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Atmospheric Environment 59 (2012) 312e319

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Atmospheric Environment

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An observational study of the atmospheric ultra-fine particle dynamics

C. Varotsos a,*, J. Ondov b, C. Tzanis a, F. Öztürk c, M. Nelson b, H. Ke b, J. Christodoulakis a

aClimate Research Group, Division of Environmental Physics and Meteorology, Faculty of Physics, University of Athens, University Campus Bldg. Phys. V, Athens 15784, GreecebUniversity of Maryland, Department of Chemistry and Biochemistry, College Park, MD 20742, USAc Environmental Engineering Department, Middle East Technical University, Dumlupınar Bulvarı, 06800, Ankara, Turkey

h i g h l i g h t s

< Ultrafine particle observations were obtained in Athens in urban and semi-rural areas.< Distribution parameters of component particle populations are provided.< LNDF parameters of component particle populations are provided.

a r t i c l e i n f o

Article history:Received 3 October 2011Received in revised form2 April 2012Accepted 4 May 2012

Keywords:Ultra-fine particlesAerosolsAir qualityEmissionsAthenseGreece

* Corresponding author. Tel.: þ30 210 7276838.E-mail address: covar@phys.uoa.gr (C. Varotsos).

1352-2310/$ e see front matter � 2012 Elsevier Ltd.doi:10.1016/j.atmosenv.2012.05.015

a b s t r a c t

This paper presents results derived from ultra-fine particle observations conducted in urban and semi-rural areas of the Athens basin in Greece. Aerosol particle size spectra were collected at 2.5-min timeresolution with a Scanning Mobility Particle Sizer for approximately two months, along with standardmeteorological, NO, NO2 and O3 measurements. The results obtained showed that a 10-fold lessmaximum number concentration of the mean spectrum was noticed at the semi-rural site comparedwith that at the urban site. The corresponding maximum for the median spectrum of urban site was only20% less, indicating that extreme cases had little effect, at least in maximum mean concentration of9.8 nm particles. The largest number concentration maximum in the mean size distribution spectrum foreach area occurred at a modal diameter �9.8 nm. For particles �13.4 nm, the mean spectrum for Patisioncontained prominent accumulation particle populations at number median diameters of 13.4, 29.7, and43.7 nm. In contrast, the major features of the accumulation region of the mean semi-rural spectrumwere fit with 5 distribution functions of nearly the same amplitude. The most dominant feature occurredat a number median diameter of 70.1 nm, and thus substantially greater than the 43.7 nm most-dominant in the mean urban spectrum. High ultra-fine particle concentrations at the urban site generallycoincided with periods of high NO concentrations and were well correlated with benzene, signifyingemissions from motor vehicles.

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1. Introduction

In recent decades there is an increasing interest in studies ofatmospheric aerosols, which are a complex mixture of particles(being ubiquitous in air, often observable as dust, smoke and haze)arising from a large number of discrete natural and anthropogenicsources (e.g., Ondov and Wexler, 1998; Murr and Garza, 2009;Varotsos and Alexopoulos, 1977; Varotsos, 2007). Complex studiesshowed that aerosol loading in the atmosphere is importantbecause of the aerosol direct and indirect effects on planetaryradiative transfer processes (Appel et al., 1985; Charlson et al., 1987,1992; Varotsos et al., 1995, 2005, 2006; Kondratyev and Varotsos,

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1995, 1996; Kim et al., 2002; IPCC, 2007; Tzanis and Varotsos,2008) and acute health effects (Katsambas et al., 1997; Alexandriset al., 1999; Pope, 2000; Feretis et al., 2002; Kanakidou et al.,2005; Sioutas et al., 2005). A size class of ambient nanoscaleparticles is the ultra-fine particles (UFP) which are commonlydefined as particles with diameters less than 100 nm (althoughothers prefer <50 nm). Their atmospheric size distributions,composition, morphology, and source strengths can vary signifi-cantly with meteorology, location, and time (Pekney et al., 2006).This is especially true for urban atmospheres wherein emissionsfrom concentrated industrial and dispersed sources lead to urbanpollutant excesses above rural background concentrations (Parket al., 2006). In urban street canyons, traffic is a major source ofaerosol particles and thus strongly influences local particle sizedistributions. Traffic-emitted particles are predominately classified

Fig. 1. Map of the location of the two measurement sites. The University Campus site is located in a semi-rural area (in the foothills of mountain Hymettus). Patision site is located indowntown Athens.

