Charging state of atmospheric nanoparticles during the nucleation burst events

Atmospheric Research 82 (2006) 536 – 546 www.elsevier.com/locate/atmos

Research Article

Charging state of atmospheric nanoparticles during the nucleation burst events M. Vana a,b,⁎, E. Tamm a , U. Hõrrak a,b , A. Mirme a , H. Tammet a , L. Laakso b , P.P. Aalto b , M. Kulmala b a b

Institute of Environmental Physics, University of Tartu, Ülikooli 18, 50090 Tartu, Estonia Department of Physical Sciences, P.O. Box 64, FIN-00014 University of Helsinki, Finland Accepted 1 February 2006

Abstract In this work, the charging state of atmospheric nanoparticles was estimated through simultaneous measurements of aerosol size distribution and air ions mobility distribution with the aim to elucidate the formation mechanisms of atmospheric aerosols. The measurements were performed as a part of the QUEST 2 campaign at a boreal forest station in Finland. The overlapping part of the measurement ranges of the particle size spectrometers and air ion mobility spectrometers in the mass diameter interval of 2.6– 40 nm was used to assess the percentage of charged particles (charging probability). This parameter was obtained as the slope of the linear regression line on the scatterplot of the measured concentrations of total (neutral + charged) and charged particles for the same diameter interval. Charging probabilities as a function of particle diameter were calculated for different days and were compared with the steady state charging probabilities of the particles in the bipolar ion atmosphere. For the smallest particles detectable by the particle size spectrometers (2.6–5 nm), the high percentages of negatively charged particles were found during the nanometer particle concentration bursts. These values considerably exceeded the values for the steady charging state and it was concluded that negative cluster ions preferably act as condensation nuclei. This effect was found to be the highest in the case of comparatively weak nucleation bursts of nanoparticles, when the rate of the homogeneous nucleation and the concentration of freshly nucleated particles were low. The nucleation burst days were classified according to the concentration of the generated smallest detectable new particles (weak and strong bursts). Approximately the same classification was obtained based on the charge asymmetry on particles with respect to the charge sign (polarity). The probabilities of negative and positive charge on the particles with the diameter of 5–20 nm were found to be nearly equal and they approximately agree with the values corresponding to the steady state charge distribution for negative particles known from lab experiments. It means that the steady charging state was reached during the growing time of particles up to 5 nm. The natural charging state of particles with a diameter between 2.5 and 4.5 nm was estimated by means of a special DMPS setup. Results were found to be in good correlation with the data by the particle size spectrometers and air ion mobility spectrometers. © 2006 Elsevier B.V. All rights reserved. Keywords: Atmospheric ultrafine particles; Air ions; Charging probability; New particle formation; Nucleation

1. Introduction ⁎ Corresponding author. Institute of Environmental Physics, University of Tartu, Ülikooli 18, 50090 Tartu, Estonia. 0169-8095/$ - see front matter © 2006 Elsevier B.V. All rights reserved. doi:10.1016/j.atmosres.2006.02.010

Most of the atmospheric nanoparticles (particles with the diameter dp ≤ 20 nm) are the product of various gas-

