Transport of Po Valley aerosol pollution to the northwestern Alps. Part 1

45 Pages·2017·8.62 MB·English

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Transport of Po Valley aerosol pollution to the northwestern Alps.
Part 1: phenomenology
HenriDiémoz1,FrancescaBarnaba2,TizianaMagri1,GiordanoPession1,DavideDionisi2,
SaraPittavino1,IvanK.F.Tombolato1,MonicaCampanelli2,LaraSofiaDellaCeca3,MaximeHervo4,
LucaDiLiberto2,LucaFerrero5,andGianPaoloGobbi2
1ARPAValled’Aosta,Saint-Christophe,Italy
2InstituteofAtmosphericScienceandClimate,CNR,Rome,Italy
3InstitutodeFísicaRosario,Rosario,Argentina
4MeteoSwiss,Payerne,Switzerland
5UniversityofMilan-Bicocca,Milan,Italy
Correspondenceto:HenriDiémoz([email protected])
Abstract.
Mountainous regions are often considered pristine environments, however they can be affected by pollutants emitted in
morepopulatedandindustrialisedareas,transportedbyregionalwinds.Basedonexperimentalevidence,furthersupportedby
modellingtools,wedemonstrateandquantifyheretheimpactofairmassestransportedfromthePoValley,aEuropeanatmo-
5 spheric pollution hotspot, to the northwestern Alps. This is achieved through a detailed investigation of the phenomenology
ofnear-range(fewhundredskm),trans-regionaltransport,exploitingsynergiesofmulti-sensorobservationsmainlyfocussed
on particulate matter. The explored dataset includes vertically-resolved data from atmospheric profiling techniques (Auto-
mated LiDAR-Ceilometers, ALC), vertically-integrated aerosol properties from ground (sun photometer) and space, and in
situmeasurements(PM andPM ,relevantchemicalanalyses,andaerosolsizedistribution).Duringthefrequentadvection
10 2.5
10 episodesfromthePobasin,allthephysicalquantitiesobservedbytheinstrumentalsetuparefoundtosignificantlyincrease:
thescatteringratiofromALCreachesvalues>30,AODtriplicates,surfacePM reachesconcentrations>100µgm 3 even
10 −
in rural areas, secondary inorganic compounds such as nitrate, ammonium and sulfate increase up to 28%, 8% and 17% of
the total PM mass, respectively. Results also indicate that the advected aerosol is smaller in size and less light-absorbing
10
comparedtotheaerosoltypelocally-emittedinthenorthwesternItalianAlps,andhygroscopic.Inthiswork,thephenomenon
15 is exemplified through detailed analysis and discussion of three case studies, selected for their clarity and relevance within
the wider dataset, the latter being fully exploited in a companion paper quantifying the impact of this phenomenology over
the long- term (Diémoz et al., 2018). For the three case studies investigated, a high-resolution numerical weather prediction
model(COSMO)andalagrangiantool(LAGRANTO)areemployedtounderstandthemeteorologicalmechanismsfavouring
the transport and to demonstrate the Po Valley origin of the air masses. In addition, a chemical transport model (FARM) is
20 usedtofurthersupporttheobservationsandtopartitionthecontributionsoflocalandnon-localsources.Resultsshowthatthe
simulationsarenotabletoadequatelyreproducethemeasurements(withmodelledPM concentrations4–5timeslowerthan
10
theonesretrievedfromtheALC,andmaximaanticipatedby6–7hours),likelyowingtodeficienciesintheemissioninventory
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andparticlewateruptakenotfullytakenintoaccount.Theadvectedaerosolisshowntoremarkablydegradetheairqualityof
theAlpineregion,withpotentialnegativeeffectsonhumanhealth,climateandecosystems,aswellasonthetouristicdevelop-
mentoftheinvestigatedarea.Thefindingsofthepresentstudycouldalsohelpdesignmitigationstrategiesatthetrans–regional
scaleinthePobasin,andsuggestanobservations-basedapproachtoevaluatetheoutcomeoftheirimplementation.