C. Varotsos et al. / Atmospheric Environment 59 (2012) 312e319 313

as soot particles, i.e., complex mixtures of elemental carbon (EC),hydrocarbons (HC; including polynuclear aromatic hydrocarbons,PAH) and their oxidation products, sulphur compounds and othersubstances. Although particles originating from gasoline and dieselpowered engines may be as large as 300e400 nm in diameter(Suarez et al., 1998; Wahlin et al., 2001), both emit soot particlesbelow 100 nm in diameter (Morawska et al., 2004). Typical particles(from modern diesel engines) are agglomerates consisting ofmainly spherical primary particles of about 15e40 nm, or larger forolder diesel engines (Burtscher, 2005). These primary particles cangrow into the near accumulation range 60e100 nm (Karasev et al.,2004) by coagulation and depositional mechanisms (Zhang et al.,2004). Larger particles (>300e1000 nm in diameter) typicallyrepresent aged primary particles upon which water and secondarymass has accumulated (Ondov and Wexler, 1998).

Due to their small size UFP are respirable particles depositingefficiently in human airways penetrating deep within the lung

(Penttinen et al., 2001; Pope et al., 2002; Symons et al., 2005). Theirtoxicity tends to increase as particle size decreases (e.g., Donaldsonand MacNee, 1998; Li et al., 2003) and hence with increasingparticle number concentration (e.g. Kumar et al., 2010). Moreover,Li et al. (2003) found that the increased biological potency of LosAngeles UFP is related organic compounds, notably PAH, i.e.,primary components of soot particles, e.g., those emitted frommotor vehicles. For these reasons, atmospheric UFPs have recentlyreceived substantial attention (Kulmala et al., 2004; Tolocka et al.,2004; Herner et al., 2006; Kulmala and Kerminen, 2008; Kumaret al., 2010). The need for such measurements is especially urgentin large urban areas, where sizeable populations are exposed tohigh concentrations of UFP from motor vehicles.

Airborne UFP can be measured using condensation particlecounters (see next section) and several UFP datasets have recentlybeen acquired, especially in mega-cities. Previous air qualitystudies performed in the Athens area have largely focused on

C. Varotsos et al. / Atmospheric Environment 59 (2012) 312e319314

particulate mass concentrations and chemical composition(Colbeck et al., 2002; Chaloulakou et al., 2003; Ferm et al., 2005,2006; Dall’Osto and Harrison, 2006; Karageorgiou, 2006; Saarnioet al., 2008; Varotsos et al., 2009; Tzanis et al., 2009, 2011). Ingeneral, there is a lack of information on UFP concentrations andthe characteristics of their size distributions in the Athens region.Varotsos (2005) measured the distributions of the aerosol charac-teristics aloft of the Athens area via aircraft. In addition, aerosolnumber concentrations and hygroscopicity were measured duringbrief periods in summer in both the Athens and Marseille regionsduring the “Biogenic Aerosols and Air Quality in the MediterraneanArea” (BOND) project (Petaja et al., 2007). However, in the formerstudy, particles in the UFP region were not measured. And, in thelatter study, the Athens-area measurements were conducted ata sub-urban site, 20 km north of the city, in the foothills of ParnithaMountain. During their study, the prevailing winds were mostlynorth, allowing only infrequent observation of aerosol transportedfrom the City of Athens. Even though there are some case studies onparticles in the ultra-fine size range (Grivas et al., 2004; Diapouliet al., 2007, 2008), UFP measurements in Athens are sparse.

The present study provides new experimental information onthe UFP size distribution characteristics of the urban Athens aerosoland its temporal evolution, in particular, as needed to assessrespiratory deposition, subsequent toxicology, and radiative effects.

2. Measurement sites, instrumentation, and data reduction

2.1. Measurement sites

The measurements were made at Patision Street (105 m a.s.l.) indowntown Athens and on the University of Athens Campus, nearthe eastern edge of the Athens basin (Fig. 1). The Campus site(245 m a.s.l.) is located in a semi-rural area in the foothills ofmountain Hymettus, about 6 km south-east of the Patision site.

