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A European aerosol phenomenology--1: physical characteristics of particulate matter at kerbside, urban, rural and background sites in Europe

A European aerosol phenomenology--1: physical characteristics of particulate matter at kerbside, urban, rural and background sites in Europe
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  See discussions, stats, and author profiles for this publication at: A European aerosol phenomenology - 1:Physical characteristics of particulatematter at k erbside, urban, rural and...  Article   in  Atmospheric Environment · May 2004 DOI: 10.1016/j.atmosenv.2004.01.040 CITATIONS 483 READS 139 27 authors , including: Some of the authors of this publication are also working on these related projects: ASAP-Delhi: An Integrated Study of Air Pollutant Sources in the Delhi NCR   View projectNERC ClearfLo - Clean air for London   View projectMaria Cristina FacchiniItalian National Research Council 240   PUBLICATIONS   14,441   CITATIONS   SEE PROFILE Roy M HarrisonUniversity of Birmingham 795   PUBLICATIONS   26,532   CITATIONS   SEE PROFILE Sergio RodriguezAgencia Estatal de Meteorología 118   PUBLICATIONS   5,649   CITATIONS   SEE PROFILE Harry ten BrinkEnergy Research Centre of the Netherl… 328   PUBLICATIONS   5,819   CITATIONS   SEE PROFILE   All content following this page was uploaded by Alfred Wiedensohler on 11 January 2017. The user has requested enhancement of the downloaded file. All in-text references underlined in blue are added to the srcinal documentand are linked to publications on ResearchGate, letting you access and read them immediately.  Atmospheric Environment 38 (2004) 2561–2577 A European aerosol phenomenology—1:physical characteristics of particulate matter at kerbside,urban, rural and background sites in Europe Rita Van Dingenen a, *, Frank Raes a , Jean-P. Putaud a , Urs Baltensperger b ,Aur ! elie Charron c , M.-Cristina Facchini d , Stefano Decesari d , Sandro Fuzzi d ,Robert Gehrig e , Hans-C. Hansson f  , Roy M. Harrison c , Cristoph H . uglin e , AlanM. Jones c , Paolo Laj g , Gundi Lorbeer h , Willy Maenhaut i , Finn Palmgren  j ,Xavier Querol k , Sergio Rodriguez k , J . urgen Schneider h , Harry ten Brink l ,Peter Tunved f  , Kjetil T ^ rseth m , Birgit Wehner n , Ernest Weingartner b ,Alfred Wiedensohler n , Peter W ( ahlin  j a Institute for Environment and Sustainability, Joint Research Centre, European Commission, T.P. 290, Ispra (VA) 21020, Italy b Laboratory of Atmospheric Chemistry, Paul Scherrer Institut, 5232 Villigen PSI, Switzerland  c University of Birmingham, Division of Environmental Health and Risk Management, Edgbaston, Birmingham B15 2TT, UK  d Istituto di Scienze dell’Atmosfera e dell’Oceano, Consiglio Nazionale delle Ricerche, Via P. Gobetti, 101 Bologna 40129, Italy e Swiss Federal Laboratories for Materials Testing and Research, D . ubendorf 8600, Switzerland  f  Institute of Applied Environmental Research (ITM), Stockholm University, Stockholm 106 91, Sweden g Laboratoire de M  ! et ! eorologie Physique, Universit ! e Blaise Pascal, 5 rue Kessler, Clermont-Ferrand Cedex 63038, France h Umweltbundesamt GmbH, Spittelauer L . ande 5, Wien 1090, Austria i Ghent University, Institute for Nuclear Sciences, Department of Analytical Chemistry, Proeftuinstraat 86, Gent 9000, Belgium  j National Environmental Research Institute, Postboks 358, Frederiksborgvej 399, Roskilde 4000, Denmark  k Instituto de Ciencias de la Tierra, Consejo Superior de Investigaciones Cient !  ıficas (CSIC), Sol  ! e i Sabar !  ıs, s/n. Barcelona 08028, Spain l Energy Research Centre of the Netherlands (ECN), P.O. Box 1, Petten 1755 ZG, The Netherlands m Norwegian Institute for Air Research (NILU), P.O. Box 100, Kjeller 2027, Norway n Institut f  . ur Troposph . arenforschung, Permoserstr. 