Hygroscopic properties of Amazonian biomass burning and European background HULIS and ...

15 Pages·2010·2.56 MB·English

Atmos. Chem. Phys.,10,5625–5639,2010
Atmospheric
www.atmos-chem-phys.net/10/5625/2010/
Chemistry
doi:10.5194/acp-10-5625-2010
©Author(s)2010. CCAttribution3.0License. and Physics
Hygroscopic properties of Amazonian biomass burning and
European background HULIS and investigation of their effects on
surface tension with two models linking H-TDMA to CCNC data
E.O.Fors1,J.Rissler1,*,A.Massling1,**,B.Svenningsson1,M.O.Andreae2,U.Dusek2,***,G.P.Frank2,****,
A.Hoffer2,*****,M.Bilde3,G.Kiss4,S.Janitsek4,S.Henning5,M.C.Facchini6,S.Decesari6,andE.Swietlicki1
1LundUniversity,DepartmentofPhysics,DivisionofNuclearPhysics,Lund,Sweden
2MaxPlanckInstituteforChemistry,DepartmentofBiogeochemistry,Mainz,Germany
3UniversityofCopenhagen,DepartmentofChemistry,Copenhagen,Denmark
4UniversityofPannonia,AirChemistryGroupoftheHungarianAcademyofSciences,Veszpre´m,Hungary
5Leibniz-InstituteforTroposphericResearch,DepartmentofPhysics,Leipzig,Germany
6IstitutodiScienzedell’AtmosferaedelClima–CNR,Bologna,Italy
*nowat: LundUniversity,DepartmentofDesignSciences,DivisionofErgonomicsandAerosolTechnology,Lund,Sweden
**nowat: AarhusUniversity,NationalEnvironmentalResearchInstitute,DepartmentofAtmosphericEnvironment,Roskilde,
Denmark
***nowat: UtrechtUniversity,InstituteforMarineandAtmosphericResearch,Utrecht,TheNetherlands
****nowat: LundUniversity,DepartmentofPhysics,DivisionofNuclearPhysics,Lund,Sweden
*****nowat: UniversityofPannonia,AirChemistryGroupoftheHungarianAcademyofSciences,Veszpre´m,Hungary
Received: 6December2009–PublishedinAtmos. Chem. Phys.Discuss.: 15December2009
Revised: 29April2010–Accepted: 2May2010–Published: 28June2010
Abstract. HUmic-LIke Substances (HULIS) have been growthfactorsbetween1.04and1.07,reachingvaluesof1.4
identified as major contributors to the organic carbon in at- at98%RH.Thecloudnucleatingpropertiesofthetwosets
mospheric aerosol. The term “HULIS” is used to describe ofaerosolsampleswereanalysedusingtwotypesofthermal
the organic material found in aerosol particles that resem- static cloud condensation nucleus counters. Two different
bles the humic organic material in rivers and sea water and parameterizationmodelswereappliedtoinvestigatethepo-
insoils. Inthisstudy, twosetsoffiltersamplesfromatmo- tentialeffectofHULISsurfaceactivity,bothyieldingsimilar
spheric aerosols were collected at different sites. One set results. FortheK-pusztawinterHULISsample,thesurface
of samples was collected at the K-puszta rural site in Hun- tensionatthepointofactivationwasestimatedtobelowered
gary, about 80km SE of Budapest, and a second was col- bybetween34%(47.7mN/m)and31%(50.3mN/m)fordry
lected at a site in Rondoˆnia, Amazonia, Brazil, during the sizes between 50 and 120nm in comparison to pure water.
Large-Scale Biosphere-Atmosphere Experiment in Amazo- Amoderateloweringwasalsoobservedfortheentirewater
nia–SmokeAerosols, Clouds,RainfallandClimate(LBA- solubleaerosolsample,includingbothorganicandinorganic
SMOCC)biomassburningseasonexperiment. HULISwere compounds,wherethesurfacetensionwasdecreasedbybe-
extracted from the samples and their hygroscopic proper- tween2%(71.2mN/m)and13%(63.3mN/m).
ties were studied using a Hygroscopicity Tandem Differen-
tialMobilityAnalyzer(H-TDMA)atrelativehumidity(RH)
<100%,andacloudcondensationnucleuscounter(CCNC)
1 Introduction
at RH >100%. The H-TDMA measurements were carried
outatadrydiameterof100nmandforRHrangingfrom30 Aerosol particles play an important role in the atmosphere
to 98%. At 90% RH the HULIS samples showed diameter duetotheirinfluenceontheradiativebudgetoftheearthby
directlyscatteringandabsorbingtheincomingsunlight(e.g.
Ramanathanetal.,2001;SatheeshandMoorthy,2005),and
Correspondenceto: E.O.Fors indirectlybyservingascloudcondensationnuclei(CCN)in
([email protected]) theformationofclouddroplets(e.g.Kaufmannetal.,2002;
PublishedbyCopernicusPublicationsonbehalfoftheEuropeanGeosciencesUnion.
5626 E.O.Forsetal.: HygroscopicpropertiesofAmazonianbiomassburning
Water soluble organic matter A typical aerosol sample can be described in terms of
the inorganic and the total carbonaceous fraction. The to-
Total carbonaceous matter
tal carbonaceous matter can be subdivided into water insol-
Water soluble (Extract ) ubleorganicmatterplusblackcarbonandwatersolubleor-
ganicmatter.Thewatersolubleorganicmattercanbefurther
Worgaatenri cin msoaltutberle I–somlaotsetdly ohrugmanicicl imkea tter More hydrophilic Inorganic salts subdivided into more hydrophilic organic matter and a less
organic matter
+ black carbon substances (HULIS) hydrophilic organic fraction called isolated organic matter
(ISOM), which consists mostly of HUmic-LIke Substances
Effluent (HULIS), characterised by relatively long chains of organic
molecules (Fig. 1). These can originate from a number of
Fig.1.Classificationofatypicalaerosolsample. sources. Examples of possible origins are biomass burning
(Mayol-Bracero et al., 2002), polymerisation in the aerosol
aqueous phase (Gelencser et al., 2002), oxidation of soot
AndreaeandRosenfeld,2008). Theindirecteffectisdepen-
(Decesarietal.,2002)andtheacidcatalysedreactionofiso-
dent on particle hygroscopicity at water vapour supersatu-
prenoidsandterpenoids(Limbecketal., 2003). HULISare
ratedconditions,morespecificallythesaturationrationeces-
significant contributors to the organic fraction of the atmo-
sary to activate the CCN into forming a cloud droplet. The
spheric aerosol in various environmental reservoirs and an
propertiesoftheCCNareimportantforunderstandingcloud
evaluationofhygroscopicandCCNnucleatingpropertiesof
formation processes and for predicting the resulting droplet
HULISisanimportanttasktofurtherunderstandtheroleof
sizedistributionsthatdeterminethecloudalbedoandcloud
organiccarbonincloudformationprocessesandtoquantita-
lifetime(e.g.Warner,1968;Rosenfeld,2000).Theselasttwo
tivelyevaluatethecontributionfromHULISinthiscontext.
parametersarestronglylinkedtotheindirectaerosoleffect.
