New particle formation in Beijing, China: Statistical analysis of a 1-year data set

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1 JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 112,, doi: /2006jd007406, 2007 New particle formation in Beijing, China: Statistical analysis of a 1-year data set Zhijun Wu, 1 Min Hu, 1 Shang Liu, 1 Birgit Wehner, 2 Stefan Bauer, 2 Andreas Ma ßling, 2 Alfred Wiedensohler, 2 Tuukka Petäjä, 3 Miikka Dal Maso, 3 and Markku Kulmala 3 Received 13 April 2006; revised 18 December 2006; accepted 5 January 2007; published 11 May [1] Particle number size distributions between 3 nm and 10 mm were measured in Beijing, China. New particle formation events were observed on around 40% of the measurement days from March 2004 to February 2005 and were generally observed under low relative humidity and sunny conditions. Though occurring during all seasons, new particle formation events had highest frequency in spring and lowest frequency in summer. Events were classified as clean or polluted groups mainly according to the condensational sink and the local wind. The formation rate range was from 3.3 to 81.4 cm 3 s 1. The growth rate varied from 0.1 to 11.2 nm h 1. The seasonal variation of condensable vapor concentration showed the highest values during summer months due to enhanced photochemical and biological activities as well as stagnant air masses preventing exchange with cleaner air. Citation: Wu, Z., M. Hu, S. Liu, B. Wehner, S. Bauer, A. Ma ßling, A. Wiedensohler, T. Petäjä, M. Dal Maso, and M. Kulmala (2007), New particle formation in Beijing, China: Statistical analysis of a 1-year data set, J. Geophys. Res., 112,, doi: /2006jd Introduction [2] New particle formation events have been observed in many different atmospheric environments over the past decade [Kulmala et al., 2004a]: in clean settings such as coastal environments [O Dowd et al., 1999], polar areas [Park et al., 2004], remote boreal forest [Mäkelä etal., 1997], as well as continental rural areas [Birmili et al., 2003], and urban areas such as Birmingham [Alam et al., 2003], Atlanta [Woo et al., 2001],Pittsburgh[Stanier et al., 2004],Athens[Kulmala et al., 2005], and Helsinki [Hämeri et al., 1996], and also recently in very polluted megacities such as Mexico City [Dunn et al., 2004],Beijing[Wehner et al., 2004], and New Delhi [Mönkkönen et al., 2005]. New particle formation events usually occur during daytime when the preexisting particle mass concentration is low and under sunny and dry conditions [Birmili and Wiedensohler, 2000;Dunn et al., 2004; Stanier et al., 2004]. With the variety of measurement sites, the contributing precursor gases may vary too. Elevated SO 2 concentrations during new particle formation events were found in several measurements [Dunn et al., 2004; Stanier et al., 2004]. Biogenic iodine emissions were related to new particle formation in coastal regions [O Dowd et al., 2002a]. Observations of new particle events cover all seasons, 1 State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences, Peking University, Beijing China. 2 Leibniz-Institute for Tropospheric Research, Leipzig, Germany. 3 Division of Atmospheric Sciences, Department of Physical Sciences, University of Helsinki, Helsinki, Finland. Copyright 2007 by the American Geophysical Union /07/2006JD but their frequency was dependent on seasons and locations [Dal Maso et al., 2005;Vehkamäki et al.,2004]. [3] Typical particle growth rates (GRs) span at 1 20 nm h 1 in midlatitudes [Kulmala et al., 2004a]. Newly formed particles may grow to larger particles (>100 nm) within the subsequent 1 2 days [Kulmala et al., 2004a], and thus they may influence regional climate due to a change in the concentration of cloud condensation nuclei and also direct scattering of solar radiation. [4] There are several hypotheses to explain the nucleation processes [Kim et al., 2002; Korhonen et al., 1999; Kulmala et al., 1998; O Dowd et al., 2002b]. Sulfuric acid is considered to play a key role in the nucleation [Kulmala, 2003]. The newly formed nuclei face a competition between coagulation scavenging and condensational growth [Kerminen et al., 2001]. At least in the boreal forest conditions, nucleation and early growth are likely to be uncoupled from each other [Kulmala, 2003; Kulmala et al., 2004b]. Besides sulfuric acid, organics also contribute to the subsequent condensational growth [Kulmala, 2003]. However, models which are limited to a small number of contributing species cannot explain nucleation and growth for all the different geographical locations. The contribution of sulfuric acid to the particle growth is larger in urban area than in an environment less affected by human activities [Kulmala et al., 2005]. Information about chemical composition of the ultrafine fraction is very rare and limited to few species. Recent measurement of 6 15 nm particles showed that ammonium and sulfate are major components of newly formed particles in Atlanta [Smith et al., 2005]. [5] The goal of this work is to report and analyze the new particle formation events observed in Beijing between 1of10

