Sub-Antarctic marine aerosol: significant contributions from - ACPD

36 Pages·2013·4.36 MB·English

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Abstract D
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BgDaieotcegedemnoibcneirBn2iflr0du1eI0ns.claTenhsdiso(rn5e4mt◦h0oe0te0cSSmoo,mal3irdp8in o◦Ee0sai3etri0ontWhvniOpen Access)raoinnndmthecenhtaSirsoaucchtthearrAiasttcliactensrtiioscefddauSebrryionollgisadDori sNgElcueoawssvrsieoteenhrsmeaOpen Accessbbiienrdvreaasnntddi- cussionP
a
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5 seal colonies. The chemical compositionOpof the submicron particles, measureOpd by an er
ameornoisuoml,m2a2s%ssopregcatnroicmseTathenerd (C4A7rMy%oSs)ps,ehwaearssea2en Accelt1i%nclnuodnin-sgesaesaasltasltuTslfhuaeltfea Ct2ery.%oADsnispnictheursawesitorenems,en Accee7t%hoadmto- |
isolatetheseasaltsignaturefromthehighss-resolutionAMSdatawasapplied.Gssenerally, D
is
theaerosolwasfoundtobelessacidicthaninothermarineenvironmentsduetothe cu
s
10 high availability of ammonia, from local fauna emissions. By positive matrix factorisa- sio
tionfivedifferentorganicaerosol(OA)profilescouldbeisolated:anaminoacids/amine n
P
factor(AA-OA,18%ofOAmass),amethanesulfonicacidOAfactor(MSA-OA,25%),a a
p
marineoxygenatedOAfactor(M-OOA,40%),aseasaltOAfraction(SS-OA,7%)and e
r
locally produced hydrocarbon-like OA (HOA, 9%). The AA-OA was dominant during
|
thefirsttwoweeksofNovemberandfoundtoberelatedwiththehatchingofpenguins
15
in a nearby colony. This factor, rich in nitrogen (C:N ratio = 0.13), has implications Dis
c
for the biogeochemical cycling of nitrogen in the area as particulate matter is often u
s
transportedoverlongerdistancesthangaseousN-richcompounds.TheMSA-OAwas sio
n
mainly transported from more southerly latitudes where phytoplankton bloomed. The
P
20 bloomwasidentifiedasoneofthreesourcesforparticulatesulfateonBirdIsland,next ap
e
toseasaltsulfateandsulfatetransportedfromSouthAmerica.M-OOAwasthedom- r
inant organic factor and found to be similar to marine OA observed at Mace Head, |
Ireland. An additional OA factor highly correlated with sea salt aerosol was identified
D
(SS-OA). However, based on the available data the type of mixture, internal or ex- is
c
25 ternal, could not be determined. Potassium was not associated to sea salt particles us
s
during19%ofthetime,indicatingthepresenceofbiogenicparticlesinadditiontothe io
n
MSA-OAandAA-OAfactors. P
a
p
e
r
8262 |
1 Introduction D
is
c
u
Themarineenvironmentrepresentsoneofthelargestnaturalaerosolsources(Rinaldi ss
et al., 2010), driven by the emission of 133Tgyr−1 submicron particulate matter from ion
sea-spray,includingprimaryandsecondaryorganicmatter(13%)andseasalt(Vignati Pa
p
5 et al., 2010; Gantt et al., 2011). Marine aerosol systems are important as they exert er
a significant influence on the Earth’s radiative balance through provision of a large
|
numberofcloudcondensationnuclei(e.g.,Meskhidzeetal.,2011).Atthesametime,
marineparticulatematterplaysasubstantialroleinbiogeochemicalcyclingofchemical D
is
elementsandnutrients(O’DowdanddeLeeuw,2007).Numerousrecentstudieshave cu
s
been conducted to investigate the role of marine organic aerosol for these important s
10 io
functions.Theyhavefocusedonthecharacterisationandquantificationofprimaryand n
P
secondarymarineorganicaerosol(Cavallietal.,2004;Facchinietal.,2008b;Hawkins a
p
etal.,2010;Ceburnisetal.,2011;Decesarietal.,2011;Ganttetal.,2011;Lapinaetal., e
r
2011;Ovadnevaiteetal.,2011;Dall’Ostoetal.,2012;GanttandMeskhidze,2012)and
|
theproductionofprimaryorganicaerosolfromsea-spray(Ganttetal.,2011;O’Dowd
15
D
etal.,2008).Whilsttheemissionofprimaryorganicaerosol(POA)isassociatedwith is
c
wavebreakingandthebubbleburstingprocessandhencerelatedtowindspeed(e.g., u
s
BlanchardandWoodcock,1957;Russelletal.,2010;Ganttetal.,2011)theproduction sio
n
of secondary marine organic aerosol is associated with biologically driven emissions
P
20 ofvolatileorganiccompoundssuchasdimethylsulfidefromphytoplankton(e.g.,Bates ap
e
etal.,1992).POAcontainsorganicmatteroriginatingfromthesea-surfacemicrolayer r
consistingofimmisciblesubstancessuchascolloidsandaggregatesfromphytoplank- |
ton (Facchini et al., 2008b). However, despite such research efforts, many aspects of
D
marineaerosolsystemsarenotyetfullyunderstood,particularlywithrespecttochem- is
c
25 icalcomposition,sources,secondaryparticleformationprocessesandchemicallyre- us
s
solvedsizedistributionsamongothertopics.Adetailedunderstandingoftheseaspects io
n
isessentialtoquantifytheroleofmarineaerosolinthefunctioningoftheEarthsystem P
a
morefully. p
e
r
8263 |
Further studies on the biogenic organic fraction of marine aerosol are essential, D
is
as they may help distinguish anthropogenic from natural climate forcing in the ma- c
u
s
rine atmosphere. Biological components of marine organic aerosol (MOA) consist of s
io
wholeviruses,bacteriaandothermicrobiologicalorganisms,biologicaldebrisandby- n
P
5 products including proteins, amino acids and amines (Aller et al., 2005; Kuznetsova ap
et al., 2005; O’Dowd et al., 2004; Facchini et al., 2008a; Russell et al., 2010; Scal- e
r
abrinetal.,2012).Thephysicalandchemicalpropertiesoftheseorganiccomponents
|
willaffecttheradiativeproperties,cloudcondensationandicenucleatingabilitiesofthe
D
particulatematter(PM)theyarepartof.ModellingstudiessuchasBurrowsetal.(2013) is
c
10 havelookedattheroleofbiogenicicenucleiinthemarineenvironmentandfoundthat us
they are of particular importance in the Southern Ocean, where the authors recom- sio
mendconductingfieldstudiesduetothelackofdata.Todate,fewstudieshavebeen n
P
conducted on MOA source apportionment (Decesari et al., 2011) and even fewer in- ap
e
vestigationsofMOAintheremotemiddletohighlatitudeSouthernHemisphere(Bates r
15 et al., 1998; Quinn et al., 1998; Po´sfai et al., 2003; Zorn et al., 2008; Lapina et al., |
2011)areavailable.