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to-particle transformation processes: homogeneous and heterogeneous nucleation of the gaseous ingredients and the growth of the newborn nuclei by condensation, coagulation and/or chemical reactions on their surface. Burst-type events of nanoparticle formation have been observed at different places over the world: at coastal sites (O'Dowd et al., 1999, 2002), in European boreal forests (Mäkelä et al., 1997; Kulmala et al., 2001), in the marine boundary layer (Covert et al., 1996), in the Arctic (Wiedensohler et al., 1996), etc. Kulmala et al. (2004a) reviewed more than 100 publications that report observations of ultrafine particles in the atmosphere. Most of them are dealing with burst-type particle formation events. Probably, the above-mentioned transformation processes are permanently going on with some quite a low rate, but the experimental detection of them is very complicated and has not been realized yet. Some possible nucleation mechanisms are known. Homogeneous nucleation of only one substance requires very high supersaturations, which are not detected in the atmosphere. Therefore, binary nucleation of H2O and SO2, or ternary nucleation of H2O, SO2 and NH3 are thought to be the most probable homogeneous nucleation mechanisms in the atmosphere (Kulmala et al., 2000, Kulmala, 2003; Korhonen et al., 1999). Some experimental results support the theory of these processes (Kulmala et al., 2004a), although the agreement between experiment and theory is only qualitative. Ion-induced nucleation has also been considered as a possible particle formation mechanism (Yu and Turco, 2001; Lovejoy et al., 2004; Kazil and Lovejoy, 2004), since charged clusters are thought to experience an enhanced growth rate and stability as a consequence of electrostatic interactions (Laakso et al., 2003; Nadykto and Yu, 2003). This process can be considered as a heterogeneous nucleation on cluster ions as condensation centers; a well-known example of this phenomenon exists in case of Wilson chamber. Some attempts have been made to use observational data for discussing the occurrence of ion-induced nucleation in the atmosphere (Hõrrak et al., 1998a,b, 2003; Tamm et al., 2001; Mäkelä et al., 2003; Laakso et al., 2004a). However, the problem has not been solved yet, mainly because of the lack of suitable apparatus, and it needs further investigation. The idea of the experimental–observational investigation of the ion-induced nucleation phenomenon in the atmosphere is as follows. If we can measure the number concentration of the smallest (freshly nucleated) nanoparticles in some narrow diameter interval, and at the same time, the number concentration of the charged fraction of particles for the same diameter interval, we can calculate the percentage of charged particles

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(charging probability) for this interval. Charging probability as a function of particle diameter for the steady charging state in case of a bipolar ion atmosphere is known from literature (e.g. Reischl et al., 1996). If a substantial amount of nanoparticles is generated by ioninduced nucleation, then the smallest particles have to be overcharged, comparing with the steady state. In this work we applied the air ion mobility spectrometers (Tammet, 2004; Mirme, 2004), capable of measuring the mobility (size) distribution of charged particles even for the smallest thermodynamically stable particles with the diameter of the order 1–1.6 nm (Kulmala et al., 2000; Hõrrak et al., 1998c, 2000). But the lower limit of the diameter measurement range of the particle size spectrometers is approximately 3 nm, so we can experimentally determine the charging probability for the particles with a diameter over 3 nm. Abovedescribed idea about the verification of nucleation mechanism is realizable when the particle growth time up to 3 nm is smaller than the relaxation time for the steady state charge distribution. It can occur during nucleation burst events, when rapid growth of the nanoparticles takes place. The aim of this study is to determine experimentally the charging probabilities for atmospheric aerosol particles as a function of particle size in the nucleation mode size range, to elucidate the formation mechanisms of atmospheric aerosols from the measurements of aerosol size distribution and air ion mobility distribution and to estimate the charging state of atmospheric aerosol particles during the nucleation burst situations. The particular attention is paid to the examination of conditions, including the deviation of the particle charge distribution from the steady state one. 2. Instrumentation In Fig. 1 air ion and aerosol particle measurements are schematically illustrated. As aerosol particle spectrometers have the cutoff diameter of about 3 nm, neutral clusters and aerosol particles below 3 nm cannot be measured by means of state-of-the-art technology. However, the charged clusters and aerosol particles with a diameter between 0.5 and 3 nm can be measured by air ion spectrometers. In present work the number size distribution (number size spectrum) of atmospheric aerosol particles was measured simultaneously by two electrical spectrometers – the Differential Mobility Particle Sizer (DMPS) and the Electrical Aerosol Spectrometer (EAS). The DMPS system is a well-known instrument, containing two Hauke-type differential mobility analyzers (DMA) of

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Fig. 1. Schematic picture representing air ion and aerosol particle measurements.

