JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 107, NO. D21, 8127, doi: /2001jd000514, 2002

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1 JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 107, NO. D21, 8127, doi: /2001jd000514, 2002 Characterization and parameterization of atmospheric particle number-, mass-, and chemical-size distributions in central Europe during LACE 98 and MINT C. Neusüß, 1 H. Wex, 2 W. Birmili, 2 A. Wiedensohler, 2 C. Koziar, 2 B. Busch, 2 E. Brüggemann, 2 T. Gnauk, 2 M. Ebert, 3 and D. S. Covert 4 Received 15 February 2001; revised 3 July 2001; accepted 14 August 2001; published 1 October [1] Intensive measurements of chemical and physical properties of the atmospheric aerosol have been performed at two sites in central Europe during the Melpitz-Intensive (MINT) in November 1997 and the Lindenberg Aerosol Characterization Experiment 1998 (LACE 98) in July and August Number-size distributions, hygroscopic particle growth, size-segregated gravimetric mass, and size-segregated chemical masses of water-soluble ions and organic and elemental carbon of aerosol particles have been measured. To obtain information on the quality of the different methods, the number-derived, gravimetric, and chemically derived mass distributions are compared. Gravimetric mass of fine particles is attributed completely to chemical composition by carbonaceous material and ions, including an estimate of the water content due to hygroscopic compounds. For the characterization of coarse particles, which contribute less to the total mass concentration, insoluble material has to be included in the mass balance. Mass concentrations calculated from the numbersize distributions are well correlated with the gravimetric mass concentration; however, the calculated mass is larger, especially for the Aitken and accumulation modes. The numberderived mass concentration is most sensitive to the sizing uncertainty of the measured number-size distribution. Moreover, the impactor cutoffs and the limited knowledge about the density of the particles (especially with high carbon content) account for a major part of the uncertainties. The overall uncertainty of the calculated mass, determined as the standard deviation of the average value in a Monte Carlo approach, is found to be about 10. Lognormal parameters for the number-size and volume-size distributions as well as gravimetric mass-size distribution and corresponding chemical composition are presented for different air mass types. Most of the modal parameters do not differ significantly between the air mass types. Higher mass concentrations are mostly due to an increase in size (of Aitken and accumulation mode) rather than an increase in the number of particles in a given mode. Generally, the mass percent carbon content increases with decreasing particle size. The most pronounced difference with season is an increase of carbon content from summer to winter as well as an increase in nitrate content, resulting in a decrease of sulfate. For nitrate a strong dependence on air mass direction is observed. Sulfate and nitrate are predominantly neutralized by ammonium. With the results of the two experiments, quality-controlled mode parameters and corresponding chemical composition of atmospheric aerosol particles in central Europe are now available for application in models. INDEX TERMS: 0305 Atmospheric Composition and Structure: Aerosols and particles (0345, 4801); 0345 Atmospheric Composition and Structure: Pollution--urban and regional (0305); 0365 Atmospheric Composition and Structure: Troposphere--composition and chemistry; 0394 Atmospheric Composition and Structure: Instruments and techniques KEYWORDS: atmospheric aerosol, size-segregated chemical composition, number-size distribution, mass closure, chemical mass balance Citation: Neusüß C., H. Wex, W. Birmili, A. Wiedensohler, C. Koziar, B. Busch, E. Brüggemann, T. Gnauk, M. Ebert, and D. S. Covert, Characterization and parameterization of atmospheric particle number-, mass-, and chemical-size distributions in central Europe during LACE 98 and MINT, J Geophys Res., 107(D21), 8127, doi: /2001jd000514, Bruker Saxonia Analytik GmbH, Leipzig, Germany. 2 Institut für Troposphärenforschung, Leipzig, Germany 3 Fachbereich Materialwissenschaften, Technische Universität Darmstadt, Darmstadt, Germany 4 Department of Atmospheric Sciences, University of Washington, Seattle, Washington, USA Copyright 2002 by the American Geophysical Union /02/2001JD Introduction [2] Aerosol characterization experiments are essential to describe the atmospheric aerosol for different polluted regions in the world as a matter of defining the state of the atmosphere and providing model input. Several international field measurements such as the First Aerosol Characterization Experiment (ACE 1) [Bates et al., 1998] and the Second Aerosol LAC 9-1

2 LAC 9-2 NEUSÜß ET AL.: AEROSOL CHARACTERIZATION IN EUROPE Characterization Experiment (ACE 2) [Raes et al., 2000] were performed to characterize the clean marine aerosol in the South Pacific, and European aerosol outflow over the North Atlantic, respectively. Emphasis was put on intensive ground and airborne measurements. For central Europe, which is one of the major source regions of anthropogenic aerosol, no comparable data were available up to now. Closure experiments are performed to assess the combined uncertainty of measurement techniques and theoretical knowledge [Quinn et al., 1996]. Mass closure experiments have been performed for marine aerosol [Quinn et al., 1995; Quinn and Coffman, 1998; Neusüß et al., 2000a]. [3] The chemical composition of the atmospheric aerosol in central Europe has been investigated with respect to ions [e.g., Mehlmann and Warneck, 1995; Mészáros et al., 1997; Mihalopoulos et al., 1997] and carbonaceous material [e.g., Brémond et al., 1989; Castro et al., 1999; Lavanchy et al., 1999] but only recently for both of these main compounds [e.g., Heintzenberg et al., 1998; Molnár et al., 1999; Müller, 1999; Zappoli et al., 1999]. However, none of these studies measured the composition from size-segregated particles. Such an approach is necessary due to the strong dependence of aerosol properties on particle size. [4] Here continental aerosols from different seasons and air masses were studied to characterize the chemical and physical properties of the aerosol over central Europe and to define the uncertainties of the