Biomass-burning impact on CCN number, hygroscopicity and cloud formation during summertime ...

21 Pages·2016·3.52 MB·English

Atmos.Chem.Phys.,16,7389–7409,2016
www.atmos-chem-phys.net/16/7389/2016/
doi:10.5194/acp-16-7389-2016
©Author(s)2016.CCAttribution3.0License.
Biomass-burning impact on CCN number, hygroscopicity and cloud
formation during summertime in the eastern Mediterranean
AikateriniBougiatioti1,2,3,SpirosBezantakos4,5,IasonasStavroulas3,NikosKalivitis3,PanagiotisKokkalis2,11,
GeorgeBiskos6,7,NikolaosMihalopoulos3,7,10,AlexandrosPapayannis2,andAthanasiosNenes1,8,9,10
1SchoolofEarthandAtmosphericSciences,GeorgiaInstituteofTechnology,Atlanta,GA,USA
2LaserRemoteSensingUnit,NationalTechnicalUniversityofAthens,Zografou,Athens,Greece
3ECPL,DepartmentofChemistry,UniversityofCrete,Voutes,71003Heraklion,Greece
4DepartmentofEnvironment,UniversityoftheAegean,Mytilene,81100,Greece
5InstituteofNuclearTechnologyandRadiationProtection,NCSR“Demokritos”,15310Ag.Paraskevi,Athens,Greece
6FacultyofCivilEngineeringandGeosciences,DelftUniversityofTechnology,Delft2728CN,theNetherlands
7EnergyEnvironmentandWaterResearchCenter,TheCyprusInstitute,Nicosia2121,Cyprus
8SchoolofChemical&BiomolecularEngineering,GeorgiaInstituteofTechnology,Atlanta,GA,USA
9InstituteofChemicalEngineeringSciences(ICE-HT),FORTH,Patras,Greece
10IERSD,NationalObservatoryofAthens,P.Penteli15236,Athens,Greece
11IAASARS,NationalObservatoryofAthens,P.Penteli15236,Athens,Greece
Correspondenceto:AikateriniBougiatioti([email protected])andAthanasiosNenes([email protected])
Received:14July2015–PublishedinAtmos.Chem.Phys.Discuss.:10August2015
Revised:26February2016–Accepted:24May2016–Published:14June2016
Abstract. This study investigates the concentration, cloud positive matrix factorization (PMF) analysis of the organic
condensationnuclei(CCN)activityandhygroscopicproper- ACSM spectra, CCN concentrations follow a similar trend
tiesofparticlesinfluencedbybiomassburningintheeastern asthebiomass-burningorganicaerosol(BBOA)component,
Mediterraneanandtheirimpactsonclouddropletformation. withtheformerbeingenhancedbetween65and150%(for
Air masses sampled were subject to a range of atmospheric supersaturationsrangingbetween0.2and0.7%)withthear-
processing (several hours up to 3 days). Values of the hy- rival of the smoke plumes. Using multilinear regression of
groscopicityparameter,κ,werederivedfromCCNmeasure- the PMF factors (BBOA, OOA-BB and OOA) and the ob-
mentsandaHygroscopicTandemDifferentialMobilityAn- served hygroscopicity parameter, the inferred hygroscopic-
alyzer(HTDMA).AnAerosolChemicalSpeciationMonitor ity of the oxygenated organic aerosol components is deter-
(ACSM)wasalsousedtodeterminethechemicalcomposi- mined. We find that the transformation of freshly emitted
tion and mass concentration of non-refractory components biomass burning (BBOA) to more oxidized organic aerosol
ofthesubmicronaerosolfraction.Duringfireevents,thein- (OOA-BB)canresultina2-foldincreaseoftheinferredor-
creasedorganiccontent(andlowerinorganicfraction)ofthe ganichygroscopicity;about10%ofthetotalaerosolhygro-
aerosol decreases the values of κ, for all particle sizes. Par- scopicity is related to the two biomass-burning components
ticlesizessmallerthan80nmexhibitedconsiderablechemi- (BBOAandOOA-BB),whichinturncontributealmost35%
caldispersion(wherehygroscopicityvariedupto100%for tothefine-particleorganicwateroftheaerosol.Observation-
particles of same size); larger particles, however, exhibited derivedcalculationsoftheclouddropletconcentrationsthat
considerablylessdispersionowingtotheeffectsofconden- develop for typical boundary layer cloud conditions sug-
sationalgrowthandcloudprocessing.ACSMmeasurements gest that biomass burning increases droplet number, on av-
indicate that the bulk composition reflects the hygroscopic- erageby8.5%.Thestronglysublinearresponseofcloudsto
ityandchemicalnatureofthelargestparticles(havingadi- biomass-burning (BB) influences is a result of strong com-
ameter of ∼100nm at dry conditions) sampled. Based on petition of CCN for water vapor, which results in very low
PublishedbyCopernicusPublicationsonbehalfoftheEuropeanGeosciencesUnion.