2 Figure 1. Map of Beijing and location of our measurement site. Black dot denotes the location of measurement site. March 2004 and February This includes the classification of events, the analysis of conditions during new particle formation events such as meteorological data, and the calculation of the particle formation rate, growth rate, condensable vapor concentration, and source rate in order to understand the particle formation and growth processes in urban atmosphere of Beijing. 2. Experimental Procedure 2.1. Sampling Method [6] Aerosol particle number size distributions between 3 nm and 10 mm have been measured for 1 year since the beginning of March [7] A twin differential mobility particle sizer (TDMPS) system consisting of two Hauke-type differential mobility analyzers and two condensation particle counters (model 3010 and model 3025, TSI Inc., St. Paul, MN, USA) was used to measure the particle number size distributions from 3 to 800 nm (mobility diameter). Additionally, an aerodynamic particle sizer (APS, TSI model 3321, TSI Inc., St. Paul, MN, USA) measured particle number size distributions between 800 nm and 10 mm (aerodynamic diameter). The APS results were transformed from aerodynamic to Stokes diameters with a particle density of 1.7 g cm 3. This particle density was decided according to the density of sulfate, a major aerosol component in Beijing [e.g., Yao et al., 2002]. A low flow PM10 inlet was used in this system. The relative humidity within the system was kept below 30% by adding a silica-gel dryer in the inlet line and also in the sheath air cycle. Size distributions were taken every 10 min. The data were corrected for losses due to diffusion and sedimentation within the inlet line. Size-dependent losses for the TDMPS inlet line were estimated using empirical particle loss corrections (diffusion and gravitation) from the study of Willeke and Baron [1993]. Losses of 4- and 10-nm particles were estimated to be 35% and around 10%, respectively. [8] A meteorological station located in the campus of Peking University, on the roof of one sixth-floor building, measured the wind direction, wind speed, relative humidity (RH), and temperature. This monitoring station is located approximately 500 m away from our sampling site. [9] SO 2 concentration was measured by using an SO 2 Analyzer (model 43C, Thermo Electron, Waltham, MA, USA) during summertime and wintertime intensive campaigns. The summertime intensive campaign covered June, July, and August The wintertime intensive campaign was performed from 23 December 2004 to 28 February Sampling Site [10] The sampling site is on the roof of an academic building (15 m above the ground level) in the campus of Peking University, located in the northwestern urban area of Beijing, outside the fourth-ring road (cf. Figure 1). East of the site is a major road with heavy traffic, in a distance of about 500 m. South of the campus is a one-way street approximately 500 m away. North and northwest of the site lie the main parts of the campus. No significant stationary sources were found nearby the monitoring site. 3. Theory [11] The formation rate, growth rate, source rate, and concentration of condensable vapors were calculated by using the method reported by Kulmala et al. [2001, 2004a, 2005] and Dal Maso et al. [2005]. 2of10

3 [12] The aerosol size distribution measurement setup was able to detect only particles larger than 3 nm in diameter. Actual nucleation rate (J nuc ) below the detection limit can be expressed as [Dal Maso et al., 2005]: RH. Hygroscopic growth was measured size dependent at 90% RH. Hygroscopic growth at ambient RH was determined using the parameterization of Laakso et al. [2004]: J nuc ¼ dn nuc þ F coag þ F growth dt ð1þ RH g GF D p ; RH ¼ 1 ð6þ 100 In this study, N nuc is the number concentration of nucleation mode particles. F coag represents a loss of formed particles due to coagulation to the preexisting particle population. F growth is the flux of particles out of the specified size range. The diameter range of N nuc is from 3 to 25 nm for calculating