15, Leipzig 04318, Germany Received 16 June 2003; received in revised form 20 December 2003; accepted 19 January 2004 Abstract This paper synthesizes data on aerosol (particulate matter, PM) physical characteristics, which were obtained inEuropean aerosol research activities at free-troposphere, natural, rural, near-city, urban, and kerbside sites over thepast decade. It covers only two sites in the semi-arid Mediterranean area, and lacks data from Eastern Europe. The datainclude PM10 and/or PM2.5 mass concentrations, and aerosol particle size distributions. Such data sets are morecomprehensive than those currently provided by air quality monitoring networks (e.g. EMEP, EUROAIRNET). Dataavailable from 31 sites in Europe (called ‘‘The Network’’) were reviewed. They were processed and plotted to allowcomparisons in spite of differences in the sampling and analytical techniques used in various studies. A number of conclusions are drawn as follows:Background annual average PM10 and PM2.5 mass concentrations for continental Europe are 7.0 7 4.1 and4.8 7 2.4 m gm  3 , respectively. ARTICLE IN PRESS AE International – Europe *Corresponding author. Tel.: +39-0332-78-9300; fax: +39-0332-78-5837. E-mail address: (R. Van Dingenen).1352-2310/$-see front matter r 2004 Elsevier Ltd. All rights reserved.doi:10.1016/j.atmosenv.2004.01.040  The EU 2005 annual average PM10 standard of 40 m gm  3 is exceeded at a few sites in The Network. At all near city,urban and kerbside sites, the EU 2010 annual average PM10 standard of 20 m gm  3 , as well as the US-EPA annualaverage PM2.5 standard of 15 m gm  3 are exceeded. In certain regions, PM10 and PM2.5 in cities are strongly affectedby the regional aerosol background.There is no ‘‘universal’’ (i.e. valid for all sites) ratio between PM2.5 and PM10 mass concentrations, although fairlyconstant ratios do exist at individual sites. There is no universal correlation between PM mass concentration on the onehand, and total particle number concentration on the other hand, although a ‘baseline’ ratio between number and massis found for sites not affected by local emissions. This paper is the first part of two companion papers of which thesecond part describes chemical characteristics. r 2004 Elsevier Ltd. All rights reserved. Keywords:  Aerosol; Chemical composition; PM10; PM2.5; Compilation 1. Introduction Today, the interest in aerosols is high mainly becauseof their effect on human health and their role in climatechange. They have also a determining effect on visibilityand contribute to the soiling of monuments. Comparedto trace gases, aerosols are relatively complex tocharacterize because of their multi-component chemicalcomposition, and because of the large range in particlesize, ranging from nanometers to several micrometers.Furthermore, aerosol sampling is still a challenge due tothe fact that a significant fraction of the mass is semi-volatile and can transfer between the gas and aerosolphase as a function of temperature, relative humidity,aerosol acidity, sampling and handling procedures,etc. (e.g. ammonium nitrate, semi-volatile organiccompounds). Data on comprehensive physical– chemical aerosol characterization are needed for severalreasons. 1.1. Aerosols and health Epidemiological studies show that an increase inPM10 mass concentration by 10 m gm  3 results in anincrease of 0.5–1.5% in premature total mortality in caseof short term/episodic exposure, and in an increase up to5% in premature total mortality in case of long-term/life-long exposure (Wilson and Spengler, 1996). As yet,there is no indication which physical or chemical PMcharacteristic is responsible for these effects. However,recent research seems to indicate that PM10 is associatedwith respiratory responses and PM2.5 with cardio-vascular diseases (Wyzga, 2002). Legislation in the EUand US is therefore expressed in terms of target valuesfor PM10 and PM2.5 (= the mass of particles with adiameter below 10 or 2.5 m m, respectively). Because of the undifferentiated nature of the metric ‘‘PM mass’’and the many sources contributing to it, implementingsuch legislation might be unnecessarily costly. Ideally,health effects of aerosol particles should be related to awell-defined set of physical or chemical aerosol char-acteristics, which can be related to a well-defined set of sources. Major research programmes are devoted tounderstand the effects of aerosols on health and to theapportionment of their sources. 1.2. Aerosols and climate Observations and model calculations show that theincrease in the atmospheric aerosol burden is delayingthe global warming expected from the increase ingreenhouse gasses (GHG: CO 2 , CH 4 , N 2 O, halocar-bons). Whereas the increase in GHGs since pre-industrial times is producing a warming of 2.4Wm  2 ,the overall cooling effect of aerosols might be up to  2.5Wm  2 (IPCC, 2001). The latter value is composedof contributions by e.g. sulphate and organic particles,which have a cooling effect, and black carbon, which hasa heating effect. International and EU climate changepolicies aim at reducing the emissions of GHGs byimplementing the Kyoto Protocol. It is expected thatnegotiations of reductions beyond the Kyoto Protocolmight consider also the role of aerosols (Hansen et al.,2000). The effect of policies on climate to reduce adverseeffects of aerosols on health (see above) also needs to beaddressed. As with the health issue, knowledge aboutphysical and chemical aerosol characteristics and theirrelationship with sources is important to develop cost-effective mitigation policies. 