7390 A.Bougiatiotietal.:ImpactofbiomassburningonCCNproperties
maximum supersaturation (0.08% on average). Attributing terizetherelativeroleofaerosolnumberandchemicalcom-
dropletnumbervariationstothetotalaerosolnumberandthe position(hygroscopicity)variabilitytothepredicteddroplet
chemical composition variations shows that the importance numbervariabilityincloudsformedfromBB-influencedair
of chemical composition increases with distance, contribut- masses.Theseissuesareimportant,becausethesupersatura-
ingupto25%ofthetotaldropletvariability.Therefore,al- tionthatdevelopsincloudsisnotknownbeforehand,noris
though BB may strongly elevate CCN numbers, the impact itconstant,butratherastrongfunctionoftheCCNlevelsand
ondropletnumberislimitedbywatervaporavailabilityand clouddynamicalforcing(updraftvelocity).
depends on the aerosol particle concentration levels associ- Inthecurrentstudywefocusonthehygroscopicity,CCN
atedwiththebackground. concentrations and resulting droplet formation characteris-
tics (droplet number and cloud supersaturation) associated
withairmassesinfluencedbysummertimebiomass-burning
events in the eastern Mediterranean. The smoke-laden air
1 Introduction masses sampled were subject to a range of atmospheric
processing (several hours up to three days), identified us-
Globally, biomass burning (BB) is a major source of at- ing remote sensing techniques (Moderate Resolution Imag-
mospheric aerosols (Andreae et al., 2004). In the eastern ing Spectroradiometer, Kaufman and Remer, 1994; Cloud-
Mediterranean,uptoone-thirdofthedrysubmicronaerosol Aerosol Lidar with Orthogonal Polarization, Winker et al.,
mass during the summer period consists of highly oxidized 2009; Mamouri et al., 2012), back-trajectory analysis and
organiccompounds(Hildebrandtetal.,2010).DuringJuly– other in situ chemical metrics. Values of the hygroscopic-
September, biomass-burning aerosol originates from long- ity parameter, κ, were derived from CCN and Hygroscopic
range transport from southern Europe and countries sur- TandemDifferentialMobilityAnalyzer(HTDMA)measure-
rounding the Black Sea (Sciare et al., 2008). Bougiati- ments and linked to distinct chemical constituents identi-
oti et al. (2014) showed that of the total organic aerosol fied with positive matrix factorization of the chemical con-
(OA),about20%isfreshlyemittedbiomass-burningorganic stituents measured with an Aerosol Chemical Speciation
aerosol(BBOA),30%isoxidized,processedOAoriginating Monitor (ACSM). Finally, the observations are used to pre-
from BBOA (BB-OOA), and the remaining 50% is highly dicttheclouddropletnumberandsupersaturationformedin
oxidizedaerosolthatresultsfromextensiveatmosphericage- clouds that develop in each air mass, focusing on the con-
ing.Hence,intermsoforganicmass,duringtimeperiodsof tribution of aerosol number and hygroscopicity to the pre-
high biomass-burning activity, at least 50% of the aerosol dicteddropletnumbervariability.Thisisoneoftheveryfew
canbeattributedtoBBemissions. field studies that use in situ observations to (i) unravel the
Aerosol liquid water content (LWC) is a key medium for contributionsofcompositionandaerosolsizetoBB-related
atmosphericchemistrythatalsodrivesthepartitioningofsol- CCNdistributionsandtheirimpactsonclouddropletnumber
ubleorganicvaporstotheparticlephase(CarltonandTurpin, and (ii) quantify the contributions of biomass-burning con-
2013). LWC is a prime modulator of aerosol direct radia- stituentstoaerosolhygroscopicityandliquidwaterinthere-
tiveforcing(e.g.,Pilinisetal.,1995),andbypromotingsec- gion.
ondary aerosol formation it can influence aerosol mass and
number that impact both the direct and indirect effect of
aerosols(Kanakidouetal.,2005). 2 Experimentalmethods
Biomass-burningaerosolparticleshavethepotentialtoact
as cloud condensation nuclei (CCN), thereby impacting on 2.1 Samplingsiteandperiod
cloud properties and climate. Modeling studies suggest that
BBisasignificantglobalsourceofCCNnumber(Spracklen The measurements were performed at the Finokalia at-
et al., 2011). Laboratory and field studies have shown that mospheric background station (35◦32(cid:48)N, 25◦67(cid:48)E; http://
biomass-burning aerosol is highly hygroscopic and water- finokalia.chemistry.uoc.gr)oftheUniversityofCrete,which
soluble,exhibitinguptoabouthalfthewateruptakecapacity is part of the Aerosols, Clouds, and Trace gases Re-
of ammonium sulfate (Asa-Awuku et al., 2008; Cerully et search Infrastructure Network (ACTRIS; http://www.actris.
al.,2015).Engelhartetal.(2012)foundthatfreshlyemitted net/). More details about the sampling site are provided by
BBOAdisplaysabroadrangeofhygroscopicity(κ parame- Mihalopoulos et al. (1997) and Sciare et al. (2003). Al-
terfrom0.06to0.6)thatconsiderablyreducesafterjustafew though measurements took place from mid-August to mid-
hoursofphotochemicalageing,toaκvalueof0.2±0.1(Pet- November 2012, the focus of our analysis involves the pe-
tersandKreidenweis,2007).Fewstudies,however,focuson riods of intense biomass-burning influence from August to
the hygroscopicity of ambient BB aerosol as a function of September2012.BBplumessampledwerefresh,originating
atmosphericageextendingouttoafewdays.Relativelyfew from the Greek islands and mainland (transport time 6–7h)
studiesalsogobeyondCCNtocalculationsofdropletnum- but also from long-range transport from the Balkans (trans-
ber(e.g.,Robertsetal.,2003),andevenfewerstudiescharac- port time >1 day) as determined by using Hybrid Single
Atmos.Chem.Phys.,16,7389–7409,2016 www.atmos-chem-phys.net/16/7389/2016/
A.Bougiatiotietal.:ImpactofbiomassburningonCCNproperties 7391
ParticleLagrangianIntegratedTrajectoryModel(HYSPLIT)
back-trajectory analysis as shown in detail in Bougiatioti et
al.(2014),combinedwiththehotspots/firedatafromModer-
ateResolutionImagingSpectroradiometer(MODIS)/FireIn-
formationforResourceManagementSystem(FIRMS;Remy
andKaiser,2014).