D
The perturbation of the composition of the remote Southern Hemispheric MOA by is
c
large animal colonies (e.g., Macaroni penguin Eudyptes chrysolophus, Gentoo pen- us
s
guinPygoscelispapuaandAntarcticfursealArctocephalusgazelle)hasbeenreported io
n
20 in a number of studies. For example, Legrand et al. (1998) and Zhu et al. (2011) ob- P
a
servedhighammoniaemissionsfrompenguinandsealexcretaandcolonysoilsdur- p
e
ingthesummermonthsassociatedwithless-acidic,sulfate-richmarineaerosol.Itwas r
concluded that this effect was due to the ammonia partitioning from the gas phase |
intotheparticulatephase.Blackalletal.(2007)estimatedthatseabirdemissionsadd D
25 about 20% to the oceanic ammonia emissions south of 45◦S, using a global seabird isc
u
databasecoupledtoanemissionsmodel.Calculationsbasedonthesamemodeland s
s
database byRiddick etal. (2012) found that penguinsare responsiblefor about 80% io
n
oftheglobalseabirdNH emissions.Becausesuchemissionsaredominatedby“hot P
3 a
spots”,i.e.denselypopulatedcolonies,theydrivethelocalnitrogencycleandwillalso pe
r
8264 |
affect the regional biogeochemistry by both gas emissions and aerosol chemistry. In D
is
addition to ammonia, decomposition of ornithogenic soils is thought to make a sig- c
u
s
nificant contribution to the organic matter contained in particulates through oxalate s
io
enrichments (Legrand et al., 2012). Particles have slower deposition rates than reac- n
P
5 tive gas phase species, such as ammonia or certain volatile organic species (Nemitz ap
et al., 2009). Thus, gas-to-particle conversion enables transport of chemical species e
r
over longer distances and hence broadening the footprint of these large sources and
|
potentiallyincreasingimpactsonecosystems.
D
Inthispaperwereportmeasurementsofthechemicalandmicrophysicalcharacter- is
c
10 isticsofremotemarineaerosolonBirdIsland,tothewestofSouthGeorgia,aremote us
oceanicarchipelagosouthoftheAntarcticPolarFrontintheSouthAtlanticOcean,and sio
assess the influence of emissions from local fauna compared with regional sources. n
P
The island is densely populated by penguins and fur seals. It is estimated that there ap
isaboutonesealandpenguinforevery1.5m2.Thispaperdetailstheresultsfroman er
15 aerosolmassspectrometeroperatedattheBirdIslandResearchStationoftheBritish |
Antarctic Survey (BAS) for eight weeks, with other ancillary measurements made at
D
several locations on the island. This represents the first stationary deployment of an is
c
aerosolmassspectrometerinthesub-Antarctic.Thesourcesoforganicaerosolwere us
s
apportioned using positive matrix factorisation, and special emphasis was placed on io
n
20 theinvestigationofbiogeniccontributionstoparticulatematterandthesourcesofor- P
a
ganicandinorganicnitrogen. p
e
r
|
2 Experimentalandmethods
D
is
2.1 Measurementsite cu
s
s
io
MeasurementswereconductedontheResearchStationontheremotesub-Antarctic n
25 Bird Island (54◦000S, 38◦030W) over an 8-week period in November and Decem- Pa
p
ber 2010. The island is approximately 4km long and 800 m wide, with a hilly e
r
8265 |
topographyandamaximumelevationof350m(seeFig.1anddetailsonthewebsite D
is
www.antarctica.ac.uk/living and working/research stations/bird island/). The island is c
u
s
animportantbreedinglocationforseabirdsandsealsintheaustralspring.Thelargest s
io
assemblages of fauna on Bird Island are the colonies of Macaroni penguin Eudyptes n
P
5 chrysolophus,GentoopenguinPygoscelispapuaandAntarcticfursealArctocephalus ap
gazella. The immediate surroundings of the field station were inhabited by more than e
r
3500fursealsand1000penguinsinspringandsummer2010/2011.Theislandasa
|
wholeishometoabout50000breedingpairsofpenguins,14000pairsofalbatrosses,
D
700000nocturnalpetrelsand65000breedingfurseals.Furtherlargeanimalcolonies is
c
10 are found on the neighbouring islands to the West, Willis Islands, and to the East, us
SouthGeorgia.Themainresearchactivitiesfocusonseabird(penguins,albatrossand sio
petrels among others) and seal population dynamics, feeding ecology and reproduc- n
P
tion statistics. The predominant mesoscale wind direction is from the west. However ap
e
the local topography was expected to be of significant influence and to mix aerosol r