measured parameters. Two intensive field measurement campaigns were performed. First, intensive ground-based aerosol measurements (MINT) were done in winter 1997 in Melpitz, Saxonia, Germany. The second campaign (LACE 98) included ground-based and airborne measurements and was performed near Berlin, Germany, in summer 1998 [Ansmann et al., 2002]. [5] In this investigation the ground-based aerosol measurements of both field campaigns were analyzed to retrieve fundamentalparametersoftheaerosolmassconcentration,numbersize distribution, and chemical composition for different air mass histories. These parameters are based on a three-way mass closure test to check the internal consistency of the independent measurements. The number-derived mass-size distributions are compared with the gravimetric mass-size distributions of cascade impactor samples. The overall uncertainty of the calculated mass concentrations is determined in a Monte Carlo approach by varying all the input parameters randomly at the same time, according to their assumed uncertainty. Furthermore, gravimetric and chemically derived mass was compared in order to check whether all of the main chemical compounds are identified. 2. Experiment 2.1. Locations [6] Measurements during LACE 98 were performed in July/August 1998 at the research station of the German Weather Service (DWD) close to Falkenberg, N, 14 8 E, about 70 km southeast of the center of Berlin, Germany. The MINT campaign took place near Melpitz, N, O, about 50 km northeast of Leipzig, Germany. Since the distance between Melpitz and Falkenberg is only about 130 km and no distinct aerosol sources are close by, the obtained parameters can be regarded as being representative for the central European aerosol. 2.2 Inlet [7] For aerosol sampling, two different inlets were used. For the number concentration, number-size distribution, and hygroscopicity measurements a low-flow (16.7 L/min) Anderson PM 10 was set up. For the impactor samples a high-flow Anderson PM 10 inlet was modified to a total flow rate of 300 L/min. The aerosol flows in the inlet pipes were kept laminar to avoid turbulent losses. The height of the inlets was 7 and 10 m above ground during the Melpitz campaign and the Lindenberg experiment, respectively, and thus clear of the laboratory containers Number-Size Distribution [8] Particle number-size distributions (diameter D nm) were measured using a high-resolution Twin Differential Mobility Particle Sizer (TDMPS) [Birmili et al., 1999]. The distribution in the size range D m was measured by an Aerodynamic Particle Sizer (APS). During the Melpitz measurements an APS model TSI 3310 was used. For the Lindenberg experiment, additionally an APS model TSI 3320 was employed. The number-size distributions of the TDMPS and APS were measured at relative humidities (RH) less than 10. The APS number-size distributions were converted from aerodynamic (D ae ) to Stokes equivalent diameters (D g, geometric in the case of spherical particles) with a density of 1.7 g/cm 3, which is found to be the best general value in calibration experiments with atmospheric aerosol (DMPS-APS in series) Hygroscopic Particle Growth and Water Mass [9] A Hygroscopic Tandem Differential Mobility Analyzer (HTDMA) was used to measure hygroscopic growth factors of particles. These factors were determined for the growth of dry particles (RH 10) to a relative humidity (RH) of 60. The growth of four to five distinct particles sizes within D g m was measured. [10] During MINT these growth factors were measured continuously with a HTDMA system described by Covert et al. [1998]. For LACE 98, growth factors at 60 were measured once or twice during each impactor sampling interval [Busch et al., 2002]. To calculate the mass of water, the following equations are applied: with m H2O m dry wet dry f 1 (1) wet 1 1 f H2O 1 f dry, (2) where m H2 O is the mass of water, m dry is the dry (chemically derived) mass, wet is the density of the wet particle, dry is the density of the dry particle, f (D wet /D dry ) 3 is the volume growth factor, and D wet/dry is the diameter of wet/dry particle Mass- and Chemical-Size Distribution [11] Two five-stage low-pressure cascade impactors [Berner et al., 1979] with 50-size cuts at 0.05, 0.14, 0.42, 1.2, 3.5, and a precut at 10 m aerodynamic diameter were used for aerosol sampling. The relative humidity (RH) in the impactor was maintained at 60 RH in order to (1) prevent sampling errors due to particle bounce, (2) sample particles of the same air mass on the same stage independent of variation in the ambient RH, and (3) facilitate comparison with hygroscopicity measurements. At the bottom of the high-volume inlet, two bundles of seven 1.5 m by 3/8 inch diameter tubes were used to

3 NEUSÜß ET AL.: AEROSOL CHARACTERIZATION IN EUROPE LAC 9-3 control the aerosol RH. The RH of the aerosol was measured at the impactor inlet and was kept constant by a softwarecontrolled slight heating or cooling of the tube bundles. [12] Tedlar (Polyvinylfluoride) and aluminum foils were used as sample substrates in the impactors for the analysis of ionic compounds and mass, and organic and elemental carbon, respectively. Prior to sampling, the Tedlar foils were cleaned with deionized water (18 M cm 1, nanopure), then with diluted H 2 O 2, and finally several times with pure water again. The aluminum foils were preheated in air to 350 C for several hours to evaporate volatile compounds. [13] The mass of the samples was determined by weighing the aluminum foils before and after exposure using a Mettler UMT 2 microbalance (Mettler Toledo, Greifensee, Switzerland). The microbalance was placed in a box with a constant RH of approximately 60. The constant RH was provided by a saturated NaBr solution and was regularly controlled. The foils were conditioned in this box for at least 12 hours before weighing. [14] The aluminum foils were analyzed for carbon by means of a commercial system (C-mat 5500 Ströhlein). Organic carbon (OC) was determined by heating the sample to 590 C under N 2, oxidation of the volatized material, and quantification of the resulting CO 2 with an NDIR detector. Subsequently, elemental carbon (EC) was determined by heating the same sample in O 2 to 650 C and similar detection. [15] To convert OC to organic matter (OM), a factor of 1.4 was used for LACE 98 data and 1.2 for MINT data. These values have been widely used [Turpin and Lim, 2001]. The lower