2.2 Instrumentationandmethodology
Chemical composition and mass concentration of non-
refractorycomponents(ammonium,sulfate,nitrate,chloride
and organics) of the submicron aerosol fraction was pro-
vided by an Aerodyne Research Aerosol Chemical Speci-
ation Monitor (ACSM; Ng et al., 2011) with a temporal
resolution of 30min. More details of the ACSM measure-
ments and subsequent analysis can be found in Bougiati-
oti et al. (2014). Total absorption measurements provided
theblackcarbon(BC)concentrationsbyaseven-wavelength
aethalometer (Magee Scientific, AE31). From the BC mea-
surementsandusingtheapproachofSandradewietal.(2008)
thewoodburningandfossilfuelcontributiontothetotalBC
concentrationswerecalculatedusinganabsorptionexponent
of1.1forfossilfuelburningand1.86forpurewoodburning.
Theaerosolparticle-sizedistributionsfrom9to850nmwere
measuredwitha5minresolutionbyacustom-builtscanning Figure1.SchematicofthesetupusedfortheCCNandmixingstate
mobilityparticlesizer(SMPS;TROPOS-type,Wiedensohler measurements.
et al., 2012) equipped with a condensation particle counter
(CPC; TSI model 3772; Stolzenburg and McMurry, 1991).
Sample humidity was regulated below the relative humid- al., 2006; Bezantakos et al., 2013) coupled with a conden-
ity of 40% with the use of Nafion® dryers in both aerosol sation particle counter (CPC, TSI Model 3772). The RH in
andsheathflow,andthemeasurednumbersizedistributions both the aerosol and the sheath flow in DMA-2 was con-
werecorrectedfordiffusionalparticlelosses(Kalivitisatal., trolled by proportional-integral-derivative (PID) controllers
2015). towithin±2%accuracy.BothDMAsintheHTDMAsystem
A Continuous Flow Stream-wise Thermal Gradient CCN were calibrated with polystyrene latex (PSL) spheres. The
Chamber (CFSTGC; Roberts and Nenes, 2005) was used other classified stream was introduced into the CFSTGC to
in parallel with a Hygroscopic Tandem Differential Mobil- measuretheCCNactivityofparticles.TheCFSTGCwasop-
ityAnalyzer(HTDMA;RaderandMcMurry,1986)tomea- eratedinscanningflowCCNanalysis(SFCA)mode(Moore
sure the CCN number, activity and hygroscopicity of ambi- andNenes,2009),inwhichtheflowrateinthegrowthcham-
entaerosolforsupersaturated,(0.1–0.7%)andsubsaturated berchangesovertime,whileaconstantstreamwisetemper-
conditions(relativehumidity,RH=86%),respectively.The ature difference is applied. This causes supersaturation to
whole system, which is illustrated in Fig. 1, sampled air changecontinuously,allowingtherapidandcontinuousmea-
withatotalflowrateof1.8Lmin−1.Afterpassingthrougha surementofCCNspectrawithhightemporalresolution.The
Nafiondryer(MD-110-12S-2,PermaPureLLC,RH<30%) SFCA cycle used involved first increasing the flow rate lin-
the dried particles were selected based on their electrical earlybetweenaminimumflowrate(Q ∼300cm3min−1)
min
mobility by a Differential Mobility Analyzer (DMA-1; TSI and a maximum flow rate (Q ∼1000cm3min−1) over a
max
Model 3080; Knutson and Whitby, 1975). The sheath flow ramptimeof60s.TheflowwasmaintainedatQ for10s
max
and classified aerosol outlet flow of DMA-1 were 10.8 and and then linearly decreased to Q over 60s. Finally, the
min
1.8Lmin−1, respectively, while the mobility diameter was flowratewasheldconstantatQ for10sandthescancy-
min
changedevery6minbetween60,80,100and120nm. clewasrepeated.TheactivateddropletsintheCFSTGCwere
TheclassifiedaerosolfromDMA-1wasthensplitintotwo counted and sized at the exit of its growth chamber with an
streams. The first stream was passed through a Nafion tube opticalparticlecounter(OPC)thatdetectsdropletsandclas-
humidity exchanger where its RH was increased to 86%. sifiestheminto20sizebinswithdiameterrangingfrom0.7
ThesizedistributionoftheRH-conditionedparticleswasde- to10µmevery1s.
termined by a second DMA (DMA-2; custom-made DMA The water vapor supersaturations developed in the CF-
using a closed-loop sheath flow with RH control; Biskos et STGC during an SFCA cycle were characterized with am-
www.atmos-chem-phys.net/16/7389/2016/ Atmos.Chem.Phys.,16,7389–7409,2016
7392 A.Bougiatiotietal.:ImpactofbiomassburningonCCNproperties
monium sulfate calibration aerosol following the procedure where κ = 4A3 expresses the dependence of κ on d and
27d3s2 p
ofMooreandNenes(2009).Inbrief,anammoniumsulfate p
s, A= 4Mwσw is the Kelvin parameter, while M , σ and
solution was atomized, dried, charge-neutralized and clas- RTρw w w
ρ are,respectively,themolarmass,thesurfacetensionand
sified by DMA-1. The resulting monodisperse aerosol flow w
thedensityofwater.RistheuniversalgasconstantandT is
was split between DMA-2 and the CFSTGC, operating in
temperature.