Several experimental studies have been conducted on the
The atmospheric aerosol is known to contain a complex
hygroscopicpropertiesofHULIS.Theyhaveproducedquite
mixture of different chemical compounds comprising inor-
diverseresultsduetothevastnumberofspeciesthatcanfall
ganicaswellasorganicconstituents. Thefractionoforganic
under the HULIS definition; since HULIS is ultimately de-
materialintheatmosphericaerosolvariesgreatlyandthefine
fined by the separation method used in the isolation proce-
fraction(particlediameter(D )<1µm)valuesarereported
p
dureofthesample. Gyseletal.(2004), Dinaretal.(2006),
to vary between 20 and 80% in the US alone (Jacobson et
Wex et al. (2007) and Ziese et al. (2008) all determined the
al.,2000). Ofthisorganicfraction,about10–60%hasbeen
hygroscopicpropertiesofisolatedHULISsamples,measur-
foundtobewatersolubleorganiccarbon(WSOC)(Krivacsy
ing hygroscopic growth factors between 1.05 and 1.24 at
et al., 2001; Kleefeld et al., 2002). Until now, the knowl-
90%RH.
edge about the hygroscopic growth and CCN properties of
In this study, the hygroscopic and CCN nucleating prop-
the multitude of water soluble organic compounds found in
erties of two sets of atmospheric samples were investigated
aerosol particles has been very limited (Kanakidou et al.,
using a Hygroscopic Tandem Differential Mobility Ana-
2005; Dinar et al., 2006, 2007; Taraniuk et al., 2007; Wex
lyzer (H-TDMA) and two different cloud condensation nu-
etal.,2007).
clei counters (CCNC). Connecting these datasets, two dif-
Eventhoughsuper-micronparticlesconstitutemostofthe
ferentparameterizationmodelswereappliedtoquantifythe
particle mass, the dominant number of particles in atmo-
possible surface tension altering effects of the HULIS frac-
spheric samples is found in the sub-micron size range and,
tion. One model extrapolates H-TDMA data to supersatu-
thus,theirhygroscopicpropertiesareofhighimportance. It
rationtopredictthecriticalsupersaturationratio. Theother
hasbeenshownthatsomeoftheWSOCsaresurfaceactive
modelusesaniterativescheme,requiringbothH-TDMAand
andmayaffectthewateruptakeandclouddropletactivation
CCNCdata,toobtainaconcentrationdependentparameteri-
of aerosol particles, not only by contributing to the soluble
zationofthesurfacetension.
mass,butalsobyreducingthesurfacetension(Graberetal.,
2006; Facchini et al., 2000; Charlson et al., 2001; Nenes et
al., 2002). It has also been discussed whether or not sur-
2 Samples
facetobulkpartitioningisanimportanteffectinatmospheric
aerosols. Thesurfacepartitioningofsomecomponents,such
A set of six samples was taken during the Large-Scale
as fatty acids, have been shown to affect the critical super-
Biosphere-Atmosphere Experiment in Amazonia – Smoke
saturation. Thisresultsinanincreasedmoleculeconcentra-
Aerosols, Clouds, Rainfall and Climate (LBA-SMOCC)
tion at the surface of the particle at the expense of the bulk
campaign in Rondoˆnia, Brazil, 17 September–4 October
concentrationofthatparticularcomponent(Sorjamaaetal.,
2002,duringthedryperiod. Rondoˆniaisaregionwithhigh
2004;Prisleetal.,2007,2009). Astheparticletakesupwa-
rates of deforestation and biomass burning. The sampling
ter, the volume to surface ratio increases, which leads to a
timevariedbetween36and84h. Threesamplesweretaken
migrationofmoleculesfromthesurfacetothebulk.
duringdaytimehours,whilethreeothersamplesweretaken
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E.O.Forsetal.: HygroscopicpropertiesofAmazonianbiomassburning 5627
Table1.OriginofaerosolsamplesanalysedwiththeH-TDMAandtheCCNCtechniques.