particle formation rate in this study. The newly formed particles rarely grew beyond 25 nm before formation ended, and F growth can be neglected. [13] Observed particle GR can be expressed as: GR ¼ DD m Dt where D m is a mean geometric diameter of log-normal ultrafine particle mode, which has been fitted to the number size distribution [Heintzenberg, 1994]. GR means evolution of the mean diameter within a time period Dt. [14] The growth rate can also be expressed as [Kulmala, 1988]: dd p dt ¼ 4m b M DC D p r Here D p is the particle radius, m u is the molecular mass of condensable vapor, D is the diffusion coefficient, C is the vapor concentration, r is the particle density, and b M is the transitional correction factor for the mass flux. The saturation vapor pressure of the condensing vapor is assumed to be zero. Equation (3) can be integrated from D p,0 to D p, which results in [Kulmala, 1988]: C ¼ r D 2 p D2 p;0 þ 2 0:312 DtDm 8 3a : l Dp D p;0 þ 0:623l 2 ln 2l þ D p 2l þ D p;0 Here a is the mass accommodation coefficient, and l is the mean free path of the gas molecules. [15] The particulate condensational sink (CS) can be calculated by using equation (5). This equation determines how rapidly molecules can condense onto the preexisting aerosols: CS ¼ 2pD Z 1 0 D p b M D p ndp ddp ¼ 2pD X i b M D p;i N i Here n(d p ) represents the particle size distribution function, and N i is the particle number concentration in the size section i: in this study, 3 nm 10 mm. The particle number size distributions at ambient RH were calculated based on the measured dry number size distributions and the calculated size-dependent hygroscopic growth factors at ambient ð2þ ð3þ ð4þ ð5þ Here GF is the growth factor of a particle of size D p at a relative humidity RH. g is a parameter derived by a least squares fit to the hygroscopicity data measured during the summertime (June/July 2004) and wintertime (January/ February 2005) intensive campaigns in Beijing. The mean GFs from the summer campaign were used to calculate ambient size distributions from April to October, whereas those from the winter campaign were used for data from November to March. [16] The time dependence of the concentration (C) can be expressed as: dc dt ¼ Q CS C ð7þ Q is the source rate of the condensable vapor. With a pseudo steady state assumption, the vapor source rate can be estimated from equation (7): Q ¼ CS C [17] In the calculations, the saturation vapor pressure of the condensing vapor is assumed to be zero. In addition, the observed GR is used in the condensable vapor concentration estimation, but intramodal and extramodal coagulations are not considered. Thus the estimated condensable vapor concentration and its source rate should be considered as upper limit estimation. 4. Results and Discussion [18] The criterion for discerning these so-called new particle formation events was the burst in the nucleation mode particle concentration [Birmili and Wiedensohler, 2000]. In this study, particles between 3 and 10 nm were considered to represent the newly formed particles. One burst was counted as new particle formation event if the duration time was longer than 2.5 h and the maximum number concentration of 3 10 nm particles was larger than 10 4 cm 3. One example of a new particle formation event observed in our site is shown in the left panel of Figure 2. In this example, an increase and a subsequent decrease of 3- to 10-nm particle concentrations lasted for around 8 hours. A slight increase of SO 2 concentration was observed during an increase of 3- to 10-nm particle concentration. [19] The events with bursts in the 3- to 10-nm size range, lasting a short time but without the growth of 3- to 10-nm particles to larger sizes, were not included in new particle formation events discussed in this study. The right panel of Figure 2 shows an example of this kind of event. Both SO 2 and 3- to 10-nm particle concentrations sharply increased, followed by a sharp decrease within 2 hours. It indicates that the increase in 3- to 10-nm particles might be produced ð8þ 3of10