SFCA mode and with a CFSTGC streamwise temperature
In Eqs. (2), (3), s* and κ∗ correspond to the characteris-
difference of (cid:49)T =5K. From this setup, we obtain the in-
tic critical supersaturation and hygroscopicity parameter of
stantaneous concentrations of the classified aerosol and the
the monodisperse aerosol, respectively, and correspond to
resulting CCN during the SFCA flow cycles. The ratio of
the most probable value of the parameters (Cerully et al.,
CCN to total aerosol number gives the activation ratio, R ,
a 2011). From Eq. (3), the probability distribution function
whichvarieswiththeinstantaneousvolumetricflowrate,Q,
for κ,ps(κ), can be derived for the ambient monodisperse
intheCFSTGC.UsingdatafrommultipleSFCAflowcycles,
aerosol(Cerullyetal.,2011):
R isthenfittoasigmoidfunctionthatdependsonQ:
a
Ra≡ CCCNN =ao+1+(aQ1/−Qa500)−a2, (1) ps(κ)= E1 dRdaκ(κ) =−(cid:18)κC∗2(cid:0)κκ∗(cid:1)C2−(cid:19)12. (4)
where a0,a1,a2 and Q50 are constants which describe the 1+(cid:0)κκ∗(cid:1)C2
minimum, maximum, slope and inflection point of the sig-
moidal, respectively. The “critical flow rate”, Q50, corre- Analysis of ps(κ) can provide a direct measure of the
sponds to the instantaneous flow rate that produces a level
chemicalheterogeneityoftheCCNpopulation.Forthis,we
of supersaturation, s, required to activate the measured
adoptthemetricofchemicaldispersion,σ(κ),introducedby
monodisperse aerosol and determined from the size of the
Lance(2007)andfurtherdevelopedinCerullyetal.(2011)
classifiedaerosolusingKöhlertheory(Mooreetal.,2012a).
andLanceetal.(2013):
Repeating the procedure for many sizes of classified am-
moniumsulfateresultsintheSFCAcalibrationcurve,which 1
gives the supersaturation in the CFSTGC as a function of R(κ−κ∗)2ps(κ)dκ
flowrate(i.eQ50vs.s)throughoutanSFCAflowcycle.Ab- σ2(κ)= 0 , (5)
soluteuncertaintyofthecalibratedCCNCsupersaturationis R1
ps(κ)dκ
estimatedtobe±0.04%(Mooreetal.,2012a,b).
0
Inourinstrumentsetup,R canchangeeitherfromvaria-
a
tions in the size of the monodisperse aerosol, dp, or the in- whereσ(κ)isthesquarerootofvarianceofκ∗;asthechem-
strument supersaturation, s (or flow rate, Q). The indepen- icalheterogeneityoftheCCNincreases,thedistributionofκ
dentlyvariedparameterisindicatedhereafterinparentheses broadens,andσ(κ)becomeslargersothattherangeinCCN
infrontoftheactivationratio,e.g.,Ra(Q),Ra(s),Ra(dp)for hygroscopicityisgivenbyκ∗±σ(κ).
RaasafunctionofQ,s anddp,respectively. Particle water uptake at subsaturated conditions in the
AnalysisofRaobtainedforourexperimentalsetupforam- NafiontubehumidityexchangerandDMA-2wasalsoeval-
bientparticlessamplesprovidesveryimportantinformation uated by the growth factor measured for the calibration
on the activity and chemical mixing state of the CCN. This (NH ) SO . Particle hygroscopic growth at subsaturated
4 2 4
iscarriedoutasfollows.Foreveryparticlesizedp setbythe conditions(gi)isobtained:
DMA-1,R (Q),ismeasuredateveryinstantintheCFSTGC
a
accordingtoEq.(1).Typicallya0(cid:28)a1;giventhatQands g(RH)= dm(RH), (6)
arerelatedthroughthecalibration,Ra(Q)datacanbetrans- dp
formedtoR (s):
a
where d (RH) and d are the geometric mean mobility di-
E m p
Ra(s)= 1+(cid:0)ss∗(cid:1)C, (2) aamtRetHer=s o8f6t%he)assammpelaesdurpeadrtbicyleDsMatAt-h2eahnyddtrhaeteCdPsCta,tean(di.ea.t,
where s, s∗ correspond to Q, Q of the monodisperse thedrystateselectedbyDMA-1(RH<30%).Particle-size
50
distributions at 86% RH were inverted using the TDMA fit
aerosol.EandCareparametersdeterminedfromfitting.Ac-
algorithm (Stolzenburg and McMurry, 1988), which is also
cordingtoCerullyetal.(2011),R (s)representsacumula-
a
capable of distinguishing between internally and externally
tivedistributionofcriticalsupersaturationforparticleswith
mixedaerosols(e.g.,Bezantakosetal.,2013).
drydiameterd ;Köhlertheorycanthenbeappliedtoexpress
p
HygroscopicitiesdeterminedfromtheCCNmeasurements
R (s)intermsofthehygroscopicityparameterR (κ):
a a
aredifferentiatedbycorrespondingvaluesfromtheHTDMA
E
R (κ)= , (3) measurementsbyaddingasubscriptCCNorHTDMA(e.g.,
a 1+(cid:0)κκ∗(cid:1)C/2 κHTDMA, κCCN). κHTDMA is calculated from the HTDMA-
Atmos.Chem.Phys.,16,7389–7409,2016 www.atmos-chem-phys.net/16/7389/2016/
A.Bougiatiotietal.:ImpactofbiomassburningonCCNproperties 7393
measuredsubsaturatedhygroscopicgrowthfactors: in detail by Bougiatioti et al. (2014). Nevertheless, the or-
ganicaerosolderivedfromtheageingofthebiomass-burning
 
κHTDMA=(g(RH)3−1)exp(gR(RHHA)·dp)−1, (7) afielero,sreogla(OrdOleAss-BofBt)hiedBenBtiOfiAeditfowraaslldeevrievnetdshfraodma(sBimouilgairaptiroot-i
100% et al., 2014). A transport time estimate and back-trajectory
analysis were conducted with the plume arrival (h) from
with A being the Kelvin parameter defined in Eq. (3). The
base time graphics with the help of the HYSPLIT model
exponential term of this equation (i.e., the Kelvin term) is
(http://www.arl.noaa.gov/HYSPLIT_info.php).
usedtoaccountforcurvatureeffectsonvaporpressure.