15 producedlocallybyseabirdsandsealswithairmassesarrivingwiththepredominant |
westerlies.TheBirdIsland(BI)researchstationislocatedabout50mfromtheshore
D
inashelteredbayonthesouthsideoftheisland(seeredstarinFig.1). is
c
u
s
2.2 Aerosolmassspectrometer sio
n
P
Thechemicalcompositionofsubmicronaerosolwasdeterminedwithahigh-resolution a
p
20 time-of-flight (HR-ToF-) aerosol mass spectrometer (AMS). The functioning and field er
deployment of the AMS has been extensively described in the literature (DeCarlo et
|
al.,2006;Canagaratnaetal.,2007).OnBItheAMSwasoperatedalternatingbetween
D
the W- and V-modes. In W-mode, the ion path length in the mass spectrometer is is
c
2.9 m, leading to higher mass to charge ratio resolution than the V-mode where the u
s
25 ions follow a path of 1.3 m. However, in V-mode detection limits are lower (DeCarlo sio
n
et al., 2006). Both W-mode and V-mode were averaged over 150 s each. In W-mode
P
only mass spectra were recorded and the sampling switched every 5s between the ap
e
open and closed positions of the chopper. In V-mode, 60% of the time mass spectra r
8266 |
were recorded at 15 s in both open and closed chopper positions, while during 40% D
is
ofthetimetheparticlesizedistributionwasmeasured.OnlytheV-modespectrawere c
u
s
usedtoderivetheaerosolmassconcentrationsreportedinthiswork.W-modespectra s
io
were only used to identify individual ion fragments when the V-mode resolution was n
5 nsuoltfastueffi(acbiebnrte.vTiahteedvaaspo(SriOse2r−)w),aasmsmeotntoium60(0N◦HC+.)M,oarsgsanciconmcaetntetrra(tOiorngs),fnoirtrpaatert(iNcuOla−t)e, Pape
4 4 3 r
chloride(Cl−)andpotassium(K+)arereported.Inaddition,wereportanestimationof
|
seasaltsubmicronaerosol(fordetailsseeSect.2.2.2).
D
is
2.2.1 AMSdataanalysis,calibration,collectionefficiency,limitofdetectionand cu
s
errorestimation s
10 io
n
P
AllAMSdatawereanalysedusingstandardanalysissoftware(SQUIRREL1.51Hand a
p
PIKA1.10H;Sueper,2012)withinIgorPro6.2(Wavemetrics,LakeOswego,OR).The e
r
reportedmassconcentrationsofSO2−,Org,NO−,NH+,Cl−andK+werederivedfrom
4 3 4 |
thehigh-resolutiondataPIKAanalysis.
15 The ionisation efficiency (IE), with respect to NO−3, in V-mode was calibrated twice Dis
everyweekwith400nmd ammoniumnitrateparticlesatapulsingperiodof25µs cu
mob s
fortheextractionofionsintothemassspectrometer.IEvalueswereaveragedforevery sio
twoweeksandappliedtothedatacorrespondingtothesemeasurementperiods.The n
P
W-mode IE was estimated to be the same fraction of the V-mode IE as the W-mode a
p
e
20 MS air beam is of the V-mode MS air beam. After each IE calibration a HEPA parti- r
clefilterwasinstalledinfrontoftheinstrumenttosampleambientairbetween30min
|
and one hour for the determination of the detection limits. The limit of detection was
D
calculated as three times the standard deviation from the mean species concentra- is
c
tion during all filter measurements (see Table 1). The relative IE (RIE) for ammonium u
s
s
25 was found to agree with the default value of 4, based on the mass spectrum ammo- io
niumnitratedatafromIEcalibrations.TheRIEforSO24−wasdeterminedbycomparing nPa
the theoretical to measured mass concentration of sulfate in a solution of ammonium p
e
r
8267 |
ncaitrliabtreataionndsawmemreonciounmdusuctlfeadtet.wTihcee,reinsuthlteingfirRstIEaSnOd24−lawsatsw1e.e1k4o(dfetfhaeulctavmalupeai1g.n2,).uSsiinzge Discu
s
polystyrenelatexspheres(PSL). sio
Due to the island’s unusual organic aerosol composition, for the unit mass reso- n
P
lution mass spectral analysis, the fragmentation table had to be edited at m/z 30 a
5 p
+ + + e
wherethefragmentsCH2O andCH4N occasionallydominatedoverNO .Normally, r
frag nitrate[30]iscalculatedasm/z 30minusthecontributionsfromairandorganics
|
atthismasstochargeratio,wherethelatterisreferencedtotheorganicsignalatm/z
D
29 (Allan et al., 2004b). However, since the organic contribution as assumed by the is
c
standardfragmentationtabledidnotapply,thenitratecontributionatm/z 30wasset u
10 s
s
tobefixedtoitscontributionatm/z46(3.92*frag nitrate[46]),basedonthedatafrom io
n
allIEcalibrations.Thus,theorganicmassatm/z30wascalculatedasm/z30minus P
a
frag air[30]andminusfrag nitrate[30]. p
e
The determination of the BI ambient aerosol collection efficiency (CE), including r
15 losses due to incomplete particle transmission in the instrument’s inlet system, mal- |