5 1 Introduction
In mountainous regions, mutual exchanges between the valley atmosphere and the nearby plains have been recognised and
studied for more than a century (e.g., Thyer, 1966, and references therein). Notably, daytime up-valley (nighttime down-
valley) flows systematically develop as a result of faster heating (cooling) of mountain valleys compared to the foreland
(Rampanellietal.,2004;SerafinandZardi,2010;Schmidli,2013;Wagneretal.,2014),andhencemanifestonaveryregular
10 basis,especiallyduringfair-weatherdays(nights)withweaksynopticcirculation(BorghiandGiuliacci,1980;Tampierietal.,
1981).Theplain-to-mountaincirculationregimeconveysmass,heatandmoisturewithintheplanetaryboundarylayer(PBL),
thus contributing to horizontal mixing on the mesoscale (Weissmann et al., 2005). Additionally, air parcels can be lifted by
convectionabovetheridgesandtransportedtothefreetroposphere,whichfavoursairmassexchangeintheverticaldirection
(Henneetal.,2004;Gohmetal.,2009;Schnitzhoferetal.,2009;Langetal.,2015).
15 Thermally-driven wind systems are observed in mountainous regions throughout the world (e.g., Cong et al., 2015; Col-
laudCoenetal.,2018;Dhungeletal.,2018).TheEuropeanAlpshavebeentheidealscenarioforsuchkindofstudies,owing
to their rugged shape forming hundreds of main and tributary valleys, and large surrounding plains with strong emission
sources,themostsignificantbeinginthePobasin.Indeed,thisvastregion,whichincludesalargeportionofnorthernItaly,
is one of the most densely populated (more than 20 millions of people and a population density of 414 inhabitants per km2
20 (WMO, 2012)), industrialised, and thus polluted areas in Europe (Chu et al., 2003; Van Donkelaar et al., 2010; Fuzzi et al.,
2015;EMEP,2016).Thevalleymorphologyexacerbatestheairquality.Infact,heavyemissionsfromproductiveactivitiesas
wellasfromvehiculartrafficandresidentialheatingareoftentrappedwithinthePobasinduetoitscharacteristictopography
strongly limiting the dispersion of pollutants, with the Alpine chain and the Apennines enclosing the plain on its northern,
western and southern sides. As a consequence, the Po basin is one of the EU hotspots suffering from premature mortality
25 associatedtoatmosphericpollution(EEA,2015).Inspiteoftheimprovementsinthelastdecades(e.g.,BigiandGhermandi,
2016),theairqualityinthePoValleyisstillfarfromthestandardsestablishedbytheEuropeanCommission(EUCommission,
2008)andexceedancesofthesestandardsareexpectedtocontinueinthenextyears(Belisetal.,2017;Caserinietal.,2017;
EEA,2017;GuarisoandVolta,2017).
Boththeoreticalstudiesandexperimentalcampaignsdemonstratedthattransboundarytransportofseveralkindofpollutants
30 fromthePobasinaffectspre-Alpineareas(Dosioetal.,2002;Nefteletal.,2002;MélinandZibordi,2005),theItalianAlpine
valleys(Nyekietal.,2002;Larsenetal.,2012;Ferreroetal.,2014),otherItalianregions(Cristofanellietal.,2009;Carbone
et al., 2014; Moroni et al., 2015) and even neighbouring countries (e.g., Wotawa et al., 2000; Finardi et al., 2014). Over the
impactedareas,acorrectpartitioningbetweenlocalandnon-localsourcesisthereforenecessaryto1)correctlyinterpretthe
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Figure1.(a)PanoramicviewofthemainvalleyovertheAosta–SaintChristophestationduringapollutionadvectionevent.Thepicturewas
takenfromCrocediFana(2200ma.s.l,Quartvillage,6kmnorth-eastofAosta–SaintChristophe)on21October2017.Onthatday,the
advectedlayerofaerosol–visibleinthepictureasahazylayer–reachedanaltitudeofabout2000ma.s.l.PhotokindlyprovidedbyC.
