radiometerswere used to remotely sense the aerosol absorption and other optical properties in several key locations. Estab-lished procedures for maintaining and calibrating the global network of radiometers, cloud screening, andinversion techniques allow for a consistent retrieval of the optical properties of aerosol in locations with varyingemission sources and conditions. The multiyear, multi-instrument observations show robust differentiation inboth the magnitude and spectral dependence of the absorption—a property driving aerosol climate forcing, fordesert dust, biomass burning, urban–industrial, and marine aerosols. Moreover, significant variability of theabsorption for the same aerosol type appearing due to different meteorological and source characteristics as wellas different emission characteristics are observed. It is expected that this aerosol characterization will help refineaerosol optical models and reduce uncertainties in satellite observations of the global aerosol and in modelingaerosol impacts on climate.

1. Introduction

The lack of detailed knowledge of the optical prop-erties of aerosols results in aerosol being one of thelargest uncertainties in climate forcing assessments (cf.Charlson et al. 1992; Houghton et al. 1996; Tegen etal. 1996; Hansen et al. 1997, 2000; Heintzenberg et al.1997). Monitoring of atmospheric aerosol is a funda-mentally difficult problem. First, compared to atmo-spheric gases, aerosol is highly inhomogeneous and var-iable; that is, aerosol observations have to be global andcontinuous. Second, the available accuracy of aerosolcharacterization is often not sufficient. For instance, insitu measurements traditionally considered as the mostreliable observations are inappropriate for global mon-itoring of aerosol radiative forcing parameters and usu-ally do not characterize the aerosol in the total atmo-spheric column (cf. Heintzenberg et al. 1997; Sokoliket al. 1993; Sokolik and Toon 1996). Satellite remote

Corresponding author address: Oleg Dubovik, NASA GoddardSpace Flight Center, Code 923, Greenbelt, MD 20771.E-mail: [email protected]

sensing provides nonintrusive measurements and globalcoverage; however, radiation measured from satellitesdepends on the earth’s surface reflectance, and extrac-tion of the aerosol contribution presently has a limitedscope and accuracy (Kaufman et al. 1997a; King et al.1999). Ground-based aerosol remote sensing does notprovide global coverage; however, its wide angular andspectral measurements of solar and sky radiation arebest suited to reliably and continuously derive the de-tailed aerosol optical properties in key locations. In spiteof high temporal and spatial aerosol variability, thereare a rather limited number of general categories ofaerosol types with distinctly different optical properties.The following four general aerosol types are associatedwith different sources and emission mechanisms and areexpected to exhibit significant differences in opticalproperties: (i) urban–industrial aerosol from fossil fuelcombustion in populated industrial regions, (ii) biomassburning aerosol produced by forest and grassland fires,(iii) desert dust blown into the atmosphere by wind, and(iv) aerosol of marine origin. Detailed knowledge of theoptical properties of these key aerosol types is neededto clarify the mechanisms of aerosol radiative forcing.

1 FEBRUARY 2002 591D U B O V I K E T A L .

Additionally, refining aerosol optical models is impor-tant for improving the accuracy of satellite retrieval al-gorithms that rely on assumptions of the optical prop-erties associated with each aerosol type (e.g., King etal. 1999; Kaufman et al. 1997b; Tanre et al. 1997; Torreset al. 1998; Stowe et al. 1997; Kahn et al. 1998; Mar-tonchik et al. 1998; etc.).

Modeling the aerosol effects on atmospheric radia-tion, by solving the radiative transfer equation, requiresthe following aerosol optical properties: aerosol opticalthickness t(l) (loading); phase function P(Q; l) (an-gular dependence of light scattering), and single-scat-tering albedo v0(l) (ratio of scattering to scattering 1absorption). The sensitivity of radiative forcing to ob-served natural and anthropogenic variations of theabove-listed optical properties characterizes the impactof the atmospheric aerosol on climate change. Studies(cf. Hansen et al. 1997) show that single-scattering al-bedo determines the sign (cooling/heating, dependingon the planetary albedo) of the aerosol radiative forcing,while the asymmetry of the phase function together withoptical thickness of the atmospheric aerosol drive themagnitude of the forcing. Most of the aerosol opticalmodels (Shettle and Fenn 1979; WMO 1983; Koepkeet al. 1997; Hess et al. 1998) associate aerosol radiativeproperties [t(l), P(Q; l), and v0(l)] with physical andchemical characteristics of the atmospheric aerosol: par-ticle sizes, shape, and composition.

This strategy allows one to employ knowledge of thephysics and chemistry of atmospheric aerosol for mod-eling aerosol optics and, vice versa, to infer some phys-ical and chemical aerosol information from optical mea-surements (e.g., by remote sensing). However, an ade-quate modeling of the entire complexity of the inter-relationship of optical, physical, and chemical aerosolproperties is a fundamentally challenging task. On theother hand, the optical properties exhibit clear sensitiv-ities to a rather limited set of physical and chemicalfeatures of the aerosol. Therefore, optical models (Shet-tle and Fenn 1979; WMO 1983; Koepke et al. 1997;Hess et al. 1998) employ the following confined set ofthe aerosol parameters: particle size (particle size dis-tribution), composition (complex index of refraction),and shape (deviation from sphericity; e.g., Mischenkoet al. 1997). Certainly, there are numerous studies sug-gesting sophistication of the optical model by variousdetails, such as internal inhomogeneity of the particles,complex geometrical shapes of the particle, etc. Indeed,remarkable progress in modeling of light scattering bynonspherical particles achieved during the last two de-cades (e.g., Mishchenko et al. 2000) has significantlystimulated recognition of the issue of aerosol particlenonsphericity by the aerosol community and in manyapplications. Correspondingly, in both aerosol modelingand applications there are many efforts to account forparticle nonsphericity (cf. Kahn et al. 1997; Krotkov etal. 1999, etc.), in particular by substituting the commonassumption of spherical aerosol by randomly oriented

spheroids (Mishchenko et al. 1997). Nevertheless, non-sphericity as well as inhomogeneity are not completelyclarified issues in atmospheric aerosol modeling andmost aerosol applications rely on an optical model thatconsiders aerosol as a mixture of spherical homoge-neous particles of different sizes with composition char-acterized by the complex refractive index. Scientific ex-perience indicates that, in many cases, these assump-tions allow models to adequately reproduce the ob-served aerosol affected radiation fields.

Obviously, wide acceptance of optical models basedon the above-described simplified assumptions reflectsthe limitations of present aerosol knowledge and doesnot mean that in reality the aerosol exists as an ensembleof chemically homogeneous particles of regular shape.Clarifying the details of physical and chemical aerosolstructure and their connections with optical propertiesrequires the involvement of physical and chemical aero-sol analysis, which are provided by many kinds of insitu aerosol measurements. Correspondingly, in the pre-sent paper, we will verify and enrich the aerosol prop-erties derived from ground-based remote sensing ofaerosol by intercomparisons with available in situ aero-sol information.

Present aerosol radiation models are particularly un-certain concerning values of the single-scattering albedov0(l) (Kaufman et al. 1997a). The magnitude of v0(l)is mostly dependent on the complex part of the refractiveindex k(l) and particle size. For example, v0(l) of de-sert dust simulated according to a number of models(Shettle and Fenn 1979; WMO 1983; Koepke et al.1997; Hess et al. 1998) ranges from 0.63 to 0.87 at 0.5mm, while aircraft radiation measurements (Fouquart etal. 1987a) suggest lower absorption (v0 5 0.95 for thebroadband solar spectrum). Such uncertainty is unac-ceptable, since even smaller changes of v0 (from 0.95to 0.85) would change the radiative forcing of desertdust from significant cooling to significant warming(Hansen et al. 1997). In addition, even a low loadingof the absorbing aerosol [v0(550) ; 0.88)] may affectradiative forcing semidirectly by evaporating clouds(Ackerman et al. 2000). The optical properties of pureblack carbon (soot)—a component of smoke and urban–industrial aerosol driving aerosol absorption—has beenwidely studied. However, aerosol absorption dependsalso on the mixing mechanism of soot with other aerosolcomponents (Ackerman and Toon 1981; Martins et al.1998; Jacobson 2001). This, in addition to measurementuncertainties, is why the v0 reported in the literature(Shettle and Fenn 1979; WMO 1983; Remer et al. 1998;Reid et al. 1998) for absorbing aerosol ranges fromnearly 1.0 to 0.6 with unclear spectral dependence. Theoptical properties of the urban component are reportedin a number of models (Shettle and Fenn 1979; WMO1983; Koepke et al. 1997; Hess et al. 1998); however,the presence and relative contribution of this componentin the total column of the ambient aerosol is rather un-certain. Models of urban–industrial columnar aerosol


are sometimes based on single locality studies (Remerand Kaufman 1998) and the possible discrimination ofthe urban aerosol by concentration level and type oflocal pollution is unclear.

Thus, taking into account both the lack of the reliableinformation on aerosol absorption (Kaufman et al.1997a) and, its critical importance for aerosol radiativeforcing assessments (Hansen et al. 1997, 2000), we willfocus the present analysis on a discussion of the ob-served aerosol absorption. We discuss the single scat-tering albedo as a parameter characterizing absorption,because radiative transfer properties are sensitive to ab-sorption via sensitivity to the ratio of scattering to totalextinction (scattering 1 absorption) rather than the ab-solute value of absorption. Therefore, the spectral de-pendence of v0 is driven by the spectral dependence ofboth absorption and scattering (e.g., Dubovik et al.1998).