value for MINT is due to a lower fraction of oxidized matter in this winter campaign, corresponding probably to the reduced photochemical activity [Neusüß et al., 2000c]. For a discussion of the consequences for chemical mass balance, see section 3.3. [16] Ions were determined from exposed Tedlar films by cutting these into small pieces and leaching them in deionized water. Cations were determined either by ion chromatography [Brüggemann and Rolle, 1998] or capillary electrophoresis (CE) which also was used to determine anions [Neusüß et al., 2000b]. [17] Usually, day and night samples were taken. For stable conditions during MINT some sampling times were extended to 24 hours. [18] Two additional analytical methods, electron microscopy and particle-induced X-ray emission, were used to determine a mass fraction of insoluble, crustal material in the aerosol samples. For the electron microscopy, particles with D ae m were sampled on glassy carbon disks in an impactor about 5 m above ground during LACE 98. High-Resolution Scanning Electron Microscopy (HRSEM) and energydispersive X-ray microanalysis (EDX) were applied to analyze individual particles with respect to shape as well as elemental composition and to group the particles in different classes [Ebert et al., 2002]. In the first part of MINT, filter samples were analyzed by particle-induced X-ray emission (PIXE) to determine elemental composition. 3. Internal Consistency of Mass-Size Distributions 3.1. Calculation of Number-Derived Mass Concentration [19] To convert number-size distributions to mass-size distributions for comparison to mass and chemical data from the impactor samples, a procedure based on that reported by Neusüß et al. [2000a] was applied to the data during the 51 Table 1. Densities of Dry Particles as Calculated From Chemical Composition During LACE 98 and MINT a Impactor Stage D ae, m Density (LACE 98) gcm 3 Density (MINT), gcm ( 0.32/ 0.10) 1.20 ( 0.43/ 0.14) ( 0.22/ 0.08) 1.38 ( 0.27/ 0.10) ( 0.17/ 0.06) 1.45 ( 0.21/ 0.08) ( 0.23/ 0.05) 1.58 ( 0.24/ 0.06) ( 0.26/ 0.04) 1.75 ( 0.32/ 0.03) a D ae, aerodynamic particle diameter (50 cutoffs of impactors). impactor samples, 28 from MINT and 23 from LACE 98. First, the measured low-rh number-size distributions were converted to number-size distributions at relative humidities of 60 with hygroscopic growth factors measured with the HT- DMA. From these number-size distributions the volume-size distributions were calculated, assuming spherical particles. Then the volume-size distributions were averaged over the impactor sampling intervals. Mass distributions were calculated from the volume-size distributions with hydrated particle densities for the different size ranges of the aerosol as derived from the chemical composition from the impactor samples. The composition-weighted densities of dry particles are summarized in Table 1 and are converted to wet densities with equation (2) in section 2.4. The density of carbonaceous material is not well known, therefore an estimated average of 1 g/cm 3 was applied. A lower limit of 0.8 g/cm 3 was used as an effective density of nonspherical agglomerates as determined by Smekens et al. [1999]. However, Stein et al. [1994] used 1.6 g/cm 3 which is used here as an upper estimate. For want of speciation the density of carbonaceous material is highly uncertain. Sulfate and nitrate compounds dominated the ionic mass, thus the well known density of roughly 1.7 g/cm 3 of (NH 4 ) 2 SO 4 and NH 4 NO 3 [Tang, 1996] is used. For the coarse mode the undetermined part of the chemical mass balance after accounting for water was assumed to be material with a density of 2.0 g/m 3 with an upper estimate of 2.3 g/m 3 [Stein et al., 1994; Ebert et al., 2002]. [20] The densities derived from the chemical composition were also used to convert the aerodynamic cutoff diameters of the impactors to Stokes diameters. Using these diameters, the calculated mass-size distributions were divided into the five impactor size ranges. Integration over these size ranges leads to mass distributions which are equivalent to the ones determined gravimetrically Results of Gravimetric Versus Number-Derived Mass Comparison [21] An example of a number-derived and gravimetric mass-size distribution and the corresponding chemical composition of one sample during LACE 98 is given in Figure 1a. The mass distribution derived from the measured number-size distribution, showing a maximum in the range of D ae m, generally agrees with the gravimetric mass distribution, although the latter cannot show detailed structure of the original number-size distribution. As shown in Figure 1b, the sum of the chemical components including water equals the gravimetrically determined mass within 10 for this example. Methods used for an estimate of silicates and oxides from HRSEM/EDX analysis are described and discussed below. [22] The comparison of gravimetric and number-derived

4 LAC 9-4 NEUSÜß ET AL.: AEROSOL CHARACTERIZATION IN EUROPE Figure 1. Example of (a) number-derived and gravimetric mass-size distribution and (b) chemical composition of a sample during LACE 98 at 60 RH (August 11, 1998). mass concentrations for four impactor size ranges is shown in Figures 2a 2d for the combined MINT and LACE 98 data. Mass concentrations related to impactor stage 5 (D ae m) are not considered, since the upper size range of the APS (D ae 5 m) was affected by false counts leading to an overestimate of the number concentration in that size range. The correlation was forced through the origin, which had only minor influence on the coefficient of determination, since potential axis intercepts were small. [23] The relationships between the gravimetric and number-derived mass concentration comparison for each size range for the two sites are summarized in Table 2. In spite of the difference in location and season for MINT and LACE, the comparison shows that at each size the results are quite consistent between the sites. The number-based, calculated mass concentrations generally exceed the measured mass concentrations by 20 to 70 as can be seen from the average relative differences and the slopes of the regressions. Only for the smallest stage of the MINT samples was the calculated mass less than the gravimetric mass. Since only a small fraction of the total aerosol mass was sampled on this stage, it does not contribute significantly to the total mass balance. For the total mass