Methodused
Sample Location Samplingtime Type
H-TDMA CCNC
HULIS(SMOCC,D1) Rondoˆnia,Brazil Day,17–21Sep2002 biomassburning ×
HULIS(SMOCC,D2) Rondoˆnia,Brazil Day,21–28Sep2002 biomassburning ×
HULIS(SMOCC,D3) Rondoˆnia,Brazil Day,28Sep–4Oct2002 biomassburning ×
HULIS(SMOCC,N1) Rondoˆnia,Brazil Night,17–21Sep2002 biomassburning ×
HULIS(SMOCC,N2) Rondoˆnia,Brazil Night,21–28Sep2002 biomassburning ×
HULIS(SMOCC,N3) Rondoˆnia,Brazil Night,28Sep–4Oct2002 biomassburning ×
Extract(Winter) K-puszta,Hungary Day/Night,16Feb2001 ruralbackground × ×
Effluent(Winter) K-puszta,Hungary Day/Night,16Feb2001 ruralbackground × ×
HULIS(Winter) K-puszta,Hungary Day/Night,16Feb2001 ruralbackground × ×
Extract(Summer) K-puszta,Hungary Day/Night,11Jul2001 ruralbackground × ×
Effluent(Summer) K-puszta,Hungary Day/Night,11Jul2001 ruralbackground × ×
HULIS(Summer) K-puszta,Hungary Day/Night,11Jul2001 ruralbackground ×
during nighttime, referred to as “SMOCC D1”, “SMOCC 3 Extraction
D2”, “SMOCC D3”, “SMOCC N1”, etc., where D and
N denote day and night samples, and the numbers repre- First, the water soluble aerosol components were extracted
sent the collection periods. The three intervals were 17– by placing the filters for 24h in MilliQ water. Then the
21 September (period 1), 21–28 September (period 2) and extract was filtered through a Millipore membrane filter of
28September–4October(period3). Thesampleswerecol- 0.45µm pore size (the remaining sample from here on de-
lected with a high volume sampler, with a cut-off diameter notedasExtract)andthepHwasadjustedtopH=2withhy-
of 2.5µm, meaning that all particles with an aerodynamic drochloric acid. The separation of HULIS from other dis-
diameter less than 2.5µm were deposited on a filter. A de- solved components was performed on Oasis HLB (Waters,
taileddescriptionoftheaerosolsamplingandchemicalmea- USA)solidphaseextraction(SPE)columns. Typically60%
surementsperformedduringtheSMOCCexperimentcanbe ofthewater-solubleorganiccarboncontentisretainedunder
foundinDecesarietal.(2006)andinFuzzietal.(2007).The theseconditions,whileinorganicionspassthroughtheSPE
limitedcollectedmassofeachsamplemadeonlyonetypeof columns together with the most hydrophilic organic com-
measurementpersamplepossible,eitherusingtheH-TDMA pounds (Effluent). The retained organic compounds, in the
or the CCNC. Table 1 shows which samples were used for method denoted ISOM, were eluted with methanol. The
which measurements. For the SMOCC samples, only iso- methanoleluatewasevaporatedtodryness,andtheisolated
latedHULISsampleswereavailable. organic matter was re-dissolved in water prior to H-TDMA
A set of two 24-h samples was taken at the K-puszta ru- andCCNCmeasurements. AdetaileddiscussionoftheSPE
ral site about 80km south of Budapest, Hungary, between procedure,includingcolumnselectionandperformance,can
16 February and 11 July 2001. The sampling station was befoundinVargaetal.(2001). InthisworktheISOMfrac-
situated in a forest clearing on the Great Hungarian Plain. tion is hereafter referred to as HULIS, in consistency with
A more detailed description of the site can be found in Pio literature (Kiss et al., 2005; Wex et al., 2007; Ziese et al.,
et al. (2007), for example. These samples were denoted K- 2008). The extraction procedure of the HULIS was identi-
puszta winter and summer. The samples were collected on calfortheSMOCCandK-pusztasamples. FortheK-puszta
quartzfibrefilterswithahighvolumesampler,withacut-off samples, all fractions were saved and analysed. However,
of1.5µm. UnliketheSMOCCsamples,eachK-pusztasam- for the SMOCC samples, only the HULIS fraction was ex-
pleresultedinthreetypesofsub-samples: Extract, Effluent tracted,astherewereatthispointnoplansforanalysingthe
andHULIS(definedinthefollowingsection). Eachsample ExtractandEffluentsamples.Aftertheextractionprocedure,
wasevaluatedusingboththeH-TDMAandtheCCNCforall thesampleswerefrozenuntilanalysis.
samplesexceptforthesummerHULISsample. Table1lists
thesetofaerosolsamples.
4 Methods
For both the H-TDMA and the CCNC measurements,
monodisperse aerosol particles were generated from the so-
lutionsusingasmallnebuliser. Theyweredriedindiffusion
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5628 E.O.Forsetal.: HygroscopicpropertiesofAmazonianbiomassburning
dryers, dilutedwithcleanoil-freeairandthengivenawell- was studied. At each measurement, the particle diameter
definedchargedistributionwithabipolarcharger. was kept fixed and the supersaturation was changed step-
wise. For the SMOCC samples, the error estimates for the
4.1 H-TDMAmeasurements critical supersaturation are 95% confidence intervals. The
uncertaintywascalculatedusingtwomethods. Firstly,acu-
The measurements of hygroscopic growth at subsaturation
mulative Gaussian (normal) distribution function was fitted
were carried out using an H-TDMA system (Swietlicki et
toeachCCNspectrumtoderiveamidpointactivationdiam-
al., 2008)withthesameinstrumentalsetupusedby, forex-
eter (d ) of the aerosol. This was defined as the diameter
a
ample, Svenningsson et al. (2006). The H-TDMA consists
at which the cumulative Gaussian function reaches half of
of two DMAs with a humidifier as a conditioning section
itsmaximumheight. Secondly,theuncertaintyofthesuper-
in between. The first DMA selects a monodisperse fraction
saturationsettingoftheinstrumentwascalculatedaccording
of the aerosol while the second DMA, in combination with
to Frank et al. (2007). It turned out that the supersaturation
a condensation particle counter (CPC), analyses the altered
setting of the instrument accounts for the major part of the
size distribution after humidification to a specific RH. Both
uncertainty.
DMAs were operated as open-end systems, with humidity
The size dependent CCN properties of the K-puszta par-
controlled for both the aerosol and for the sheath air flow.
® ticlesweredeterminedusingastaticthermal-gradientdiffu-
Thiswasdonethroughwater-to-gasGore-Tex membranes
sionCCNchamberfromtheUniversityofWyoming,model
byregulatingthetemperatureofthesurroundingwater. For
CCNC-100B.ThisCCNcounterusesthesameprinciplefor
the sheath flow, mass flow controllers were subsequently
generatingthesupersaturationastheMainzCCNcounterde-
mixing humid and dry air to obtain the desired RH. This
scribedabove,whilethecentreaxisofthechamberisillumi-
setup enables measurements of both possible deliquescence
natedbyalaserdiode(670nm)andtheactivateddropletsare
and efflorescence behaviour of the aerosol. Measurements
detectedbymeasuringtheforwardscatteredlightintensityat
were made for the particles with an initial electrical mobil-
anangleof45degreestothediodelightbeam. TheCCNC-
ityequivalenttoadryDMA1diameterof100nmatDMA2
100B was calibrated using monodisperse sodium chloride
relativehumidity(RH)valuesbetween30%and98%. Mea-
andammoniumsulphateparticlesasinBildeandSvennings-
surements at high RH were controlled by test salt measure-
son (2004). For the K-puszta samples, the error estimates
ments of known hygroscopic growth to determine the exact
for the critical supersaturation were 95% confidence inter-
RH during the growth measurements. The results are pre-
vals based on the calibration data for the CCN spectrom-
sented as the measured hygroscopic growth factor, GF, de-
eter. Sodium chloride and ammonium sulphate were used
finedaccordingto
for the calibration. A van’t Hoff factor of 2 was used for
D
GF= drop (1) sodium chloride whereas for ammonium sulphate, the fac-
Dp tor was adopted from the literature (Low, 1969; Young and
whereD isthedropletdiameterandD isthedrydiame- Warren,1992)andrangedbetween2.2–2.4atthepointofac-
drop p
teroftheparticle. tivation. H-TDMAdataonsodiumchloridesupportstheuse
ofashapefactorforacube(i.e.1.08). Thisshapefactoralso
4.2 CCNcountermeasurements resulted in a better agreement between the ammonium sul-
phate and sodium chloride data, compared to a unity shape
To determine the size-dependent activation curve of the in-
factorandwas,thus,usedforthesodiumchloridedatainthis
vestigated aerosol, a narrow size fraction was selected us-
case.