Cometto.(b)ImageofthePoValleyfromtheMODISAquaradiometer(correctedreflectance,truecolour)onlyfewdaysbeforethepicture
inthefirstpanelwastaken(18October,https://worldview.earthdata.nasa.gov).Thesatelliteviewclearlyshowsthatthehazy,aerosol-rich
layerfromthePobasinisstartingtopouroutintotheAlpinevalleys.ThepinkmarkeridentifiestheAosta–SaintChristophesite.
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exceedances of air quality limits; 2) develop joint efforts and large-scale mitigation strategies (WMO, 2012) to reduce the
frequencyandimpactofpollutionepisodes(anexampleistherecentlysigned“antismog”agreementfortheimprovementof
airqualityinthePobasin,ItalianMinistryoftheEnvironment(2018));3)assesstheimpactofairpollutantsoncitizenhealth
(Straif et al., 2013; WHO, 2016; Zhang et al., 2017), climate (Clerici and Mélin, 2008; Lau et al., 2010; Zeng et al., 2015)
5 and ecosystems (Carslaw et al., 2010; Bourgeois et al., 2018; Burkhardt et al., 2018). As an additional important aspect, in
mountainousregions,pollutionlayersunderminethevisualqualityofthelandscape(e.g.,Fig.1a)andtouristicattractiveness,
withobviouseconomicsimplications(deFreitas,2003).
In the present study, we aim at illustrating and deeply investigating the phenomenology of aerosol transport events to the
northwestern Alpine region through a detailed analysis and discussion of specifically-selected case studies. The impacts of
10 thisphenomenonoverthelong-termarethenquantifiedinacompanionpaper(Diémozetal.,2018).Thisresearchexploitsa
multi-techniqueapproach,combiningalargesetofmeasurements(atsurfacelevel,columnintegratedandvertically-resolved)
with modelling tools such as chemical transport models (CTM). In fact, several previous field campaigns investigated the
atmosphericcompositionandtransportmechanismsintheeasternandcentralpartofthePoValley(Nyekietal.,2002;Barnaba
et al., 2007; Ferrero et al., 2010; Larsen et al., 2012; Decesari et al., 2014; Khan et al., 2016; Rosati et al., 2016; Cugerone
15 et al., 2018), but very few studies are available on the westernmost side of the basin (Anfossi et al., 1988; Mercalli et al.,
2003;Manaraetal.,2018).EarlierevidencesofpossibleadvectionsofpollutantsfromthePobasintothenorthwesternAlps
werecollectedintheframeworkoftwointensive,4-days-longcampaignsperformedbetween2000and2001(Agnesodetal.,
2003).Atthattime,anequippedaircraftflewduringanticyclonicconditionswithweaksynopticcirculation,inordertoassess
theeffectsofthelocalwindsontheairqualityintheAlpinevalleysclosetoMontBlanc(inItaly,FranceandSwitzerland).
20 The experiment was focussed on ozone measurements and its precursors, however aerosol concentrations were additionally
measured. Capping inversions limiting the development of the mixing layer, vertical transport of pollutants along the valley
slopes,andtheozone-pollutedresiduallayeraloft(entrainedintothemixinglayerduringthenextday)werethemostinteresting
phenomena explored by that study. Advections from the Po Valley with thermally-driven flows were hypothesised to be the
mainfactorcontributingtothehighozoneconcentrationsfoundintheelevatedlayers.Althoughthisresultwassupportedby
25 measurementsofcarbonmonoxide,ambientparticulatematter(PM)andrelativehumidity,theshortdurationofthecampaign
couldnotallowtoexcludeothereffects.Morerecently,Diémozetal.(2014a)analysedaone-year-longtimeseriesofcolumnar
aerosolopticalpropertiesmeasuredbyasun/skyphotometerinthesameareaandfoundthattheheaviestburdenofparticles
didnotcomefromurbansettlementswithinthevalley,butratherfromoutsidethevalley,namelythePobasin.