concentrations (D ae 3.5 m, sum stage 1 to stage 4) the average relative differences are 39 and 33 for LACE 98 and MINT, respectively. Still, the coefficients of determination of about 0.7 and 0.9 for stage 1/stage 2 and for stage 3/stage 4, respectively, show a good correlation between gravimetric and number-derived mass concentration. [24] Several factors may have contributed to the differences between measured and calculated masses. As a first step, several input parameters as sizing and the number concentration of the number-size distributions, the impactor cutoff diameters, the hygroscopic growth factors, and the density of the aerosol were varied independently within their assumed uncertainties. The estimated uncertainties given in Table 3 represent one standard deviation. The resulting deviations of the mass concentration as averages and standard deviations over the 23 LACE 98 and 28 MINT samples are given. Table 3 shows results for shifting the parameters by 1. (A negative 1 shift led to similar deviations in the opposite direction not

5 NEUSÜß ET AL.: AEROSOL CHARACTERIZATION IN EUROPE LAC 9-5 Figure 2. Comparison of number-derived and gravimetric mass concentration for LACE 98 (solid triangles) and MINT (open circles) for the four impactor stages. The error bars for the number-derived mass concentrations were taken to be 2 standard deviations as determined with the Monte-Carlo approach (see below). For the combined gravimetric and sampling error, values of 40 and 10 are used for stage 1 and stages 2 4, respectively, based on measured impactor uncertainties [Neusüß et al., 2000a]. Additionally, an uncertainty due to sampling loss of is assumed (see discussion in the text). shown in Table 3; differences smaller than 1). For the variation of the density, different values for the positive and the negative variation according to Table 1 were used. [25] The uncertainties for the TDMPS and APS measurements are considered separately. (Subsequently, these will be referred to as the submicrometer and the APS size range, respectively.) The counting uncertainties of the CPC, the UCPC, and the APS were assumed to be 10. The sizing uncertainty of the number-size distribution was taken as 5 for the submicrometer and 9 for the APS size range. Uncertainties in the data inversion based on uncertainties of the charge distribution of the particles as well as the conversion Table 2. Slope and Coefficient of Determination of Number-Derived Versus Gravimetric Mass for LACE 98 and MINT (According to Figure 2) Impactor Stage LACE 98 MINT M a Slope b R 2 M a Slope b R a M (M calculated M gravimetric )/M gravimetric. b M calculated /M gravimetric. from aerodynamic to Stokes equivalent diameters for the APS are included. [26] For the cutoff diameters of the impactors the uncertainties are assumed to be 4.5 for the cutoffs at D ae 1.2 m and larger and 18 for D ae 0.42 m and smaller, according to calibrations of an impactor of the same type but with different cutoffs [Wang and John, 1988]. [27] For the measured particle growth factor an uncertainty of 3 was used. Uncertainties in particle density were determined separately for the different impactor stages, according to the values given in Table 1. [28] The results of the calculations for submicrometer particles are mostly influenced by the uncertainty of the cutoff diameters of the impactor. However, even small assumed sizing uncertainties of DMPS and APS have a strong influence on the mass concentration. [29] Particle losses during sampling with the impactors may have occurred. Bounce-off of particles is reduced by sampling at 60 RH. A loss of 10 is observed at a comparable humidity in calibration experiments [Wang and John, 1988; Vasiliou et al., 1999]. Here particle bounce-off is less than 20 as shown by comparing the impactor-derived masses and ions with those obtained by filter sampling (see discussion in the next section and Figure 4). [30] To obtain an overall uncertainty of the calculation results caused by uncertainties of the different input parame-

6 LAC 9-6 NEUSÜß ET AL.: AEROSOL CHARACTERIZATION IN EUROPE Table 3. Influence on Mass Calculation of Shifting Different Variables to 1 (and 1 for the Density) a D g (DMPS) N (DMPS) D ae (APS) N (APS) D ae(cutoff) gf p p Uncertainty / 1.7 b 1.0 c c Stage Stage Stage Stage Stage Total (1 5) a All values are in percent. b Six percent for D ae 0.42 m and 1.7 for D ae 1.2 m. c Depending on size, according to density calculations (Table 1). Table 4. Standard Deviations s for the Calculated Masses, Derived From Monte Carlo Simulations and the Percentage of Measured Values Lying Within a Range of 2s (95 Level) Within the Gravimetric Mass Concentration (Including Above Discussed Uncertainties) Impactor Stage s LACE 98 Overlap for 2s, s MINT Overlap for 2s, Sum ters, a Monte-Carlo simulation was performed. All input parameters were varied at random assuming a normal distribution about their mean with standard deviations as given in Table 3. Wex et al. [2002] found the results of these kinds of calculations to be normally distributed and that 800 calculations were sufficient for convergence of the average mean value. Eight hundred Monte Carlo simulations with randomly varied input parameters were thus performed for the LACE 98 and MINT samples. The results are expressed in terms of time-averaged standard deviations s, given in Table 4. These standard deviations in the range of 9 to 19 for single stages for LACE 98 and MINT, respectively, represent the overall uncertainty of the calculated results. The standard deviations of the total mass concentration are 10 and 8 for LACE 98 and MINT, respectively. [31] The percentages of measured values lying within the 95 confidence range (2s) are given in Table 4. For the different stages, 39 to 96 of the measured aerosol mass concentrations (including uncertainties) are within this 95 confidence range around the calculated values. For the total mass concentration, 86 of the measured values are covered by the 95 range, respectively. However, there is a clear and systematic difference between measurements and calculations. The calculated values exceed the measurements by an amount which cannot completely be explained by the uncertainties. These deviations are particularly pronounced for the particles on stage 1 and stage 2. The differences between the stages might be explained by uncertainties which shift the diameters of the number-size