ing a DMA (TSI, Model 3080). The monodisperse aerosol
was divided between a condensation particle counter (TSI,
4.3 CCNmodelling
Model3010)andastaticthermal-gradientCCNchamber.
The size dependent CCN properties of the SMOCC
particles were determined with a static thermal-gradient There are a number of different model parameterizations
CCN counter from the Max Planck Institute for Chemistry availableforcalculatingcriticalsupersaturationratiosbyex-
(MPIC), Mainz. The main part of the CCN counter is an trapolatingH-TDMAdataintothesupersaturatedregime. In
80mmdiameterchamberwithadistanceof10mmbetween this study, we have not included any limitations in the sol-
theupperandlowerplates. Theplatesarekeptcontinuously ubility of the analysed samples. Implicitly, this means that
wet and their temperature difference is controlled to define we assume that the samples are completely dissolved at the
the supersaturation in the chamber. Various supersaturation RHofwhichH-TDMAGFvalueswereusedasinputforthe
ratios,s ,canbeadjusted. Thedeviceuseslaserillumination respective models. All model parameterizations rely on an
c
and a video camera for the detection of activated droplets. assumptionofthevalueofthesurfacetensionasafunction
The two CCN counters were intercalibrated, using the cali- of surfactant concentration. In this work, we used two sin-
brationproceduredescribedinFranketal.(2007). Theacti- gleparametermodels:κ introducedbyRissleretal.(2004),
R
vationofparticleswithdrydiametersbetween40and125nm alsodescribedinVestinetal.(2007),andρ fromZieseet
ion
Atmos. Chem. Phys.,10,5625–5639,2010 www.atmos-chem-phys.net/10/5625/2010/
E.O.Forsetal.: HygroscopicpropertiesofAmazonianbiomassburning 5629
al.(2008). BotharebasedontheKo¨hlerequation was used as the model salt, since this is common and of-
tenthedominatinginorganiccompoundinmanyatmospheric
(cid:18) (cid:19)
4M σ
pw(Dp)=p0awexp w (2) aerosols. The water activity correction term (χφ) is derived
RTρwDdrop fromPotukuchiandWexler(1995),Tangetal.(1994)andat
higherwateractivitiesfromLow(1969).
wherep isthewatervapourpressure,p0thesaturationwa-
w Thecriticalwatervapoursupersaturation,s ,(S −1)can
tervapourpressure,a theactivityofwaterinsolution,M c c
w w beapproximatedbythefollowingequation,whichisderived
themolarweightofwater,σ thesurfacetension,R theuni-
fromsimplifiedKo¨hlertheoryandsimilartothatderivedin
versalgasconstant,T thetemperature,ρ thedensityofwa-
w SeinfeldandPandis(2006):
ter,andD thedropletsize.
drop
In addition to the two models used in this work, Petters s
4A3 1
and Kreidenweis (2007) have suggested an approach based s = · (4)
c 27C κ ·χ ·D3
onasingleparameter, alsonamedκ, definedthroughitsef- R φ p
fect on the water activity of the solution. Kreidenweis et
whereAandC aredefinedas
al.(2005)suggestedasimilardefinition, butwithapolyno-
mial expression included to take non-ideal effects into ac- A=4Mwσ and C=Mw (5)
count. Forthisapproachtowork, growthfactorsatthreeor RTρ ρ
w w
moreRHvaluesarerequired,incontrasttotheothermodels
Foramoredetaileddescriptionoftheprocedure,seeRissler
requiringgrowthfactorsatonlyoneRH.Whilethismodelis
etal.(2004),Vestinetal.(2007)andRissleretal.(2006). In
wellsuitedfornon-idealandgraduallydissolvingparticles,a
Rissleretal.(2004),thesolublevolumefraction,ε,wasused
lotofH-TDMAdatahasbeencollectedatafixedRHof90%
insteadofκ ,otherwisethecalculationswereanalogous. It
(Swietlickietal.,2008),wherethepolynomialapproachwill R
shouldbenotedthatEq.(4)isonlyvalidundertheassump-
not work. All the mentioned models have equally correct
tion that the dry particle volume is negligible, a fact which
ways of describing the hygroscopicity of a particle. In this
willbefurtheranalysedlaterinthispaper.
study,wepreferredtousetheparametersκ andρ dueto
R ion
Byusingthesurfacetensionofwater,thepresenceofsur-
theirintuitivephysicalmeaning,namelythenumberofsolu-
faceactivecompoundsis,toalargeextent,neglected. Asur-
bleentitiesperdryvolumeunit.
faceactivecompoundwould,infact,influencetheκ value
R
4.3.1 κRmodel viatheconversionfromRHtoaw,andagainthesurfaceten-
sionreappearsasaparameterinEq.(4)inthes approxima-
c
Inthefirstmodel,thenumberofsolubleentitiespervolume tion. However,HULISaresuspectedtoactassurfaceactive
unitiscalculatedfromthemeasuredhygroscopicgrowthfac- compounds,reducingthesurfacetensionofwateratthepoint
tor, GF, according to Ko¨hler theory assuming volume addi- of activation (Kiss et al., 2005). To get an estimate of the
tivity surfacetensioneffectofHULIS,thesurfacetensionwasad-
justeduntilthemodelledsupersaturationbasedonHTDMA
s
M a derivedgrowthfactorswasequaltothemeasuredcriticalsu-
GF= 3 1+κ ·χ · w w (3a)
R φ ρ 1−a persaturation. This was done for the HULIS sample from
w w
K-puszta,wherebothCCNCandH-TDMAdatawereavail-
orrearranged able. Note that a measurement or model error will result in
anincorrectestimationofthesurfacetension.