Overall,thisworkattemptstoanswerthefollowingscientificquestionsstilllackingacomprehensiveunderstanding:
30 1. WhatistheoriginoftheaerosollayersdetectedinthenorthwesternAlps?
2. Whatconditionsarefavourabletotheaerosolflowintothevalley?
3. Howdotheadvectedaerosollayersevolveinbothaltitudeandtime?
4. WhatistheimpactofthetransportedaerosolonPMsurfaceconcentrationsandchemicalcomposition?
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Figure2.(a)ElevationmapofItaly,showingthepositionoftheinvestigatedAlpineregionandthegeographicaldomainsof:1)theNumerical
WeatherPredictionmodel(COSMO-I2,orangebox),2)thenationalemissioninventory(QualeAria,redbox)and3)thelocalinventoryof
theAostaValley(bluebox).(b)ZoomovertheAostaValleyandnorthwesternItaly,withlocationofthemeasurementstations.Thebluebox
correspondstothegeographicdomainofthelocalinventoryasinpanel(a).Theelevation(colour)scaleiscommontobothfigures.
5. Are the current chemical transport models able to reproduce and explain the observations at the ground and along the
verticalprofile?
Though referred to the location object of the study, these questions are of more general interest, as several regions of the
world are characterized by basin valleys surrounded by mountains. Hence, the role of pollution advections, their vertical
5 behaviourandthefinalimpactatground-levelisamatterofglobalinterest.
Thepaperisorganisedasfollows:theinvestigatedareaispresentedinSect.2,whileSect.3describesboththeexperimental
(3.1)andthemodelling(3.2)approachused.Results(Sect.4)arepresentedbyaddressingspecificcasestudiestoexemplify
theadvectionofpolluted,aerosol-richairmassesandcomparingthemtothesimulations.ConclusionsaredrawninSect.5.
2 Investigatedareaandexperimentalsites
10 This study is mainly focussed on the Aosta Valley, the smallest Italian administrative region (130000 inhabitants, Fig. 2).
It is about 80 km by 40 km wide, and is located in the northwestern side of the Alps, not far from the two major urban
settlements and industrial areas of the Po Valley, i.e. Turin (80 km) and Milan (150 km). The region is characterised by a
complex topography, typical of the Alpine valleys. Its surface elevation varies from 300 to 4800 m a.s.l. (average altitude
>2000ma.s.l.),withseveraltributaryvalleysstartingfromthemainvalley.ThelatterconnectsMt.Blanc(attheborderwith
15 France,Fig.2)tothePiedmontregionthrougha90km-longdirectrix,approximatelydivisibleintothreesegmentswithNW-
SE,W-EandNW-SEdirections.Thismainvalleyisnarroweratbothends(withminimumwidthoffewhundredsmeters)and
5
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widensincorrespondenceoftheAostacity,thelargesturbansettlementoftheregion(about35000inhabitants).Thecomplex
topographytriggersseveralmeteorologicalphenomenatypicalofmountainvalleys,suchaswindchannellingalongthemain
valley,thermally-drivenwindsfromtheplaintothemountains(andviceversa),rain-shadow(foehn)windsandtemperature
inversions. The latter are very frequent during wintertime, occurring about 50% of the time (Vuillermoz et al., 2013). Not
5 surprisingly,thesedynamicsstronglyaffectthedispersionofpollutantsandtheairqualityinthelowestatmosphericlayers.