2. Observations and methodology

The Aerosol Robotic Network (AERONET; Holbenet al. 1998) of ;100 identical globally distributed sun-and sky-scanning ground-based automated radiometersprovides measurements of aerosol optical properties,based on up to 8 yr of observations in some locations.These data have the potential to narrow the uncertaintyin knowledge of the aerosol optical properties. The spec-tral sky radiance is measured in a wide angular rangefrom the sun and is minimally affected by surface re-flectance (cf. Dubovik et al. 2000). The standardizednetwork procedures (Holben et al. 1998; Smirnov et al.2000b) of instrument maintenance, calibration, cloudscreening, and data processing allow for quantitativecomparison of the aerosol data obtained in differenttimes and locations. The new AERONET inversion al-gorithm (Dubovik and King 2000) provides improvedaerosol retrievals by fitting the entire measured field ofradiances—sun radiance and the angular distribution ofsky radiances—at four wavelengths (0.44, 0.67, 0.87,and 1.02 mm) to a radiative transfer model. The radiationfield is driven by the (wavelength dependent) aerosolcomplex index of refraction and the particle size dis-tribution (in the size range: 0.05 # r # 15 mm) in thetotal atmospheric column. Using such a general aerosolmodel in the retrieval algorithm allows us to derive theaerosol properties with minimal assumptions. Onlyspectral and size smoothness constraints are used, pre-venting unrealistic oscillations in either parameter (Du-bovik and King 2000).

a. Accuracy assessment of individual retrievals

The accuracy of individual retrievals was analyzedby extensive sensitivity simulations (Dubovik et al.2000), studying the effects of both random measurementerrors and systematic instrumental offsets for severalaerosol models. The analysis showed that an accurate

v0(l) retrieval (with accuracy to the level of 0.03) andcomplex index of refraction (errors on the order of 30%–50% for the imaginary part of the refractive index and0.04 for the real part of the refractive index) can beretrieved only for high aerosol loading [taer(440) $ 0.5]for solar zenith angle .508 (i.e., the range of scatteringangles in measured solar almucantar .1008). For ob-servations with lower aerosol loading, the retrieval ac-curacy of v0(l), k(l), and n(l) significantly decreasesbecause of a decrease of the information content. In-deed, the calibration accuracy becomes an obstacle be-cause it causes an error in measuring taer (Dtaer 5 60.01)that is on the order of at least of 5%–10% of the opticalthickness for taer(440) # 0.2, and it is comparable withthe absorption partition in the total optical thickness.Correspondingly, the retrieval of v0(l) and k(l) be-comes difficult, as well as n(l), because scattering ef-fects of n(l) and k(l) are not completely independent.Thus, our studies (Dubovik et al. 2000) have shown thatfor taer(440) # 0.2, the accuracy levels drop down to0.05–0.07 for v0(l), to 80%–100% for the imaginarypart of the refractive index, and to 0.05 for the real partof the refractive index.

The retrieval of the particle volume size distributionwas demonstrated to be adequate in practically all sit-uations [e.g., taer(440) $ 0.05], as demonstrated by Du-bovik et al. (2000). These studies show that the errorof the retrieved volume density dV(r)/d lnr changes asa nonlinear function of particle size, aerosol type, andactual values of the size distribution. In particular, forthe intermediate particle size range (0.1 # r # 7 mm),the retrieval errors do not exceed 10% in the maximaof the size distribution and may increase up to about35% for the points corresponding to the minimum val-ues of dV(r)/d lnr in this size range. For the edges (0.05# r , 0.1 mm, and 7 , r # 15 mm) of the assumedparticle size interval, the accuracy of the size distri-bution retrieval drops significantly, because of the lowsensitivity of the aerosol scattering at 0.44, 0.67, 0.87,and 1.02 mm to particles of these sizes. Correspond-ingly, the retrieval errors rise up to 80%–100% (andeven higher) for the sizes less than 0.1 mm and higherthan 7 mm. The high errors at the edges do not signif-icantly affect the derivation of the main features of theparticle size distribution (concentration, median and ef-fective radii, etc.), because typically the aerosol particlesize distributions [dV(r)/d lnr] have low values at theedges of retrieval size interval.

The aerosol particles in the retrieval are assumed tobe polydispersed homogeneous spheres. Dubovik et al.(2000) showed how such assumptions bias the retrievalsin the case of nonspherical aerosols or externally/inter-nally mixed spheres. The tests showed that for exter-nally/internally mixed spheres the assumption ofspheres with effective refractive index is sufficient forreproducing AERONET observations and retrieval ofthe main radiative properties of the aerosol (absorptionand scattering). Light scattering by nonspherical parti-


cles can be clearly detected in the retrieval, which as-sumes spheres, and these retrieval results need to becorrected. Namely, artificially high concentrations ofvery small particles with radii less than 0.1 mm can beobtained if the inversion uses observations at solar ze-nith angles of 208 or higher (scattering angles of $408).This artifact disappears if the fine mode of particle sizedistributions was adopted from retrievals relying onmeasurements at scattering angles less than 408. Also,nonspherical scattering causes an artificial spectral de-pendence of the real part of the refractive index andonly values obtained for long wavelengths (870 and1020 nm) are close to the true values. Nevertheless, ourtests have shown that v0(l) and k(l) [and n(l) at 0.87and 1.02 mm] of nonspherical dust particles can be re-trieved using an assumption of sphericity nearly as ac-curately as for truly spherical aerosol for high aerosolloading [taer(440) $ 0.5] in addition to solar zenith angle.508.

Also, we have shown (Dubovik et al. 2000) that theminimum value of the residual given by the best fit ofmeasured radiances to a theoretical model is sensitiveto both the presence of experimental error and the failureof the radiative model. The fitting error in absence ofstrong systematic biases is usually less than 5% (max-imum 7%). Therefore, this residual value can be adoptedas an indicator of the quality of the retrieval.

The accuracy levels described above are expected forAERONET retrieval in cloud-free conditions. The skyradiance measured in the solar almucantar is checkedfor symmetry. Indeed, for a spatially homogeneous at-mosphere the sky radiances in the left and right partsof the measured almucatar should be very similar. Cor-respondingly, any local asymmetry of the left and rightparts of the almucantar is an indication of cloud or otherinhomogeneity and this measurement (scattering angle)can be eliminated from the inversion. Correspondingly,for a partially cloudy or perturbed atmosphere, the in-verted almucantars have a strongly reduced number ofscattering angles per almucantar. We consider these dataas less reliable and do not include them in our analysisif the criterion of the symmetry was satisfied at less than21 scattering angles (from a maximum of 26) in themeasured almucantar.

b. Quality control criteria for individual retrieval

Thus, in order to use the retrieved aerosol informationof the highest accuracy in our analysis, we selected thedata according to the following criteria.

1) Only symmetrical almucantars were used for retriev-als (symmetry criterion was satisfied at $21 scat-tering angles).

2) The results were used only from the retrievals withfitting accuracy of 5% or less (this was not appliedto dust retrievals, where fitting error increases to;15% due to nonspherical scattering).

3) The retrieved values of v0(l), k(l), and n(l) [fordust n(l) only at 0.87 and 1.02 mm] were utilizedonly from the retrieval obtained for high aerosolloading taer(440) $ 0.5 (except marine aerosol forwhich typical loading is much lower) and for solarzenith angle $508.

4) For dust, the shape of the size distribution for fineparticles (r , 0.6 mm) was adopted only from theretrievals obtained from sky-radiance measurementsin the scattering angular range 408 or less.

c. Retrieval data presentation

We focused our analysis on 12 selected aerosol siteswith well-known meteorological and environmentalconditions where all four principal aerosol types can beidentified. We included a mixed aerosol over the Mal-dives, which was extensively analyzed during the IN-DOEX closure experiment (Ramanathan et al. 2001,hereafter R01; Satheesh et al. 1999). Preference wasgiven to data obtained at a given site by several instru-ments and/or during long periods of time (multiyear datawere prioritized). Figure 1 and Table 1 summarize ouranalysis. The figure highlights the aerosol spectral sin-gle-scattering albedo. Figure 1 shows urban–industrial,biomass burning, desert dust and mixed aerosol inter-polated for heavy loading conditions text(440) 5 0.7.As an exception, we used text(440) 5 0.15 for oceanicaerosol, because the loading does not reach a highervalue for maritime aerosol. Table 1 covers the completerange of text observed for each aerosol type and showsthe complex refractive index and the parameters of thebiomodal volume particle size distribution. Namely, foreach mode of the volume particle size distribution[dV(r)/d lnr] we compute the particle volume concen-tration, the median radius, and the standard deviation(formulas given in the appendix). For this analysis, wedefined all particles with radius smaller than 0.6 mm asbelonging to the fine mode and all particles with radiuslarger than 0.6 mm as belonging to the coarse mode. Infact, practically all observed size distributions have bi-modal structure with quite wide local minimum withlow values of dV(r)/d lnr around 0.6 mm. The exactlocation of the inflection point is not critical for esti-mating CVi, rVi, and si.

