ARTICLE IN PRESS

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Atmospheric Environment 41 (2007) 7969–7976

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Short communication

Characterization and contribution to PM2.5 of semi-volatileaerosols in Paris (France)

Olivier Faveza,�, Helene Cachiera, Jean Sciarea, Yvon Le Moullecb

aLSCE/IPSL, Laboratoire CEA-CNRS-UVSQ, Gif-sur-Yvette, FrancebLaboratoire d’Hygiene de la Ville de Paris, Paris, France

Received 8 June 2007; received in revised form 6 September 2007; accepted 10 September 2007

Abstract

Collocated PM2.5 measurements using a conventional R&P TEOM (model 1400a) and a TEOM-FDMS were performed

at a Paris urban background site during winter/summer field experiments. Results showed that conventional TEOM

underestimates PM2.5 mass concentrations by about 50% in winter and 35% in summer. They also confirmed that this

negative sampling artifact, due to the volatilization of semi-volatile material (SVM) inside the instrument, cannot be

accurately accommodated by a single correction factor because of SVM routine fluctuations. A basic filter-based

investigation of the SVM chemical composition also indicated that SVM, measured by the TEOM–FDMS, is mainly

formed by ammonium nitrate in winter while significant contributions of semi-volatile organic matter were observed in

summer. The latter species was found to possibly account for more than 50% of secondary organic aerosol formed during

summer afternoons. These findings call for more investigation of the SVM chemical composition, particularly during the

summer season, in Paris and in Europe.

r 2007 Elsevier Ltd. All rights reserved.

Keywords: Semi-volatile material; Ammonium nitrate; Organic aerosol; TEOM(–FDMS); PM2.5

1. Introduction

Due to their climatic impact as well as theirnegative effects on human health (Slanina andZhang, 2004), airborne particles are a subject ofgreat scientific concern. For a couple of decades,they have thus been monitored and regulatedworldwide as PM10 (mass of ambient particles withaerodynamic diameter below 10mm), and, morerecently, as PM2.5. Several organizations, including

e front matter r 2007 Elsevier Ltd. All rights reserved

mosenv.2007.09.031

ing author. Tel.: +331 69 08 12 72;

8 77 16.

ess: olivier.favez@lsce.ipsl.fr (O. Favez).

the European Commission, the US EnvironmentalProtection Agency (EPA) and the World HealthOrganization, elaborated standard methods for theevaluation of PM concentration levels. Thesemethods commonly rely on manual filter-basedgravimetric measurement (EPA, 1990; CEN, 2003).Nevertheless, most of the monitoring networks havealso been using on-line automatic systems, such asthe Rupprecht & Patashnik Tapered ElementOscillating Microbalance (R&P TEOM; see Patash-nik and Rupprecht, 1991), which are globally moreconvenient, less expensive and provide results morerapidly than labour-intensive manual gravimetricmethods. Numerous studies (Allen et al., 1997;

.

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Eatough et al., 2003; Hitzenberger et al., 2004)however reported that the conventional TEOMmodel (R&P TEOM 1400a) is likely to under-estimate PM due to the volatilization of semi-volatilematerial (SVM) inside the instrument (heated at50 1C). SVM, which is mainly formed by ammoniumnitrate and semi-volatile organic material (SVOM),might be responsible for significant aerosol radiativeforcing (Haywood and Boucher, 2000) as well as forsevere human health effects (Eatough et al., 2003;Reiss et al., 2007). The measurement of SVM andthe investigation of its chemical composition is thusof prime interest. In ambient air, the partitioning ofSVM between the gaseous and the particulate phasesstrongly depends on temperature and relativehumidity (Charron et al., 2004; Sciare et al., 2007),and contributions of ammonium nitrate and SVOMto total SVM were found to vary from oneEuropean place to another (Charron et al., 2004;Cachier et al., 2004). Noteworthy, as most of semi-volatile matter belongs to the fine mode, SVM isexpected to be relatively more abundant withinPM2.5 than within PM10.

This paper presents results of collocated PM2.5

measurements in Paris using a conventional TEOMand a TEOM equipped with two devices recentlydeveloped by R&P in order to limit and to take intoaccount SVM losses: the Sample EquilibrationSystem (SES) and the Filter Dynamic MeasurementSystem (FDMS). Seasonal and diurnal variations ofSVM mass concentrations were investigated fromtwo 1-month-long field experiments performedduring winter and summer 2005, respectively.Measurements also comprised filter-based determi-nation of the particle main chemical species, andparticularly NH4NO3 and OC (organic carbon), inorder to explore the chemical composition of SVM.