Data from several measuring sites in the Aosta Valley are used in this work (Fig. 2b). Most of the instruments employed
(Sect.3.1)areoperatedatthetwoobservatoriesrunbytheregionalEnvironmentProtectionAgency(ARPA)inAosta:Aosta–
SaintChristophe,andAosta–Downtown.TheAosta–SaintChristophestation(45.7 N,7.4 E,560ma.s.l.)islocatedinalarge
◦ ◦
floorwithawidefieldofview,atthebottomofthemainvalley,about2.5kmeastofAosta–Downtown.Thesiteisinasemi-
10 ruralcontext,partiallyinfluencedbyvehiculartrafficandanthropogenicactivitiesfromthecity,suchasdomesticheatingand
industry.TheexperimentalsetupatthissiteincludesanAutomatedLiDAR-Ceilometer(ALC)fortheoperationalmonitoring
oftheaerosolprofile(Dionisietal.,2018),aPOM-02sunphotometerfortheretrievalofcolumnaerosolpropertiesandwater
vapour(Diémozetal.,2014a;Campanellietal.,2018),andaFidas200sOpticalParticleCounterforthesurfaceaerosolsize
distribution, in addition to instruments measuring solar radiation and trace gases (Diémoz et al., 2011, 2014b; Siani et al.,
15 2013,2018;Federicoetal.,2017).Aosta–Downtown(580ma.s.l.)isaurbanbackgroundsite.Thisstationisequippedwith
samplers for continuous monitoring of atmospheric pollution, mainly coming from car traffic, domestic heating and a steel
milllocatedsouthofthecity.ToprovideanideaoftheaerosolloadinAosta–Downtown,theannualaveragesofPM and
10
PM concentrationscalculatedforthelastthreeyearsofmeasurements(2015–2017)rangebetween18–21µgm 3 and11–
2.5 −
12µgm 3,respectively.Despitetheselowaverageconcentrations,dailyPM exceedanceepisodeswithmaximauptoabout
− 10
20 100µgm−3canbeobserved,theiroccurrencestronglydependingontheencounteredmeteorologicalconditions(5exceedance
episodesin2016,13in2015and17in2017).Thus,thereistheneedtounraveltheirbehaviourandtheroleplayedbyregional
transportfrommostpollutedareas.AdditionalmeasurementsusedherewereperformedattheelevatedsitesofLaThuile(1640
ma.s.l.),Saint-Denis(840ma.s.l.)andAntey(1040ma.s.l.),andatDonnas,alow-altitudesite(316ma.s.l.,Fig.2b)closeto
theborderwiththePiedmontregion,attheentranceoftheAostaValley.LaThuileisaremotemountainsiteinatributaryvalley
25 hosting a meteorological and air quality station managed by ARPA. Similarly, a weather station is operated in the village of
Saint-Denisbytheregionalmeteorologicalbureau.AnteyisafurthersmallvillageinatributaryvalleywhereanARPAmobile
laboratory was temporary operated. Finally, the Donnas station is located in a rural area, only partially influenced by traffic
andagriculturallocalactivities,suchasburningofagriculturalresiduals.However,duetoitsproximitytothePobasin,itis
expectedtobeheavilyinfluencedbypollutionfromtheplain.
30 As the vertical dimension is important in this investigation, we also used measurements from an ALC operating in Milan
(Fig.2),thisbeingrepresentativeofthecontrastingconditionswithinthePoValley.ThesystemislocatedontheU9-building
(45.5 N,9.2 E,132ma.s.l.)oftheUniversityofMilano-Bicocca,inanurbanbackgroundareanortheastofthecitycentre.
◦ ◦
AfulldescriptionofthesiteandmeasurementsisreportedinFerreroetal.(2018).
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3 Methods
3.1 Measurements
The experimental setup used in this work includes vertically-resolved measurements from ALCs (Sect. 3.1.1), vertically-
integrated(columnar)aerosolmeasurementsfrombothground(Sect.3.1.2)andspace(Sect.3.1.3),andinsitumeasurements
5 ofaerosolconcentrationandcomposition(Sects.3.1.4–3.1.5),complementedbyancillarygas-phasepollutantsandmeteoro-
logicalmeasurements(Sect.3.1.6).Table1summarisestheinstrumentsusedthroughoutthisstudyintheirrespectivemeasuring
stations.