MODIS and CALIOP measurements confirm the validity
Anaveragevalueofthehygroscopicparameterateachdry
of the Bougiatioti et al. (2014) analysis by clearly showing
particle size, d , which is representative of the hygroscopic
p
theorigin,transportpathandcharacteristicsofthebiomass-
propertiesoftheentireparticlepopulation,isobtainedasfol-
burningplumefromtheChiosfireon18and19August2012.
lows:
Indeed, in Fig. 2a we show the MODIS true color image
gZmax showingtheplumeemergingfromtheChiosfireson18Au-
κHTDMA= κ(g(RH))p(g(RH))dg(RH), (8) gust 2012 as obtained during its 09:39UTC overpass over
gmin Greece (Kyzirakos et al., 2014). The blue and red lines de-
lineatethegroundtrackoftheCALIPSOsatelliteduringits
whereκ(g )isobtainedfromthegrowth-factorprobabil-
(RH) overpass over Crete several hours later on 19 August 2012
itydistributionusingEq.(5)andp(g )istheprobability
(RH) (the first between 00:27 and 00:40 and the second between
ofeachgrowthfactor.g ,g aretheminimumandmax-
min max 11:34and 11:47UTC); theredstarshows thesamplingsite
imumgrowthfactorsobtainedfromthegrowth-factorproba-
at Finokalia station. The CALIPSO vertical profiles of the
bilitydistributionandrepresenttheminimumandmaximum aerosol backscatter coefficient (in km−1sr−1) at 532 and
gwithnon-zeroprobabilityvalue.
1064nm for the two overpasses are shown in Fig. 2b (left-
To support the in situ instruments, we used space-borne
handside)togetherwiththecorrespondinglinearparticlede-
laserremotesensing(lidar)datafromtheCloud-AerosolLi-
polarization ratio at 532nm obtained between 00:27:30 and
darwithOrthogonalPolarization(CALIOP)(Mamourietal.,
00:40UTC (right-hand side). Comparing the midnight and
2009;Winkeretal.,2009)tocharacterizetheplumesemerg-
the daytime aerosol backscatter profiles in Fig. 2b, we ob-
ing from the fire hot spots. The fire plume originating from
serve that the midnight values are 3–4 times lower than the
any location can be tracked by HYSPLIT back-trajectory
daytime ones for altitudes up to 3km height. In addition,
analysis(Bougiatiotietal.,2014),andlidarobservationscan
the daytime observations show a discrete aerosol layer be-
be used to check the presence of aerosol layers and aerosol
low 1.5km. As for the linear particle depolarization ratio it
types.Opticalconfirmationofthesmokeplumesisprovided
shows a mean value of 19% up to 1.25km height and less
byMODISandFIRMSasshowninthesupplementaryma-
than6–10%above(1.25–2km).
terialofBougiatiotietal.(2014).
Finally, we made use of the classification scheme of the
CALIPSO data (Omar et al., 2009) to classify the different
subtypes of aerosols in the plume captured during its first
3 Resultsanddiscussion
overpassoverCreteon19August2012(00:27–00:40UTC).
3.1 Identifyingperiodsofbiomass-burninginfluence This classification scheme, based on the optical and micro-
physical properties of the sampled aerosols indeed reveals
Bougiatioti et al. (2014) identified the BB events analyzed the presence of a mixture of smoke, polluted dust and ma-
herebythetimeevolutionofabsorptionenhancements(BC) rine particles observed below a 3km altitude (black color
in the aerosol, which was further verified by FIRMS and for smoke, brown for polluted dust and blue for marine) as
back-trajectory analysis. During these events mass spectro- shown in Fig. 2c, within the depicted area between 39◦N,
metricbiomass-burningtracers(i.e.,fragmentsm/z=60and 24.1◦E–37◦N,23.4◦E,justNWoftheFinokaliastationand
73) also exhibited elevated levels. Clear biomass-burning along the CALIPSO ground track. According to this clas-
contribution was identified by source apportionment using sification, over Crete the presence of polluted dust (mixed
positive matrix factorization (PMF) analysis for four dis- withsmokeandmarineaerosols)prevailswithinthemarine
tinctevents.TheBBeventsconsideredincludeaseverefire boundary layer, which for Finokalia is approximately 1km
event that burned most of the island of Chios (19–21 Au- (Kalivitis et al., 2007), extending up to 0.8–1.2km height.
gust), an extensive wildfire at the Dalmatian coast in Croa- This implies that for the 00:27–00:40UTC time slot, the
tiaresultinginsmokeplumesthatspreadacrosstheBalkans BB aerosols sampled by the ground-based in situ measure-
during the period 28–30 August, and less extensive fires on mentsatFinokaliawouldcontributeless(duetodilution)to
the Greek islands of Euboea (3–5 September) and Andros theglobalaerosolmassloadingthanifmeasuredoverwest-
(12–13September).AllfireeventsexhibiteddiscreteBBOA ernCrete.
profilesdependingonthebiomass-burningfuel,aspresented
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7394 A.Bougiatiotietal.:ImpactofbiomassburningonCCNproperties
Figure2.(a)SatellitecompositeviewfromMODISofthefireplumeemergingfromtheislandofChioson18August2012(courtesyof
NASA).TheblueandredlinesdelineatethetwogroundtracksoftheCALIPSOsatelliteduringitsoverpassoverCreteon19August2012
between00:27–00:40and11:34–11:47UTC.(b)Verticalprofilesoftheaerosolbackscattercoefficient(inkm−1sr−1)at532and1064nm
(left)andlinearparticledepolarizationratioat532nm(right)measuredbyCALIPSOand(c)verticalprofilesoftheaerosolsubtypescaptured
byCALIPSOduringitsoverpassoverCrete;themarkedareaislocatedattheNWofFinokaliastation(00:27–00:40UTC).