Located near the centre of Athens, “Patision” is characterized asan urban area. Patision Street is one of the main traffic roads of theAthens basin and the vehicle traffic almost never stops. Themeasurements at Patision site were begun on 6 December 2005and lasted for about 45 days. The sampling systemwas then movedto the University Campus, an area extended at the north-easternpart of the Athens basin, at a distance of about 5 km from down-town Athens. The measurements at the University Campus tookplace for about 20 days (13/1/2006e31/1/2006).

2.2. Measurements

Particle number versus size distributions were acquired every2.5-min, in 105 nearly equally-spaced logarithmic size intervals forparticles between 9.65 and 422 nm, using a Thermo Systems, Inc.(Shoreview, Minnesota, USA) Scanning Mobility Particle Sizerconsisting of a model 3080L Electrostatic classifier, model 3077krypton-85 aerosol neutralizer, and model 3010 continuouscondensation particle counter (CPC). The SMPS was located insidethe 2nd floor of a 4-story office building on Patision Street. We chosethis location because at the same building the main station of thenational network for air pollution monitoring is operating for manyyears. Aerosol was aspirated at 0.11 LPM through a 1.5-m, ¼ʺstainless steel probe extending 1 m from the outer wall of thebuilding and 3 m from street level. A 0.0457-cm single orificeimpactor was fitted between the sampling probe and the ES inlet toremove interference from large particles. In accordance with US“supersites” protocols, an inlet dryer was not used; however,sampled aerosol was conditioned to indoor room temperature bycontact with the instrument’s internal plumbing. We note thatindoor temperatures typically exceeded those outdoors by more

than 6 �C during the study such that the Relative Humidity (RH) ofthe aerosol inside the instrument (herein internal RH) ranged from27 to 77% between Christmas and the end of New Year’s Day,averaging 52% overall for spectra acquired at Patision site. More-over, the instrument’s internal RH was likely somewhat less thanthese values due to heat of compression of the sheath-air blower.

Tail-pipe aerosol dilution factors and measurement tempera-tures were well within the ranges (38e390, and 22e28 �C,respectively) employed for SMPS particle size-distributionmeasurements made on exhaust aerosol of dynamometer oper-ated vehicles (e.g., Robert et al., 2007).

Finally, supporting meteorological (temperature, RH, windspeed and direction) and gaseous phase components (O3, NO, NO2,NOx, and benzene) were also measured at the both measurementsites by local air quality monitoring stations of the Ministry ofEnvironment, Energy, and Climate Change (National Service for AirPollution Monitoring). Ozone and NOx concentrations wereobtained as one-hour averages.

2.3. Data reduction and presentation

Particle size distributions were calculated from the CPCconcentrations and EC parameters (up-scan time, 120 s; aerosolflow, 0.11 LPM; and sheath-air flow, 6 LPM) using TSI’s SMPSacquisition/inversion software (Aerosol Instrument Managementsoftware, AIM, v4.9), which employs the algorithms of Wang andFlagan (1990). All spectra were corrected for instrument andprobe diffusion losses using the AIM software and the parameteri-zation of Hinds (1999), respectively. Herein, the various particlenumber concentrations were plotted against the midpoint particlemobility diameter. Because logarithmic size intervals of the SMPSwere highly uniform, the distributions have the same shape as thosenormalized to the logarithmic binwidth, while allowing the numberconcentrations in each interval to be read directly from the figures.

To facilitate the discussion of temporal and dynamical behav-iour, both time series of individual spectra for typical or illustrativedays and various study-widemetrics were computed: i.e., themeanand median of all number distributions (herein referred to asspectra) collected at each location, their (statistical) geometricmean diameters ðdgÞ, and standard deviations (sg). Statisticalgeometric distribution parameters were also calculated for RHranked subsets of spectra acquired at each location, whereininternal RH was estimated from the difference between indoor andoutdoor temperatures, and measured outdoor RH. As describedbelow, themean spectra for both siteswere dominated by the tail ofa particle distribution with modal diameters �9.8 nm, hence,distribution function (LNDF) parameters (herein denoted d̂gmn andd̂gmd for geometric mean diameters of the mean and mediansspectra respectively) could not be determined for these subpopu-lations. However, lognormal distribution parameters were obtainedfor components fit to the mean spectra for dp > 13.3 nm (the lowerbound of the size interval with median diameter of 13.6 nm), toestimate the modal diameters of the principle components in thisrange and to parameterize the mean distributions. For Patision site,this was done after transforming the mean number distribution toits surface distribution and then calculating the correspondingnumber median diameters for each component from the resultingsurface parameters using a HatcheChoate equation with b ¼ 2(Hinds, 1999); for Campus, the mean number distribution was fitdirectly and, for completeness, surface modal diameters werelikewise obtained using the HatcheChoate equation with b ¼ 2.Because LNDFs were used for each component, their mediandiameters are equal to their modal diameters.