focusingofnon-sphericalparticlesandbounceofffromthevaporiser(Huffmanetal., D
2005),wasdifficultforseveralreasons.Intheory,knowingtheparticledensity,sizedis- is
c
u
tributions derived from AMS measurements can be compared to SMPS size distribu- s
s
tionstoyieldthecollectionefficiency(CE).TheAMSprovidesthevacuumaerodynamic io
n
diameter(d )ofaparticlewhiletheSMPSmeasuresthemobilitydiameter(d ).d P
20 va mob va a
andd arerelatedbythefollowingequationafter(DeCarloetal.,2004): p
mob e
r
ρ
d =d ·S· p (1) |
va mob ρ0 D
is
c
with S being the Jayne shape factor ρ the particle density and ρ the unit density. u
p 0 s
s
However,duetothesignificantinfluenceofseasaltinthesubmicronparticulates,the io
n
SMPSaccountsforalargernumberofparticlesthantheAMS.EventhoughtheAMS
25 P
a
sees a fraction of the submicron sea salt, it cannot be quantified (see Sect. 2.2.2). In p
addition, mass concentrations were rather low with 0.36µgm−3 (CE=1) on average, er
8268 |
sothatAMSderivedsizedistributionswereverynoisy.Bothfactorswouldintroducetoo D
is
largeerrorstocalculateareasonableCE.Alternatively,CEcanbedeterminedbased cu
onitsdependencyontheNO−-fraction(Crosieretal.,2007),howeverBINO−concen- ss
3 3 io
trationswereinvariablylow,withapproximately0.005µgm−3(CE=1)onaverage,and n
P
were thus not suitable for a method developed for urban aerosol. Based on previous a
5 p
e
measurements in marine environments, it is known that the CE of the acidic marine r
aerosolisnearoneduetothehighcontributionofsulfuricacidandtheprevailingliquid
|
phaseofparticles(Quinnetal.,2006;Matthewetal.,2008;Zornetal.,2008).However,
D
BIischaracterizedbymanylargeseabirdcoloniesandAntarcticfursealrookeriesthat is
c
10 emit quantities of ammonia of up to 350µgm−3 (unpublished data, paper in prepara- us
s
tion) leading mostly to neutralised aerosol (see Sect. 3.2) despite the strong marine io
n
influence.Consequently,efflorescedammoniumbisulfateandammoniumsulfatesalts P
areformedwhichtendtobounceofftheheatingelementintheAMSmorefrequently. ap
e
IntheabsenceofanotherinstrumenttowhichAMSresultscouldhavebeencompared, r
15 the collection efficiency was set to CE=0.5, based on experiences from several ear- |
lier field campaigns with this particular and other AMS instruments (e.g., Allan et al., D
2004a; Drewnick et al., 2005; Hings et al., 2007). In addition to the uncertainties in isc
u
aerosolmassconcentrationquantificationduetotheCE,thereisalsoastatisticalion s
s
countingerror(seeTable1). io
n
P
a
2.2.2 AMSseasaltdetectionanditsinfluenceonparticulateorganicsand p
20 e
sulfatequantification r
|
Formerly, sea salt was thought not to be accounted for by AMS measurements due
D
to its evaporation temperatures higher than 600◦C (Bahreini et al., 2003; Jimenez et is
c
al.,2003).However,arecentstudyattemptedtoquantifytheseasaltmassconcentra- us
s
25 tionsdetectedbytheAMS(Ovadnevaiteetal.,2012).FollowingtheBIfieldcampaign, ion
additional laboratory measurements were undertaken with a different AMS (compact P
a
time-of-flight aerosol mass spectrometer as described by Schmale et al., 2010) to p
e
r
8269 |
characterise the extent to which the AMS is capable of sea salt quantification and D
is
identify potential cross-sensitivities to other AMS standard chemical species. Known cu
s
amounts ofNaCl and seasalt (SIGMA-Aldrich sea saltstandard S9883), eachmixed s
io
separately with ammonium nitrate in solution, were measured with the AMS across a n
5 rsaenagseaoltffvraagpmouernistse,rNteam+p(emra/tzur2e3s)baentdweNeanC4l+80(ma/nzd5782)0,◦aCn.dTthheerAaMtioSssopfetwcioesNcahClolraidned Pape
r
(basedonthestandardfragmentationtable)tonitratewerecharacterized.
|
For the NaCl solution, the ratio of m/z 58 and m/z 23 to NO− increased linearly
3 D
with temperature (R2=0.94, slope 4.7 × 10−5, and R2=0.99, slope 6.4 × 10−4, re- is
c
10 spectively,seeFig.2,bottompanel).Thesamem/z ratiosbehaveddifferentlyforthe us
seasaltsolutionforwhichtheresponsewasnon-linear:Whiletheratiom/z58toNO− sio
3 n
peaked near 550◦C, the m/z 23 to NO− ratio increased steadily but not linearly with P
temperature(seeFig.2).Thesedifferen3tbehavioursoftheNa+ andNaCl+ ionsinthe ap
e
r
SIGMA-AldrichseasaltsolutionhavealsobeenreportedbyOvadnevaiteetal.(2012).