2. Experimental

Measurements were performed on the terracedroof (14m above ground level) of the Laboratoired’Hygiene de la Ville de Paris (Paris, 13th district).This site corresponds to a station of the AIRPARIFair quality monitoring network and is considered asbeing representative of Paris background air pollu-tion. Results presented here were obtained from 10January 2005 to 8 February 2005 and from 4August 2005 to 5 September 2005. Ambient airtemperature and relative humidity were measured atthe site every 5min using an Oregon ScientificWMR-918 Weather Station. Hourly mean tempera-

tures ranged from �3 to 12 1C and from 12 to 33 1Cduring the winter and summer periods, which areassessed to be representative of wintertime andsummertime meteorological conditions in Paris.

2.1. PM2.5 continuous measurements

PM2.5 were continuously measured using a R&PTEOM (model 1400a), similar to those generallyused in monitoring networks, and a R&P TEOMequipped with a SES and a FDMS (series 8500).These two instruments, referred in this paper as‘‘conventional TEOM’’ and ‘‘TEOM–FDMS’’, re-spectively, were equipped with a similar inlet systemformed by an R&P PM10 16.67 Lmin�1 inletfollowed by a R&P 2.5 mm sharp cut cyclone.

2.1.1. Conventional TEOM

PM2.5 data from the conventional TEOM wereobtained on a 10min basis and are referred in thispaper as PM2.5,TEOM. As mentioned in the intro-duction, the conventional TEOM is likely tounderestimate PM concentration levels. This nega-tive sampling artefact arises from SVM losses at50 1C, which is the instrument recommended work-ing temperature in order to remove particle-boundwater. Based on comparisons with manual gravi-metric measurements, several correction factorswere unsatisfactorily proposed in order to accom-modate SVM losses (Gehrig et al., 2005; Green andFuller, 2006). In this study, following Charron et al.(2004), the correction factors implemented in theTEOM software (b0 ¼ 3 mgm�3 and b1 ¼ 1.03) wereremoved. Subsequently, PM2.5,TEOM data representhere PM2.5 concentrations directly measured by aconventional TEOM (reported to standard tem-perature and pressure).

2.1.2. TEOM– FDMS

In order to limit and to take into account SVMlosses inside the instrument, R&P recently devel-oped SES and FDMS devices (Meyer et al., 2002).The SES allows the reduction of heating at the inletfrom 50 to 30 1C, maintaining sample RH below25%, by means of a Nafion dryer. On the otherhand, volatilization of SVM at 30 1C is resolved bythe use of the FDMS system, which provides a fulldetermination of volatile mass through a self-referencing gas conditioning scheme. PM2.5 mea-surements provided by a TEOM equipped with bothSES and FDMS systems have shown to comparevery well with other real-time automatic analysers

ARTICLE IN PRESSO. Favez et al. / Atmospheric Environment 41 (2007) 7969–7976 7971

accounting SVM (Wilson et al., 2006; Grover et al.,2006). PM2.5 and SVM data provided by theTEOM–FDMS were obtained on a 6min basis,and are referred in this paper as PM2.5,FDMS andSVMFDMS, respectively.

Noteworthy, SVMFDMS represents a measurementof SVM at 30 1C, while the discrepancy betweenPM2.5,FDMS and PM2.5,TEOM represents a measurementof SVM at 50 1C. SVMFDMS is thus expected to belower than the difference {PM2.5,FDMS�PM2.5,TEOM}.