different length (10.9 cm and 28 cm), a closed loop sheath flow arrangement and two different CPCs (TSI models 3025 and 3010) (Aalto et al., 2001). The measurement range of this device, according to particle diameter is from 2.5 nm to 500 nm; it was calibrated, as described in Aalto et al. (2001). The DMPS is a stepwise scanning instrument, measuring the spectrum fractions sequentially in time. The EAS is a multichannel instrument, designed at the University of Tartu, Estonia (Tammet et al., 2002). The EAS has 32 measuring channels, each of which is provided with an electrometer for the detection of the particles precipitated on the isolated sections of the two DMAs. The EAS uses the parallel measurement principle; it measures all the spectrum fractions simultaneously. The measurement range of this device according to particle mass diameter (Tammet, 1995) is from 2.6 nm to 10 μm. The EAS operates with a unipolar corona charger, while the DMPS has bipolar neutralizer (charger) to control the particle charging. The EAS was calibrated by a special procedure based on the mathematical model of the spectrometer and the experimental determination of some free parameters of that model, using quasimonodispersed standard aerosols with known size spectrum (Tamm et al., 2003). The mobility distribution (mobility spectrum) of air ions (cluster ions and charged fraction of the aerosol particles) was measured by two ion mobility spectrometers – the Balanced Scanning Mobility Analyzer (BSMA) and the Air Ion Spectrometer (AIS) – both designed at the University of Tartu and built by Airel Ltd. The BSMA (Tammet, 2004) measures ion number concentrations in 16 fractions consecutively in time, one polarity after the other. Its ion mobility measurement range is from 3.2 to 0.032 cm 2 V − 1 s − 1 ; the

corresponding particle mass diameter range is from 0.34 nm to 7.4 nm. The AIS (Mirme, 2004) is a multichannel, parallel-principle device, simultaneously measuring ion concentrations in 28 mobility fractions of both, positive and negative ions. The measurement range of ion mobility is from 2.4 to 0.00075 cm2 V− 1 s− 1, which corresponds to the particle mass diameter range from 0.46 to 55 nm. For diameters dp N 3 nm, the AIS was calibrated by the standard aerosols similarly as the EAS. In steady state conditions, charges on aerosol particles are in equilibrium with their electrical environment. If the system changes, it takes some time until a new equilibrium is reached. In the DMPS-setup, aerosol particles are led through a neutralizer/charger, which balances the charge distribution. Before sizing the aerosol is neutralized with a 74 MBq (2 mCi) Krypton85 beta source. If particles have fewer charges than the equilibrium requires, then some more particles are charged by cluster ions. If there are too many charges on particles, ions of opposite polarity discharge a fraction of the particles. During the QUEST campaign at Hyytiälä the natural charging state of the particles having a diameter between 2.5 and 4.5 nm was also estimated with a special DMPS setup. Two similar inlets, one with a neutralizer, the other without a neutralizer (a dummyone), were used. The DMPS-system switched between these two inlets every 75 s. The natural charging state of the aerosol can be obtained, when the concentration measured without the charger is divided by the corresponding charged particle concentration. If the value is equal to 1, aerosol particles are in the charge equilibrium. Values b 1 represent undercharged particles and values N 1 indicate overcharge of the particles.