Those authors argue that either the fragmentation of NaCl+ ions increases at higher |
15
vapourisertemperatures,leadingtolowerionconcentration,ortheionthermalvelocity D
increases resulting in a lower detection efficiency. For Na+ the increasing concentra- isc
u
tionwithhighertemperaturesisassumedtoberelatedtohigherfragmentationofthe ss
NaCl+ ion and partly to surface ionisation. In addition, the different behaviours of the ion
20 twoionsasafunctionofthesaltsolutionsuggestthattheAMSvapourisationandioni- Pa
p
sationprocessesaresignificantlyinfluencedbythemixtureofsalts.Derivingascaling e
r
factor based on these fragments would thus lead to a highly uncertain quantification
|
for sea salt on Bird Island, especially since the contributing salts in ambient marine
airarelargelyunknownandlikely tovarystronglydependingonthelocation(e.g.,BI D
is
25 areevreoasloeldissiingflnuifiecnacnetddsifftreornegnlcyebsyinNpHr3opeemritsiessio(nhsy)g.rIonsdceoepdi,cugnrpouwbtlhis,hcerydsmtaellaissautiroenmeetnct.s) cuss
io
of reference sea salts from different suppliers, further emphasising the influence of n
P
trace metals on its physicochemical behaviour (C. Braban, personal communication, a
p
2013). er
8270 |
+ + D
Whiletherewasalargediscrepancyofafactorgreaterthan2forNaCl andNa ions is
in the scaling factor between pure NaCl and sea salt standard at 600◦C, for chloride cu
s
the results were more consistent, ranging between a factor of 3.15±0.20 and 3.97± s
io
0.14 across all experiments. However, up-scaling based on AMS chloride might lead n
P
toerrorsforatleasttworeasons:(1)particulatechlorideconcentrationsmightnotbe a
5 p
quantified correctly by AMS measurements as it forms salts that have relatively high er
vapourisation temperatures (>600◦C), and (2) other sources beside sea salt might
|
contribute to the overall chloride concentration. Also, comparison with other available
D
literaturesuggeststhatAMSseasaltquantificationneedsmorethoroughinvestigation. is
c
Zorn(2009)foundascalingfactorforchloridetoseasaltbetween150and220inthe u
10 s
s
SouthAtlantic,basedonacomparisonbetweenmeasurementsofanAMSandaparti- io
n
cleintoliquidsampler(PILS;Zornetal.,2008),asopposedtothemethodhereapplied P
basedonlyonAMSNO− quantification.Ovadnevaiteetal.(2012)determinedascal- ap
ing factor between the N3aCl+ reported by the AMS and the actual sea salt contained er
15 in PM1 (particulate matter with a diameter equal to or smaller 1µm) of 51, while our |
experimentsyieldedafactor13. D
Tobeconsistentwithavailabledatafromtheexistingliterature,massconcentration isc
u
related data for sea salt reported in this study, have been determined on the basis of s
theintensityofm/z 58(NaCl+)andscaledupusingthefactorof51,assuggestedby sio
n
Ovadnevaiteetal.(2012). P
20 a
InadditiontothequestionwhethersubmicronseasaltcanbequantifiedbytheAMS, pe
r
thepotentialinfluenceofthepresenceofambientseasaltparticlesonthequantifica-
tionofotherchemicalspecieswasinvestigated,assessingthevalidityofthestandard |
+
fragmentationtable.OneobservedseasaltionfragmentisNa Cl atm/z81,whichis D
+ 2 is
typicallyinterpretedastheHSO fragmentofparticulatesulfateintheunitmassres- c
25 olution spectrum. To correct for 3this interference, the concentration o+f Na2Cl+ at m/z ussio
81intheHRspectrumwascorrelatedtom/z 23whereonlytheNa fragmentisob- n
served.ThelinearregressionyieldedacorrelationcoefficientR2of0.99andaslopeof Pa
p
0.036acrossalldata.Thefragmentationtablefortheunitmassresolution(UMR)data e
r
8271 |
waseditedasfollows: D
is
c
u
frag SO4[81] = 81−frag organic[81]−0.036×frag Na[23] (2) ss
io
n
Thecorrectionmakesadifferenceintheorderof1%forthetotalparticulateSO2−. P
4 a
The presence of sea salt particles is responsible for artefacts in the UMR organ- p
e
r
icsspectrum.Forexample,tungstenemittedfromthefilamentintheionsourcereacts
5
withCl−.WCl,WOClandWOCl isotopesbetweenm/z214and276andseasaltfrag- |
2
mentsaslistedinTable2contributetothestandardparticulateorganicsquantification. D
To avoid overestimation of organics due to this effect, only mass to charge ratios up isc
u
to232wereconsidered,asnon-organicpeakscompletelydominatedthemassabove ss
io
10 thisthreshold.Laboratoryexperimentsindicatethatthequantificationofparticulateor- n
ganics with mass to charge ratios smaller than 232 might also be influenced by the Pa
p
amountofseasaltpresent.However,noclearpatterncouldbeisolated.Derivingthe e
r
organicmassconcentrationfromthePIKAHRanalysishowevercircumventsthispo-
|
tentialUMRproblem.
D
is
2.2.3 Positivematrixfactorisation c
15 u
s
s
Positivematrixfactorisation(PMF,PaateroandTapper,1994;Lanzetal.,2007)wasap- io
n
pliedtotheV-modeUMRorganicspectraobtainedbytheAMS,toinvestigatethevar- P
a
ious source contributions to the submicron aerosol organic matter (PMF v2.04 based pe
r
on Ulbrich et al., 2009). Details of the mathematical model behind the algorithm, its
application,resultevaluationandinterpretationhavebeendescribedelsewhere(e.g., |
20
Lanz et al., 2007; Ulbrich et al., 2009; Ng et al., 2010; Zhang et al., 2011). Briefly, D
is
the underlying assumption of this bilinear problem is, with respect to AMS data, that c
u
thedatasetcanbedividedintoanumberofunvariedcomponents,i.e.chemicalmass ss
io
spectra,whichcontributewithvaryingconcentrationsovertimetothetotalorganicmat- n
P
25 termeasured.Theproblemisreducedtoanm×nmatrixXasshowninEq.(3)(with a
p
mthenumberofrows,i.e.numberoftimesteps,andnthenumberofmasstocharge e
r
8272 |
ratios): D
is
c
u
X=GF+E (3) s
s
io
n
Fisap×nmatrixwithpbeingthenumberoffactorprofiles,i.e.constantAMSmass P
a
spectra,Gisanm×pmatrixwiththerespectivemassspectracontributions,andEis p
e
the m×n matrix of residuals. G and F are fitted to minimize the sum of the weighted r
5
squaredresidualsQ. |
D
Q=Xm Xn (e /σ )2, (4) iscu
ij ij s
i=1j=1 sio
n
P
witheij beingtheresidualnotfittedbythemodelform/zj attimestepi,andσij being ap
anelementofE. e
r
The input matrices were prepared following the recommendations by Ulbrich et
10
|
al. (2009) and Zhang et al. (2011), and comprised a range of mass to charge ratios
D