3.2 PM composition of that of sulfate. Source apportionment clearly shows that
1
these increases are related to BB influences (Bougiatioti et
al.,2014).DuringallBBeventsthereisacleardominanceof
The average mass concentration for the whole measure-
woodburningoverfossilfuelcontributionstoBC.Thewood
ment period (mid-August to mid-November 2012), based
burningcomponentofBCisalsoprovidedasareference,de-
on the ACSM measurements combined with BC from the
pictingtheenhancedcontributionofbiomassburningduring
aethalometer,was9.2±4.8µgm−3.Thecorrespondingme-
thehighlightedevents.
dian concentrations for the main aerosol constituents were
Based on the size-resolved CCN activity measurements
3.56,1.31,3.03and0.47µgm−3 forsulfate,ammonium,or-
and the inferred hygroscopicity parameter κ of the aerosol
ganicsandBC,respectively.Figure3representsthetimese-
(Eq.3),itisevidentthatthechangesintheorganicsandsul-
ries of the major submicron species where it can be seen
fate mass fractions will also influence the CCN concentra-
that during the fire events the contribution of organics and
tions,activationfractionsandhygroscopicity.AstheACSM
BCincreasedsubstantially(from34.9to46.5%fororganics
provides bulk submicron chemical composition and thus is
andfrom6.1to9.5%forBC)withasimultaneousreduction
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A.Bougiatiotietal.:ImpactofbiomassburningonCCNproperties 7395
trationsforthelargerparticlessizesincreaseandfollowthe
BBOA trend. This increase was more pronounced, depend-
ingontheproximityofthefireandthereforethetraveltime
oftheairmasses.Roseetal.(2010)alsoobservedincreases
in CCN during a biomass-burning event near the megacity
Guangzhou, China, where CCN number concentrations at
s=0.068and0.27%,increasedby90and8%,respectively.
The same study attributed these changes to increases in the
particlesizewhenBBinfluencewaspresent.
Of all particle sizes examined, it appears that those hav-
ingmobilitydiameterof60nmexhibittheleastvariabilityin
Figure 3. Time series concentrations of major PM1 species that terms of CCN number concentration before and during the
contributeintheidentificationoftheBBevents.Theshadedareas BBinfluence(Fig.4,opencircles).Theconcentration,how-
representthefourconsideredfireevents. ever,significantlyincreasedduringtheBBeventfromCroa-
tia(Fig.4b).Thisevent,togetherwithothersofsmallerex-
tent,isassociatedwithnewparticleformation(NFP)events.
not able to capture any size-dependent chemical composi- The observed frequency of NPF days at Finokalia is close
tion, the size-resolved CCN activity measurements are able to 30% (Kalivitis et al., 2015), regardless of the presence
toresolvedistinctCCNactivityandmixingstateofthedif- or not of BB-laden air masses. Based on aerosol chemical
ferent particle sizes. These aspects are thoroughly investi- composition, it appears that both gaseous sulfuric acid and
gatedinthefollowingsections. organiccompoundstakepartinthegrowthofnucleatedpar-
ticlestoCCN-relevantsizes.Theseorganiccompoundsthat
3.3 CNandCCNnumberconcentrationsand contribute to the nuclei growth may be of different origins,
biomass-burningevents including biogenic emissions, biomass burning and other
possible anthropogenic sources from long-range transport
Forallfoureventsofbiomass-burning-influencedairmasses (Kalivitisetal.,2015).FromFig.4bitappearsthatwhenthe
arriving at Finokalia, the observed aerosol number concen- BB event is combined with such a NPF event within a few
tration increased considerably, regardless of size. The in- hours,60nmparticlesarestronglyinfluencedandtheirCCN
creasesarequantitativelyexpressedusingaverageddatafrom concentrations increase considerably. The influence on BB
at least 6h prior to the arrival time of the BB smoke. For tothehygroscopicityof60nmparticlesandtheothersizesis
particlesizesabove100nm,BBincreasedconcentrationsby examined in a subsequent section. A detailed discussion on
65% for the Chios fire, around 50% for the Croatia fire, theseeventsandtheircontributiontoCCNconcentrationsis
88% for the Euboea fire and about 150% for the Andros providedbyKalivitisetal.(2015).