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3. Data acquisition Data used in this paper were collected during a measurement campaign in the framework of the EUfunded project QUEST (Quantification of Aerosol Nucleation in the European Boundary Layer) at SMEAR II Station (Station for Measuring Forest Ecosystem–Atmosphere Relations) (Vesala et al., 1998) in Hyytiälä, Southern Finland (61°51′N, 24°17′ E, 181 m asl) in March and April 2003. All four spectrometers worked during 19 days, from March 22 to April 9. The station is located in about 40-year-old Scots pine forest. The DMPS and the EAS were installed sideby-side in the main cottage with inlets about 2 m and 1 m above the ground surface, respectively; the BSMA and the AIS were mounted also side-by-side in a small cottage, approximately 30 m from the main one. The time period for the intensive measurement campaign was chosen so that it allowed catching the maximal number of the springtime nucleation burst events. 3- (BSMA), 5- (AIS and EAS) or 10-min (DMPS) mean (size or mobility) number distributions were recorded by all four particle spectrometers for the whole period of the measurement campaign. The structure of the spectrum data files is different for different spectrometers. The BSMA and the AIS give out the information about ion mobility distributions in form of the set of fraction number concentrations; fraction boundaries are distributed uniformly in logarithmic scale of the ion mobility. Eight fractions per decade have been chosen. As the probability of multiple electronic charges on the nanoparticles is negligible, the particle electrical mobility and diameter are related biuniquely, but not linearly, so the distribution of the fraction boundaries in the logarithmic scale of particle diameter is not uniform; there are 12 fractions per decade for nanoparticles. The DMPS describes the particle number size distribution in form of the set of distribution density function values for some knot points in the diameter scale, which do not coincide with the above-mentioned fraction boundaries of the ion spectrometers. Output information of the EAS is also formed as a set of particle fraction number concentrations; 8 fractions per decade of particle diameter were chosen. Fraction boundaries are uniformly distributed in the logarithmic scale of particle diameter, but once again they do not coincide with the boundaries of ion spectrometers. (The AIS and the EAS can give out the distribution density function values as well, but for our purposes, the fraction concentrations are necessary.) As the ion spectrometers have the narrowest fractions for nanoparticles, the data of the DMPS and the EAS were transformed into the format of fraction

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concentrations with fraction boundaries coinciding with ion spectrometers' ones. Fraction boundaries in electrical mobility scale are (in cm2 V− 2 s − 2): 2.37, 1.78, 1.33, 1.00, 0.750, 0.562, 0.422, 0.316, 0.237, 0.178, 0.133, 0.100, 0.075, 0.0562, 0.0422, 0.0316, 0.0237, 0.0178, 0.0133, 0.0100, 0.00750, 0.00562, 0.00422, 0.00316, 0.00237, 0.00178, 0.00134. By normal meteorological conditions (0 °C temperature and 1013 hPa atmospheric pressure), the corresponding boundaries in particle mass diameter scale are (in nm): 2.6, 3.3 3.9, 4.6, 5.4, 6.4, 7.4, 8.7, 10.2, 11.9, 13.8, 16.1, 18.7, 21.8, 25.4, 29.6, 34.6, 40.1. The higher limit of the measurement range of the BSMA is 7.4 nm. Throughout this paper we use the concept of particle mass diameter dm, recommended by Tammet (1995) as a fundamental parameter characterizing particle size. The conception of mass diameter is based on the postulate that the density of the particulate matter in case of nonaggregated nanoparticles does not depend on particle size, and the particle mass diameter is determined via its mass m and density ρ: sffiffiffiffiffiffiffiffi 3 6m dm ¼ : 4pq In the air at standard normal meteorological conditions, dm is approximately 0.6 nm smaller than the mobility equivalent diameter, calculated from the Millikan equation via measured mobility. Millikan equation is not precise enough when the size of the ambient gas molecules cannot be neglected, compared with the particle size. Side-by-side installation of the spectrometers in Hyytiälä enables to perform an intercomparison of them based on the data collected during the whole measurement campaign (Tamm et al., 2004). In Fig. 2, the mean ratio of the fraction concentrations of the BSMA and AIS over all data set for the overlapping diameter range of all four spectrometers is depicted. We can see that the BSMA tends to show higher ion concentrations than the AIS, especially for 4–5 nm. In Fig. 3, the size dependence of the mean ratio of the number distribution density function values measured by the EAS and DMPS is depicted. Three curves correspond to (1) all data, (2) the data of non-burst days, when the concentration of the nanoparticles was low during the whole day, and (3) the data of particle nucleation burst time intervals, when the nanoparticle concentration was high. The first two curves practically coincide; the outlier by 3 nm is caused by the DMPS, which cannot measure small concentrations of such particles properly. For non-burst days, there are very few

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Fig. 2. Ratio of the fraction number concentration values measured by the ion spectrometers (BSMA vs. AIS) during the QUEST campaign at Hyytiälä, 2003.