Many studies indicate that a bimodal lognormal func-tion is the most appropriate model for aerosol particlesize distributions (cf. Whitby 1978; Shettle and Fenn1979; Remer and Kaufman 1998; etc.):

2 2dV(r) C (lnr 2 lnr )V,i V,i5 exp 2 , (1)O 2[ ]d lnr 2si51 Ï2ps ii

where CVi denotes the particle volume concentration, rVi

is the median radius, and si is the standard deviation.Indeed, the retrieved average size distributions shownin Fig. 1 exhibit a distinct bimodality with shapes vi-sually close to lognormal curves. Some deviations of


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each mode from true lognormality, such as asymmetry,appearance of local peaks, etc. are present but they areunlikely to have a significant radiative effect. It shouldbe noted that our equations (see appendix) for com-puting CVi, rVi, and si are simple, general, and theirformulation does not assume any function for the sizedistribution. Nevertheless, we formulated these equa-tions so that they give the parameters of a lognormalsize distribution if a true lognormal size distribution isobserved. Correspondingly, the simplest and, accordingto our tests, quite accurate way of simulating aerosoloptical properties with the parameters given in Table 1is using a lognormal function.

We represented aerosol concentration (and other pa-rameters with dynamic variability) as a function of op-tical thickness in a manner similar to other dynamicaerosol models (Remer and Kaufman 1998; Remer etal. 1998), which can help with the parameterization ofaerosols in climate models and satellite remote sensing.Presenting aerosol optical properties as regressions withoptical thickness helps to outline the dynamics of theaerosol optical properties associated with the growth ofthe aerosol mass and aerosol processes (aging, particlesize and composition transformations, etc.) stimulatedby the accumulation of aerosol in the atmosphere. Ad-ditionally, we present the Angstrom parameter (Ang-strom 1929) a, defined by the spectral dependence ofthe optical thickness t(l) ; l2a and computed fromtwo wavelengths, 440 and 870 nm. Here, a is a basicmeasure of the aerosol size distribution: a ; 0 corre-sponds to large dust particles, a ; 2 corresponds tosmall smoke particles. The single-scattering albedo is afunction of the refractive index (mainly its imaginarypart) and particle size. Therefore, we try to identify howspecific features in v0(l) are related to features in dV(r)/d lnr and k(l) and suggest a cause (physical, geograph-ical, meteorological, etc.) responsible for each feature.

d. Data limitations

The limitations of the presented data set should beoutlined.

First, sky-radiance measurements in general introducesampling bias, because cloudy days are underrepre-sented in the database (cf. Remer et al. 1997).

The inversion stability criteria [such as high aerosolloading required for more accurate retrieval of n(l),k(l), and v0(l)] introduce additional biases. Neverthe-less, these biases hardly decrease the value of the re-trieval results, because many other measurement tech-niques would likely suffer from somewhat similar dif-ficulties under low aerosol loading conditions. Indeed,low aerosol concentrations produces radiance fields ofrather small magnitude, which can easily be corruptedor distorted during detection by minor natural or in-strumental disturbances to the level where the effect ofa property such as aerosol absorption is almost indis-tinguishable. Also, larger uncertainties in absorption

(and index of refraction) at lower optical thickness likelywould have less impact on radiative forcing assessmentsand remote sensing developments. However, we do notwish to imply that aerosol absorption is not importantat low optical depths below 0.5 (e.g., at 440 nm). Forexample, Ackerman et al. (2000) have shown that ab-sorbing aerosol at text(550) 5 0.2 with v0(550) 5 0.88can result in reduced cloud coverage as a result of solarheating from aerosol in the boundary layer.

We choose to represent the retrieved aerosol prop-erties as regressions with optical thickness in the ab-sence of discrimination of seasonal and meteorologicalvariations in the optical properties. It should be notedthat for some aerosol sites considered, high opticalthickness (desirable for aerosol absorption retrieval) wasobserved only seasonally. We indicated such seasonalityin Table 1 for sites where it was observed. More detailedinformation on the seasonal and meteorological vari-ability of the aerosol properties for several of these sitescan be found in the studies by Holben et al. (2001), Ecket al. (1998, 2001a,b) and Smirnov et al. (2000a, 2002a,b), etc.

The retrieved parameters dV/d lnr, n(l), and k(l) arenot independent in the sense that the retrieval techniqueinsures only the fact that the retrieved combination ofall of these parameters would accurately reproduce themeasured radiation field in the scope of the chosen ra-diative transfer model. Correspondingly, the retrievalaccuracy of each individual aerosol parameter dV/d lnr,n(l), and k(l) is dependent on the accuracy of our ra-diative transfer model.

3. Aerosol optical property characterization

a. Biomass burning aerosol

1) 1) SINGLE-SCATTERING ALBEDO

Figure 1 compares v0(l) for all the sites studied.Biomass burning smoke is known as an absorbing aero-sol with high concentration of black carbon producedby combustion. However, our data show that the valueof v0 varies significantly for smoke of different origin(and possibly age) and correlates with the presence ofblack carbon in the combustion products. The highestabsorption (lowest v0) with the strongest spectral de-pendence was observed for African savanna regions.The lowest absorption was observed for the two forestedregions with v0 values very similar to each other at allwavelengths, even though these regions are very dis-similar in forest type and structure (Amazonian tropicalforest versus North American boreal forest). The v0

values of the South American cerrado region are inter-mediate in magnitude. Much of the differences in ab-sorption magnitude between these regions may be at-tributed to differences in the relative percentage of com-bustion occurring in the flaming versus the smolderingphases. Extensive field measurements in both Brazil andAfrica (Ward et al. 1992, 1996) have shown that for


TABLE 1. Summary of aerosol optical properties retrieved from worldwide AERONET network of ground-based radiometers.

Urban–industrialand mixed

GSFC, Greenbelt, MD(1993–2000)

Crete–Paris, France(1999)

Number of measurements (total)Number of measurements (for v0, n, k)Range of optical thickness; ^t&Range of Angstrom parameter^g& (440/670/870/1020)n; kv0(440/670/870/1020)rVf (mm); sf

rVc (mm); sc

CVf(mm3/mm2)CVc(mm3/mm2)

2400200 (Jun–Sep)0.1 # t(440) # 1.0; ^t(440)& 5 0.241.2 # a # 2.50.68/0.59/0.54/0.53 6 0.081.41 2 0.03t(440) 6 0.01; 0.003 6 0.0030.98/0.97/0.96/0.95 6 0.020.12 1 0.11 t(440) 6 0.03; 0.38 6 0.013.03 1 0.49 t(440) 6 0.21; 0.75 6 0.030.15 t(440) 6 0.030.01 1 0.04 t(440) 6 0.01

30040 (Jun–Sep)0.1 # t(440) # 0.9; ^t(440)& 5 0.261.2 # a # 2.30.68/0.61/0.58/0.57 6 0.071.40 6 0.03; 0.009 6 0.0040.94/0.93/0.92/0.91 6 0.030.11 1 0.13 t(440) 6 0.03; 0.43 6 0.052.76 1 0.48 t(440) 6 0.30; 0.79 6 0.050.01 1 0.12 t(440) 6 0.040.01 1 0.05 t(440) 6 0.02

Biomass burningAmazonian forest, Brazil

(1993–1994); Bolivia (1998–1999)South American cerrado, Brazil

(1993–1995)


rVc (mm); sc

CVf (mm3/mm2)CVc (mm3/mm2)

700250 (Aug–Oct)0.1 # t(440) # 3.0; ^t(440)& 5 0.741.2 # a # 2.10.69/0.58/0.51/0.48 6 0.061.47 6 0.03; 0.00093 6 0.0030.94/0.93/0.91/0.90 6 0.020.14 1 0.013t(440) 6 0.01; 0.40 6 0.043.27 1 0.58t(440) 6 0.45; 0.79 6 0.060.12 t(440) 6 0.050.05 t(440) 6 0.02

550350 (Aug–Oct)0.1 # t(440) # 2.1; ^t(440)& 5 0.801.2 # a # 2.10.67/0.59/0.55/0.53 6 0.031.52 6 0.01; 0.015 6 0.0040.91/0.89/0.87/0.85 6 0.030.14 1 0.01t(440) 6 0.01; 0.47 6 0.033.27 1 0.51t(440) 6 0.39; 0.79 6 0.040.1 t(440) 6 0.060.04 1 0.03 t(440) 6 0.03

Desert dust and oceanicBahrain–Persian Gulf

(1998–2000)Solar-Vil.–Saudi Arabia

(1998–2000)

Number of measurements (total)Number of measurements (for v0, n, k)Range of optical thickness; ^t&Range of Angstrom parameter^g& (440/670/870/1020)nk(440/670/870/1020)v0(440/670/870/1020)rVf (mm); sf

rVc (mm); sc


18001000.1 # t(1020) # 1.2, ^t(1020)& 5 0.220 # a # 1.60.68/0.66/0.66/0.66 6 0.041.55 6 0.030.0025/0.0014/0.001/0.001 6 0.0010.92/0.95/0.96/0.97 6 0.030.15 6 0.04; 0.42 6 0.042.54 6 0.04; 0.61 6 0.020.02 1 0.1 t(1020) 6 0.0520.02 1 0.92 t(1020) 6 0.04