Linear regression parameters were calculated for correlationsbetween total particle concentrations and hourly NO, NO2, NOx, and

C. Varotsos et al. / Atmospheric Environment 59 (2012) 312e319 315

benzene measurements made at Patision site. These were calcu-lated day-wise, i.e., one correlation was made for all data acquiredover each day of the study.

3. Results and discussion

3.1. Statistical distribution parameters of mean and median spectra

The mean and median particle size distributions of all spectraacquired at Patision and Campus sites are shown in Fig. 2a. Theprincipal feature in each is an enormous maximum numberconcentration in the first measurement channel, i.e., at a midpointmobility diameter of 9.8 nm, with concentrations declining steeplyto a minimum near 13.3 nm. These general features are consistentwith urban street canyon measurements (e.g. Violante et al., 2006).

Herein, particles with midpoint mobility diameters�13.3 nm arereferred to as nuclei particles and those >13.3 nm, as accumulationparticles. For the Patision site, the maximum number concentrationof the mean spectrumwas 1.08 � 106 cm�3, compared with 10-foldless (1.18 � 105 cm�3) for Campus. The corresponding maximum forthe median spectrum of Patision (8.69 � 105 cm�3) is only 20% less,indicating that extreme cases had little effect, at least in maximummean concentration of 9.8 nm particles.

Fig. 2. Top panels: (a) the mean and median particle size distributions of all measuremecomponent distributions (dp � 13.3 nm) for fits to the surface distribution of the mean nuCampus (d) Black and orange curves represent the actual and fitted curve, respectively. LNinterpretation of the references to colour in this figure legend, the reader is referred to the

Because sample conditioning designed to lower the RH at whichaerosol size distributions are made is now practiced by the majorEuropean aerosol network of stations (Philippin et al., 2009),a cursory attempt was made to reveal the effects of changingoutdoor and hence instrument RH, by comparing the statisticalgeometric distribution parameters listed in Table 1.

The median internal RH for all spectra acquired at Patision was52%, i.e., below the deliquesce point of ammonium sulphate andammonium nitrate (but not ammonium bisulphate), which at thislocation, were surely only minor constituents. More than two-thirds of the Patision spectra and all the Campus were acquired atinternal RH <52%. Accordingly, statistical geometric distributionparameters listed in Table 1 were calculated for means andmediansof the distributions acquired for all spectra, those acquired at RH<52%, and RH �52%. Such parameters are often calculated fromparticle counts in all measured sizes. However, for reasons notedabove, geometric parameters were calculated for measured parti-cles with diameters below and above 13.3 nm.

The statistical dg calculated for mean of the number distribu-tions acquired at Patision at RH<52% (28.6 nm)was greater than itsvalue (25.1 nm) at RH �52% and their respective sgs (1.89 and 1.83)were more narrow at higher RH. The corresponding values for themean surface distributions are less affected by the enormous

nts at the Patision and (b) at University Campus stations. Bottom panels: lognormalmber distribution spectrum for Patision (c) and to the mean number distribution forDF parameters for component distributions (other colours) are listed in Table 2. (Forweb version of this article.)

Table 2Fitted lognormal distribution parameters, for means of all Patision and Campusspectra, for dp � 13.3 nm.