distributions such as (1) sizing uncertainty, (2) the particle growth factor, (3) density due to its influence on the conversion of the impactor cutoff diameters from aerodynamic to Stokes diameters, and (4) incorrect impactor cutoffs. [32] However, the discrepancy in the total mass concentration needs to be explained. No difference in the degree of consistency between winter and summer aerosol was observed, indicating that the measurements are independent of aerosol composition or are at least influenced in the same manner. Thus particle loss in the impactor sampling due to volatile compounds, which show different behavior during different seasons, cannot account for the discrepancies. On the other hand, the density of the particles might be distinctly lower, e.g., due to pores. Furthermore, there might be a systematic error in the sizing of the submicrometer size fraction of the numbersize distributions. DMA size calibrations with latex spheres have shown that the particle diameter might be overestimated by a few percent. Furthermore, there are possible sources for the differences due to systematic errors not yet accounted for. [33] The directly measured total particle number concentrations are greater than the integral of the independently measured number-size distribution [Wex et al., 2002]. However, in a comparison between measured and calculated optical aerosol properties, no indication of an underestimate of the number-size distribution was found for particles in the accumulation mode and larger. An underestimate of the total particle number concentrations possibly stems from an underestimate of small particles (D g 0.1 m) in the measured number-size distributions, due to the uncertainty of the bipolar charge distribution. However, this would have only a minor effect on the calculated optical properties and on the calculated particle mass. [34] An important contribution to the overestimate of the mass by the number-derived method could be the nonsphericity of the particles. Even a low shape factor of 1.1 (compare, cube: 1.08, cluster of two spheres: 1.12 [Davies, 1979]) would lead to an overestimate of mass by about 15 with respect to mass calculation on the basis of spheres Chemical Mass Balance [35] Parallel filter and impactor samples and repetitive chemical analysis provide a tool for the quantitative estimate of artifacts and uncertainties. Sampling artifacts may be due to inlet losses, sampling losses, e.g., bounce-off in impactors, volatilization, or adsorption of semivolatile species. [36] The sampling reproducibility of the two impactors with gravimetric mass as an analysis criteria, including weighing uncertainties, has been shown to be within 8 13 [Neusüß et al., 2000a]. A comparison of impactor and PM 10 (Anderson sampler) high-volume quartz fiber filter results during MINT is

7 NEUSÜß ET AL.: AEROSOL CHARACTERIZATION IN EUROPE LAC 9-7 Figure 3. Gravimetric PM 10 mass concentration derived from high-volume quartz fiber filters versus impactor foils. shown in Figure 3. The intercept of 4.8 g/m 3 is probably due to adsorption of volatile compounds (e.g., organic compounds) on the quartz fibers, whereas the slope of 1.1 could be due to differences in the cutoffs or particle losses in the impactor. [37] Similar observations have been made during LACE 98. A comparison of mass and ion concentration of Nuclepore filter and impactor samples is shown in Figure 4. Impactor data are presented as the sum over all stages (PM 10 ). The mass concentration is on average approximately 20 higher on filters compared to impactor sampling. This is expected to be at least partly due to sampling of larger particles, due to imprecise cutoff of the modified Anderson inlet used for the filter sampling. Calcium and magnesium concentrations, as an indicator of large coarse mode particles, are much higher on the filter than on the impactor. Loss of large particle mass (D ae 10 m) in the impactor is confirmed by the visible particle deposits on the preimpaction plate of the impactor. Sampling of mainly fine particle species like sulfate is found to be equivalent for both sampling systems. Lower values for nitrate, chloride, and partly ammonium on the Nuclepore filters are expected to be sampling losses of these volatile species. The reason might be the segregation of different (more acidic and more basic) particle types in the impactor or the reduced ventilation of collected particles on the impactor substrates compared to the filter substrates. Such better impactor sampling efficiencies for semivolatile particles have been observed by Wang and John [1988]. [38] As an indication of a complete chemical characterization, the sum of the single species concentrations should add up to the gravimetric mass concentration. The chemical mass concentration is plotted versus gravimetric mass for LACE 98 and MINT in Figure 5. For Figures 5a 5e, chemical mass consists of ions, carbonaceous material, and water. In Figure 5f, insoluble material is included for those cases where data were available. Error bars of gravimetric mass concentrations are calculated based on the combined sampling and weighing uncertainty of 40 and 10 for impactor stage 1 (D ae m) and stages 2 5, respectively. An uncertainty of 10 is assumed for ions, based on repeated analyses of impactor samples during MINT leading to 5 10 difference for the main ions. A 50 uncertainty is used for water mass, based on the variation of the growth factor of 0.05 during the experiments and uncertainty of particle densities. For the total carbon an uncertainty of 10 is applied. Moreover, the conversion factor of organic carbon to organic matter has been assumed to be uncertain in the range between 1.2 and 1.6. The conversion factors used here (LACE 98: 1.4; MINT: 1.2) seem to be to low with respect to a recent study by Turpin and Lim, [2001]. However, low amounts of oxidized matter, especially observed for MINT [Neusüß et al., 2000b, 2000c], and the following discussion of the chemical mass balance imply these low values. [39] For fine particles a good correlation and agreement within the uncertainties between chemical and gravimetric mass concentration is found (Table 5). However, the chemical results are slightly greater than the gravimetric for the most mass relevant fine particles (Figures 5b and 5c). For coarse Figure 4. Filter-to-impactor ratio of atmospheric concentration of mass and ionic species during LACE 98.