3.1.1 AutomatedLiDARCeilometers
Verticalprofilesofairconstituentsareparticularlyusefulinidentifyingtransportofpollutantsofnon-localorigin.However,
10 theprofilingcapabilityoftheItalianregionalEnvironmentProtectionAgenciesisstillscarce.OverthePobasin,continuous
monitoringoftheatmosphericcompositionalongtheverticalprofileislackingandinformationatdifferentaltitudesismostly
availableforshortperiodsandduringspecific,dedicatedfieldcampaigns(e.g.,Barnabaetal.,2007;Osborneetal.,2007;Raut
andChazette,2009;Barnabaetal.,2010;Ferreroetal.,2014;Curcietal.,2015;Rosatietal.,2016;Buccietal.,2018).
Light detection and ranging (LiDAR) instruments permit to resolve the vertical distribution of particles. The recent tech-
15 nological and data-processing advances (Wiegner and Geiß, 2012), and commercialisation, of simple LiDAR systems with
operationalcapabilitiesallowtousethiskindofsysteminmonitoring(24/7)modeandinwidenetworks.Inthepresentstudy,
we employ two commercially-available ALCs (CHM15k-Nimbus, manufactured by Lufft GmbH, and formely by Jenoptik
ESW), which have been operating since 2015 at the Aosta–Saint Christophe observatory and in Milan. Both ALCs are part
of the Italian Alice-net (http://www.alice-net.eu/) and the European E-PROFILE (https://ceilometer.e-profile.eu/profileview)
20 networks.Theyallowforcontinuousverticalprofilingoftheradiationemittedbyasingle-wavelength(1064nm)pulsedlaser
(Nd:YAG; 6.5–7 kHz; 8 µJpulse 1) and backscattered by the atmosphere. At the operating wavelength, the backscatter is
−
mainlydominatedbyaerosolsandcloudsintheatmosphere,whereasinterferencebywatervapourhasbeenestimatedtobe
negligible (Wiegner and Gasteiger, 2015). The systems enable a typical temporal resolution of 15 s (integration time) and a
verticalresolutionof15m,upto15kmabovetheground.Mainlimitationsoftheinstrumentsare:1)needforcorrectionsin
25 the lowermost levels, and 2) blind view above thick clouds. 1) In the lowermost levels, the field of view (0.45 mrad) of the
receiver is only partially overlapped to the laser beam (90% overlap is achieved at about 700 m), therefore, an overlapping-
correctionfunctionisneededtocorrectthesignal.Thiswasprovidedbythemanufacturer.2)Thickcloudscausesaturationin
thedetectorsignal(anavalanchephotodiodeoperatedinphotocountingmode),followedbycompletesignalextinction.Thus,
theattenuatedbackscatterabovethecloudceilingisnotconsidered(norplotted)inthisstudy.TheALCfirmwaresusedsofar
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Table1.Observationsites,measurementsandinstrumentsemployedinthisstudy.