15002500.1 # t(1020) # 1.5; ^t(1020)& 5 0.170.1 # a # 0.90.69/0.66/0.65/0.65 6 0.041.56 6 0.030.0029/0.0013/0.001/0.001 6 0.0010.92/0.96/0.97/0.97 6 0.020.12 6 0.05; 0.40 6 0.052.32 6 0.03; 0.60 6 0.030.02 1 0.02 t(1020) 6 0.0320.02 1 0.98 t(1020) 6 0.04

* Each value in the table is accompanied by a std dev, for example, 60.01 (this is not an accuracy of the retrieval). The values of realand imaginary parts of the refractive index, as well as single-scattering albedo, are given only for the condition of t(440) $ 0.4 for Urban–industrial, mixed, and biomass burning aerosols, and for the conditions of text(1020) $ 0.3 and a # 0.6 for desert dust. The parameters ofparticle size distribution are given for complete observed ranges in optical thickness and Angstrom parameter. The dynamic dependenciesof dust parameters are presented as functions of optical thickness at 1020 nm, since the regressions of optical parameters with text(1020)were more robust than those with text(440) for this aerosol type.

savanna ecosystems ;85% of the biomass (largelygrass) was consumed by flaming combustion while, fordeforestation fires, ;50% or less of the combustion wasin the flaming phase. However, differences in absorptionmay also be due in part to other factors such as theinfluence of the moisture content of the fuel, the degreeof aging of the particles (Reid et al. 1999; Jacobson etal. 2001), ambient temperature, relative humidity, andfire intensity. Although high-intensity tree-crown firesare common in boreal forests, and these predominatelyflaming phase crown fires likely produce significantamounts of black carbon (Cofer et al. 1998), our datafor boreal forest fire smoke suggest that this phase of

the burning does not dominate the smoke production inthe boreal zone. The relatively high v0 values we mea-sure in boreal forest regions are likely due to smolderingcombustion occurring over a much longer period of timerelative to the comparatively short lives flaming phaseof the crown fires. Radke et al. (1991) presented mea-surements (at 2.0–2.5-km altitude) of v0 as a functionof time after ignition for two small North Americanforest fires. They showed a rapid increase in v0 as thefires progressed from intense burning (initial v0 , 0.7)to predominantly smoldering combustion with the v0

values stabilizing at ;0.92 approximately 60 min afterignition. In the South American cerrado region, there is


TABLE 1. (Continued)

Urban–industrial and mixedMexico City(1999–2000)

Maldives (INDOEX)(1999–2000)


rVc (mm); sc

CVf(mm3/mm2)CVc(mm3/mm2)

15003000.1 # t(440) # 1.8; ^t(440)& 5 0.431.0 # a # 2.30.68/0.61/0.58/0.57 6 0.071.47 6 0.03; 0.014 6 0.0060.90/0.88/0.85/0.83 6 0.020.12 1 0.04 t(440) 6 0.02; 0.43 6 0.032.72 1 0.60 t(440) 6 0.23; 0.63 6 0.050.12 t(440) 6 0.030.11 t(440) 6 0.03

700150 (Jan–Apr)0.1 # t(440) # 0.7; ^t(440)& 5 0.270.4 # a # 2.00.74/0.67/0.64/0.63 6 0.051.44 6 0.02; 0.011 6 0.0070.91/0.89/0.86/0.84 6 0.030.18 6 0.03; 0.46 6 0.042.62 1 0.61 t(440) 6 0.31; 0.76 6 0.050.12 t(440) 6 0.030.15 t(440) 6 0.04

Biomass burningAfrican savanna, Zambia

(1995–2000)Boreal forest, United States and Canada

(1994–1998)


rVc (mm); sc


2000700 (Aug–Nov)0.1 # t(440) # 1.5; ^t(440)& 5 0.381.4 # a # 2.20.64/0.53/0.48/0.47 6 0.061.51 6 0.01; 0.021 6 0.0040.88/0.84/0.80/0.78 6 0.0150.12 1 0.025t(440) 6 0.01; 0.40 6 0.013.22 1 0.71t(440) 6 0.43; 0.73 6 0.030.12 t(440) 6 0.040.09 t(440) 6 0.02

1000250 (Jun–Sep)0.1 # t(440) # 2.0; ^t(440)& 5 0.401.0 # a # 2.30.69/0.61/0.55/0.53 6 0.061.50 6 0.04; 0.0094 6 0.0030.94/0.935/0.92/0.91 6 0.020.15 1 0.015t(440) 6 0.01; 0.43 6 0.013.21 1 0.2t(440) 6 0.23; 0.81 6 0.20.01 1 0.1 t(440) 6 0.040.01 1 0.03 t(440) 6 0.03

Desert dust and oceanic Cape Verde (1993–2000) Lanai, HI (1995–2000)

Number of measurements (total)Number of measurements (for v0, n, k)Range of optical thickness; ^t&Range of Angstrom parameter^g& (440/670/870/1020)nk(440/670/870/1020)v0(440/670/870/1020)rVf (mm); sf

rVc (mm); sc


915003000.1 # t(1020) # 2.0; ^t(1020)& 5 0.3920.1 # a # 0.70.73/0.71/0.71/0.71 6 0.041.48 6 0.050.0025/0.0007/0.0006/0.0006 6 0.0010.93/0.98/0.99/0.99 6 0.010.12 6 0.03; 0.49 1 0.10 t 6 0.041.90 6 0.03; 0.63 2 0.10 t 6 0.030.02 1 0.02 t(1020) 6 0.030.9 t(1020) 6 0.09

8001500.01 # t(1020) # 0.2 ^t(1020)& 5 0.040 # a # 1.550.75/0.71/0.69/0.68 6 0.041.36 6 0.010.0015 6 0.0010.98/0.97/0.97/0.97 6 0.030.16 6 0.02; 0.48 6 0.042.70 6 0.04; 0.68 6 0.040.40 t(1020) 6 0.010.80 t(1020) 6 0.02

a combination of smoke from the local burning of cer-rado (savanna-like) vegetation and agricultural pastureburning in addition to the long range transport of smokefrom Amazonian forest regions to the north. Thus theintermediate magnitude of v0 at the cerrado sites is due(Eck et al. 2001a) in part to a mixture of smoke fromdifferent source regions and also possibly from the burn-ing of small cerrado trees that sometimes occurs asso-ciated with conversion of native cerrado ecosystems toagricultural land use. The spectral dependence and mag-nitude of v0 inferred from analysis of spectral irradiancedata for a cerrado site in Brazil (Eck et al. 1998) wassimilar to the Amazonian forest values in Fig. 1 whentransport from the north-of-forest burning smoke oc-curred, versus values more resembling African savannav0 when smoke originated from regional cerrado burn-ing.

Comparison of the AERONET retrievals of v0 forbiomass-burning aerosols in South America with in situ

aircraft measurements made during the Smoke, Cloudsand Radiation-Brazil (SCAR-B) experiment show thatAERONET values are significantly higher. For regionalhazes over a region of forest in Amazonia, Reid et al.(1998) computed an average v0 value at 550 nm of 0.86with a standard deviation of 0.05. This compares to anaverage v0 of 0.935 from AERONET retrieval for thesame Amazonian forest region. Similarly, in situ mea-surement from aircraft over Brazilian cerrado siteshowed average v0(550) 5 0.79 6 0.04 for locallyproduced smoke and v0(550) 5 0.85 6 0.02 for agedsmoke (Reid et al. 1998), as compared to v0(550) 50.90 6 0.02 retrieved from AERONET over Braziliancerrado. It is noted that v0 determined from in situ mea-surement techniques are typically lower than AERO-NET retrieval values (see comparison for GoddardSpace Flight Center (GSFC), Mexico City, and Maldivesin section 3b(1). The cause for those significant differ-ences from different measurement types (in situ versus


remote sensing) is not fully understood and should bethe focus of future examination.

2) 2) PARTICLE SIZE DISTRIBUTION

The particle size distribution for all smoke from allregions investigated is dominated by the accumulationmode. Correspondingly, the following features of smallparticle scattering are observed: (i) high values of a (1.7; 2.0); (ii) the decrease of v0(l) with increasing l; and(iii) the pronounced decrease of the asymmetry param-eter to relatively low values [from g(440) 5 0.69 tog(1020) 5 0.52]. At the same time, the aerosol sizedistributions of the smoke in these different regions alsodemonstrate distinct differences. The fine-mode medianradius is smallest for the African savanna smoke andlargest for the smoke from both forest regions (Ama-zonian and boreal). The larger-sized particles for smokein forested regions may be partly a result of the greaterpercentage of smoldering combustion, as Reid andHobbs (1998) measured larger particle sizes for fresh(,4 min old) smoldering smoke (0.145-mm volume me-dian radius) than for fresh flaming-phase smoke (0.12mm). Other factors that affect the particle size, in ad-dition to the phase of combustion, are the characteristicsof the fuel, the degree of aging of the particles, fireintensity, and ambient relative humidity and tempera-ture. The size of the fine-mode biomass burning particlesfor all four regions is dynamic, exhibiting increases insize as aerosol optical depth increases. This correlationbetween fine-mode median particle size and ta is likelyrelated to aging of the aerosol and associated changesin particle size distribution as a result of coagulation,condensation, and gas-to-particle conversion (Reid etal. 1998). Comparison of the fine-mode volume medianradius of the AERONET cerrado retrievals to valuesmeasured in situ from aircraft (Differential MobilityParticle Sizes instrument) during the SCAR-B experi-ment (Reid et al. 1998) for a cerrado site shows similarvalues for both local cerrado smoke [assuming taer(440)5 1.0] and aged smoke [assuming taer(440) 5 2.0].