2.2. Filter sampling and chemical analyses

Fine particulate matter was collected using StackFilter Unit (SFU), consisting of an 8 mm-pore-size47mm-diameter Nuclepore polycarbonate filtermounted in front of a 0.4 mm-pore-size 47mm-diameter Nuclepore polycarbonate filter. At theflow-rate used in this study (1m3 h�1) the 50% cut-point diameter of the 8 mm filter is approximately2.570.2 mm (John et al., 1983). NO3

� and NH4+

mass concentrations were determined by IonChromatography analyses following the extractionand analytical protocol described in Sciare et al.(2005). For each filter sample, NO3

� was checked tobe fully neutralized by NH4

+, and ammoniumnitrate mass concentrations were then calculatedas being equivalent to {1.29� [NO3

�]}.Fine carbonaceous particulate fractions, namely

organic carbon (OC) and elemental carbon (EC),were also collected at a flow-rate of 1m3 h�1 andusing SFU with a 47mm-diameter Whatmann QMAfilter downstream of the 8mm Nuclepore filter. OCand EC mass concentrations were determined using athermo-optical carbon analyser (EC–OC Lab Instru-ment, Sunset Laboratory) implemented with the DRIthermal program (Chow et al., 1993).

A different sampling strategy was applied forwinter and summer field studies. During winter,samples were collected on a 24 h basis (noon tonoon) during 17 weekdays. During summer, sam-ples were collected from 4 August 2005 to 11 August2005 only. However, during this period, threesamples were collected everyday (05:00–10:30 h,11:00–16:30 h and 17:00–22:30 h local time).

SVM losses from the filter during sampling maynot be excluded. However, for the summer fieldexperiment this negative artefact is assessed tobe limited due to short-time sampling intervals.For OC, positive artifact, due to gaseous organicspecies adsorption onto the filter matrix, may not beexcluded too.

2.3. Aethalometer measurements

Magee Scientific Aethalometer AE30 model(7 wavelength channels) measurements were alsoperformed. In this study, this instrument was usedto obtain black carbon mass concentrations (on a5-min basis and using the 660 nm wavelengthchannel), but also to investigate the behaviour ofsemi-volatile polycyclic aromatic hydrocarbons(PAHs) in the particulate phase by means ofthe comparison between the 370 and 660 nmchannels. Indeed, as reported by the manufacturer(www.mageesci.com), the discrepancy between ab-sorption measurements at these two wavelengthsprovides a qualitative indication of UV-absorbingparticulate material (UVPM), which is mainlyformed by PAHs.

3. Results and discussion

As expected, the conventional TEOM is found tounderestimate PM2.5 concentrations. This artefactappears to be very significant for both seasons withan averaged underestimation of 51724% duringwinter and of 35726% during summer (based onhourly mean data). These high values are consistentwith those found by Eatough et al. (2003), whoperformed such wintertime/summertime PM2.5 in-ter-comparison exercise in Salt Lake City.

As shown in Fig. 1 for the winter season, thediscrepancy between hourly mean PM2.5,TEOM andPM2.5,FDMS strongly fluctuates with time. This hasto be related to the variations of meteorologicalconditions (temperature, relative humidity) as wellas to the variations of the strength of aerosol andgaseous precursor sources. This routine SVMfluctuation is also observed on a daily basis, asshown by Fig. 2 presenting the comparison of dailymean PM2.5,TEOM and PM2.5,FDMS obtained for thetwo field campaigns. This figure displays a signifi-cant scatter, which points out that a constantcorrection factor may not accurately accommodatethe conventional TEOM SVM losses, even within agiven season. This is illustrated by the fact thatmean values obtained for 2 given days (19 January2005 and 4 February 2005 for instance) displayingroughly the same PM2.5,TEOM concentration (7.9and 7.6 mgm�3, respectively), could display verydifferent PM2.5,FDMS/PM2.5,TEOM ratios (1.3 and2.6, respectively).

As expected SVMFDMS mass concentrations arefound to be lower than discrepancies between

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y = 2.5x

y = 1.4x

0

10

20

30

40

50

60

0 5 10 15 20 25 30

PM2.5 conventional TEOM, µg.m-3

PM

2.5

TE

OM

-FD

MS

, µg

.m-3

Winter

Summer

Fig. 2. Comparison of daily mean PM2.5 concentrations obtained

by conventional TEOM and TEOM–FDMS during both winter

and summer field campaigns.

0

10

20

30

40

50

60

70

80

01/10 01/15 01/20 01/25 01/30 02/04 02/09

time (mm/dd)

PM

2.5

, µg

.m-3

PM-2.5 TEOM-FDMS

PM-2.5 conventional TEOM

Fig. 1. Hourly mean PM2.5 concentrations measured by conventional TEOM and TEOM–FDMS from 10 January 2005 to 8 February

2005.