Station Elevation Measurement Instrument Data
(ma.s.l.) availability
Aosta–Saint 560 Vertical profile of attenuated backscat- CHM15k-Nimbusceilometer 2015–now
Christophe terandderivedproducts
(ARPAobservatory)
Aerosolcolumnarproperties POM-02sun/skyradiometer 2012–nowa
Surfaceparticlesizedistribution Fidas 200s optical particle 2016–now
counter
Aosta–Saint 545 Standardmeteorologicalparameters SiapandMicros 1974–now
Christophe
(weatherstation)
Aosta–Downtown 580 PM10hourlyconcentration TEOM1400a 1997–now
PM10andPM2.5dailyconcentrations OpsisSM200 2011–now
Water-solubleanion/cationanalyseson Dionex Ion Chromatography 2017–now
PM10samples System
EC/OCanalysesonPM10samples Sunsetthermo-opticalanalyser 2017–nowb
NOandNO2 HoribaAPNA-370 1995–now
Standardmeteorologicalparameters VaisalaWA15 1995–now
Southmountainslope 550–1200 Temperatureprofile HOBO H8 Pro (10 thermome- 2006–now
ters)
LaThuile 1640 PM10hourlyconcentration TEOM1400a 2015–now
NOandNO2 TeledyneAPI200E 1997–now
Saint-Denis 840 Standardmeteorologicalparameters SiapandMicros 2002–now
Antey 1040 PM10dailyconcentration OpsisSM200 2017
Donnas 316 PM10dailyconcentration OpsisSM200 2010–now
NOandNO2 TeledyneAPI200E 1995–now
Milan 132 Vertical profile of attenuated backscat- CHM15k-Nimbusceilometer 2015–now
terandderivedproducts
Standardmeteorologicalparameters VaisalaWXT5 2012–now
aUnderwentmajormaintenanceinthesecondhalfof2016andJanuary2017.
bAvailable4daysevery10.
(versions0.730–0.743forAosta–SaintChristopheand0.730forMilan)providethebackground-,overlap-andrange-corrected
attenuatedbackscatter(RCS)intermsofinstrumentalrawcounts,i.e.
(P(z,t) B(t))z2
RCS(z,t)= − (1)
O(z) 8
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whereP(z,t)isthesignalintensity(rawcounts)backscatteredfromaspecificdistance(z)andmeasuredatground,B(t)
the time-varying background baseline and O(z) the overlap function. To express the backscatter coefficient in SI units and
maketheresultscomparablewithothersimilarinstruments,acalibrationfactor(C )mustbeassessed,sothat
L
RCS(z,t) =βatt(z,t)=βT(z,t)e−2(cid:82)zzminαT(z0,t)dz0 (2)
C
L
5 whereβatt istheattenuatedbackscattercoefficient,βT isthetotal(particlesandmolecules)backscattercoefficientandαT
is the total extinction coefficient. C is determined during clear-sky time windows of at least 3 hours at night, i.e. when the
L
backgroundradiationislow,bythemethod(Rayleightechnique)describedhereafter.First,thebackscatterandextinctionpro-
filesarecalculatedbytheKlett-Fernaldbackwardalgorithm(Fernald,1984;Klett,1985),thenC isdeterminedbyinverting
L
Eq.2.Onceaseriesofcalibrationfactorshasbeenestimated,thetotal(α ,β )andparticle(α ,β )extinctionandbackscatter
T T p p
10 coefficients are computed for all times and sky conditions using a forward Klett method as described by Wiegner and Geiß
(2012).
Usually, the above-mentioned solving techniques are based on an a-priori or independent estimate of the lidar ratio (LR,
i.e.theratioα /β )asafurtherconstraint.Inourcase,LRisnotfixeda-priori,butratherobtainedusingspecificfunctional
p p
relationships linking α to β . Dionisi et al. (2018) demonstrated that this approach, previously proposed and tested on the
p p
15 signalinversionofresearch-typeelasticLiDARs(e.g.,BarnabaandGobbi,2001,2004),providesbetterretrievalsofαp and
β also from ALCs than using an a-priori, fixed LR. More specifically, an iterative data inversion scheme is adopted: at the
p
first iteration, LR is set to an initial value of 38 sr (average value from the functional relationships) and a first retrieval of
the backscatter coefficient β is calculated; starting from the second iteration, the calculated backscatter coefficient and the
p
functional relationships are used to determine an altitude-dependent lidar ratio. The loop continues until convergence of the
20 column-integrated backscatter is reached. The good agreement between the ALC-derived and the sun photometer-measured
aerosolopticaldepth(AOD,i.e.theintegraloveraltitudeofthetheextinctioncoefficient)isemployedasavalidationofthe
qualityoftheinversionresults(Sects.4.1.4and4.3.5)usingthesefunctionalrelationships,atleastindaytimeconditions(see
alsoDionisietal.(2018)andFig.S2d,Sect.S4,andFig.S8e,Sect.S6,intheSupplementarymaterial).