3) 3) INDEX OF REFRACTION

The retrievals of the real part of the refractive indexfor biomass burning smoke range from an average of1.47 for Amazonian forest region smoke to 1.52 forSouth American cerrado smoke. Yamasoe et al. (1998)also retrieved refractive indices from some of the sameAERONET datasets for one of the cerrado sites but witha different methodology and found mean values rangingfrom 1.53 at 440 nm to 1.58 at 1020 nm. Other inves-tigators have estimated the real part of the refractiveindex of biomass burning aerosols to range between;1.52 and ;1.55 (Westphal and Toon 1991; Lenoble1991; Li and Mao 1990).

b. Urban–industrial aerosol

The optical properties of urban–industrial aerosolsalso demonstrate significant variability, depending onthe complex combination of natural and anthropogenicfactors influencing aerosol formation and evolution in-cluding relative humidity, cloudiness, altitude, fueltypes, emission characteristics, etc.


Haze at GSFC is almost nonabsorbing [v0(550) ;0.97], while the pollution of Mexico City [v0(550) ;0.89] and aerosol over the Maldives [v0(550) ; 0.90]absorb almost as strongly as African savanna smoke.The aerosol absorption in Creteil (a suburb of Paris) isintermediate [v0(550) ; 0.94–0.93] to the absorptionof aerosols in GSFC and Mexico City. The retrievedlow absorption values at GSFC are close to the valuesexpected for water-soluble aerosol (Shettle and Fenn1979; Koepke et al. 1997) with high relative humidity(Remer and Kaufman 1998; Tanre et al. 1999). However,other models give much lower v0 values for urban aero-sol such as v0(550) ; 0.82 by Hess et al. (1998) andv0(550) ; 0.84 by Shettle and Fenn (1979) for relativehumidity (RH 5 90%). The AERONET retrievals forGSFC are in reasonable agreement with in situ aircraftmeasurements from aircraft in the SCAR-America(SCAR-A; Remer et al. 1997) and the TroposphericAerosol Radiative Forcing, Observational Experiment(TARFOX; Hegg et al. 1997; Russell et al. 1999; Hartleyet al. 2000). The integration of aircraft in situ mea-surements during SCAR-A (Remer et al. 1997) showv0(450) ; 0.98–0.99. The TARFOX estimates (Hegget al. 1997) of average single-scattering albedo of am-bient (wet) aerosol were lower: v0(550) 5 0.94 (‘‘meanupper limit’’). However, the reanalysis of the same setof the measurements by Hartley et al. (2000) gave highervalues of single-scattering albedo of hydrated aerosol[v0(550) 5 0.95 6 0.03]. The estimates of v0 by Rus-sell et al. (1999) simulated from in situ aircraft sizedistribution for the values of refraction index n 5 1.4and k 5 0.005 (close to our retrieval results) gave similarvalues [v0(550) ; 0.95].

The highest absorption of urban–industrial aerosol forour small sample of urban sites was observed in MexicoCity [v0(550) ; 0.90], however it is still significantlylower than reported by many models. For example, Hesset al. (1998) give v0(550) ; 0.84, and Shettle and Fenn(1979) give v0(550) ; 0.79 for urban aerosol with RH5 80% and even lower values for RH 5 50%–60%,which are typical relative humidities for Mexico City(Baumgardener et al. 2000). High aerosol absorption inMexico City was also observed by in situ measurements(Vasilyev et al. 1995; Baumgardener et al. 2000). Theestimates of single-scattering albedo from aerosol sizedistributions obtained by a photoelectrical counter nearthe ground (Vasilyev et al. 1995) gave the very low


values of v0(550) ; 0.6–0.8. More recent measure-ments of Mexico City aerosol by the nephelometer andabsorption photometer (Baumgardener et al. 2000; D.Baumgardener 2001, personal communication) indicatesingle-scattering albedo values closer to our retrievalresults v0(550) ; 0.80–0.88, but still lower.

The aerosol observed over the Maldives, as a part ofthe INDOEX experiment, shows absorption [v0(550) ;0.90–0.91] that is similar to that observed for MexicoCity. Such high aerosol absorption over the Maldivesagrees well with other results of the INDOEX experi-ment conducted in the same region and for a partiallyoverlapping time frame to our measurements (Eck et al.2001b; R01; Satheesh et al. 1999). Several independenttechniques were used during the INDOEX experimentto estimate the aerosol single-scattering albedo, v0, uti-lizing both in situ and remote sensing techniques basedon measurements made from land, ships, and aircraft.Comparison of retrievals from all of these techniqueswith the addition of the Kaashidho Climate Observatory(KCO) AERONET (‘‘KCO-AERONET’’) retrieval (Du-bovik and King 2000) was presented by Ramanathan etal. (2001). The v0 values estimated for 530 nm obtainedby these diverse methods for the Maldives–INDOEXregion ranged from ;0.86 to 0.90 for column averages.These values show good agreement, within the uncer-tainty levels of the AERONET and in situ retrievals (fora more detailed discussion see R01 and Eck et al.2001b).

Unfortunately, there have not yet been any reportedretrievals or measurements of v0 for the Paris region.Nevertheless, the existing aerosol chemical measure-ments (Rueallan and Cashier 2001; Liousse and Cashier1992) near surface indicate high concentrations of blackcarbon in the Paris aerosol.

The observed wide variability of v0 for the urbanlocations probably can be explained by differences infuel types, emission conditions, long-range transportand environmental and meteorological conditions. Au-tomobile traffic around GSFC is the strongest localsource of pollution, while pollution transported longdistances from the Gulf of Mexico, Tennessee and Ohiovalleys, etc. is also present. The mixed aerosols ob-served over the Maldives (INDOEX) are produced pri-marily as a result of anthropogenic combustion pro-cesses mainly from the use of fossil fuels (Novakov etal. 2000) with some biomass fuels and also various in-dustrial processes. The large number of diesel vehicleand two-stroke engines is also a significant factor inaerosol formation in the Indian subcontinent (Satheeshet al. 1999). Correspondingly, the relatively strong ab-sorption properties of the aerosols observed in the Mal-dives (INDOEX) is due to the presence of soot primarilyfrom fossil fuel combustion and biomass burning, whichSatheesh et al. (1999) have determined contributes;11% to the midvisible aerosol optical depth[taer(500)]. The in situ aerosol measurements from Paris(Liousse and Cachier 1992) indicate significant presence

of the atmospheric inputs from fossil fuel combustion.The intense traffic (with a larger fraction of diesel en-gines in Europe compared to the United States) affectsthe aerosol in Paris (Rueallan and Cachier 2001). Also,the transport of aerosol from Eastern Europe and theshorter distance from sources of sulfate (so that less SO2

converts to SO4) and/or lower emissions of SO2 relativeto the United States (due to the use of nuclear powerrather than coal burning) can be important factors af-fecting aerosol formation in Paris. Emission controls ofcar and industrial pollution is more advanced in Francethan in Mexico and India, which may contribute to theless absorbing aerosol in Paris than in Mexico City andthe Indian subcontinent.


Comparing the particle size distribution of urban–industrial aerosol in different locations (Fig. 1, Table1), one notes the same tendencies as those seen in v0

comparisons: the aerosol at GSFC is more similar to theaerosol in Creteil–Paris than to aerosols in Mexico Cityand the Maldives. The total volume of fine-mode par-ticles is clearly larger than the total volume of coarse-mode particles for GSFC (CVf/CVc ; 3) and Creteil (CVf/CVc ; 2.5) aerosols. Nevertheless, it is noted that theretrieved optical properties of all urban–industrial aero-sols sites studied are dominated by fine particle scat-tering. This results in v0(l) decreasing with increasingl, while a is quite high and the asymmetry factor g isstrongly decreasing to low values with increasing l.This domination of fine particle scattering can be ex-plained by the fact that light in the considered spectralrange (440–1020 nm) is much more efficiently scattered(cf. Bohren and Huffman 1983) by particles of fine-mode sizes (r , 0.6 mm) than coarse-mode particles (r. 0.6 mm).