non-zero measurement results by the DMPS at 3 nm, which produces the statistically insignificant point in Fig. 3. These curves show clearly that, in general, the EAS overestimates (or the DMPS underestimates) the concentration of small particles. This tendency strengthens in the case of higher concentrations, as shown by the third curve. The differences discovered by both pairs of spectrometers can partly be caused by calibration errors, but partly also by different measurement procedures. For instance, the DMPS measures particles dried by dry sheath air, but the EAS measures particles approximately in situ conditions. Although these differences are not extremely high for aerosol spectrometers and they do not prevent finding out the main qualitative regularities of particle charging state (see below), the work for specifying the calibration of spectrometers is ongoing. Below, in most cases the charging probabilities are presented as calculated from the AIS and DMPS data. The DMPS was chosen as accepted by the aerosol community device; the AIS was selected, since it gives more reliable results (compared to the BSMA) for bigger particles (dp N 5 nm), where there obviously exists steady charging state.

According to the value of aerosol particle concentration in this figure, all the measurement days can be conditionally classified into three groups (CL1 in Table 1): days with a “strong” burst, days with a “weak” burst, and non-burst days. Such a classification is, naturally, quite subjective and no clear frontier exists between the strong and weak bursts. In case of the current data set, the limit between “strong” and “weak” bursts is about 1500–2000 cm − 3 in 2.6–3.3 nm aerosol particle concentration. Our classification is complementary to the four-step classification, introduced by Mäkelä et al. (2000) based on “banana-shaped” surface plots of particle distributions (CL2 in Table 1). Many of the strong bursts belong to the first class with clearly expressed growth of nucleated particles up to the Aitken mode sizes, but some of them must be rated to second class with not so distinct particle growth. The weak bursts tend to belong mainly to the second class, with some exceptions, belonging to the first or even to the third class. The non-burst days coincide according to both classifications, except March 27. Fig. 5 illustrates the measurement range of the four instruments from 0.4 nm to 10 μm. The aerosol size spectrometers and ion mobility spectrometers have an overlapping measurement range in the particle mass diameter interval of 2.6–40 nm. Hence, the simultaneous measurements of aerosol particle size distribution and air ion mobility distribution enable to estimate the charging probability of atmospheric aerosol particles. This parameter can be obtained as the slope of the linear regression line on the scatterplot of the measured concentrations of total and charged (air ions) particles for the same fraction (diameter interval). Fig. 6 shows the scatterplot of the concentrations of the smallest particles (2.6–3.3 nm) detectable by particle size

4. Analysis of the data and discussion The data collected during the above-described measurement campaign in Hyytiälä have already been reported (e.g. Kulmala et al., 2004b; Laakso et al., 2004a; Hõrrak et al., 2004a,b). Here we give the more detailed analyses of the data. In Fig. 4, the time variations of the concentration of 2.6–3.3 nm size aerosol particles and air ions are depicted. We can see several concentration bursts.

Fig. 3. Ratio of the distribution density function values measured by the aerosol spectrometers (EAS vs. DMPS) during the QUEST campaign at Hyytiälä, 2003.

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Fig. 4. Time variations of the concentration of 2.6–3.3 nm size aerosol particles and air ions measured by the EAS and AIS.