8 LAC 9-8 NEUSÜß ET AL.: AEROSOL CHARACTERIZATION IN EUROPE Figure 5. Chemical versus gravimetric mass concentration for the single impactor stages during LACE 98 (solid triangles) and MINT (open circles). In Figure 5f, open squares symbolize the particle size D ae m, and crossed denote D ae m. particles there is a large part being neither water-soluble ions nor carbonaceous material. This undetermined fraction is expected to be insoluble. Insoluble material was obtained from HRSEM/EDX analysis of single particles for five samples during LACE 98 [Ebert et al., 2002] and by PIXE analysis for some total filter samples during MINT. For MINT the insoluble material is calculated based on a mean silicate fraction in the upper Earth crust of 32 [Warneck, 1988]. Silicate is assumed to be equally distributed in both coarse particle size classes. HRSEM/EDX analysis groups particles into different classes (D g 0.1 m, corresponding to impactor stages 2 5, D ae 0.14 m). Assuming the class of metal oxides and silicates to be the only and completely undetermined fraction of particles (with respect to ion and carbon analysis), a mass of insoluble

9 NEUSU ß ET AL.: AEROSOL CHARACTERIZATION IN EUROPE LAC 9-9 Table 5. Slope and Coefficient of Determination of Chemical Versus Gravimetric Mass for LACE 98 and MINT (According to Figure 5) LACE 98 MINT Impactor Stage Slopea R2 Slopea R a Mchemical/Mgravimetric. material can be calculated. The low vacuum used in this technique is expected to result in fractional or complete particle losses. However, sulfate, a main and relatively volatile constituent, is found to be only slightly reduced by comparing the Total Reflection X-Ray Fluorescence Analysis (performed subsequent to HRSEM/EDX) with the impactor-based IC and CE results. To convert this number-based measurement to mass fraction, the same problems and assumptions as for the above discussed number-to-mass conversion have to be considered, namely, an assumed density, sphericity, and water amount of the particles. Here the densities, size classes, and normalization to the DMPS/APS number-size distribution as described by Ebert et al. [2002] have been applied. For coarse particles the chemical mass balance including insoluble material is shown in Figure 5f. All five samples of the LACE 98 campaign and seven samples for MINT are included. The least squares regression for these cases is mchem 0.92 mgrav; R [40] Some uncertainties and corrections have not been included or applied to the analysis. For example, data on silicates and metal oxides were not included in the calculation of fine particles in Figures 5a 5c. The five samples analyzed by HRSEM/EDX lead to a mean insoluble fraction in fine particles of 10. Assuming this value to be applicable for all LACE 98 samples, fine chemical mass would be even greater leading to the conclusion that probably the water mass in the impactor samples is overestimated. The uncertainty of the water mass estimation is high with a value of about 50 (see above). Additionally, it has been found previously that single particle growth may not correspond with associated water mass on filters [McInnes et al., 1996], which might be due to crystallization. Moreover, hygroscopic growth has only been measured for particles with Dg ⱕ 0.25 m and may be different for other sizes. 4. Parameterization of Number-, Mass-, and Chemical-Size Distribution for Different Air Masses 4.1. Air Mass Categories [41] On the basis of backward trajectories obtained from the DWD, the LACE 98 and MINT samples have been divided into two categories, shown in Figure 6. Since the time resolution was only hours and precision is expected to be in the range of 20 [Stohl, 1998], the air masses can only be separated with limited accuracy. [42] During LACE 98, air masses originating in the North Atlantic (LACE_M) were dominant. Some samples were taken Figure 6. Air mass history according to backward trajectories for LACE 98 and MINT. LACE_C is not shown due to different air mass histories. when trajectories and corresponding chemical composition (sodium content in coarse particles) indicate the absence of marine influence. These periods are summarized as LACE_C, but are not shown in Figure 6 due to air masses arriving both from southwesterly and easterly directions. Air masses arriving in Melpitz during MINT were grouped according to the prevailing direction of air mass in MINT_SW and MINT_E Size Distribution Parameters [43] The particle number-size distributions obtained from the DMPS and the APS were parameterized in terms of lognormal distribution functions using a multimoment least squares fit algorithm [Birmili et al., 2001]. Multimoment implies that not only number-size distributions were fitted but also simultaneously the