Our particle size distribution retrievals agree wellwith various in situ aerosol measurements for the GSFCregion. The in situ aircraft measurements (Hartley et al.2000) of dV/d lnr show distinct bimodality (with cleardomination of fine-mode volume) at different altitudeswith maximums at rVf ; 0.15–0.17 mm and rVc ; 2.5–5 mm for taer(450) ranging from 0.5 to 0.6. For the sameoptical depth levels our retrieval yields rVf ; 0.17–0.18mm and rVc ; 3.0 mm. The aerosol particle size distri-butions retrieved from the airborne optical particle coun-ter (Hignett et al. 1999) and nephelometer measurements(Russell et al. 1999) also show domination of fine-modeparticles with rVf ; 0.1–0.2 mm (after recalculating tovolume distributions). The detailed comparison of theresults of the ground-based size distribution retrieval(using the same AERONET measurements but a dif-ferent inversion code) with aircraft in situ measurementshas been performed for data of the SCAR-A experiment(Remer et al. 1997). The comparison showed goodagreement of both techniques in the placement of themodes of dV/d lnr (rVf ; 0.1–0.2 mm; rVc ; 1.0–2.0


mm), with better agreement for fine-mode particles. Ourretrieval shows similar values for rVf, but coarse par-ticles have a larger size in our retrieval: rVc ; 3–3.5mm. It is important to note that the comparison of Remeret al. (1997) outlined a number of fundamental differ-ences between remote sensing and in situ measurements,which make the comparisons of the remote sensing andin situ measurements rather difficult and uncertain.

For the Mexico City site, our observations are in qual-itative agreement with available in situ measurements.Measurements (at a nearby mountain ;400 m above thecity) of the mass of aerosol transported from the citybasin showed significant presence (;50% of the totalaerosol mass) of the large particles with the radius;1.5–5 mm (Raga et al. 1999; Baumgardener et al.2000). The measurement (Baumgardener et al. 2000) ofthe volume particle size distribution of the aerosol finemode (0.05 , r , 0.5 mm) showed a maximum at r ;0.15 mm, which is in good agreement with our results[rVf ; 0.14 mm at the mean taer(440)].

In order to verify the results for Maldives aerosol, acomparison of our retrieval with in situ-measured sizedistributions (S. Howell 2001, personal communication)vertically integrated from aircraft (;80 km from theAERONET site on Kaashidhoo) was done for one day,7 March 1999. Some of the data corrections of the air-craft data were preliminary, however the initial com-parison between the size distributions for these two verydifferent approaches showed bimodality for both data-sets with both distributions also showing very similarlysized particles for each of the modes. It is necessary tonote that our data (Table 1 and Fig. 1) represent resultsaveraged for the whole period of observations. However,as Satheesh et al. (1999) have discussed in detail, theproperties of aerosol over the Maldives (during the IN-DOEX experiment) were rather variable. [The variationsobserved in AERONET retrievals are described in detailby Eck et al. (2001a).] They identified several majorcomponents to the aerosol, which contribute in varyingamounts to the total loading. The fine mode aerosolsobserved over Maldives are produced primarily as aresult of anthropogenic combustion processes mainlyfrom the use of fossil fuels. The coarse-aerosol moderesults partly from combustion processes and partlyfrom entirely different processes and source regions.These aerosols have significant contributions from seasalt formed from the action of ocean waves and fromthe long distance transport of airborne soil dust fromarid and semiarid regions, such as the Arabian Peninsulaand the Thar Desert.

Growth of the aerosol particles

The increase in fine mode size as optical thicknessincreases is noticeable in our retrievals for some sites.Figure 2 illustrates the observed change of size distri-bution as a function of optical thickness for GSFC. Itshows the increase of the median size of the fine mode

with increasing optical thickness [from ;0.12 mm attaer(440) 5 0.04 to ;0.21 mm at taer(440) 5 0.9]. Sim-ilar growth related to optical depth magnitude can beseen for the aerosol in Creteil (Table 1). The same phe-nomenon was observed by both ground-based remotesensing and aircraft in situ measurements during theSCAR-A experiment in the mid-Atlantic region of theeastern United States (Remer et al. 1997). The hygro-scopic growth of small particles with high humidity(Kotchenruther et al. 1999) is one of the possible mech-anisms responsible for the observed increase of the me-dian radius of the aerosol fine mode at GSFC with in-creasing aerosol loading. Indeed, there are a number ofobservations supporting this assumption. A strong cor-relation between aerosol optical thickness and total col-umn water vapor content is observed at GSFC (Smirnovet al. 2000a; Holben et al. 2001). TARFOX results showthat condensed water on aerosols is the main contributorto the aerosol optical thickness on the U.S. east coast(Hegg et al. 1997). The variation of the relative humidityderived from lidar measurement during the TARFOXexperiment was found to be highly correlated with theeffective radius derived by remote sensing techniquesfrom aircraft measurements (Ferrare et al. 2000). In ad-dition to hygroscopic growth, the aging processes ofcoagulation, condensation, and gas-to-particle conver-sion may also contribute to the increase in particle size(Reid et al. 1998; Jacobson 2001). Indeed, a similar butmore moderate increase in fine particle size with in-creasing aerosol optical depth was observed at othersites (Mexico City and all biomass burning sites) wherehigh humidity is not necessarily a primary factor. At theMaldives site this phenomenon was hidden due to theaveraging performed on the retrievals for the wholemeasurement period (2 yr). A more detailed consider-ation (accounting for different aerosol sources) of theaerosol retrievals in the Maldives indicates the presenceof fine-mode particle growth with optical thickness inthe 1999 northeast monsoon season (Eck et al. 2001b).

It should be noted that some rather minor increase(;10%–25% of rVc) of the median radius of the coarsemode with increasing aerosol optical thickness can alsobe observed at urban and biomass burning sites. How-ever, the magnitude of observed increase is comparableto the retrieval accuracy levels and there is no inde-pendent data to confirm this trend.


The indices of refraction [n(l) and k(l)] are not in-dependent from the v0(l) and size distribution in ourretrievals. Nevertheless, some different tendencies areobtained for the different aerosol types. Namely, forbiomass burning aerosols, higher v0 values were cor-related only with smaller values of the imaginary partof the refractive index. This kind of correlation is ex-pected because, in the Mie formalism, k(l) predeter-mines (Bohren and Huffman 1983) the absorption of


FIG. 2. The average aerosol volume size distribution retrieved at GSFC for aerosol optical thickness at 440 nm varying from 0.04 to 0.92.The aerosol size distributions were derived from the measurements of AERONET ground-based radiometers for 1993–2000 time period.

light by small particles (while the ratio of absorption toscattering 1 absorption also depends on particle size).For urban–industrial aerosols, higher v0 is somewhatcorrelated with lower real part of the refractive index(1.39 for GSFC, 1.40 for Creteil, 1.47 for Mexico City,and 1.44 for Maldives). This correlation is not the resultof interconnections assumed by the radiative model em-ployed. Actually, there is an opposite tendency, accord-ing electromagnetic theory (Bohren and Huffman 1983)that the total scattering increases with an increase of n.Therefore, this correlation likely appears due to geo-physical reasons rather than interconnections assumedby the radiative model employed. The sites with lowerreal parts of the refractive index are possibly associatedwith high relative humidity and resultant aerosol hy-groscopic growth (e.g., over GSFC in the summer) andthe higher n with higher concentrations of black carbonin the atmosphere (e.g., in Mexico City and the Mal-dives).

The results of our refraction index retrieval agree withthe results of available (unfortunately, very limited inthe locations considered) independent studies. Namely,the TARFOX experiment estimates of the refractive in-dex ranged from 1.33 to 1.45 for the real part and 0.001to 0.008 for the imaginary part. These values were de-rived from a combination of aerosol in situ size distri-

bution and remote sensing (Redemann et al. 2000) andagree well with our values for GSFC.

It should be noted that our estimates of the real partof the refractive index do not show any significant spec-tral dependence. However, for some cases we did ob-serve small spectral dependence (e.g., ranging from 1.38to 1.41 for GSFC, and from 1.42 to 1.46 for the Mal-dives aerosol). However, we presented only the averagedvalues in the Table 1 because observed spectral depen-dencies of n were within our uncertainty levels and mostlikely appeared due to calibration or other biases.

c. Desert dust aerosol

The domination of large particles (r . 0.6 mm) indesert dust aerosol (see Fig. 1 and Table 1) is the prin-cipal feature differentiating the optical properties of dustfrom fine-mode dominated biomass burning and urban–industrial aerosols. Therefore, in this section we firstdiscuss the results of our size distribution retrieval fol-lowed by a discussion of the retrieved v0(l) and indexof refraction. Also, we add a discussion of the effect ofparticle shape, which appeared to be an issue only forour desert dust retrievals.