between 12 and 232 at a time resolution of 5 min. PMF was run to explore solutions is
between1and8factors,forfpeaks(rotations)between−1and1(instepsof0.2),and cu
s
seeds(startingguesses)between0and50(instepsof2).Fpeak isarotationalforcing sio
parametertoexploretherotationalfreedomofthechosensolution.Fpeak =0results n
15 P
in the most central solution. Seeds are random initial values where the algorithm’s a
p
e
iterationsarestarted. r
The detailed criteria for the final selection of factor profiles are discussed in the
|
resultssectionandintheSupplement,followingthesamestepsasindicatedinZhang
D
20 etal.(2011).Zhangetal.(2011)suggestdownweightingthesignalsatm/zwithalow isc
signaltonoiseratioandm/z44andassociatedm/zthatcontainrepetitiveinformation u
s
s
(see step 2d and e, Table 1 in Zhang et al., 2011). For this study, m/z 29 was also io
n
downweighted,astoapotentialleakintheinstrument’svacuumchamberwaslikelyto P
a
be the major source of variation in the signal at that m/z. We refer the reader to the p
e
Supplementwheretheinfluenceofm/z29iselaborated. r
25
8273 |
The statistical uncertainty of each factor’s mass spectrum and time series was de- D
is
termined through bootstrapping (Ulbrich et al., 2009). For that purpose PMF was run c
u
s
on the full dataset once, and a series of 100 variations. In each variation a subset of s
io
theoriginalrows(massspectra)wasrandomlyreplacedbyotherrowsfromtheoriginal n
P
5 input. Theresult yields the 1σ – standarddeviation from the meanmass spectra and ap
timeseriesofthebootstrappedsolutions.ResultsareshowninTableS2intheSupple- e
r
ment.Generally,thestatisticaluncertaintyrangedfrom3to16%forthemassspectra
|
and3to9%forthetimeseries.Comparedtootherstudieswithhighermassloading
D
theserelativeuncertaintiesarehigher(e.g.,Ulbrichetal.,2009). is
c
10 In addition, the uncertainties of the chosen PMF solutions (mass spectra and time us
series)werecalculatedbasedonthevariationsoftheresultswhenfpeaks andseeds sio
were varied. Freutel et al. (2013) elaborate how the estimated uncertainties for each n
P
datapoint,i.e.eachm/zandtimestep,werecalculated.Foreachsolutiontheaverage ap
e
and the standard deviation were determined. For the relative uncertainty of the mass r
15 spectra,thesumoftheabsolutestandarddeviationsforeachm/z wasdividedbythe |
sumofthesignalintensitiesoftheaveragemassspectrum.Fortherelativeuncertain-
D
ties of the time series for each factor profile, the time series of the absolute standard is
c
deviation was divided by the average time series. In general, varying seeds did not us
s
result in large uncertainties (from 1 to 5% for mass spectra and below 1% for time io
n
20 series)whilevaryingfpeaks resultedinlargeruncertainties(from16to76%formass P
a
spectraand15–130%fortimeseries).FullresultsareshownanddiscussedinTable p
e
S2intheSupplement. r
|
2.3 Sub-andsupermicronparticlesizedistributionmeasurements
D
is
c
Thesizedistributionofsubmicronaerosolparticleswasmeasuredbyascanningmo- u
s
25 bility particle sizer system (SMPS; model 3936, TSI Inc. St. Paul, MN) composed of sio
n
alongDMAModel3081andanultrafinecondensationparticlecounter(Model3776).
P
The SMPS scanned for particles in the size range between 14 and 737nm mobility ap
diameter(d )in112discretestepsandin300sintervals.Duetodiffusionlossesin er
mob
8274 |
the long inlet line, particles below approximately 25nm were not detected, as can be D
is
clearlyseenintheindividualsizedistributionsforeachscan.AsdescribedinSect.2.4, c
u
s
theparticlesizedistributionsandtheresultantcalculatedtotalnumberconcentrations s
io
werecorrectedfortheestimatedtransmissionlossesoftheinlet. n
P
5 Super micron particles in the range between 0.5 and 20µm aerodynamic diame- ap
ter (d ) were detected in 53 discrete sizes bins by a TSI aerodynamic particle sizer e
a r
(APS) Model 3321, which determines the particle size via the time of flight between
|
two 633nm He-Ne lasers. The particle counting efficiency decreases below 100% at
D
da<0.7µm, and concentrations below this threshold should be interpreted as lower is
limit.Theinletflowwas5Lmin−1 andsplitinto1Lmin−1 sampleand4Lmin−1 sheath cu
10 s
s
flow.Tominimiselossesofsuper-micronparticlesintheinletline,sizedistributionmea- io
n
surements were recorded at a time resolution of 300 s on the communications tower
P
oftheresearchstation,approximately5mtotheSouthofthebuildingataheightof10 ap
e
maboveground.Theapproximateair-linedistancetotheAMS/SMPSinletwas15m. r
15 Theaerosolwassampledviaa15cmstainlesssteelinletline(1.3cmID)toppedwith |
ahomemadeTSP(totalsuspendedparticulate)head.
D
is
c
2.4 Inletsystemforsubmicronaerosolmeasurements u
s
s
io
Ambientairwasdrawnthrougha17.4mlongcopperinletline(6.4mminternaldiame- n
P
ter,flowrate10.6Lmin−1)installedacrosstherooftopoftheresearchstationatabout a
p
e
20 5maboveground.ThesampledairwasthendriedbypassingthroughaNafion™tube r
dryer, before being split to supply parallel sample flow to the SMPS and the AMS at
|
0.3and0.1Lmin−1,respectively.Sincethelengthoftheinletlineandalonghorizontal
D
sectionof7.8montheroofmayhaveledtoincompleteparticlestransmissiondueto is
c
diffusion, especially for particles sizes below 100nm, the particle losses were calcu- u
s
s
25 lated with the Particle Loss Calculator of von der Weiden et al. (2009). From 13.7nm io
(lowerSMPScut-offdiameter)to100nmparticlemobilitydiameter(dmob),thelosses nP
a
wereestimatedtodecreasefrom55%to9%.Between100and735nm(upperSMPS p
e
cut-offat736.5nm),losseswereestimatedbelow9%,withaminimumnear300nmat r
8275 |
4%.Forparticlesizesgreaterthan735nm,losseswereestimatedtoincreaseto14% D
is
at 1000nm. These estimated losses were taken into account when calculating size c
u
s
distributions and total number concentrations from the SMPS measurements, since s
io
detailedinformationontheparticlesizeswereavailable.FortheAMSderivedaerosol n
P
5 mass concentrations, the particle loss correction could not be applied, because even ap
thoughtheAMSwassettomeasureparticlesizedistributions,theaerosolmasscon- e
r
centrationsweremostlynothighenoughtoderiveamasssizedistribution.