For ease of comparison with pristine (aerosol-free) conditions, and with most LiDAR-based studies, ALCs measurements
25 areprovidedinthisstudyintermsofscatteringratio(SR,e.g.Zuevetal.,2017),i.e.
β β +β
T p m
SR= = (3)
β β
m m
where β is the molecular backscatter coefficient. In case of pure molecular scattering (no aerosol in the atmosphere),
m
SR=1,whileSRincreaseswithincreasingaerosolload.Finally,thehigh-resolutiondatafromtheALCaredownscaledto75
maveragesovertheverticaland5minaveragesovertimetoincreasethesignal-to-noiseratio.Anexampleoftheoutputfrom
30 the Aosta–Saint Christophe ALC, in terms of scattering ratio, is depicted in Fig. 3. The image refers to a typical advection
day(25May2017),characterisedbyarelativelycleanatmosphereduringthemorningandasudden increaseoftheparticle
9
Atmos.Chem.Phys.Discuss.,https://doi.org/10.5194/acp-2018-960
ManuscriptunderreviewforjournalAtmos.Chem.Phys.
Discussionstarted:24October2018
c Author(s)2018.CCBY4.0License.
(cid:13)
Figure 3. Example of particle backscatter profile, in terms of scattering ratio (SR), from the ALC in a typical advection day (25 May
2017,cf.Fig.13).Areasabovethedetectedcloudceiling,wherethebackscatterfromtheALCisnotreliable,areplottedinwhite.Noisy
measurements(e.g.interferencebysolarradiationinthemiddleoftheday)arefilteredonthebasisofaspatialandtemporalvariability
criterion (the standard deviation for each bin not exceeding 20% of the mean value). The Aosta–Saint Christophe ALC is located at an
altitudeof560ma.s.l.
backscatterduringtheafternoon,uptoanaltitudeofmorethan2000ma.s.l.(thealtitudeofthesurfacebeing560ma.s.lin
Aosta–Saint Christophe). As we will demonstrate here, this afternoon increase is due to the transport of polluted air masses
fromthePobasin(seeSect.4).SeveralanalogousepisodeswererecordedintheALCrecordsinceitsinstallationinAosta–
SaintChristophe.Theobservationofthisrecurrentphenomenonwas,infact,thedrivingmotivationforthepresentresearch.
5 Inthestudy,wealsoconverttheALC-derivedbackscatterintoaerosolvolumefollowingDionisietal.(2018),thusallowing
adirectcomparisontomorestandardairqualitymetrics(e.g.PM ,thisisdoneusingaparticledensityρ=1.3gcm 3 inde-
10 −
pendentlyestimatedforthepresentstudybyanopticalparticlecounterco-locatedwiththeALC).Theexpecteduncertainties
in the retrieval of the aerosol backscatter and extinction coefficients, and of the aerosol volume range between 30 and 40%
(Dionisietal.,2018).
10 3.1.2 Sunphotometer
APOM-02sun/skyradiometeroperatesattheAosta–SaintChristopheobservatorysince2012.Theradiometerispartofthe
EuropeanESR-SKYNETnetwork(http://www.euroskyrad.net/).TheirradiancescollectedbythePOM-02at11wavelengths
(315–2200 nm) are inverted to retrieve the aerosol optical properties using both the direct-sun (SUNRAD.pack algorithm
to provide the AOD every 1 min, Estellés et al. (2012)) and the almucantar geometries (SKYRAD.pack software version
15 4.2 to retrieve a complete set of optical and microphysical columnar properties every 10 min, Nakajima et al. (1996)). The
instrumentiscalibratedin-situwiththeimprovedLangleytechnique,describedbyCampanellietal.(2007)inmoredetail,and
10