The size distributions of desert dust (see Table 1 andFig. 1) are always bimodal and dominated by large par-ticles. Correspondingly, in contrast to biomass burningand urban–industrial aerosol, a is low (ranges from;1.2 down to 20.1) and the phase function asymmetryis relatively high at all wavelengths considered. Somedifferences for dust of different geographic origin arealso observed. Desert dust from the western part of Af-rica and the Arabian Peninsula (Saudi Arabia and CapeVerde) are strongly dominated by large particles (CVc/CVf ; 50) and seem to have optical properties morerepresentative of so-called pure desert dust. The aerosolin Bahrain–Persian Gulf has a larger fine mode (CVc/CVf ; 10) than observed in Saudi Arabia and in CapeVerde. This difference relates to the frequent presencein the Persian Gulf of small particles produced by in-dustrial activity (Goloub and Arino 2000; Smirnov etal. 2002a,b). The median sizes of the fine and coarsemodes (rVf ; 0.12–0.15 mm and rVc ; 1.9–2.54 mm)do not show any dynamics with aerosol loading andtherefore have smaller values than those for biomassburning and urban–industrial aerosols for the range ofhigh optical thickness (see Table 1). A comprehensivecomparison of our results with other existing informa-tion is difficult, since the literature on dust-measuredsize distributions is very sparse. The in situ informationis based on measurements taken mostly on ground level,while our retrieval is for the whole vertical atmosphericcolumn. The efficiency of dust in situ sampling used inthese measurements, may depend on the particle size(Fouquart et al. 1987a). The properties of the dust aero-sol may also differ due to variability of sources, ordistance from the source (Sokolik et al. 1998) althoughCarlson and Benjamin (1980) observed rather similardust particle size in several successive Saharan dust out-breaks analyzed during the Global Atmospheric Re-search Program Atlantic Tropical Experiment. Our sizeretrievals in general agree with existing models and oth-er independent observations. For example, in severalmodels (Koepke et al. 1997; Tegen and Lacis 1996), themedian radius of the coarse mode is about 2 mm. Mea-surements of Levin et al. (1980) for dust storms overthe Israeli desert, and Patterson and Gillette (1977) overTexas, also show that the dust surface area distributionhas a maximum around 2 mm. Dust originating fromChina and measured over Japan also was found to haveparticle radius around 2 mm (Tanaka et al. 1989). Themeasurements of Li-Jones and Prospero (1998), Ari-moto et al. (1997) and Haywood et al. (2001; if mea-sured dN/dr is transformed into dV/d lnr) give size dis-tributions with the maximum for the sizes ranging from1.0 to 5.0 mm. At the same time, there are some dis-agreements with other reported data. For instance,d’Almeida and Schulz (1983) present mineral aerosol-derived particle size with maximums in a wide sizerange up to 100 mm and larger. Maring et al. (2000)

retrieved number size distribution with number medianradius ;0.1 mm and less (which corresponds to volumemedian radius less than 1 mm). The model of Koepkeet al. (1997) assumes accumulation and mineral-trans-ported components with a maximum of the mass sizedistribution at ;0.4–0.5 mm. Our retrievals do not showany significant presence of these components, howevera minor secondary peak presents around r 5 0.5 mmfor the Cape Verde retrieval in Fig. 1.


Due to the domination of large particles, desert dustv0(l) increases or is neutral with l (Fig. 1 and Table1). Our retrieved spectral single-scattering albedos sug-gest that dust has significantly less absorption than the0.63–0.89 v0 values at 0.5 mm simulated according toseveral models (Shettle and Fenn 1979; WMO 1983;Koepke et al. 1997; Hess et al. 1998). This divergenceis probably the result of the existing discrepancy be-tween dust absorption reported from in situ measure-ments and absorption inferred from the radiation fieldin the atmosphere (Tanre et al. 2001, hereafter T01).The results of in situ measurements incorporated in theabove models indicate the presence of significant dustabsorption in the visible part of the spectrum (e.g., Pat-terson et al. 1977; Haywood et al. 2001). Recent satelliteretrievals (Kaufman et al. 2001; T01) show low dustabsorption values in the visible, results that are quitesimilar to our results. Some other earlier measurementsand analysis (e.g., Fouquart et al. 1987b; Otterman etal. 1982; Carlson and Benjamin 1980) also support theretrieved low dust absorption in the visible to near-in-frared wavelengths.

Modeling studies of the radiative properties of dustalso outline some difficulties in predicting mineral dustabsorption (Ackerman and Toon 1981; Claquin et al.1998, 1999; Sokolik and Toon 1999). In fact, from theviewpoint of mineralogical composition the dust ab-sorption is predetermined by the presence of hematite(iron oxide). Recent efforts on incorporating mineral-ogical composition into modeling radiative propertiesof dust (Claquin et al. 1998, 1999; Sokolik and Toon1999) emphasize that the way hematite is mixed withquartz or clay is complicated and strongly impacts theresulting absorption. These mineralogical studies indi-cate that a lack of consideration of these mixing mech-anisms is a significant limitation of the previous dustabsorption computations.

It should be noted that, due to the variable presenceof small particles in Bahrain, v0(l) as well as refractiveindex are also very variable at this site. The refractiveindex and v0(l) at Bahrain demonstrate stable valuesand spectral behavior consistent with those demonstrat-ed by desert dust in other locations only when the Ang-strom parameter is lower than 0.6 (the details of aerosoldynamics in Bahrain are given by Smirnov et al. 2002a).For this reason, v0(l) and refractive index, are shown


for Bahrain only for cases when the Angstrom parameteris lower than 0.6. However, the particle size distributionshown for Bahrain represents all observed cases reflect-ing the bimodal structure of the size distribution char-acteristic of this location.


Several models suggest that the real part of the re-fractive index of dust is 1.53 for the visible spectralregion (Shettle and Fenn 1979; WMO 1983; Koepke etal. 1997). This value is usually employed in remotesensing and allows for good consistency of radiativetransfer computations with measurements (Tanre et al.1999; T01). However, the in situ measured values re-ported in the literature may deviate from 1.53 (due todifferences in the dust composition and probably alsodue to differences in the measurement techniques) witha range of about 60.05 or more (e.g., Patterson et al.1977; Carlson and Benjamin 1980; Sokolik et al. 1993;Sokolik and Toon 1999). Thus, our retrieved values of1.48–1.56 also agree in general with available dust mea-surements.

As discussed in section 3c(1), our retrieval showssignificantly higher v0 values than many aerosol modelssuggest. Similarly, the retrieved imaginary part of therefractive index ranging from 0.0006 to 0.003 are small-er than the 0.008 value given for the visible spectrumby several models (Shettle and Fenn 1979; WMO 1983).A comparably low imaginary part of the refractive indexwas indicated (k 5 0.003) by Levin et al. (1980) and(k 5 0.001) by Otterman et al. (1982). Another featureof the retrievals is the spectral dependence of the imag-inary part, where k(l) is 3–4 times higher at 440 thanat the longer wavelengths. Such spectral dependence isnot surprising for desert dust and has been reported(however for higher absolute values of k) in many stud-ies (e.g., Patterson et al. 1977; Sokolik et al. 1993;Koepke et al. 1997; Sokolik and Toon 1999). Thus, ourretrieved values of the imaginary part of the refractiveindex have similar spectral dependence but much lowervalues than were observed by in situ measurements.

4) 4) NONSPHERICITY OF DUST PARTICLES

Extensive testing of the inversion algorithm (Duboviket al. 2000) has shown the sensitivity of AERONETretrievals to dust particle nonsphericity. According tothese tests, the presence of nonspherical dust particlesshould result in the following retrieval artifacts: (i) highconcentration of very small particles with radius lessthan 0.1 mm and (ii) strong spectral dependence of thereal part of the refractive index [n(l) increases with l].These artifacts appear in the inversion simulation ofnonspherical particles in almucantar radiances at solarzenith angle Q0 $ 458 (i.e., inverted scattering anglesare up to double the value of the solar zenith angle) anddisappear at Q0 , 208. Features very similar to these

artifacts were clearly observed in the retrievals for theobservations at all desert dust sites [for a , 0.6 and/or t(1020) . 0.2]. Figure 3 illustrates such retrieval forBahrain for the 2 May 1999 dust event. Table 1 andFig. 1 display only corrected retrievals of dV/d lnr andn(l). The applied corrections (described in section 2)allow us to retrieve a more accurate shape of dV/d lnrand value of n. However, it is important to emphasizethat the Mie simulations based on the size distributionsand index of refraction given in Table 1 may not re-produce accurately all of the optical properties of thedust. Namely, the appearance of artifacts in the retrievalswith Q0 $ 458 (i.e., using measured radiances corre-sponding to scattering angles $908) indicates that ac-curate modeling of the phase function at scattering an-gles $908 needs to account for the deviations of theparticle shape from spherical. Figure 4a illustrates thedifferences between phase functions of spheres and ran-domly oriented spheroids for Cape Verde desert dust[dV/d lnr, n(l), and k(l) simulated according Table 1].At the same time, the retrieval tests (Dubovik et al.2000) and forward calculation result (Mishchenko et al.1997) show that satisfactory values of v0(l) as well asg(l) (also see Fig. 4) can be obtained by applying Miescattering. Retrieval sensitivity tests (Dubovik et al.2000) modeled nonspherical scattering using an ap-proximation of the dust particle shape by randomly ori-ented spheroids (Mishchenko et al. 1997). This is onlyone of many available models of nonspherical scattering(cf. Mishchenko et al. 2000; Yang et al. 2000; Zakharovaand Mischenko 2000; etc.) and it is unlikely that naturaldust is represented by spheroids only. Nevertheless, thesimilarity of the artifacts observed in the retrievals tothose observed in the sensitivity tests (Dubovik et al.2000) used randomly oriented prolate spheroids withaspect ratio ;2) suggests that the chosen nonsphericalmodel is rather adequate. Future detailed studies arenecessary to clarify this issue and to incorporate non-sphericity to the AERONET retrievals.