4 Figure 2. Left panel: Example of a new particle formation event. Right panel: Example of a typical plume event. A time series of sulfur dioxide concentrations is shown in this figure. N3 10 nm means 3- to 10-nm particle number concentrations. by a plume of a nearby source. These events were classified as plume events Classification of New Particle Formation Events [20] One goal of this study was to find conditions, which favored new particle formation. Therefore the events were divided into two groups with similar conditions. This classification of new particle formation events was done by analyzing the diurnal variation of 3- to 10-nm particle number concentration, CS, and meteorological data (wind direction and wind speed). Preexisting particles between 3 nm and 10 mm were used to calculate the condensational sink. Figure 3 showed two examples for the two different kinds of new particle formation events: [21] (1) Clean case: The air mass arrived in Beijing from the north or northwest, and the condensational sink was below 0.02 s 1 (see Figures 3a1 3a3). In this group, the nucleation mode of most of the events showed an obvious growth process. The wind direction was steady during events. Relatively clean and clean air was advected from the north or northwest, which favored new particle formation. These air masses did not experience much influence Figure 3. Examples of two different kinds of events observed in Beijing, and corresponding condensational sink and meteorological parameters. (a1 a3): Clean event. (b1 b3): Polluted event. In this figure, N3 10 nm, Ntot, and CS mean 3- to 10-nm particle number concentrations, 3-nm to 10-mm particle number concentrations, and condensational sink, respectively. 4of10

5 Figure 4. Left panel: Example of case with a superposition of a sharp 3- to 10-nm particle concentration peak and a new particle formation event. Right panel: Example of a typical nonevent day observed in Beijing, and corresponding condensational sink and meteorological parameters. In this figure, N3 10 nm, N3 nm 10 mm, and CS mean 3- to 10-nm particle number concentrations, 3-nm to 10-mm particle number concentrations, and condensational sink, respectively. from the urban pollution before sampling. The duration of these events was at least 4 hours. [22] (2) Polluted case: The wind direction was mainly between 120 and 240 ; that is, the air mass arrived in Beijing from the south or southwest. The condensational sink was usually larger than 0.02 s 1 (see Figures 3b1 3b3). The increase in particle number concentration covered a wide range of particle diameters when event started. The events lasted for at least 4 hours. Those events were classified as polluted events. [23] Some new particle formation events, which did not fit to clean or polluted cases, were classified as others. One example is shown in the left panel of Figure 4. The new particle formation event lasted for several hours and showed a clear growth process before the wind direction changed. Between 1300 and 1530 hours, the increase and then the decrease of 3- to 10-nm particle concentrations were accompanied by SO 2 spikes. The bursts in 3- to 10-nm particles between 1300 and 1530 hours might be influenced by the local plume. It is suggested that a plume event was superimposed upon a new particle formation event. Similar events were also observed in Atlanta by Sakurai et al. [2005]. New particle formation events which were interrupted by a change of wind direction or rainfall, and/or with a duration time below 4 hours, were also classified as others. [24] For comparison between new particle formation event day and nonevent day, one example of a typical nonevent day is shown in the right panel of Figure 4. Typically, nonevent days were associated with high CS and stable meteorological conditions except for cloudy and rainy days. [25] Figure 5 shows the results of classification and the frequency of new particle formation events in Beijing between March 2004 and February On around 40% Figure 5. Classification and frequency of new particle events versus month in Beijing from March 2004 to February of10

6 Figure 6. Starting and ending time of new particle formation events in Beijing. Local time is used here. of the measurement days, the new particle formation events were observed. The new particle formation events occurred most frequently in spring, followed by winter and fall months. The minimum number occurred in July and August; only few events were observed during this period. The reasons were meteorological conditions which connected with high temperature and high RH in Beijing during summertime. Slowly moving air masses were advected from southern directions, and pollutants were accumulated in the air masses. Under such conditions, the high condensational sink prevented new particle formation. During the other months, favorable conditions for new particle formation such as sunny and dry days were found to be similar to other places [Birmili et al., 2003; Stanier et al., 2004]. Other studies also found the highest frequency of new particle formation events during springtime, for