(GF3−1)·(1−a )
κ = w (3b)
R aw·χφMρww 4.3.2 ρionmodel
where κ is the number of soluble entities per volume dry Thesecondmodelusedinthisstudywasfirstintroducedby
R
unit,M themolecularweightofwater,ρ thewaterdensity, Zieseetal.(2008)forasimilarHULISsampleset. Itisalso
w w
andχ acorrectiontermintroducedtoaccountfornon-ideal basedonKo¨hlertheory, butwithouttakingintoaccountthe
φ
behaviour, while a can be calculated according to Eq. (2). non-ideality of the solute. The growth factor from the H-
w
Thecorrectiontermhereisdeterminedusingamodelsalt,as- TDMA data serves as input for the model to calculate the
sumingthatthenon-idealityofthesolutioncanbedescribed numberofsolubleentitiespervolumeunit,herecalledρ ,
ion
by the non-ideality of the model salt at the same a . The whichwasfirstintroducedbyWexetal.(2007). Itassumes
w
modelisalsotestedassumingidealbehaviour(χ =1). This a constant solubility and dissociation up into the supersatu-
φ
is,inprinciple,thesameequationaslaterusedinPettersand ratedregime. Theequationusedtodescribethewateruptake
Kreidenweis (2007), but with a somewhat different defini- is
tionoftheparameter,κ. Followingtheapproachofprevious !
publications where the κR model has been applied (Rissler S=exp 4Mwσ −ρion·Mw Dp3 (6)
et al., 2004, 2006; Vestin et al., 2007) ammonium sulphate RTρwdp ρw Dd3rop−Dp3
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5630 E.O.Forsetal.: HygroscopicpropertiesofAmazonianbiomassburning
whereρ isdefinedas basedonlyontheGFinonepointfromtheH-TDMAdataset.
ion
From Eq. (11), the critical supersaturation can now be cal-
ν·ρ ·φ
ρ = s (7) culated and the parameters a and b0, which define the sur-
ion
M
s face tension of the sample, are adjusted until the results of
where ν is the maximum number of ions that the molecule themodelledcriticalsupersaturationfromtheH-TDMAdata
can dissociate into and φ is the osmotic coefficient. Note matchtheCCNCdata.Theseparametersarenowusedtocal-
that ρion has the same meaning as κR, namely the number culateanewρionandtheiterationcontinuesuntilthesolution
ofmolesofsolublematerialperdryparticlevolume. Equa- hasconverged(Zieseetal.,2008).
tion(6)is,inprinciple,theKo¨hlerequationwithanapproxi- The main advantage of this approach is that one obtains
mationmadeofdilutesolutions(compareEq.17.24inSein- a concentration dependent surface tension function as an
feldandPandis,2006).Thisisonemoreapproximationcom- output, whichisconsistentwiththeSzyszkowski-Langmuir
paredtoEq.(3a),usedintheκ modelatsubsaturations,but equation. The drawback is that no non-ideal behaviour be-
R
doesnotassume,asintheapproximationusedatsupersatu- tweenthewateractivityusedfortheH-TDMAmeasurement
ration,Eq.(4),thatthevolumeoccupiedbythesolutecanbe andthewateractivityattheactivationpointistakenintoac-
neglectedrelativetothedropletvolume. count,unliketheκR model,wherethemodelsaltisassumed
Intheρ model,anadditionalvariableisintroduced: the todescribethenon-idealityoftheparticle. Itshouldalsobe
ion
surface tension is not held constant, or retrospectively ad- noted that the surface tension parameters are adjusted until
justedtotheCCNCdataonedrysizeatthetime,butforcedto they match the data. A measurement error (or model error)
follow the Szyszkowski-Langmuir equation (Szyszkowski, will,therefore,resultinanincorrectsurfacetensionparame-
1908): terization.
Atsubsaturation,theρ modelusesamoreapproximate
ion
σ=σw−aTln(1+bC) (8) formoftheKo¨hlerequationthantheκR model. However,at
supersaturationstheformuladoesnotassumethatthevolume
where σ is the surface tension of water, C is the number
w occupiedbythesolutecanbeneglectedrelativetothedroplet
ofmolesofsolutepermassofwateranda andb arefitting
volumeasisthecaseintheκ model(SeinfeldandPandis,
parameters. Introducinganewparameter,b0,accordingto R
2006).
ρ
b0=b· s (9) 4.4 ZSRmethod
M ρ
s w
Eq.(8)canberewrittenas ToestimatetherelativevolumepartsoftheHULISandEf-
fluent part of the K-puszta samples, the Zdanovskii-Stokes-
d3 ! Robinsonmethodwasused(StokesandRobinson,1966).At
σ=σ −aTln 1+b0 p,0 (10)
w d3−d3 anyspecificwateractivity,thehygroscopicgrowthfactorof
p p,0 themixture,GF ,canbewrittenas
mix
Equation(6)cannowberewrittenas q
GF = 3 6ε GF3 (13)
mix s s
(cid:18) (cid:18) (cid:19)(cid:19)
S =exp 4Mw σw−aTln 1+b0dp3d−p3,d0p3,0 flwuheenret iεns tahreetdhreyvpoalrutmicelef,raacntdioGnsFsofatrheethHeUiLndISivaidnudatlhceoEmf--
RTρwdp pounds’ corresponding growth factors. In this study, GFs
ρ M d3 ! from the complete humidograms of the HULIS, the Efflu-
− ion w p,0 (11) ent and the Extract samples were used as input to Eq. (13).
ρw dp3−dp3,0 Forthis,asingleparameterfunctionbasedonKo¨hlertheory
wasusedtofittheH-TDMAdata:
An iteration procedure is then carried out to find a solution s
thatmatchesboththeCCNCandtheH-TDMAdata. Asan RH/100
GF= 3 1+A· (14)
initial guess, the surface tension is assumed to be the same 1−RH/100
asforwater, andρ canbecalculatedfromEq.(11), rear-
ion whereAisafittingvariable.
rangedas
ρ = ρw(dp3−dp3,0) 5 Resultsanddiscussion
ion M d3
w p,0 5.1 Hygroscopicproperties
4M (cid:18)σ −aTln(cid:18)1+b0 dp3,0 (cid:19)(cid:19) 
· w w dp3−dp3,0 −ln(S)(12) The HULIS samples from both SMOCC and K-puszta
 RTρwdp  showed low hygroscopic growth. The variability in diame-
tergrowthfactorsat90%RHwasquitesmallandfellinthe
Atmos. Chem. Phys.,10,5625–5639,2010 www.atmos-chem-phys.net/10/5625/2010/
E.O.Forsetal.: HygroscopicpropertiesofAmazonianbiomassburning 5631
a
Table2.PreviouslymeasuredHULISgrowthfactorsat90%RHto- 2.2
HULIS Winter
getherwiththeGFsfromthisstudy.Samplenotationsareaccording
Extract Winter
tothepublishedpapers.