distributions of moments 2, 0 (number), 2 (surface), and 4. This results in a better agreement of the fitted and measured size distributions (mean difference 1) for a wide range of moments and, in particular, surface and volume. [44] Three to five particle modes were fitted to the size distributions, including the coarse mode, the accumulation mode, the Aitken mode, and up to two nucleation modes. From the number-based geometric mean diameters Dg,N and number concentrations N the corresponding volume-based parameters Dg,V and V were calculated using analytical functions. Statistics for number- and volume-based parameters were calculated separately. [45] The modal parameters (medians and quartiles) resulting from the lognormal fits of the particle number-size distributions are compiled in Table 6. Generally, several trends seem to exist between air masses of different kinds. 1. The number concentration Ng of coarse mode particles was the lowest in air of pronounced continental character (MINT_E: 0.4 cm 3), and the highest in air of pronounced marine character (LACE_M: 3.7 cm 3). The modal volume Vg did not, however, follow this trend due to an inverse trend in coarse mode diameters (MINT_E: Dg,N 1.2 m; LACE_M: Dg,N 0.65 m). The lowest coarse mode number concentration was coupled with the highest coarse mode volume concentration in MINT_E, as a result of the large modal diameter combined with a relatively large standard deviation ( g

10 LAC 9-10 NEUSÜß ET AL.: AEROSOL CHARACTERIZATION IN EUROPE Table 6. Mode Parameters for the Different Air Masses Air Mass Mode N g,cm 3 D g,n,nm V g, m 3 cm 3 D g,v,nm g LACE_M nucleation 300 ( ) 8.3 ( ) (7 13) 1.24 ( ) aged nucleation 1170 ( ) 16.7 ( ) 0.02 ( ) 27 (14 42) 1.45 ( ) Aitken 3230 ( ) 50.3 ( ) 0.5 ( ) 100 (73 140) 1.57 ( ) accumulation 570 ( ) 180 ( ) 3.6 ( ) 300 ( ) 1.50 ( ) coarse 3.7 ( ) 650 ( ) 2.7 ( ) 1840 ( ) 1.79 ( ) LACE_C nucleation 210 (90 520) 10.3 ( ) (9 15) 1.26 ( ) aged nucleation 1280 ( ) 24.0 ( ) 0.02 ( ) 38 (28 57) 1.49 ( ) Aitken 1800 ( ) 61.9 ( ) 2.0 ( ) 230 ( ) 1.73 ( ) accumulation 470 ( ) 240 ( ) 7.3 ( ) 370 ( ) 1.48 ( ) coarse 1.8 ( ) 700 ( ) 2.0 ( ) 2480 ( ) 1.90 ( ) MINT_SW nucleation 300 ( ) 6.5 ( ) (5 12) 1.30 ( ) aged nucleation 1680 ( ) 19.3 ( ) 0.02 ( ) 43 (30 59) 1.67 ( ) Aitken 2410 ( ) 73.2 ( ) 2.2 ( ) 210 ( ) 1.79 ( ) accumulation 500 ( ) 230 ( ) 9.5 ( ) 450 ( ) 1.55 ( ) coarse 0.6 ( ) 1390 ( ) 1.9 ( ) 2860 ( ) 1.70 ( ) MINT_E nucleation 150 (71 360) 6.6 ( ) (6 11) 1.27 ( ) aged nucleation 790 ( ) 17.0 ( ) 0.01 ( ) 34 (21 49) 1.59 ( ) Aitken 2520 ( ) 77.5 ( ) 3.8 ( ) 320 ( ) 1.94 ( ) accumulation 440 ( ) 290 ( ) 15.7 ( ) 460 ( ) 1.50 ( ) coarse 0.4 ( ) 1200 ( ) 3.5 ( ) 4530 ( ) 1.87 ( ) 1.87). Higher coarse mode number concentration, especially during LACE_M, is ascribed to sea spray particles resulting from short travel time of the air parcel from the sea, which is supported by the Na concentrations (compare Table 7). Regarding the modal number concentration, small variations were found between different periods in accumulation mode number concentration ( cm 3 ), and similarly, in Aitken mode number concentration, although in the latter some discrepancies exist between LACE_M (3200 cm 3 ) and LACE_C (1800 cm 3 ). 2. The modal mean diameters D g,n (and also D g,v )ofthe coarse, accumulation, and Aitken mode were smaller in air being pronounced marine-influenced (LACE_M: 650, 180, and 50 nm, respectively) than in air being more continental (MINT_E: 1200, 290, and 78 nm, respectively). The accumulation mode diameters during MINT_E were unusually high corresponding to the upper 15 of 17-month statistics at Melpitz [Birmili et al., 2001]. From the above, we see indications for the following: (1) Sources in the easterly continental region emit primary accumulation and Aitken particles at significantly larger particle sizes, or (2) under easterly flow the aerosol had more time to age, i.e., to undergo clear air and cloud processing, thereby increasing in mean size, and decreasing in number concentration. (3) Furthermore, wet deposition is expected to be a less important particle sink in the dryer continental air masses. 3. The modal parameters obtained for the nucleation and aged nucleation modes were not significantly different in view of the large overall variability of these modes, and also the limited observation periods. The variability can be seen as indicative of the presence of localized particle sources. Table 7. Mass Concentration and Chemical Composition for the Different Air Masses Air Mass Stage D ae, m Mass, g m 3 OC EC TCM a NH 4, Na, K, Ca 2, Mg 2, Cl, NO 3, SO 4 2, H 2 O, Sum LACE_M LACE_C MINT_SW b c MINT_E a TCM EC OM (OM k OC; k MINT 1.2; k LACE ). b Including 11 insoluble material. c Including 49 insoluble material.