1.3. Aerosol modelling Numerical models describing aerosol particle emis-sions and production, transport, transformation andremoval have become accepted tools to extrapolatemonitoring data (Council Directive 96/62/EC of 27September 1996 on ambient air quality). They are usedin source apportionment studies and, obviously, they arethe only tools to assess the effects of future changes inaerosol and aerosol precursor emissions. The calculationof PM10 levels or radiative forcing must necessarily bebased on a description of the emissions of the individual ARTICLE IN PRESS R. Van Dingenen et al. / Atmospheric Environment 38 (2004) 2561–2577  2562  chemical species and how they transform and mixin the atmosphere. Models with this capability arebecoming available (Hass et al., 2002) but need testingand validation against fundamental data such asthe aerosol particle size distribution and chemicalcomposition. 2. Compilation of European data  2.1. The network  The present aerosol ‘‘phenomenology’’ synthesizesphysical data that have been collected during the last 10years. In this paper we present and discuss simulta-neously measured PM10 and PM2.5 mass, and (sub-micrometer) number size distributions, from whichintegrated properties such as number concentration,(fine fraction) aerosol volume and surface area can becalculated. Such data are presently not measured inregulatory monitoring networks (such as EMEP andEUROAIRNET), but rather in research projects. Herewe consider only projects providing data representativefor a site during at least a season (i.e. minimum 6 weeksof continuous measurements). Sites and instrumentationare listed in Appendix A.Fig. 1 shows the location of the 31 sites, operatedby 12 institutes. We will refer to these sites as ‘‘TheNetwork’’. We have categorized the sampling sites usingcriteria proposed by the European Environment Agency(Larssen et al., 1999). Among those criteria are the distance of the station from large pollution sources suchas cities, power plants and major motorways, and thetraffic volume. * Natural background—distance from large pollutionsources >50km * Rural background—distance from large pollutionsources 10–50km * Near-City background—distance from large pollu-tion sources 3–10km * Urban background—  o 2500 vehicles/day within aradius of 50mTo which we have added the * Free troposphere—above the mixed boundary layer * Kerbside—within street canyonsIn the text we will also refer to * Clean sites—free troposphere, natural and ruralbackground sites, ARTICLE IN PRESS Free TroposphereNatural backgroundRural backgroundNear-cityUrban backgroundKerbsideFalkenbergBirkenesCopenhagenBolognaPuy de DômeMte FoiaSagresLeipzigMelpitzJungfraujochBaselZürichChaumontBernIspraMilanoAspvretenSevettijarviWienIllmitzSkreådalenHarwell London WaasmunsterGentMarseilleBarcelonaMonagregaHohenpeissenbergFull year data set Seasonal data set Fig. 1. Location of the sampling sites. R. Van Dingenen et al. / Atmospheric Environment 38 (2004) 2561–2577   2563  * Polluted sites—near-city, urban background andkerbside sites  2.2. Data consistency and representativeness 2.2.1. Systematic sampling and analysis errors The data set was obtained from a number of measurement and monitoring campaigns, geographi-cally and chronologically scattered, by different researchgroups, using different techniques, in particular con-cerning PM2.5 and PM10 mass determination. Compar-ing data from such a compilation requires thatsystematic errors and temporal variations that occurredover this period are carefully evaluated and consideredin the interpretation.Possible systematic errors in PM mass determination,resulting from the use of different samplers, samplingheads, substrates, gravimetric analysis and positive ornegative sampling artefacts for the various chemicalcompounds in particulate matter, are discussed in thecompanion paper by Putaud et al. (2004). The major source of uncertainty in the mass determinationoriginates from positive and negative artefacts in thecapturing