2 Effluent Winter
HULIS Winter, fit
Extract Winter, fit
1.8
Sample 90G%FRatH rotc E(NffHlu4e)n2tS OW4i n(Ttearn, gf iatnd Munkelwitz)
a
f h 1.6
KP010112-ISOM,100nmdrysize(Gyseletal.,2004) 1.08 tw
KP010126-ISOM,100nmdrysize(Gyseletal.,2004) 1.11 orG 1.4
KP010726-ISOM,100nmdrysize(Gyseletal.,2004) 1.16
KP010816-ISOM,100nmdrysize(Gyseletal.,2004) 1.17
LBO-night,60nmdrysize(Dinaretal.,2006) 1.18 1.2
LBO-day,60nmdrysize(Dinaretal.,2006) 1.24
Budapest,sample1(Zieseetal.,2008) 1.17 1
Budapest,sample2(Zieseetal.,2008) 1.05 20 40 60 80 100
K-puszta,summer 1.11
RH (%)
K-puszta,winter 1.05 b
2.2
SMOCC,D1 1.06 HULIS Summer
SMOCC,D3 1.11 Extract Summer
SMOCC,N1 1.06 2 Effluent Summer
SMOCC,N3 1.05 HULIS Summer, fit
Extract, Summer, fit
1.8
Effluent Summer, fit
rotc (NH4)2SO4 (Tang and Munkelwitz)
af h1.6
rangebetween1.05and1.11forallHULISsamples(Figs.2 tw
o
and 3 and Table 2). This is in the lower range of what has rG1.4
been reported previously by others (Gysel et al., 2004; Di-
naretal., 2007; Zieseetal., 2008), wheregrowthfactorsat 1.2
90%RHhavebeenfoundtobebetween1.05and1.24(Ta-
ble2). InTable3,theκRvaluesareshown,calculatedforthe 1
hygroscopic growth between 90–98% RH. The calculations 20 40 60 80 100
were made assuming a dissociation as that of a model salt RH (%)
(hereusingχφ accordingtoammoniumsulphate)aswellas
assumingfulldissociation(χ =1; valuesinparenthesis). In
φ
Fig. 2. Measured hygroscopic growth of K-puszta winter (a)
previous studies that use the model, epsilon has been used
and summer (b) samples and fitted functions for particles with a
to represent the soluble material (Rissler et al., 2004). For
drydiameterof100nmwithoutpre-humidificationoftheaerosol.
bothSMOCCsamplingperiods,thedaysamplesweremore
The growth factors are corrected according to efflorescence mea-
hygroscopic than the night samples. This is possibly due
surements, which indicate a slight restructuring of the particles.
to the ageing process of the aerosol. During the night, the
ThesolidlinerepresentsammoniumsulphatedatafromTangand
boundary layer collapses and the sampling is more domi- Munkelwitz(1999). Thelinesdenotedfitareparameterizationsac-
natedbyfreshparticlesfromsmouldering. Duringdaytime, cordingtoEq.(14).
the boundary layer height increases and aged particles are
mixed down (Rissler et al., 2006). As has been shown re-
centlybyJimenezetal.(2009),agedsolubleorganicaerosol Determiningtheκ valuesforallHULISsamplesrevealed
R
(SOA)tendstobemoreoxidizedandmoresolublethanfresh that the K-puszta samples, as well as the SMOCC D1 and
SOA, which would support these results. Figure 3 presents N1samples,weredissolvedandnon-idealtosimilardegrees
thehumidogramsforthetwoSMOCCperiods. Forcompar- throughout the RH range from 90 to 98%. Based on this,
ison,italsoshowsthehygroscopicgrowthmeasuredon-line we assume that they will not increase in solubility as the
at the SMOCCsite duringthe timeperiods, averaged asin- water activity further increases, but that any deviation from
ternalmixtureandweightedbymass(tosimulatethesoluble predicted water uptake can be attributed to surface activ-
ionscollectedonafilterandresuspended). Ascanbeseen, ity. However, it should be noted that fresh SOA has been
the HULIS samples are significantly less hygroscopic than showntoincreaseinsolubilitystartingatRHsofabove98%
the on-site measurements, due to the absence of inorganic (Wex et al., 2009). If this would be the case for the sam-
salts which are found in the ambient aerosol but not in the plesanalysedhere,thepredictedsurfacetensionsuppression
isolatedHULISsamples. would be overestimated, since limited solubility is not in-
cluded in the theory used in this paper. For the SMOCC
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5632 E.O.Forsetal.: HygroscopicpropertiesofAmazonianbiomassburning
Table3.κRvaluestatisticsforRHvaluesbetween90and98%.TheκRvaluespresentedarebasedontheassumptionthatthenon-idealityof
thesolutecanbeaccountedforbyamodelsalt.κRvaluesinparenthesisarevaluesresultingfromidealbehaviourorthedroplet–assuming
full dissociation. The significance of a correlation (linear increase of κR as a function of RH) was calculated (95% CI) assuming ideal
solutions. Ifcorrelationsexist,therewouldlikelybeanincreaseintheeffectivenumberofsolubleionsinthesolutionatincreasingRH,
thus,usingκRfromGFmeasurementsat90%willprobablyleadtoanoverestimationofsc.