11 NEUSÜß ET AL.: AEROSOL CHARACTERIZATION IN EUROPE LAC Chemical Composition [46] For MINT, only samples of the air mass categories shown were analyzed for chemical composition and hence taken into account in the following summary. During LACE 98 all samples were analyzed, but only those which fit clearly into either air mass class were considered. The size-resolved particle mass concentration and chemical composition of the main compounds for the different air masses are shown in Table 7. [47] The mass concentration was much higher during MINT compared to LACE 98 (mean: factor 2.5). Reasons could be higher source strength in the winter (heating, and higher energy consumption), lower mixing heights and ventilation, or lower temperatures (MINT: 4 C, LACE 98: 19 C), resulting in lower gas-to-particle ratios of semivolatile compounds (e.g., ammonium nitrate and organics). Meteorological parameters are expected to be dominant. In summer compared to winter, stronger convection and an increased boundary layer height were observed. In addition, during LACE 98 higher wind speeds transporting cleaner air masses from the northern Atlantic were observed. [48] In an attempt to compensate for such phenomena the chemical composition is expressed as a percent of the gravimetric mass concentration in Table 7. This relative chemical composition is much less variable with respect to different air masses than atmospheric concentrations of single compounds. [49] Coarse mode particles contain carbonaceous, mostly organic, material. The contribution of ionic species is low, except for the marine case during LACE 98. A fraction of the particles sampled in the size range D ae m during MINT_E are expected to be grown accumulation mode particles (compare Table 4). [50] Carbonaceous mass fraction increases toward smaller particle size, especially for elemental carbon. Organic carbon content increases toward the smallest particles only for the MINT samples. Besides water and insoluble material, the rest of the accumulation mode mass consists mainly of ions as sulfate, ammonium, and nitrate. Corresponding to the increase of carbon, a relative decrease of these ions with decreasing particle size is found. This is due to the age of particles. Freshly emitted combustion particles show a mass maximum in the range of D ae 0.1 m (e.g., emitted from cars [Kerminen et al., 1997; Venkataraman et al., 1994]) and contain mostly carbonaceous material. By comparison, accumulation mode particles, making up the main part of stage 3 (D ae m), are expected to be more highly aged and (cloud) processed and contain larger percentages of sulfates and nitrates. [51] When sea salt (sodium) is found in the coarse mode, nitrate shows up predominantly in that mode (LACE_M). The nitrate content (and the nitrate-to-sulfate ratio) is much higher for air masses arriving from western Europe compared to air masses from eastern Europe. Different source strengths for the precursors SO 2 (coal burning) and NO x (traffic) in different parts of Europe are probably the reason. The ion balances (expressed as the division of the difference between cations and anions by their mean) for LACE 98 were ; ; ; ; for stage 1 to stage 5, respectively. The same tendency is observed for MINT, with slightly positive values for the smallest (stage 1) and largest particles (stages 4 and 5) and values around zero or slightly negative values for the mainly sulfate-containing particles of stages 2 and 3. This corresponds to measured ph values of the dissolved aerosol particles during LACE 98 (not measured during MINT), giving always slightly lower values for stages 2 and 3 than for the other stages, however, never below ph 4, thus without significant influence on the ion balance. It can be concluded that sulfate and nitrate is neutralized mainly by ammonia within the measurement uncertainty (10). This is in agreement with an actual ph range of in rain water in Germany [Marquardt et al., 2001]. [52] The chemical composition of a certain impactor stage (Table 7) can be attributed to the different observed modes in Table 6. Coarse mode particles are sampled primarily on stages 4 and 5, with sea-salt particles predominantly on stage 4 and crustal material to a higher degree on stage 5. Only in the case of MINT_E does the grown aged accumulation mode extend into stage 4. The chemical composition of stage 3 alone can be used to characterize the accumulation mode. Stage 2 contains both particles from the Aitken and the accumulation mode. Depending on the actual size distribution, either mode might dominate stage 2, whereas stage 1 corresponds largely to the Aitken mode, since the volume contribution of the aged nucleation mode is around 2 orders of magnitude lower. In summary, the chemical composition of the Aitken mode and accumulation mode (Table 6) is given in Table 7 by stages 1 and 3, respectively. 5. Conclusions [53] Comparing the number-derived and gravimetric mass concentration, a combination of the incomplete knowledge of both physical properties (density, shape) and some measurement uncertainties (impactor losses and cut diameters, and DMA size accuracy) causes the observed differences in mass concentration. Further examination and improvement of these state-of-the-art methods is needed to increase the accuracy of parameters for modeling of aerosols. Nevertheless, the variation with time is at least 1 order of magnitude higher than the uncertainties. This, and the fact that a good correlation is found for number-derived and gravimetric mass concentration, independent of air mass, lends confidence in the derived parameters. The sum of carbonaceous material, ions, and water results in the gravimetric mass for submicrometer particles within the uncertainties. A contribution of about 10 of insoluble particles in this size range as indicated in the samples analyzed by SEM, however, indicates that an overestimate of the water amount was made for the impactor samples. For coarse particles the determination of insoluble material is needed. Both PIXE analysis and the conversion of numberbased measurements by SEM complement the chemical analyses. [54] Gravimetric mass-size distribution, corresponding chemical composition, and lognormal parameters of the number- and volume-size distributions were determined for different air masses. Several of the mode parameters, especially for nucleation and aged-nucleation mode particles, do not differ significantly. Particles of marine and continental air masses differ mainly in coarse mode number and diameter. Higher mass in the Aitken and accumulation mode is mostly due to an increase in size rather than in number of particles. Generally, the carbon content increases with decreasing particle diameter (ratio Aitken to accumulation mode equal to 2:1). The most pronounced difference with season is an increase of carbon from summer to winter as well as an increase in nitrate content, both resulting in a decrease of sulfate content. For nitrate a strong dependence