O. Favez et al. / Atmospheric Environment 41 (2007) 7969–79767972

PM2.5,FDMS and PM2.5,TEOM measurements. How-ever, SVMFDMS is found to significantly contributeto PM2.5,FDMS during both seasons, since itrepresents on average 23719% and 18711% ofPM2.5,FDMS in winter and in summer respectively(based on hourly mean data).

Higher conventional TEOM underestimation andSVMFDMS mass concentrations observed duringwinter (relatively to summer), should be mainlyrelated to meteorological conditions occurringduring this season. Indeed, differences in thermo-dynamic conditions between ambient air and theinner-instrument are more important. Furthermore,wintertime cold temperatures and high relative

humidity lead to a more efficient condensation ofSVM, which is thus expected to be more abundantin the aerosol phase.

Surprisingly however, discrepancies betweenPM2.5,FDMS and PM2.5,TEOM measurements as wellas SVMFDMS mass concentrations are found toslightly increase with temperature (for temperaturesbelow 30 1C) during summer. This phenomenonmay be related to photochemical oxidation pro-cesses. Indeed, a clearly marked SVMFDMS diurnalpattern, with a broad maximum peak between 11:00and 17:00 h local time (LT), is observed almosteveryday during the summer experiment, whereassuch a clear diurnal pattern is not observed duringwinter. As may be observed in Fig. 3, presenting themean SVMFDMS diurnal pattern obtained for thesummer field study, SVMFDMS mass concentrationsare found to increase by a factor of 2 duringafternoon, compared to nighttimes. The mean BCdiurnal pattern obtained during summer using theaethalometer (also presented in Fig. 3) displays aminimum between 12:00 and 18:00 h LT, whichclearly indicates that high SVMFDMS mass concen-trations recorded during afternoon do not directlyresults from primary SVM anthropogenic emis-sions. They could thus originate from secondaryaerosols photochemical formation, as previouslyobserved (Lee et al., 2005; Eatough et al., 2003).

Filter sampling and subsequent chemical analysisallowed investigating the chemical composition ofSVM. In winter, ammonium nitrate is found to beresponsible on average for about 45% of theconventional TEOM PM2.5 underestimation, and,as shown in Fig. 4, appears to be sufficient enough

EC prim:

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0.750

1

2

3

4

5

6

00:00 02:00 04:00 06:00 08:00 10:00 12:00 14:00 16:00 18:00 20:00 22:00 00:00

local time (hh:mm)

SV

MF

DM

S,

µg.m

-3

1.50

2.25

3.00

BC

, µg

.m-3

SVM-FDMS

BC

Fig. 3. Mean diurnal patterns of semi-volatile material measured by TEOM–FDMS (SVMFDMS: squares7SD) and of black carbon mass

concentrations measured by the aethalometer (BC: dotted line) obtained for the summer experiment.

y = x

0

2

4

6

8

10

12

14

0 4 8 10 12 14

SVMFDMS, µg.m-3

NH

4N

O3,

µg.m

-3

62

Fig. 4. Comparison of ammonium nitrate (filter-based measure-

ments) and semi-volatile material (TEOM–FDMS measure-

ments) mass concentrations obtained during the winter field

campaign.

O. Favez et al. / Atmospheric Environment 41 (2007) 7969–7976 7973

to possibly account for almost the whole wintertimeSVMFDMS content. However, a contribution ofother semi-volatile species may not be excluded too.This might be the case, for instance, of PAHs, asconcomitant variations of SVMFDMS and UVPMare observed during the winter experiment (Fig. 5).Such a clear pattern is not obtained for the summerexperiment, when UVPM is not significantly ob-

served, which might indicate that PAHs mainlyremain in the gaseous phase during this season.

As shown in Fig. 6, the minimum contribu-tion (20% on average) of ammonium nitrate toSVMFDMS is obtained for filters sampled duringsummer afternoons. High SVMFDMS mass concen-trations observed during these periods (see above)might thus be mainly (80%) attributed to SVOM.This seems to be confirmed by the daytime diurnalpattern of the OC/EC mass ratio. Indeed, as shownin Fig. 6, maximum OC/EC ratios are obtained forafternoon samplings and the daytime pattern ofOC/EC is found to match that of SVMFDMS. Theincrease of OC, relatively to EC, during summerafternoons could be related to SVOM photochemi-cal formation and condensation in the particulatephase.