of ammonium nitrate and semi-volatileorganic compounds on filters or other substrates. Themagnitude of these artefacts depends strongly on theactual chemical composition of the aerosols, as well ason meteorological conditions.Also the presence of particle-bound water during off-line gravimetric mass determination at 50% humiditycan cause a positive artefact. This may be an importantsource of inconsistency between the PM mass concen-trations determined according to the EN12341 normand TEOMs. TEOMs indeed dry the sampled air streamto limit the quantity of water associated with aerosolparticles. Routine TEOMs do this by heating the inlet at50  C, whereas TEOMs equipped with a sample equili-bration system (SES) achieve RH o 30% by samplingthrough dryers and heating at 30  C only.Several studies, covering a range of ambient condi-tions have demonstrated that, because of these com-bined problems, routine TEOMs underestimate PM10measurements by up to 35%, when compared with theEN12341 reference method (Airborne Particles expertgroup, 1997; Allen and Reiss, 1997). This underestima- tion is more severe in winter than in summer, because insummer the ambient and instrument temperatures aremore comparable. On an annual basis, and for thedifferent conditions for this work, we estimate that a35% difference between gravimetric PM10 measure-ments carried out at 50% RH and on-line measurementsusing TEOMs seems therefore to be an upper limit,which we also extend to PM2.5, and the PM mass datapresented here are comparable within 35%.Particle size distributions were measured using differ-ential mobility analysers (DMA) connected to a particlecounter (CPC). Some systems worked in scanning mode(SMPS) and others in step modes (DMPS). Standarddeviations among 11 SMPS and DMPS instrumentswere shown to be  o 22% and  o 10% for sizing andcounting, respectively (Dahmann et al., 2001).The size measured by the DMA is affected by the RHat which the DMA is operating, and should therefore bespecified. Most size distributions were obtained atRH o 20% (see Appendix A) and therefore comparable.Size distribution measurements at the sites Harwell,Bloomsbury and Marylebone were obtained at unspeci-fied ambient relative humidity. Assuming a particlegrowth factor of the ‘‘more hygroscopic particles’’between 1.2 and 1.5 at 90% RH (see e.g. Baltenspergeret al., 2002), and an ambient RH between 50%and 75%, this may lead to an increase of the averageparticle size with 5–28% and integrated aerosol volumeincrease of 16–110% compared to the dry size andvolume.The particle concentration is obtained by integrat-ing the number size distribution. As the range of particlediameters measured by various groups is dif-ferent (Appendix A), we considered the number of particles with  D p >10nm when comparing numberconcentrations between sites. Number concentrationsobtained in this way are expected to be comparablewithin 10%.  2.2.2. Temporal representativeness Most of the PM data are obtained in the period 1998– 2000, and span from 1 to 3 years (except for the shortcampaign datasets which are not considered in theannual averages). We have, however, also included olderPM data from Scandinavian natural stations, as well asfor two Belgian near-city and urban sites (all obtainedbefore 1996).When comparing PM characteristics of the sites with‘‘old’’ data to sites with recent data, one must consider apossible bias in the former, mainly due to a generallyEuropean-wide downward trend in SO 2  emissionsduring the last decade, which is being reflected in adownward trend in particulate sulphate (see Fig. 2a inPutaud et al., 2004). However, this trend is not asobvious to detect in the particulate  mass  measurements.For the Scandinavian background stations, EMEP dataarchives have been consulted. The EMEP network hasrecently started the conversion (in the period 1999–2001)from TSP to PM10 sampling as required by Europeannorm EN12341. Therefore, no contiguous samplingperiod with a single technique exists from which thetrend in the period 1995–2001 can be evaluated from thisdata set. Still, 2000–2001 PM10 data for the EMEP siteBirkenes (T ^ rseth et al., 2003, Eurotrac AEROSOL finalreport) can be compared with the PM10 data for thatsite (this work) collected by the Ghent University in theperiod 1991–1996. The average PM10 concentration at ARTICLE IN PRESS R. Van Dingenen et al. / Atmospheric Environment 38 (2004) 2561–2577  2564
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