|
2.5 Ammoniameasurements D
is
c
u
Gas phase ammonia was measured with an AiRRmonia wet chemistry analyzer (RR ss
10 Mechatronics). The instrument is designed for high time resolution continuous moni- ion
toringandisbasedontheprincipleofsamplinggaseousNH3 intoastrippingsolution Pa
p
through a gas permeable Teflon membrane, with subsequent analysis of the liquid e
+ + r
phaseNH viaconductivitymeasurements.ParticlephaseNH isnotretainedbythe
4 4 |
membrane.Thesystem’sresponsetimeisbetween10and15min,thedetectionlimit
is0.1µgm−3andtheaccuracy3%(Normanetal.,2009).Ambientairwassampledat D
15 is
1Lmin−1 throughaninsulated2mlongpolythenetubeinletataheightof2mabove cu
s
ground.Bycomparison,theapproximateair-linedistancetotheAMS/SMPSinletwas s
io
4m. n
P
AllinstrumentsincludingoperationdetailsarelistedinTable3. a
p
e
r
2.6 Furtherresources
20
|
Meteorologicalparameters,suchastemperature,windspeed,winddirection,pressure, D
is
relativehumidityandminutesofsunshinewereprovidedbytheBritishAntarcticSurvey c
u
researchfacility’smeteorologicalstationatatimeresolutionof1min.Themetstation ss
io
waslocatedonemeterabovetheAPSonthecommunicationstower. n
P
25 240hbacktrajectorieswerecalculatedwithHYSPLIT(DraxlerandRolph,2011)and a
startedfromtheBIresearchstationat54.008◦Sand38.053◦Wat00:00,06:00,12:00, pe
r
8276 |
and 18:00 UTC for the period between 3 November and 28 December 2010. Arrival D
is
altitudeswere10,100and500m. cu
s
Chlorophyll a data provided by the MODIS Aqua satellite were obtained from the s
io
NASAEarthObservatorywebsite(http://neo.sci.gsfc.nasa.gov/Search.html). n
P
a
p
e
r
3 Resultsanddiscussion
5
|
3.1 OverviewoftheBirdIslandmeasurementresults–aerosol D
chemicalcomposition isc
u
s
s
Table4showsbasicstatisticsforsub-andsuper-micronaerosol.Onaveragethemass io
concentration was 0.76µgm−3, with a median of 0.66µgm−3 and 75% of the data nP
10 points were <1.00µgm−3. The submicron number density was much more variable, ape
as shown by the large difference between the average (956cm−3) and the median r
(386cm−3) concentrations. 75% of the 5 min data points were <530cm−3. Super- |
micronaerosolnumberdensity,mostlikelydominatedbyseasaltparticles,wasmuch D
lowerwithanaverageof9cm−3. isc
u
Generally,theBIaerosoldetectedbytheAMS(i.e.thenon-refractoryPM )wasdom- s
15 1 s
inatedbyparticulatesulfate(46%),seeFig.4a)asexpectedbasedonearlierstudies io
n
(e.g., Quinn et al., 1998). It originated from three sources: sea salt, methanesulfonic P
a
acid (MSA) and long-range transport, as is elaborated in Sect. 3.9. Based on labo- pe
ratory experiments with SIGMA-Aldrich sea salts standard S9883 (in which ss-SO2− r
4
corresponds to 13.8% of sea salt chloride mass according to the composition data |
20
sheet), the AMS detected a ratio of particulate sea salt sulfate (ss-SO2−) to chloride D
4 is
of 63%. For the aerosol on BI, this implies that the median ss- SO2− contribution to cu
4 s
totalPM particulatesulfatewas10.8%(4.6–21.4%withintheinter-quartiles),based s
1 io
onthess-Cl− determinationdescribedinSect.2.2.2.Largevariationsoccurredduring n
P
periodswithstrongMSAcontribution,whicharediscussedfurtherinSect.3.6.Organic a
25 matter contributed nearly 38% to the mass, followed by NH+4 (12%) and NO−3 (4%), per
8277 |
see Fig. 4a). The chemical makeup of the organic mass contribution is discussed in D
is
detailinSect.3.4,wheretheresultsofthepositivematrixfactorisationanalysisarede- c
u
s
scribed.Thenitrateconcentrationwasexpectedtobesmall,sincetheonlysourcesthat s
io
emittedNO locallywerethestation’spowergeneratorandthekitchenstove.NO can n
x x P
5 beconvertedtonitricacid(HNO3),allowingnitratetopartitionintotheparticlephase. ap
However,becauseoftheslowtime-scaleofthisprocessthiswouldhaveaffectedlocal e
r
NO− concentrations only during conditions of stagnant or re-circulating air. The rela-
3 + |
tivelyhighNH fractionwasprobablyduetoseveralsources:Theopenoceanitselfhas
4 D
beenobservedtopotentiallybebothasinkandasourceofammoniaathighsouthern is
c
latitudes(Johnsonetal.,2008),butislikelyclosetoequilibriumandhighlyinfluenced u
10 s
s
by local biogeochemical cycles and long range transport. Bird Island, South Georgia io
n
andtheneighbouringrockyisland(e.g.WillisIsland)arelargelocalammoniasources
P
due to the decomposition of uric acid in the excreta from fur seals and seabirds. Or- ap
e
nithogenicsoilsmayalsobeasourceattimes(Legrandetal.,1998,2012;Zhuetal., r
15 2011).WhenaccountingforseasaltbasedonthemethodproposedbyOvadnevaiteet |
al. (2012), concentrations in the submicron aerosol composition change to 21% nss-
D
SO2−,2%NO−,7%NH+,22%Organd47%seasalt(includingss-SO2−),seeFig.4b. is
4 3 4 4 c
u
Diurnalpatternswerenotobservedforanyaerosolspecies. s
s
io
n