Due to their climatic impacts and their possiblehealth effects, secondary organic aerosols (SOA)are now a subject of great scientific concern.Eatough et al. (2003) reported that SVOM is mainlyof secondary origin. In the following, we present anattempt to evaluate the contribution of SVOM toSOA formed during summer afternoons in Parisbetween 4 August and 11 August 2005.

SOA may be calculated in the fine mode asfollows (Turpin and Huntzicker, 1990):

OCsec: ¼ OCtot: �OC� �

� EC, (1)

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0

1

2

3

4

5

6

7

8

9

10

01/12 01/13 01/14 01/15 01/16 01/17 01/18 01/19 01/20 01/21 01/22

Local Time (mm/dd)

SV

MF

DM

S,

µg.m

-3

-100

0

100

200

300

400

500

600

UV

PM

, arb

itra

ry u

nit

SVM-FDMS

UVPM

Fig. 5. Co-variation of UV-absorbing particulate material (Aethalometer qualitative evaluation) and SVMFDMS (3-h smooth-averaged

data) from 12 to 21 January 2005.

0

1

2

3

4

5

6

04/08/2005

00:00

05/08/2005

00:00

06/08/2005

00:00

07/08/2005

00:00

08/08/2005

00:00

09/08/2005

00:00

10/08/2005

00:00

11/08/2005

00:00

NH

4N

O3 a

nd

SV

MF

DM

S, µg

.m-3

1

3

5

7

9

11

OC

/ E

C m

ass r

ati

o

NH4NO3

SVM-FDMS

OC/EC

Fig. 6. Diurnal pattern of ammonium nitrate, semi-volatile material and OC/EC ratio from 4 to 11 August 2005.

O. Favez et al. / Atmospheric Environment 41 (2007) 7969–79767974

where (OC/EC)prim. represents the OC/EC massratio characteristic of carbonaceous aerosol ofprimary origin and might be approximated by themean value of the lowest OC/EC mass ratiosobtained from filter analysis. From our dataset, aminimum OC/EC ratio of 1.8 is obtained (twomorning samples) and chosen as being equivalent to(OC/EC)prim..

Assuming these hypotheses, a mean OCsec. massconcentration of 2.870.5 mgCm�3 is obtained forsummertime afternoon filters. Based on Kondoet al. (2007), an OC-to-OM conversion factorof 2.1 is applied to each obtained OCsec. massconcentrations, and a mean SOA mass concentra-

tion of 5.971.0 mgm�3 is obtained. As mentionedabove, SVOM is found to possibly represent about80% (�3 mgm�3) on average of SVMFDMS massconcentrations (3.870.9 mgm�3) recorded duringsummer afternoons between 4 August and 11August 2005. It thus appears that SVOM mightcontribute to approximately 50% of SOA formed inParis during this period.

4. Summary

PM2.5 concentrations were simultaneously mea-sured by a conventional TEOM and a TEOM–FDMS at a background site in Paris. Results of this

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inter-comparison indicate a mean underestimation of50% in winter and of 35% in summer using theconventional TEOM (uncorrected data). It was alsoconfirmed that this negative sampling artefact maynot be accurately accommodated by a single correc-tion factor due to SVM routine fluctuations. More-over, filter-based measurements indicated that SVMhave different seasonal chemical composition andorigin. In winter, low temperature and high relativehumidity induce the condensation of ammoniumnitrate and, to a lesser extent, of organic compounds;whereas in summer, SVM mostly originates fromphotochemical processes and may be mainly formedby SVOM. Furthermore, this SVOM fraction wasfound to possibly account for more than 50% of theSOA formed during summer afternoons. Given site-to-site variations of the meteorological conditions andof the chemical nature of gaseous precursors, thisstudy calls for more investigations of the SVMchemical composition in urban aerosols.

Acknowledgements

This work was supported by the Agence Gou-vernementale de l’Environnement et de la Maıtrisede l’Energie (ADEME) under the PRIMEQUALGrant no. 0462C0056 (PUFFIN program), theCentre National de la Recherche Scientifique(CNRS) and the Commissariat a l’Energie Atomi-que (CEA). Authors want to acknowledge RolandSarda-Esteve and Laurent Martinon for their helpin the field.

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