fire. Less pronounced increases were seen for the smaller
particle sizes. The corresponding impacts on CCN concen- 3.4 CCNactivationfractionsduringfireevents
trations for the classified aerosol are shown in Fig. 4 for all
fireevents.Concentrationsaregivenatthecharacteristicsu- Asdemonstratedintheprecedingsection,CCNnumbercon-
persaturation,s∗,ofthemonodisperseCCNasclassifiedby centrations during the biomass-burning events proportion-
DMA-1 (Sect. 2.2). Within each event, s∗ did not vary by ately increased for the larger particle sizes. Figure 5 shows
more than 13.6%; therefore most of the variability in CCN the activation fractions (R (Q)) for three of the four parti-
a
numbercanbeattributedtovariationsinthesizedistribution, cle sizes and the four considered fire events (120nm is not
ratherthanshiftsinthechemicalcomposition(i.e.,s∗). shown as it exhibits the same behavior as 100nm). As an
Asexpected,smallerparticlesexhibitahighercriticalsu- indicator of BB influence, we use the concentration of the
persaturation(Bougiatiotietal.,2011).Duringperiodswith aged BB factor identified in the ACSM spectra (OOA-BB),
smoke influence, critical supersaturations tend to increase, asitrepresentstheatmosphericallyprocessedcomponentof
indicating that particles associated with BB are less effec- BBOA.Thisfactorischosenasitconstitutesalargerpartof
tive CCN compared to those of the background aerosol. To theorganicaerosol(30%)withBBinfluenceanditsageing
quantify the direct influence of biomass burning to particle isexpectedtobereflectedintermsofCCNactivity.
andCCNnumberconcentrations,westudiedtheconcentra- For all particle sizes, the activation fractions are derived
tion of the BBOA component, identified by PMF analysis fromtheasymptoteofthefittingtothesigmoidalfunctionof
of the ACSM mass spectra (Bougiatioti et al., 2014). The the R (s) during each supersaturation cycle and represents
a
BBOA concentration time series depicts the arrival time of the CCN behavior at the highest supersaturations measured
thesmokeandtheintensityoftheBBinfluence. (s>0.6%).Figure 5 showsthat eventhough CCNconcen-
The data shown in Fig. 4 indicate that during the major- trationsincreaseforparticleslargerthan80nm,theiractiva-
ity of the identified biomass-burning events, CCN concen- tion fractions remain more or less stable and very close to
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7396 A.Bougiatiotietal.:ImpactofbiomassburningonCCNproperties
Figure4.CCNconcentrationsfortheselectedparticlesizesduringthearrivalofthesmokeplumesfor(a)Chios,(b)Croatia,(c)Euboea
and(d)Andros.Theblacksolidlinerepresentsthebiomass-burningcomponentoftheorganicaerosolatthegiventime.
unitythroughouttheevents.Thisobservationimpliesthatal- events where the time for transport and ageing is most lim-
most all aerosol particles larger than 80nm are CCN active ited(henceleastagedandhygroscopic).Theparticlechem-
at supersaturations higher than 0.6%, within uncertainties. ical dispersion retrievals (Sect. 3.5) also support this view.
Thisisnotthecasefor60nmparticleswhichhaveactivation The same conclusion is also drawn from the data provided
fractionsat0.6%s (andinthecaseoftheChiosfireactiva- byBougiatiotietal.(2011)forthesamesamplingsiteduring
tion fractions of 80nm particles as well at 0.4% s) exhibit summertime,andareverifiedbyanalysisofthechemicaldis-
thehighestvariability,withratiosapproachingvaluesaslow persionandHTDMAdatashowninfollowingsections.The
as40%.ItcanbeseenthatasconcentrationsoftheOOA-BB evolution of the mixing state of each particle size is further
starttoincrease,theactivationfractionsof60nmparticlesat investigated by the HTDMA measurements in a subsequent
∼0.6%s starttodiminish.Itthusappearsthatlargerparti- section(Sect.3.6)aswell.
cles are mostly internally mixed, as also seen by their high
activation ratios, while small particles could be externally 3.5 Hygroscopicityandchemicalheterogeneityduring
mixedpopulations.Anindicationoftheheterogeneityofthe thebiomass-burningevents
smallerparticlesizescomparedtothelargeronesistheslope
ofthesigmoidfittotheRa(s);thesteepertheslope,themore The characteristic hygroscopicity parameters, κ∗, derived
homogeneous the population, and given that the 60nm par-
from the CCN measurements for all particle sizes and for
ticles exhibited the broader slopes, the more heterogeneous
thefourselectedfireeventsarepresentedinFig.6.Asaref-
theseparticlesare.Thiscanbeexplainedbyasize-dependent
erence for the arrival time and magnitude of the event, the
chemicalcompositionandthepresenceofapopulationwith
concentration of the BBOA factor is also shown in the fig-
notablelowerhygroscopicitythatprohibitstheparticlesfrom
ure, which has the characteristics of the freshly emitted BB
actingasCCNandcanbeattributedtodifferentsourcesand
aerosolandisexpectedtohavemoreinfluenceonthehygro-
atmospheric processing (coagulation, cloud processing and
scopicityoftheparticles.Thesmallerparticleshavethelow-
condensationofsecondaryaerosol)thatgenerallytendtoin-
est κ values, and hygroscopicity consistently increased
CCN
ternallymixtheparticles,renderingthemmoreCCNactive.
withsize.Thishygroscopicitytrendhasalsobeenobserved
Indeed,thelowestactivationfractionsoccurforthestrongest
elsewhere(Duseketal.,2010;Cerullyetal.,2011;Levinet
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A.Bougiatiotietal.:ImpactofbiomassburningonCCNproperties 7397
Figure5.Activationfractionsfortheselectedparticlesizesduringthearrivalofthesmokeplumesfor(a)Chios,(b)Croatia,(c)Euboeaand
(d)Andros.Thebrownsolidlinerepresentstheprocessedbiomass-burningcomponentoftheorganicaerosol.