spectrometers for all measurement days (22.03– 09.04.03). Here we can separate two groups of data points: first, the group with low concentrations of aerosol particles and with the charge asymmetry with respect to particle charge sign; second, the group with higher concentrations of aerosol particles, which mainly determines the slope of the regression line and is almost symmetric concerning the charge sign. We have found that the first group of points in the scatterplot (Fig. 6) belongs mainly to 6 days with weak concentration bursts of nanometer particles on March 23–25, 28 and April 3, 9. The second group of points belongs basically to 3 days with strongest bursts on April 1, 4 and 7, but also to bursts on March 26 and 29, and April 2. Fig. 7 depicts the scatterplot for these 6 days with weak burst events (listed above); the charge asymmetry with respect to particle charge sign is clearly seen. Fig. 8 shows the dependence of the particle charging probability on their mass diameter. Probabilities are calculated from the DMPS and AIS data for the abovementioned weak burst days, as well as for the strong nucleation burst days (March 26 and 29, April 1, 2, 4 and 7). The steady state charge distribution is obtained from Reischl et al. (1996). We can see that the charging probabilities for particles bigger than 5 nm approximately agree with the curve corresponding to steady state charge distribution for negative particles, which was obtained by Reischl et al. (1996) from theoretical calculations and confirmed by laboratory experiments. We can also see that in atmospheric conditions the probabilities of negative and positive charge on particles with diameter N 5 nm are approximately equal, unlike the results given by Reischl et al. (1996). In the case of

weak bursts, the percentage of negatively charged particles in the size range of 2.6–4 nm can be more than twice higher than that for positively charged

Table 1 Classification of the nucleation event days and the ratio of the experimental charging probabilities of negative to positive charges on particles estimated by means of different air ion (AIS, BSMA) and aerosol spectrometers (DMPS, EAS) (S – strong burst, W – weak burst, NB – non-burst day) Date

CL1 CL2 Ratio of probabilities of neg. and burst strength class no. pos. charges in particle mass diameter interval 2.6–3.6 nm AIS/ BSMA/ AIS/ BSMA/ DMPS DMPS EAS EAS

26.03.03 29.03.03 01.04.03 02.04.03 04.04.03 07.04.03 08.04.03 23.03.03 24.03.03 25.03.03 28.03.03 03.04.03 AM 03.04.03 PM 09.04.03 31.03.03 06.04.03 22.03.03 27.03.03 30.03.03 05.04.03

S S S S S S S W W W W W

2 2 1 1 2 1 1 2 1 1 1 2

1.02 0.96 0.83 1.02 0.80 0.95 1.74 3.77 2.17 1.97 1.74 3.47

0.93 1.06 1.04 1.25 0.98. 1.38 2.25 2.54 1.76 1.85 1.56 4.45

1.07 0.94 0.83 1.03 0.76 0.93 1.68 3.88 2.00 1.88 1.66 3.43

1.19 1.04 1.04 1.21 0.96 1.24 2.17 2.76 1.72 1.69 1.51 4.17

W

2

1.54

1.45

1.54 1.49

W W W NB NB NB NB

3 3 2 NB 3 NB NB

2.17 1.24 1.29 2.48 2.45 3.76 0.61

1.79 1.15 1.26 0.80 1.49 2.11 –

2.22 1.07 1.23 1.78 2.01 4.16 0.52

2.14 1.41 1.26 0.92 1.03 1.39 –

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Fig. 5. Mean distribution density functions measured by means of the ion spectrometers (AIS, BSMA) and aerosol spectrometers (EAS, DMPS) at Hyytiälä on April 8, 2003.

particles. Also, the percentages of charged particles essentially exceed the values for steady charging state. For larger particles, such a drastic charge asymmetry and deviation from steady charging state disappears. During the growth time, the particles acquired steady state charge distribution. In general, in the case of strong nucleation bursts, the charge asymmetry is weak (Table 1) and the deviation from steady charging state is less significant. Fig. 9 illustrates the dispersion of the charging probability as the function of particle size for different days. Some negative values of charging probability belong to non-burst days, when the applied method gives physically incorrect results. Fig. 10 shows that the

Fig. 6. Scatterplot of the fraction number concentration values measured by the EAS and AIS on March 22–April 9, 2003 with regression straight lines and 95% prediction intervals. The approximate limits of the two groups of data points are indicated: 1) the group with low concentrations of aerosol particles and with the charge asymmetry with respect to particle charge sign; 2) the group with higher concentrations of aerosol particles.