example, at boreal sites, mainly between March and May, probably due to biological activity [Vehkamäki et al., 2004]. In Pittsburgh, PA, USA, nucleation events were found mainly in fall and spring and least frequently in winter [Stanier et al., 2004] Favorable Conditions for New Particle Formation [26] Conditions for others events formation were difficult to be found because of the short time and variant starting and ending time. Only event days with complete data sets and an uninterrupted particle formation for 4 hours were completely analyzed; thus the following analysis focused on the clean and polluted events. [27] In Beijing, the clean new particle formation events usually took place after dust storms, precipitation, and/or the passage of cold fronts associated with high wind speed and northerly or northwesterly winds. The concurrent absence of clouds and aerosol particles led to sunny and clear days. The condensational sink was thus low, and the photochemical activity was relatively high. Clean events occurred frequently on one or two consecutive days. [28] After one or two clean event days, the particle mass concentration was increased because of accumulation of pollutants in the urban atmosphere if the wind with low speed came from south. Again, polluted events happened on one or two subsequent days. The condensational sink subsequently increased, and no event occurred on the following day even if it was sunny as previous days. The condensational sink seemed to be one of the limiting factors for new particle formation in Beijing. The cycle of clean event day to nonevent day took typically for about 1 week, especially in March and April. If the weather conditions changed, another cycle started. [29] Figure 6 illustrated starting and ending time of clean and polluted events. Events occurred after sunrise and ended before sunset. Both clean and polluted events started typically between 0600 and 1000 hours and ended between 1200 and 1800 hours. [30] In springtime, the starting time of polluted events was more distributed over the day while clean events usually started within 4 hours after sunrise because the clean cases were related to the removal of the nocturnal inversion layer and took place when there was a well-mixed boundary layer. The polluted events partly started after air mass changes, which could take place at any time of the day and could lead to a decrease in condensational sink. [31] Figure 7a shows the diurnal averaged condensational sink corresponding to clean event days, polluted event days, and nonevent days. The averaged condensational sink of clean events was lower than that of polluted events. [32] We can see that the days of polluted events were not really polluted compared to the nonevent days from Figure 7a. The condensational sink was much higher on nonevent days than the polluted events. The averaged condensational sink had a large standard deviation during the nonevent days. The reason was that new particle formation events did not occur on cloudy days even when preexisting particle concentration was low. The condensational 6of10

7 Figure 7. Averaged diurnal variation of (a) condensational sink, (b) RH, (c) SO 2, and (d) temperature on event days and nonevent days in Beijing. sink on nonevent days was significantly higher compared to the event days. A high condensational sink suppressed an observable nucleation by scavenging the fresh nuclei and absorption of condensable vapors [Kerminen et al., 2001; Mönkkönen et al., 2004]. [33] The condensational sink during clean events was slightly higher between 0600 and 1000 hours than between 1000 and 1600 hours. This fact was caused by stronger primary traffic emissions in the morning. The particle formation usually started between 0600 and 1000 hours. The condensational sink decreased before that because the boundary layer development started and reached its minimum during the events. The primary traffic emission caused also an increase of particle precursor concentrations such as SO 2 and NO x. The average concentration of SO 2 is shown in Figure 7c. The standard deviations on nonevent day spanned a wide range because the SO 2 concentration in summer was much lower than winter. The concentration of SO 2 on nonevent days was significantly higher than those of polluted events and clean event days in the daytime. SO 2 was the precursor for sulfuric acid and was most probably involved in new particle formation. The concentration measured in Beijing was highly sufficient for new particle formation during clean and polluted event days. [34] Figures 7b and 7d illustrate the