Parameter Patision components

P1 P2 P3 P4 P5 P6

SMDa, nm 18.25 40 144 60 308 266sg

b 1.48 1.47 2.165 1.2 1.38 1.03NMDc, nm 13.4 29.7 43.7 56.1 250.3 265.5Amplituded 0.0875 0.1180 0.9695 0.0100 0.0122 0.00222

Parameter Campus components

C1eC3g C4 C5 C6 C7 C8 C9

SMDe, nm 17.0 23.1 32.1 47.1 93.8 152.5 236.1sg

b 1.186 1.2 1.27 1.465 1.27 1.274NMDf, nm 16.0 21.8 30 42 70.1 136 210Amplituded 0.0046 0.00558 0.0043 0.00435 0.00896 0.00142 0.000981

a Surface mean diameter of the fitted component.b Geometric standard deviation off fitted component.c Geometric number mean diameter derived from SMD and sg via HatcheChoate

equation.d Amplitudes are relative to max concentration ¼ 1, which in every case corre-

sponded to dp ¼ 9.8 nm.e Geometric surface mean diameter derived from NMD and sg via HatcheChoate

equation.f Number mean diameter of the fitted component.g Amplitude weighted SMD and NMD of component C1, C2, and C3; amplitude

and sg are those of component C2.

Table 1Statistical geometric mean diameters (nm) and geometric standard deviations fornumber distributions for dp � 13.3 nm.a

Spectra Weighting dp < 13.3 nm dp � 13.3 nm

Mean, median Meanb Medianc

dg dg sg dg sg

Patision spectraAll By number 10.3, 10.1 27.4 1.87 28.7 1.86All By surface 10.4, 10.3 99.2 2.31 98.4 2.29�52% RH By number 10.4, 10.3 25.1 1.83 24.9 1.80�52% RH By surface 10.5, 10.5 93.7 2.38 90.6 2.41<52% RH By number 10.2, 10.1 28.6 1.89 32.0 1.86<52% RH By surface 10.3, 10.1 101.5 2.27 102.2 2.22Campus spectra, all size binsd

All By number 10.1e 40.9 2.08 45.0 2.02All By surface 10.1e 137.6 2.02 140.5 1.99

a Values are the statistical geometric mean and geometric standard deviations forthe mean and median of spectra indicated.

b Parameters given are those for the mean of spectra indicated in column 1.c Parameters given are those for the median of spectra indicated in column 1.d All spectra were acquired at RH <52%.e Value is for mean spectrum.

C. Varotsos et al. / Atmospheric Environment 59 (2012) 312e319316

sub-13.3 nm particle populations dominating the mean of spectracollected at both locations (see Fig. 2a,b). These (101.5 and 93.7 nmfor the mean Patision spectrum for RH <52% and RH �52%,respectively) suggest that some particles may have shrunk athigher RH, as has been observed for lacy soot particles uponacquiring water. Narrowing is also evident in their respective sgs(2.27 and 2.38). This apparent narrowing might reflect condensa-tional growth during some of the sampling periods, which isconsistent with the compacting of soot particles. Nonetheless,corresponding (surface dg) value computed for the mean of allPatision spectra, 99.2 nm, was not so different from that (101.5 nm)calculated for samples acquired at RH <52% to warrant excludingmany of the spectra, and in the remaining data described herein, wedid not do so.

As indicated in Table 1 (1st two rows), the statistical geometricdistribution parameters for the mean and median of all Patisionspectra differed little. This was true of those for both number andsurface mean spectra and for both size ranges for which theseparameters were calculated. We note also, that particles withmobility diameters <13.3 nm could not be detected in half of thespectra acquired at the Campus site owing to our keeping the samelow sampling flow rate at both locations. For these reasons, weshow only mean spectra in subsequent figures, and in any case, wedeem these more representative of the distributions of particlesthat are inhaled or available to interact with the solar flux.

Fig. 3. Size spectra measured during the New Year’s Eve. Each spectrum has beensmoothed by binning to one-third the number of size intervals.

3.2. Component distributions

As shown in Fig. 2c, the distribution of the mean Patisionspectrum of particles larger than 13.3 nmwas well fit with the sumof six LNDFs, whereas nine were used to fit the upper range of theCampus mean spectrum (Fig. 2d). Their number median diameters(NMD) represent the modal diameters of the principle componentsof the mean distributions. As indicated in Table 2, the most abun-dant modes in the Patision surface spectrum were fit at surfacemedian diameters (SMD) of 18.25, 40, and 144 nm, correspondingto NMDs of 13.4, 29.7, and 43.7 nm. The latter mode was clearly themost abundant. Clearly the mode at 13.4 nm, was detected at thelower bound of the fitting region. Such modes are clearly evident inindividual spectra for example, as shown in Fig. 3, wherein 5spectra are shown for the evening of New Year’s Eve and earlymorning of New Year’s Day.