3.2 Aerosolacidity P
a
p
20 SinceambientNH3 wasavailableinlargeconcentrations(upto350µgm−3 measured er
in the atmosphere at the Research Station (unpublished data, paper in preparation),
|
ammoniumcouldpartitionintotheparticlephasetoneutralisethesulfuricacid.Itwas
D
assumedthatchlorideandss-SO2−werealreadyneutralizedbyseasaltcationswhile is
4 c
particulatenitrateandnss-SO2− wereneutralisedbyreactionwithgas-phaseammo- us
4 s
nia. To derive aerosol acidity, the stochiometric ratio of ammonium and sulfate ions io
25 n
was calculated, where a ratio of 2:1 represents fully neutralized (NH ) SO , a ratio P
4 2 4 a
of1:1reflectstheformationofammoniumbisulfate(NH HSO ),andaratioof<1:1 p
4 4 e
r
8278 |
meanspresenceofsulphuricacid.Duringthemeasurementperiod,onaverage,during D
is
12%ofthetimeparticulatesulfatewasfullyneutralised,whileduring79%ofthetime c
u
s
sulfate particles contained a mixture of ammonium sulfate and ammonium bisulfate s
and during 9% of the time particles contained sulfuric acid. This finding differs from ion
P
5 otherobservationsofmarineaerosol.Forexample,Phinneyetal.(2006)andZornet ap
al.(2008)foundthatmarineaerosolwasratheracidic,with60%sulfuricacid,bothin e
r
the sub-Arctic and in sub-Antarctica, while Quinn et al. (2006) found marine aerosol
|
with78%and85%sulphuricacid.
D
is
3.3 Aerosolsizedistributions cu
s
s
10 SMPSmeasurementsstartedon15November.Figure5showsthetimeseriesofthe ion
number size distributions measured by the SMPS and the APS. For SMPS data, a Pa
p
function of d , it was assumed that d is equivalent to the volume equivalent di- e
mob mob r
ameteroftheparticles(d ).APSsizedistributionsareafunctionoftheaerodynamic
ve
|
diameterd .d wasconvertedtod accordingtoEq.(5),afterDeCarloetal.(2004):
a a ve
D
s is
ρ c
d =d · χ· 0, (5) us
15 ve a ρs sio
n
P
with χ =1.25 shape factor of sea salt (DeCarlo et al., 2004); ρ =1 unit density in a
o p
gcm−3andρs=2.17gcm−3densityofsodiumchloride.TheCunninghamslipcorrec- er
tionfactorwasassumedtobe1.
|
Three size modes were observed: one showing up in the particle number size dis-
D
20 tribution at dmob <100nm, a second one between 100 and 400nm and a third one isc
between 1 and 2µm. The coarsest mode is associated with sea salt particles, which u
s
s
aregenerallyexpectedtobeinthesuper-micronsizerange(e.g.,Cavallietal.,2004). io
n
EventhoughtheAMSchloriderepresentsonlythesubmicronfraction,thischemical P
a
species turns out to be a good proxy for the super-micron sea salt mode: Chloride p
e
concentrationsco-varywiththesuper-micronparticlenumberdensity,confirmingthat r
25
8279 |
atthissitetheAMSCl−isdominatedbyseasaltandnotbyNH4Clasisusuallythought Dis
tobethecaseatmorecontinentalsites. cu
s
The campaign average size distributions of particulate sulfate and ammonium de- s
io
rivedfromtheAMSmeasurementswerecalculatedfrom80to800nmd in40bins. n
va P
Thesizedistributionsindicatethatammoniumwasinternallymixedwithsulfate.When a
5 p
fitting the particulate sulfate mass distribution with a bimodal log-normal function, the er
modediameterswere270±2nmand353±7nm,withgeometricstandarddeviations
|
of 1.3 ± 1.0 and 1.7±1.0, respectively (for details, see Table 5). The tail towards the
D
largerdiametersmightresultfromcontributionsoflargerseasaltsulfateparticlesand is
c
their slower evaporation in the AMS. Size distributions for nitrate, organics, and chlo- u
10 s
s
ridecouldnotbeobtainedfromtheAMSdataduetolowsignaltonoiseratios.Instead, io
n
sizedistributionsderivedfromSMPSmeasurements,relatedtoindividualOAfactors, P
a
weredeterminedbythePMFanalysis(seeSect.3.4fordetails). p
e
r
3.4 Speciatedcontributionsofparticulateorganicstothemarineaerosol–PMF
|
results
15 D
is
Application of the PMF method indicates that the organic aerosol measured at Bird cu
s
Island can be attributed to five specific aerosol source types (factors). We refer the sio
reader to the Supplement for a detailed discussion regarding the selection of the 5- n
P
factorsolutionwhichispresentedinFig.6. a
p
e
20 TheHOAfactororiginatedfromtheresearchstationdieselgeneratorandcontributed r
onaverage9%totheOAmass.HOAaerosolfragmentsarefrequentlyobservedwhen
|
therearefreshemissionsofincompletecombustion(e.g.,Zhangetal.,2005).TheM-
D
OOAfactorcontributedonaverage40%totheOAmass.Inaddition,threefurtherOA is
c
species were identified. Methanesulfonic acid organic aerosol (MSA-OA) contributed u
s
s
25 with25%totheorganicmatter.Sulfurcontainedintheinorganicsulfateparticlesthat io
n
alsooriginatefromMSAemissionsarenotaccountedforhere.Thethirdlargestsignal P
a
with 18% was attributed to a factor called amino acids/amines (AA), due to the nitro- p
e
gen containing marker ions identified (ion fragment and exact mass in parentheses): r
8280 |