average relative humidity and temperature on clean, polluted, and nonevent days. The average temperature of polluted events was higher than during clean events. The clean events were sometimes connected with a cold front followed by a temperature decrease. The polluted events occurred during stable weather conditions connected with a temperature increase during the day. The diurnal variation of averaged RH during clean event days was similar with polluted events. The RH ranged from 10% to 40% on event days and between 40% and 70% on nonevent days. The nonevent days with higher RH also included rainy days. Lower RH and higher temperature occurred during midday indicating typical sunny event days. [35] Figure 8 illustrates the relationship between the local wind and the number concentrations of 3- to 10-nm particles when new particle formation events occurred. To compare among clean, polluted, and plume events, 3- to 10-nm particle number concentrations as a function of wind direction and wind speed during plume events are also depicted in Figure 8. For the plume events, the winds mainly came from northeast and southeast. In contrast to the plume events, the clean and polluted events depended more on wind direction: clean events relied on wind from north or northwest, while polluted events depended on wind from south or southwest. This observation can be explained by the location of emission sources and remote regions. The north region of Beijing had a low population density and no remarkable industries; thus particle concentrations were low. For such cases resulting in low condensational sink, new particle formation would be expected. In contrast, air masses coming from the south were usually polluted because of various emission sources south of our monitoring site. The main commercial and residential areas of Beijing were located inside the fourth ring road (see Figure 1). So there were several strong sources of primary particulate emissions, such as vehicular traffic, combustion of fuels for domestic cooking and heating, and construction and industry. One important point was the low wind speed (<3 m s 1 ) on polluted event days. Pollutants such as aerosol particles were accumulated while passing the urban areas. However, the occurrence of new particle formation on such polluted days was unexpected and must be caused by a high concentration of condensable vapors. It can be found from Figure 8 that 7of10

8 Figure 8. Number concentrations of 3- to 10-nm particles versus wind speed and wind direction during clean, polluted, and plume event days. clean events are mainly associated with high wind speed (>3 m s 1 ), while polluted events are identified with lower wind speed (<3 m s 1 ). 5. Formation Rate and Growth Rate Calculations [36] Table 1 summarizes the statistical parameters describing new particle formation events, such as formation rate (J 3 ), GR, condensable vapor concentration (C), and their source rate (Q) of clean and polluted events. The condensable vapor was assumed to be sulfuric acid. J 3 was corrected by calculating the losses due to coagulation. [37] The range of formation rate spanned from 3.3 to 81.4 cm 3 s 1, which was comparable with the new particle formation rates (J 3 ) at other locations summarized by Kulmala et al. [2004a], such as in Atlanta (20 70 cm 3 s 1 ) and St. Louis (1 80 cm 3 s 1 ). More recently, Mönkkönen et al. [2005] reported that the range of J 3 in another megacity, New Delhi, was cm 3 s 1, which was smaller than this study. [38] The average formation rate of clean events was slightly higher than that of polluted events. The relatively high condensational sink on polluted event days depleted more condensable vapor, which suppressed the new particle formation. [39] The growth rates varied from 0.1 to 11.2 nm h 1, which were slightly higher than the growth rates (0.5 9nmh 1 ) in Mexico City [Dunn et al., 2004] and smaller than those of New Delhi ( nm h 1 )[Mönkkönen et al., 2005]. The mean growth rate of polluted events was higher than that of clean events. Also, the condensable vapor concentration (C), source rate (Q), and condensational sink of polluted events were higher than those of clean events. [40] On average, the newly formed particles can grow up to 30 nm before being significantly influenced by particles from evening rush-hour traffic and decrease of mixing layer height. The growth rates were relatively low in general; thus in the first moment, the climate relevance was not clear. They should grow at least above 50 nm or better 80 nm. But Table 1. Summary of Parameters Describing Both Cases of New Particle Formation GR, nm h 1 J 3,cm 3 s 1 CVC, molec. cm 3 Q, molec. cm 3 s 1 CS a,s 1 Parameters Types C P C P C P C P C P Mean Stdev Median % Quartile % Quartile Min Max a Mean condensational sink during each event was used here. C means clean event while P means polluted event. 8of10