The number modes (NMDs) found for Patision compare wellwith those observed in fresh UFP measured downwind of a Cal-ifornia freeway where 6e8 and 9 nm modes were detected atdistances�20m, and where 30- andw60-nmmodes becamemoredominant with increasing distance to 90m (see Zhu et al., 2002a,b).At Patision, we sampled aerosol from a long narrow street canyonencompassing both the freshest nuclei particle emissions as well asolder and more diluted aerosol arriving from substantial distancesupwind. Clearly the 6e8, and 9 nm aerosols measured in LA areseen as the exponential tail beginning in our 9.8 nm mobilitychannel.

In contrast, the major features of the accumulation region of themean Campus spectrum were fit with 5 LNDFs of nearly the sameamplitude. The most dominant feature occurred at a numbermedian diameter of 70.1 nm, and thus substantially greater than

12/13/2005 12/20/2005 12/27/2005 1/3/2006 1/10/2006

0

1x106

2x106

3x106

4x106

5x106

dp = 9.84~13.1 nm

0

1x106

2x106

3x106

4x106

dp = 13.6~414 nm

Particle n

um

ber co

ncen

tratio

n, #/cm

3

Fig. 4. Temporal distributions of aggregate concentrations of nuclei (dp � 13.3 nm) andlarger (dp > 13.3 nm) particles measured at Patision.

Table 3Correlation statistics for total particle concentrations against NO and benzeneconcentrations.

Period Averages for indicated periods Intercept

Averages

R2 p value Slope

Daily for all Patisiona

NO 0.69 0.028 47,785 323,557Benzene 0.57 0.058 1,588,339 �1,213,960

Dec 24 & 25thb

NO 0.67 1.32E-12 6817 984,688Benzene 0.64 7.66E-12 158,634 878,890

Dec 31 & Jan 12NO 0.70 1.03E-13 8431 186,543Benzene 0.49 2.59E-08 118,875 204,495

Daily for all weekdaysc

NO 0.69 0.031 52,634 244,857Benzene 0.58 0.07 1,769,300 �1,534,393

a Average of correlation statistic calculated for 24 hourly intervals on each of 36days.

b Average of correlation statistic calculated for 48 hourly intervals.c Average of correlation statistic calculated for 24 hourly intervals on each of 32

weekdays.

C. Varotsos et al. / Atmospheric Environment 59 (2012) 312e319 317

the 43.7 nm most-dominant in the mean Patision spectrum.Overall, the Campus spectrum can be seen as a more complexmixture of fresh and aged aerosol as we had expected. It is likelythat, measurements at the Campus site were influenced by nearbyvehicles as evidenced by the nuclei particle mode that could bedetected in approximately half the samples.

Fig. 5. The diurnal variation of the NO and total particle concentration (n

3.3. Temporal distribution of particle concentrations

Aggregate number concentrations of both particles larger andsmaller than 13.3 nm are plotted for the entire Patision studyperiod in Fig. 4. As shown, those in the latter range vary by nearlya factor of 10, with maxima reaching nearly 5 � 106 cm�3. Those inthe former varied similarly during the first week of the study, but

umber cm�3) at the Patision (a) and University Campus stations (b).

C. Varotsos et al. / Atmospheric Environment 59 (2012) 312e319318

varied less so for most of the remainder of the study. One of theworst excursions occurred on Thursday, December 29th, two daysbefore New Year’s Eve. On this day, the concentrations of nuclei andaccumulation range particles peaked (4.8 � 106 and 2.1 �106 cm�3,respectively) at 9:00 am, i.e., during the morning commute period,under light winds (2e2.6 m s�1) following a period of calm.