BSMA data give somewhat higher estimates for the charging probabilities than the AIS data. Probably, it happens due to the uncertainties in the calibration of the devices, maybe also due to some underestimation of the diffusion losses in the AIS inlet tubing. Quite probable are turbulent losses in the AIS. The charging probabilities estimated using the EAS data are a little lower than those of the estimates by the DMPS data. Nevertheless, what is important is that the shape of the curves is similar for all pairs of devices. Data in Table 1 confirm the statement, that regardless of the differences in the estimates of the particle charging probability, all four pairs of spectrometers characterize similarly the main qualitative regularities of particle charging state. Table 1 presents the ratios of the probabilities of negative to positive elementary charges on the particles in the diameter interval of 2.6–3.6 nm for all four pairs of

Fig. 7. Scatterplot of the fraction number concentration values measured by the EAS and AIS on March 23–25, 28 and April 3, 9 with regression straight lines and 95% prediction intervals. These data points determine the group with low concentrations of aerosol particles and with the charge asymmetry with respect to particle charge sign.

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Fig. 8. Charging probability as a function of size for two different types of nucleation bursts: weak bursts occurred on March 23–25, 28 and April 3, 9; strong bursts occurred on March 26, 29 and April 1, 2, 4, 7. The results are compared with the curves corresponding to the steady state charge distribution (Reischl et al., 1996).

spectrometers. Here the charging probabilities were estimated applying a similar method as described above, but with the fixed zero point (intercept of the regression line). This ratio of the charging probabilities can be named as the charge asymmetry parameter. In Table 1, we see approximately symmetric charging in case of strong bursts; from Fig. 8 we see that there is the steady charging state even for the smallest particles detectable by the particle size spectrometers. But there was one exceptional day with a high particle formation rate, April 8, when clearly asymmetric charging state existed, and the percentage of negative particles exceeded the steady state. In the case of weak bursts, in most cases the charging asymmetry can be seen, the charging asymmetry parameter varying approximately from 1.5 to 4 (Table 1). But here we can also see exceptional days. On April 3 we can notice two separate

Fig. 9. Charging probability as a function of size for all days over the whole measuring period (March 22–April 9, 2003). The results are compared with the curves corresponding to the steady state charge distribution (Reischl et al., 1996). The negative values of the charging probabilities are the artifacts caused by the applied method in the case of very low concentration of particles during the non-burst days.

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Fig. 10. Charging probability as a function of size, comparison between the AIS and BSMA data. The curves are calculated for weak burst days on March 23–25, 28 and April 3, 9.

bursts, one beginning in the morning, and the other beginning in the afternoon. The first one represents the typical case of asymmetric charge distribution on particles, but the second one, a nearly symmetric case. The weak afternoon burst on March 31 is definitely symmetric. The burst on April 6 began in the morning, but it is symmetric. The non-burst days need a special treatment. From Fig. 4 we see, that according to charged particle generation, only 2 of the 4 days, which seem to be non-burst days according to neutral particle concentration, namely March 22 and March 27, are real non-burst days. For these days, the charging asymmetry parameter in Table 1 seems to have a random value, depending on the choosing of the pair of spectrometers. During these days, the concentration of particles was close to the sensitivity limit of spectrometers and, therefore, the applied method did not give reliable results. On March 30, there were a number of short-term bursts of the charged particle concentration with the prevailing of negative charge. On April 5, there was a long-term burst with the exceptional prevailing of positive charge, but these nucleated particles in the diameter interval of 1.5– 6 nm did not grow up to the Aitken mode dimensions. Analyzing the current data set, we can say that cluster air ions, especially the negative ones, can act as condensation nuclei during weak nucleation burst events, when the nucleation rate and the concentration of freshly nucleated neutral nanometer particles are low. By ageing and the growing of the particles in the atmosphere of the bipolar cluster ions, they reach steady state charge distribution after growing over approximately 5 nm in diameter. The last is illustrated by a concentration gap between 5 and 7 nm in the surface plot of charged particle size spectra (Fig. 11): the charge of most of the particles born in charged state is neutralized, the charging rate is quite low for such

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Fig. 11. Surface plots of the charged particles size spectrum for positive and negative air ions measured by the AIS at Hyytiälä on March 25, 2003.