al.,2012;Paramonovetal.,2013;Liuetal.,2014)andisat- particlessubjecttoatmosphericprocessingwouldbepresent
tributedtotheenrichmentinorganicmaterialofsub-100nm inaseparatemodearound120nm(s ∼0.08%).Particles
max
particles.Basedonthederivedκ valuesforeachparticlesize larger than 100nm are usually more aged than the smaller
andwith knowledgeofthe distinctspeciesidentified bythe particles and more immediately associated with BB plumes
ACSM(organics,sulfate)andtheirrespectivehygroscopici- and the atmospheric processing they undergo (Kalivitis et
ties,thevolumefractionsfororganicsandinorganics(mainly al.,2015).Thehygroscopicityparameterfor100and120nm
ammonium sulfate) were estimated for each particle size. It particles are very similar and the fact that the variability in
indeedoccursthat60nmparticlesareonaverage89%com- the respective chemical composition is limited may indeed
posedoforganics,whiletherespectivevaluesfor80,100and be attributed to cloud processing, while 80nm particles are
120nm particles are 70, 50 and 41%. Most of the accumu- inbetweenthelowestandhighestκ values,anindication
CCN
lationmodeparticlesresultfromcondensationofsecondary ofsize-dependentchemicalcompositionofcomponentswith
sulfates,nitratesandorganicsfromthegasphaseandcoag- differenthygroscopicities.
ulation of smaller particles (Seinfeld and Pandis, 2006). In Figure6alsoshowsthatduringthearrivalofthebiomass-
order to examine the contribution of constituents from pri- burning-ladenairmasses,κ valuesofallparticlesizesrange
marysourcesthatarenotmeasuredbytheACSMtotheac- within0.2–0.3.Thisobservationisconsistentwithvaluesob-
cumulation mode particles, we compared the mass derived servedfromchamberexperimentsoffreshandagedbiomass-
fromtheACSM+BCandtheintegratedvolumedistribution burningaerosolandinsitustudiesfromthefield.Engelhart
fromtheSMPSconvertedtomass.Duringtheexaminedfire et al. (2012) performed a study where 12 different biomass
events,theACSM+BCwasonaverage68.6±19.3%ofthe fuels commonly burnt in North American wildfires were
SMPS-derivedmass.Thereforethisisanindicationthatnon- used to characterize their respective hygroscopicity. They
refractorymaterialneglectedbytheACSMintheaccumula- found that while κ of freshly emitted BBOA prior to pho-
tionmodeparticlesprobablyhasasmallinfluenceonparticle tochemical ageing covered a range from 0.06 to 0.6, after
hygroscopicity.Accumulationmodeparticlescanalsoresult a few hours of photochemical processing, the variability of
from cloud processing. Based on cloud droplet calculations biomass-burning κ values from the different fuels was re-
presented in a subsequent section (Sect. 3.8) it appears that duced and hygroscopicity converged to a value of 0.2±0.1
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7398 A.Bougiatiotietal.:ImpactofbiomassburningonCCNproperties
Figure6.Characteristichygroscopicityparametersoftheselectedparticlesizesfor(a)Chios,(b)Croatia,(c)Euboeaand(d)Andros.The
solidlinerepresentsthebiomass-burningcomponentoftheorganicaerosolatthegiventimeandtheshadedareasrepresentthesmokeplume
influenceperiod.
(Cerully et al., 2011; Engelhart et al., 2012). Based on the Table1.Calculatedchemicaldispersionintermsofσ(κ)/κforthe
derivedhygroscopicityparametersforeachparticlessizebe- fourstudiedfireeventsandallmeasuredparticlesizes.
foreandduringtheBBinfluence,itoccursthatsmokecauses
a relative decrease of κ in the order of 22% for 80nm par- 60nm 80nm 100nm 120nm
ticles, 30.6% for 100nm particles and 30.9% for 120nm Chios 0.85±0.14 0.73±0.14 0.60±0.20 0.41±0.16
particles on average for the four events, while κ for 60nm Croatia 0.77±0.18 0.68±0.19 0.44±0.12 0.41±0.10
particlesdeviatebyonly14%. Euboea 0.70±0.20 0.49±0.10 0.32±0.08 0.29±0.06
Andros 0.71±0.10 0.52±0.13 0.34±0.10 0.30±0.06
During the fire events the contribution of organics and
BC to the submicron aerosol mass fraction increased sig-
nificantlywhilethepresenceofsulfatedeclined.Thisisex-
pectedtoinfluencetheCCNactivityofthesampledaerosol
thechemicaldispersionσ(κ)ofthehygroscopicityparame-
particles as it would cause variations in the inorganic and
ter κ, expressed by the standard deviation of kappa around
organic mass fractions. It has already been established that
themostprobablehygroscopicityκ∗,anditsdependenceon
theκ valueofprimaryaerosoldecreasesastheorganicmass
particlesize.AsnormaloperationuncertaintiesandtheDMA
fraction of aerosol increases (Petters et al., 2009; Engelhart
transferfunctioncaninduceabroadeningofR (s)andR (κ)
etal.,2012).Withphotochemicalageing,theincreasedoxy- a a
andthereforecontributetoσ(κ),theinferredσ(κ)contains
genationofthefreshlyemittedBBOAmayinfluencethehy-
afairlyconstantinstrumentoffsetandatime-dependentcon-
groscopicity of the organic components, but the concurrent
stituentthatisrepresentativeoftherealchemicalvariability.
increase of the inorganic fraction of the aerosol contributes
This offset value, owing to the DMA transfer function and
totheobservedincreaseofκ (inorganiccontentvs.age-
CCN
otherinstrumentlimitshasbeencalculatedtoberoughly0.25
ing).
(Cerullyetal.,2011).Table1showsthecalculatedchemical
Toexaminetheimpactofatmosphericprocessingandage-
dispersion, in terms of σ(κ)/κ, for the four fire events and
ing on the composition of the sampled aerosol, we studied
the measured particle sizes. It is immediately apparent that
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