3.4. Correlations between particle and nitrogen oxideconcentrations

Much information about the sources of UFP is gained by corre-lating the temporal patterns of UFP and NO concentrations. NO isthe primary nitrogen oxide emitted from high-temperaturecombustion sources, including motor vehicles. NO is converted toNO2 by oxidants produced by photochemically induced degrada-tion of non-methane hydrocarbons and thus, NO (during morningcommute periods when NOx plumes from stationary sources aretrapped aloft) and NO2 are indicators of fresh traffic emissions andphotochemically produced ozone, respectively.

High NO concentrations generally coincided with periods ofhigh UFP concentration and during high-traffic periods, signifyingemissions from motor vehicles. Indeed, as indicated in Table 3,average daily R2 value of correlations between UFP and NO werehighly significant for both the study period average (R2 ¼ 0.69,p ¼ 0.027) and for all weekdays (R2 ¼ 0.69, p ¼ 0.031). These werefar more significant for the holiday periods: Dec. 24e25th(R2 ¼ 0.67, p ¼ 10�12) and Dec. 31eJan. 1 (R2 ¼ 0.70, p ¼ 10�13).As shown in Fig. 5a, these peaks occurred between 7:00 and 11:00am onmost days, in accordancewith peak commuter traffic periodsand generally lower mixing height, however NO peaked also in theevenings between 6:00 and 11:00 PM. Strong correlations betweenUFP and benzene, an antiknock component of gasoline thatreplaced Pb decades ago, further evidence a strong motor vehiclesource for UFP and NO.

3.5. Comparison of Patision and Campus observations

As shown in Fig. 5, Campus particle concentrations during themorning commute hours are much lower relative to those in theafternoon and evening. Nevertheless, the NO peak (Fig. 5b) is mostprominent during the morning, albeit, at w14 mg m�3, much lowerthanmorning peaks at Patision. Interestingly, the ratio of maximumcommute hour NO to total particle concentration at Campus (w2 �10�5) is about a quarter of its value (w8 � 10�5) during the sameperiod at Patision. There could be many reasons for this, e.g.,cleaner cars, or maybe the influence of the Campus boiler plant.

Overall, the median of 1 h averaged NO, NO2 and O3 concen-trations during the Campus measurement period were 2, 16 and43 mg m�3, respectively. The 1-h mean total particle numberconcentrations were typically in the range of 650,000 to870,000 cm�3. Thus, NOx and UFP at Campus were typically 1/5ththeir concentrations at Patision. This was true, despite the fact thatwind directions taken to be favourable to transport of air from theAthens basin occurred for 51% of the Campus measurementperiods.

4. Conclusions

In this study, we investigated the time e and size-resolvedconcentrations of UFP at both a source-oriented (urban) anda receptor (semi-rural) site in Athens, Greece. The observationslasted for about two months. The experimental results clearlyidentified Patision as a source site, in which UFP are generatedlargely by the near-constant traffic emissions from city streets.

In particular, the mean and median particle size distributions ofall spectra derived from Patision and Campus observations revealedan enormous maximum at a midpoint mobility diameter of 9.8 nm,with concentrations declining steeply to a minimum near 13.3 nm.For the Patision site, the maximum number concentration of themean spectrum was found 1.08 � 106 cm�3, whilst for the Campussite 10-fold less. The corresponding maximum for the medianspectrum at Patision site was only 20% less, indicating that extremecases had little effect, at least in maximum mean concentration of9.8 nm particles. The largest number concentration maximum inthe mean size distribution spectrum for each area occurred ata modal diameter �9.8 nm. For particles �13.4 nm, the meanspectrum for Patision contained prominent accumulation particlepopulations at number median diameters of 13.4, 29.7, and 43.7nm. The latter mode, was clearly the most abundant and the modeat 13.4 nm, was detected at the lower bound of the fitting region. Incontrast, the accumulation region of the mean semi-rural spectrumwas fit with 5 distribution functions of nearly the same amplitude.The most dominant feature occurred at a number median diameterof 70.1 nm, and thus substantially greater than the 43.7 nm most-dominant in the mean Patision spectrum. The fact that high NOconcentrations at the Patision site generally coincided with periodsof high ultra-fine particle concentration signifies emissions frommotor vehicles. This is also evident from the strong correlationsbetween UFP and benzene.

In a future paper we will employ the data obtained in theafore-mentioned campaign to investigate source apportionmentand evolution and transport dynamics of aerosol in the Athensbasin.

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