9 Figure 9. Comparison between four seasons for condensable vapor concentration (C) and their source rate (Q), condensational sink (CS), and corresponding ambient temperature when the event started. Median, mean, min, max, 25%, and 75% percentiles are shown for all four seasons. for the higher GR (>6 nm h -1 ) and constant cases, they grow easily above 50 nm. There were 16 cases with higher GR (>6 nm h 1 ) observed during 1 year measurement. [41] Mean source rate of condensing vapor was typically higher (four times) for polluted events than for clean events. This was mainly due to the fact that polluted events cannot occur without significant vapor production to make small cluster to grow to nuclei mode and further to Aitken mode. [42] Figure 9 illustrates comparison between four seasons for C, Q, CS, and temperature based on the 1-year data set. The seasonal variation of condensable vapor concentration was similar to vapor production rate; both were significantly higher in summer. The reason is not only the enhancement of photochemical and biological activities during summer months but also the stagnant air masses preventing exchange with cleaner air in summer in Beijing. The condensational sink during the event in summer was slightly higher than during other seasons. Higher condensable vapor source rates and CS during summertime were also observed by Dal Maso et al. [2005] based on 8 years of data. 6. Conclusion [43] One-year continuous measurements were conducted in Beijing from March 2004 to February New particle formation events with bursts in 3- to 10-nm particles were observed on 40% of the measurement days, excluding the plume events caused by plumes of nearby sources. New particle formation events were observed on sunny days with low humidity. The new particle formation events occurred most frequently in spring while significantly lower in summer because of dominating influence of more polluted air masses advected from the south. New particle formation events were classified into clean and polluted groups. Clean events were connected with northerly wind, whereas polluted events were associated with wind from the south or southwest. Polluted events were associated with higher condensational sink. [44] The range of formation rate spanned from 3.3 to 81.4 cm 3 s 1. The growth rate varied from 0.1 to 11.2 nm h 1. Condensable vapor concentration and source rate are significantly higher during summertime. The explanation was that photochemical activity and biological activity were enhanced in summer. In addition, stagnant air masses prevented an exchange with cleaner air. [45] Acknowledgments. This work was supported by the National Natural Science Foundation of China ( ), the National Basic Research Program (2002CB211605) (from the Ministry of Science & Technology, China), and the Deutsche Forschungsgemeinschaft (DFG, WI 14449/9-1). The authors would like to thank Xiaoyang Liu and Jietai Mao for providing meteorological data. References Alam, A., J. P. Shi, and R. M. Harrison (2003), Observations of new particle formation in urban air, J. Geophys. Res., 108(D3), 4093, doi: /2001jd Birmili, W., and A. Wiedensohler (2000), New particle formation in the continental boundary layer: Meteorological and gas phase parameter influence, Geophys. Res. Lett., 27(20), Birmili, W., H. Berresheim, C. Plass-Dülmer, T. Elste, S. Gilge, A. Wiedensohler, and U. Uhrner (2003), The Hohenpeissenberg aerosol formation experiment (HAFEX): A long-term study including sizeresolved aerosol, H 2 SO 4, OH, and monoterpenes measurements, Atmos. Chem. Phys., 3, Dal Maso, M., M. Kulmala, I. Riipinen, R. Wagner, T. Hussein, P.P. Aalto, and K. E. J. Lehtinen (2005), Formation and growth of fresh atmospheric aerosols: Eight years of aerosol size distribution data from SMEAR II, Hyytiälä, Finland, Boreal Environ. Res., 10(5), Dunn, M. J., J. L. Jiménez, D. Baumgardner, T. Castro, P. H. McMurry, and J. N. Smith (2004), Measurements of Mexico City nanoparticle size distributions: Observations of new particle formation and growth, Geophys. Res., 31, L of10

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Box 64, FI-00014, Finland. M. Hu, S. Liu, and Z. Wu, State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences, Peking University, Beijing , China. (minhu@pku.edu.cn) 10 of 10