κRvaluesabove90%RH[moles/m3] average std Trend95%CI
HULIS(K-puszta,winter) 1571(1177) 179(110) NO
Effluent(K-puszta,winter) 16777(11475) 2696(1758) YES
Extract(K-puszta,winter) 10968(7570) 2107(1466) YES
HULIS(K-puszta,summer) 2924(2148) 482(347) NO
Effluent(K-puszta,summer) 22584(14977) 994(496) YES
Extract(K-puszta,summer) 19233(12844) 1517(880) NO
HULIS(SMOCC,D1) 2102(1574) 134(126) NO
HULIS(SMOCC,D3) 4729(3365) 680(527) YES
HULIS(SMOCC,N1) 1605(1222) 1661(168) NO
HULIS(SMOCC,N3) 2604(1910) 381(347) YES
1.3 Effluentsamplealsodisplaythisnon-idealbehaviour(Fig.4
SMOCC D1
and Table 3). This can be due to inorganic or organic com-
SMOCC D3
SMOCC N1 poundsthatarepresentinbothsamples(recallthattypically
SMOCC N3
ro 1.2 SMOCC site 40%oftheHULISwasnotextractedfromtheEffluentsam-
tcaf h ple),whichtakeupwaterandincreasethedilutionsothatthe
tw HULISwilldissociatetoahigherextentthanintheisolated
o
rG HULISsample. Anotherinterpretationisthatinorganicsalts
1.1
withahighdeliquescencepoint,suchasK SO ,arepresent
2 4
intheExtractandEffluentsamples.
For the SMOCC samples, H-TDMA measurements were
1
20 30 40 50 60 70 80 90 100 carried out both with humidification in the aerosol and the
RH (%) sheath air, and with constant pre-humidification to 90% in
the aerosol line with subsequent RH control in the sheath
Fig. 3. Measured hygroscopic growth of 100nm HULIS aerosol
air. This means that with the pre-humidification, the parti-
particles collected during the SMOCC campaign without pre-
cles could possibly deliquescent and restructure (restructur-
humidificationoftheaerosol. Thegrowthfactorsarecorrectedac-
cordingtoefflorescencemeasurements,whichindicateaslightre- ing decreases their mobility diameter) before equilibrating.
structuringoftheparticles.ThetwoSMOCCsiteparameterizations This operating mode allowed measuring signs of efflores-
representgrowthmeasuredonsiteduringthetimeperiods,averaged cence and restructuring of the aerosol. Both SMOCC night
asinternalmixtureandweightedbymass(tosimulatethesoluble samples showed clear signs of restructuring, with GF val-
ions collected on a filter and re-suspended). The average over all uesbelow1atlowRH,indicatingshrinkageoftheparticles
sixperiodsrangesbetweenthetwosolidlines. after the pre-humidification, while for the day samples, this
effectwaslesspronounced. Thereasonforthisbehaviouris
unknown. Itcannotbedeterminedwhetherthiseffectorigi-
samples from period 3 (SMOCC D3 and N3), an increase natesfromdifferentnebulizinganddryingconditionsorifit
inthenumberofsolubleentitiespervolumeunit,κ ,above is the sample properties that are different. The growth fac-
R
90% was observed with increased RH (Figs. 4 and 5, Ta- tors used in this work are recalculated so that the minimum
ble 3). Although these are the only HULIS samples in this growthfactorequals1,toavoidunderestimatingthesolubil-
studytoshowsuchbehaviour,thiseffecthasbeenobserved ityofthesamples.
previouslyforHULISsamplescollectedinBudapest(Ziese
etal., 2008), andcanpossiblybeexplainedbythepresence 5.2 Cloudnucleatingproperties
of chemical compounds gradually dissolving as the RH in-
creases. This behaviour makes a simple parameterization As can be seen in Fig. 6 and Table 4, the critical super-
for CCN activity based on hygroscopicity at subsaturation saturations, s , experimentally determined for HULIS sam-
c
adifficulttask. ItisalsonoteworthythattheK-pusztawin- plesfromtheEuropeanruralbackgroundweresignificantly
ter samples (Extract and Effluent samples) and the summer higher than for the water Extract and the Effluent samples.
Atmos. Chem. Phys.,10,5625–5639,2010 www.atmos-chem-phys.net/10/5625/2010/
E.O.Forsetal.: HygroscopicpropertiesofAmazonianbiomassburning 5633
Table4.CriticalsupersaturationmeasuredwiththeCCNCsfordifferentdrydiametersforsamplesfromK-pusztaandSMOCC.
Criticalsupersaturation[%]
Drydiameter[nm] 40 50 60 75 80 100 120 125
Extract(K-puszta,summer) 0.84 0.60 0.43 0.29 0.20
Effluent(K-puszta,summer) 0.79 0.54 0.41 0.25 0.18
Extract(K-puszta,winter) 1.15 0.70 0.50 0.30 0.21
Effluent(K-puszta,winter) 1.07 0.69 0.51 0.33 0.24
HULIS(K-puszta,winter) 1.11 0.87 0.60 0.44 0.28
HULIS(SMOCC,D2) 1.36 0.82 0.55 0.26
HULIS(SMOCC,N2) 1.09 0.52 0.28
25000
HULIS winter
Extract winter
20000
Extract winter
3-m) 15000 EExfftlruaecnt tW Wininteterr 1 Extract summer
k(R HExUtrLaISc tW Suinmtemrer
10000 Effluent Summer
HULIS Summer
5000 )%
(
sc
0
90 92 94 96 98
RH (%)
Fig.4. κRfortheK-pusztasamplescalculatedindependentlyfrom
GFsatallRHs.
0.1
6000
30 60 90 120 150
5000 Dp (nm)
4000
3-km()R 3000 SSSMMMOOOCCCCCC DDN131 FTihge.6li.nMeseraespurreesdenctritthicealsusuppeersrasatuturaratitoionnrsaftoiorsthoefKth-rpeueszdtiaffsearmenptlaers-.
2000 SMOCC N3 bitraryidealcompoundsasafunctionofdrydiameter,Dp,andare
intendedsolelytoguidetheeyeontheidealdependenceofsc on
1000 Dp.ThesescvaluesarecalculatedaccordingtoEq.(4).
0
90 92 94 96 98
RH (%)
5.3 ComparisonCCNmeasurementsandmodelresults
Fig. 5. κR for the SMOCC HULIS samples calculated indepen-
dentlyfromGFsatdifferentRHs.