The presence of nonsphericity in desert-dust lightscattering was detected in many previous observations(cf. Nakajima et al. 1989, and detailed discussion byMishchenko et al. 1997). However, the significance ofthe dust nonsphericity is not a completely clarified issue.For example, ground-based and satellite remote sensingstudies (Kaufman et al. 1994; T01) did not show a sig-nificant presence of nonspherical scattering by dust (forscattering angle #1208). This possibly can be explainedby the fact that a confident retrieval of nonsphericaleffects requires redundant spectral and, in particular,angular (in the scattering angle range from 08 to $1208)measurements. Indeed, in the studies of Kaufman et al.(1994) and T01, the retrievals of size distributions andphase functions were performed from sky radiancesmeasured in the solar aureole (scattering angle #408)where nonspherical effects are minimal (e.g., Fig. 4a).Also, the nonspherical scattering observed in the dustsky radiance measurements is less pronounced than it


FIG. 3. Illustrations of the retrieval artifacts caused by the presence of the nonspherical particles that appear at low solar zenith angles(due to using large scattering angles in the retrieval): (a) artificially high concentrations of very small particles with radius #0.1 mm; (b)an artificial spectral dependence of the real part of the refractive index. The data presented were observed in Bahrain during a dust eventon 2 May 1999, when the optical thickness of the dust was nearly constant at all wavelengths considered (within 0.02).

is in most models (probably, due to the constant pres-ence of some fine mode particles). For example, ourretrieval algorithm fit AERONET radiances measuredin the almucantar with a root-mean-square of the fittingerror ;15% or less. The fitting error has clear angulardependence that increases for higher scattering anglesand reaches a maximum of 30%–35% at scattering an-gles ;1008–1208 (Dubovik et al. 2000). Differences ofthe same magnitude were observed by T01, but wereconsidered insignificant.

It should be noted that nonsphericity is not likely tobe an issue for the fine-mode-dominated biomass burn-ing and urban–industrial aerosols. This is because thescattering of visible and near-infrared light (we use 440–1020 nm) is not sensitive to the nonsphericity of finemode particles [because the wave number of dominating(rVf) particles is rather small 2pr/l , 3]. Figure 4billustrates that the phase functions at 440 nm of spheresand prolate spheroids with aspect ratio 2 are practicallyidentical for Mexico City aerosol size distribution (cho-sen for this illustration because of pronounced presenceof the coarse mode). Besides, the analysis of microscopeimages of biomass burning (Martins et al. 1998) andINDOEX study region particles (R01) showed that theseparticles were largely spherical.

d. Oceanic aerosol

Here we discuss optical properties of the aerosol ob-served at Lanai, Hawaii. We expect that aerosol of mar-itime origin dominates this aerosol, even though someinfluence of long-range transport of Asian dust and pol-lution may also be present. An important characteristicof the oceanic aerosol is the substantially lower opticalthickness compared to desert dust, as well as to urban–industrial and biomass burning aerosols. The loading ofoceanic aerosol usually does not exceed taer(440) 50.15. Therefore, as shown by Dubovik et al. (2000; seesection 2), the retrieval uncertainty of aerosol absorptionand index of refraction is significantly higher than forother aerosols. Nevertheless, in Table 1 and Fig. 1, wecomplemented the retrieved size distributions (which arestable even for low aerosol loading) of oceanic aerosolby the retrieved v0(l), n, and k values to make morecomplete our comparison of the optical properties offour main aerosol types. Besides, relatively small re-trieval standard deviations given in Table 1 for v0(l),n, and k indicate good stability of our results.

The aerosol observed at Lanai has a very pronouncedmode of coarse particles (sea salt): CVc/CVf ; 2, whichis higher than for urban–industrial and biomass burning


FIG. 4. (a) Illustration of the difference of the phase function of spherical particles vs spheroids for the optical models of Cape Verde dustand (b) Mexico City aerosol for an aerosol loading taer(440) ; 0.7. The nonspherical scattering was approximated by a model of randomlyoriented prolate spheroid with aspect ratio 2. The calculations were performed by the T-matrix code (e.g., see Mishchenko et al. 1997) for(2pr/l) # 20 and by the geometric-optics-integral-equation method of Yang and Liou (1996) for larger particles.

aerosol but lower than for desert dust. Correspondingly,Lanai aerosol exhibits (see Table 1 and Fig. 1) low (fornondust aerosol) Angstrom parameter and rather highasymmetry of the phase function [g(440) 5 0.75; g(670)5 0.71; g(870) 5 0.69; g(1020) 5 0.68]. This obser-vation of a substantial coarse-particles mode, in general,agrees with models (cf. Shettle and Fenn 1979; WMO1983; Gathman 1983; Koepke et al. 1997; Hess et al.1998; Tanre et al. 1999) that assume the domination oflarge sea-salt particles in oceanic aerosol. The low ab-sorption (v0 $ 0.97) and the value of the complex re-fractive index (n 5 1.36; k 5 0.0015) agree reasonablywell with the expectations for sea-salt and water-solubleparticles with high relative humidity (cf. Shettle andFenn 1979; WMO 1983; Koepke et al. 1997; Hess etal. 1998; Tanre et al. 1999).

More detailed and comprehensive analysis of the op-tical depth and size distributions retrieved for severaloceanic AERONET sites can be found in the paper bySmirnov et al. (2002b).

4. Conclusions

This paper presents aerosol optical properties re-trieved in key geographic locations as they vary withthe aerosol column loading. The extensive AERONETdatabase of several measurements per day for 2–6 yrfor each site, in conjunction with advanced retrievaltechniques, was used for this purpose. The data allowed

the development of robust models of real undisturbedaerosols in the total atmospheric column and, for thefirst time, allow quantitative comparison of the averageoptical properties between aerosols of different types aswell as within the same type of aerosol but in differentgeographical locations. While the reported data agreewith known aerosol information in some cases (cf. Shet-tle and Fenn 1979; WMO 1983; Koepke et al. 1997;Hess et al. 1998), they reveal several important differ-ences and clarify some features inherent for each typeof aerosol [e.g., spectral dependence of v0(l), partitionof fine- and coarse-mode in dV/d lnr, etc.].

For example, we found that in contrast to aerosolmodels found in the literature, and in qualitative agree-ment with recent analysis of satellite data (Kaufman etal. 2001; T01), desert dust absorption of solar radiationis very weak for wavelengths greater than 550 nm (v0

; 0.96–0.99). However, dust exhibits a pronounced ab-sorption in the blue spectral range [v0(440) ; 0.92–0.93].

Biomass burning optical properties are related to thevegetation type burned and relative contribution of theflaming and smoldering combustion phases. Boreal andAmazonian forest fire smoke absorbs distinctly less[v0(440) ; 0.94] than grassland-dominated smoke fromAfrican savanna [v0(440) ; 0.88] and mixed-sourcesmoke at South American cerrado sites [v0(440) ;0.91].

Absorption for urban–industrial aerosol also dem-


onstrates significant variability from almost no absorp-tion [v0(440) ; 0.98] at GSFC (east coast of UnitedStates) to rather strong absorption in places known fortheir high level of industrial pollution: v0(440) ; 0.90in Mexico City, and v0(440) ; 0.89 for aerosol ob-served over the Maldives (INDOEX; aerosol transportedlargely from the Indian subcontinent). Aerosol over Par-is demonstrated an intermediate level of absorption[v0(440) ; 0.93–0.94].

Particle nonsphericity was consistently observed indesert dust retrievals as the appearance of retrieval ar-tifacts [high concentration of very small particles withr , 0.1 mm and strong spectral dependence of n(l)]associated with the presence of nonspherical particles(Dubovik et al. 2000). The similarity of these retrievalfeatures with ones observed in numerical tests suggeststhat a nonspherical-scattering model of randomly ori-ented spheroids is rather adequate for desert dust aero-sol. However, this is only a suggestion, which requiresfurther detailed investigations and clarification.

Acknowledgments. We thank the EOS Project ScienceOffice for continued support. We would also like tothank the following AERONET PIs for contributing datato this study: Mexico City–Amando Leyva, Observatoryof Solar Radiation, IGEF-UNAM, Mexico D.F., 04510,MEXICO; Lanai–Dennis Clark, NOAA; ChristophePietras and Charles McClain, NASA GSFC, SIMBIOSProject, boreal forest sites; Brian Markham, NASAGSFC. We thank Dr. Niaf Al-Abbadi, KACST SaudiArabia; B. Chatenet from LISA CNRS Universite Paris7 et 12, who was in charge of the Creteil instrument;and M. Santos Soares, Director of the Servico Nationalde Meteorologiae Geophysica (SNMG), Cape Verde.We also thank the AERONET staff for the data collec-tion, calibration and processing. Additional thanks toMichael Mishchenko, NASA GISS; and Ping Yang,NASA GSFC for providing us with the codes for mod-eling light scattering by nonspherical particles.

APPENDIX

Formulas Utilized for Aerosol Size DistributionParameter Calculations

Volume median radius (mean logarithm of the radius)computed for both fine and coarse modes:

rmax dV(r)lnr d lnrE d lnrrmin

lnr 5 . (A1)V rmax dV(r)d lnrE d lnrrmin

Standard deviation from the volume median radius:

rmax dV(r)2(lnr 2 lnr ) d lnrE V d lnrrmin

s 5 . (A2)V rmaxÎ dV(r)d lnrE d lnrrmin

Volume concentration (mm3/mm2):rmax dV(r)

C 5 d lnr. (A3)V E d lnrrmin

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