particles (many times lower than the neutralization rate), and therefore the concentration of charged particles is low. Formation rate of the cluster ions in Hyytiälä boundary layer does not exceed 5 cm− 3 s− 1 (Hõrrak et al., 2005; Laakso et al., 2004b); the mean formation rate of 1-nm neutral particles, assessed from our data set, is approximately 12 cm− 3 s− 1 for strong burst events, and 4 cm− 3 s− 1 for weak burst events. The formation rate of 1-nm neutral particles was calculated using a calculation scheme introduced by Dal Maso et al. (2002). Obviously, by the strong bursts ion-induced nucleation plays less essential role. There exists another possible explanation: the growth rate of the particles can be low by strong bursts (deficit of the condensing gases), so that particles reach steady charging state, before they grow over 3 nm in diameter. However, 3- to 5-nm particle diameter growth rate, assessed from our data set, was 2– 4 nm h− 1; no systematic difference between the days with weak and strong burst was found. It is difficult to explain the phenomena on April 8, when the ioninduced nucleation seems to play an essential role by the strong burst. Database of the Hyytiälä measurement campaign contains a large variety of the meteorological, radiation and gaseous impurities concentration data, which allow searching correlations of these data with nucleation bursts. Analysis shows that the existence of direct sun

radiation is almost obligatory for the occurrence of both the strong and weak particle nucleation bursts. Only one burst, on April 2, happened under the cloudy sky. Most of the bursts occurred after the nights with temperature inversion. This find coincides with previous investigations (Nilsson et al., 2001). No correlation was observed between the occurrence of the ion-induced nucleation

Fig. 12. Scatterplot of the ratio of the number concentration of negative air ions (measured by the AIS) to aerosol number concentration (measured by the ordinary DMPS) in the diameter range 2.6–4.6 nm and the overcharge measurement results by the special DMPS setup indicating the natural charging state of the particles with a diameter between 2.5 and 4.5 nm on March 22–April 9, 2003.

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and the concentration of SO2, NOx and H2O. Based on the available data, it is difficult to explain which gaseous substances are responsible for ion-induced nucleation processes. Obviously, there must be different substances for the days, when negative ions prevail as condensation centers, and for April 5, when positive ions prevail. There is another possibility to estimate the charging state of atmospheric nanometer particles. This method was described by Laakso et al. (2004a). The abovedescribed special DMPS setup was used for that purpose. The natural charging state of the aerosol was estimated by means of the overcharge ratio. We have compared the data by the special DMPS setup with the data by the AIS and the ordinary DMPS. In Fig. 12 the scatterplot of the ratio of the number concentration of negative air ions (measured by the AIS) to aerosol number concentration (measured by the ordinary DMPS) in the diameter range of 2.6–4.6 nm and the overcharge measurement results for particles having a diameter between 2.5 and 4.5 nm are depicted. The data points are 30-min mean values over the whole measuring period. Fig. 12 shows a good correlation between two independent methods to estimate the natural charging state of newborn particles. This could be one validation to our results, which we have got by means of the ion spectrometers (AIS and BSMA) and aerosol spectrometers (DMPS and EAS). 5. Conclusions From the analysis of the charging properties of atmospheric nanoparticles during the QUEST campaign in Hyytiälä on March and April 2003, we can draw the following conclusions. (i) Overlapping measurement ranges of the particle size spectrometers (EAS, DMPS) and air ion mobility spectrometers (AIS, BSMA) enable to assess the percentage of charged particles (charging probability). (ii) We can conclude that negative cluster ions preferably act as condensation nuclei during nucleation bursts. Relative importance of the ion-induced nucleation with respect to the homogeneous nucleation seems to be the highest in case of comparatively weak concentration bursts of nanometer particles, when the nucleation rate and the concentration of freshly nucleated neutral nanometer particles are low. Here, the essential part of nanometer particles could be generated by the ioninduced nucleation as particles with a diameter b5 nm were found to be overcharged in comparison

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