For the modelling of critical supersaturations, average val-
ues of κ and ρ calculated from H-TDMA data between
R ion
95and98%RHwereused. Bothmodelsweretestedatfirst
This is consistent with the hygroscopic growth measured at usingthesurfaceactivityofpurewaterandtheresultingcrit-
subsaturations. Thisresultisnotsurprising,consideringthat icalsupersaturationwascomparedtothatmeasured. Forthe
the hygroscopic inorganic salts and highly soluble organic Extract and Effluent samples from K-puszta, the modelled
compounds are contained in the water Extract and the Ef- and measured critical supersaturations were in good agree-
fluent. Thesmalldifferenceins betweentheEffluentsand ment, withaslightlyoverestimateds . Thisisexplainedby
c c
theExtractsindicatesthattheHULISintheEuropeansam- thedropletsurfacetensionbeingsomewhatlowerthanthatof
ple only poorly influence the point of activation. The criti- pure water. However, using the surface tension of pure wa-
calsupersaturationsmeasuredbytheCCNCfortheSMOCC terinthecalculationsfortheK-pusztaHULISsampleleads
samples are presented in Table 4 and Fig. 7. The measured toaclearoverestimationofthecriticalsupersaturation. This
s valueswereinthesamerangeasintheEuropeanHULIS meansthattheHULISactivatemoreeasilyintheCCNCthan
c
winter sample, although the SMOCC day sample (SMOCC predictedbythemodelcalculations(Fig.8aandb). Thisis
D2)wasfoundslightlylesshygroscopic. consistent with previous findings that HULIS can lower the
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5634 E.O.Forsetal.: HygroscopicpropertiesofAmazonianbiomassburning
Table5.SurfacetensionsatthepointofactivationaccordingtotheρionmodelfortheK-pusztawintersample.
Surfacetensionatactivation[mN/m]
Diameter[nm] 40 50 60 80 100 120
Effluent(K-puszta,winter),Surfacetensionatpointofactivation[mN/m] 70.9 71 71 71.1 71.2
Extract(K-puszta,winter),Surfacetensionatpointofactivation[mN/m] 60.3 60.7 60.9 61.5 61.8
HULIS(K-puszta,winter),Surfacetensionatpointofactivation[mN/m] 47.7 48.2 49 50 50.3
Effluent(K-puszta,summer),Surfacetensionatpointofactivation[mN/m] 66.7 67 67.3 67.6 67.9
Extract(K-puszta,summer),Surfacetensionatpointofactivation[mN/m] 63.6 64 64.2 64.6 64.9
Table6. Fittedparametersfortheρion modelforK-pusztacomparedtopreviouscalculationsfromZieseetal.(2008). Notethatρion is
givenusingthefittedsurfacetensionswhileinTable3thecorrespondingnumbersfortheκR modelarelistedusingthesurfacetensionof
purewater.
Substance a[N/mK] b0 ρion[moles/m3]
HULIS(K-puszta,winter) 2.01E−05 E6 1157
Effluent(K-puszta,winter) 8.03E−07 E6 12692
Extract(K-puszta,winter) 1.53E−06 E6 8952
Effluent(K-puszta,summer) 6.63E−06 E6 15552
Extract(K-puszta,summer) 7.31E−06 E6 12105
HULIS,firstsample,Budapest,Hungary(Zieseetal.,2008) 9.51E−06 E2 5434
HULIS,secondsample,Budapest,Hungary(Zieseetal.,2008) 2.14E−05 E2 5268
HULIS,LBOnight,Rehovot,Israel(Zieseetal.,2008) 3.51E−05 E2 3516
HULIS,LBOday,Rehovot,Israel(Zieseetal.,2008) 3.57E−05 E2 7317
HULIS,3WSFA,Rehovot,Israel(Zieseetal.,2008) 2.68E−05 E2 13269
surfacetensionand,thereby,reducethecriticalsupersatura- Thiscanbeseenfromthedifferenceincriticalsupersatura-
tion (Graber et al., 2006; Taraniuk et al., 2007; Wex et al., tion predicted by the two models used in this paper. This
2007). Forasurfacetensionofwater,bothmodelsoveresti- effectanditsdependenceonmeasuredGFanddrysizeisil-
matethecriticalsupersaturationbyafactorof∼2. lustrated in Fig. 9, where the predicted supersaturations for
The ρ and the κ models showed quite similar results. 50 and 100nm dry particles are presented as a function of
ion R
Thisisthecaseeventhoughthenon-idealbehaviouriscon- measuredGFat90%RH.Whenthehygroscopicgrowthap-
sideredintheκR model, whichisexplainedbythefactthat proaches1(hydrophobicparticles),thescvaluesshouldcon-
the correction term (χ ) at subsaturation and at activation vergetowardsthetheoreticalvalueoftheKelvineffect. This
ϕ
is nearly the same. Thus, the effect of taking the non-ideal is the case for the ρion model, while the κR approach over-
behaviourintoaccountisminor. FortheHULISsample,the predicts the sc values. Based on the results from this study,
ρ modelgivesalowers valuethantheκ model.Thisdif- Eq. (4) should only be applied for GF>1.1, which overes-
ion c R
ferenceoriginatesmainlyfromthedifferentdegreesofsim- timates the sc value by 2% for 50nm particles. However,
plificationsincludedintheKo¨hlerequationsusedtocalculate forsmallerparticles,largergrowthfactorsshouldbeusedas
the activation. In the predictions of the critical supersatura- thresholdvaluesforthesamerelativeerror. Inthestudiesby
tionbasedontheκ model,thesolutevolumeisassumedto Rissler et al. (2004) and Vestin et al. (2007) this effect was
R
besmallenoughtobeneglectedatdropletactivation, while corrected.
theρ modeldoesnotmakethisassumption.Undernormal To determine the surface tension effect of the K-puszta
ion
circumstances, such as measurements of ambient aerosols, samples,theiterationproceduredescribedinSect.4.3.2was
thereareoftenbothmorehygroscopicandlesshygroscopic carried out to derive the Szyszkowski surface tension pa-
particlespresent,aswellasnearhydrophobicparticles(Swi- rameterization. Thisapproachalsoaffectstheestimationof
etlicki et al., 2008). When performing CCN closure stud- ρ from the hygroscopic growth at subsaturations. The
ion
iesorparameterizationsofCCNconcentrationsbasedonH- results are presented in Tables 5 and 6. For the HULIS
TDMA data, for example, it can, therefore, be important to sample, this reveals a value of ρ =1157moles/m3 which
ion
take this fact under consideration as well as when dealing is lower than reported previously (between 3516moles/m3
with isolated compounds of low solubility such as HULIS. and13269moles/m3)insimilarstudies(Zieseetal.,2008).
Atmos. Chem. Phys.,10,5625–5639,2010 www.atmos-chem-phys.net/10/5625/2010/