Scanning supersaturation CPC applied as a nano-CCN counter for size-resolved analysis of the hygroscopicity and chemical composition of nanoparticles

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Introduction
New particle formation (NPF) and subsequent growth have been intensively studied owning to their important roles in air pollution and climate (Kulmala et al., 2000(Kulmala et al., , 2013(Kulmala et al., , 2014;;Kerminen et al., 2012;Zhang et al., 2012).Chemical composition of the newly formed particles is key to understand the production and transformation of atmospheric aerosol particles.A number of apparatuses have been developed to analyze the chemical compositions of ultrafine particles (Fig. 1).Despite these progresses, there is still Introduction

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Full a gap in the size range of 1-10 nm where chemical composition can be hardly measured.
The ability of aerosol particles to serve as cloud condensation nuclei (CCN), i.e., to initiate the formation of droplets by condensation of water vapor, is closely linked to their chemical composition.Size-resolved measurements have shown that atmospheric aerosol particle hygroscopicity and CCN activity are closely correlated with particle composition expressed as organic and inorganic mass fractions determined by aerosol mass spectrometry (Dusek et al., 2006(Dusek et al., , 2010;;Gunthe et al., 2009Gunthe et al., , 2011;;Jurányi et al., 2010;Rose et al., 2010Rose et al., , 2011Rose et al., , 2013;;Cerully et al., 2011;Lance et al., 2013;Lathem et al., 2013;Mei et al., 2013;Wu et al., 2013).Hygroscopicity distributions derived from size-resolved CCN measurements also provide insight into the mixing state of aerosol particles (Lance, 2007;Su et al., 2010).Widely used CCN counters based on the continuous-flow thermal gradient technique can potentially measure at water vapor supersaturations up to 6 % (S = (saturation ratio − 1) × 100 %; Lance et al., 2006).Traditionally, however, atmospheric CCN measurements were mostly focusing on supersaturations less than ∼ 1 % corresponding to particle sizes above ∼ 30 nm as referenced above.For the activation of sub-10 nm particles, higher levels of water vapor supersaturation are required as shown in Fig. 2 as a function of particle size and hygroscopicity.In the atmosphere, supersaturations > 1 % are less common but do occur in convective clouds (Pruppacher and Klett, 1997), especially at low aerosol concentrations and high updraft velocities (aerosol-limited regime of CCN activation; Pöschl et al., 2010).
In this study, we present the concept of a nano-CCNC for measuring hygroscopicity and inferring chemical composition of nanoparticles in the diameter range of ∼ 2-10 nm.The method builds on recent progresses in size-resolved CCN measurements of ultrafine aerosol particles as referenced above.We first explain the theoretical basis, instrument setup and the data retrieval methodology.Subsequently, we report experimental data for a proto-type nano-CCNC and its performance in discriminating Figures

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Full The activation of sub-10 nm particles with water vapor requires a higher supersaturation S, which goes beyond the measurement range of most CCN counters, but falls into the range of water-based condensation particle counters (CPC).The water CPC is based on a similar working principle as a CCNC but running at a much higher S. High S reduces the critical activation size of particles so that "almost all" interested particles can be activated and detected (McMurry, 2000b, a).In theory, the counting efficiency curve of CPC is the same as the activation curve of CCNC, but extended to smaller size ranges (Fig. 3).
In practice, CPCs and CCNCs have different applications by making use of different parts of their activation curves.As shown in Fig. 3, the CPC is mainly used for the accurate particle counting, ideally operated at size ranges with activation fractions (F act ) equal to 1.The size-resolved CCN measurements are often designed to determine the whole activation curves, especially the composition-sensitive parts with F act varying between 0 and 1.

Design and operation of nano-CCNC
Our nano-CCNC system adopted a similar design from previous size-resolved CCN measurements (Rose et al., 2008;Moore et al., 2010).It comprises of a nanodifferential mobility analyzer (nano-DMA, TSI model 3085), a total particle counter (electrometer or ultrafine CPC with smaller critical detection size) and a nano-CCNC along with drying system and a neutralizer (TSI model 3077).The nano-CCNC is a water-based CPC with a control unit regulating the scan of S. Introduction

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Full The measuring protocol of nano-CCNC is (1) to use a nano-DMA to select monodisperse particles of certain dry diameter (D d ); and (2) to measure the number concentration of total particles (N tot ) by the total particle counter and activated particles (N act ) at varied S by SS-CPC, respectively.This results in a size and superaturation-resolved activation fraction, F act = f (D d , S).By scanning D d and S, the whole 3-D activation spectra over the D d −S plane can be achieved (Su et al., 2010).In practice, people can first keep D d constant and vary S, then select another value of D d and iterate the procedure as the "S scan" mode in CCN measurements (Dusek et al., 2006;Moore and Nenes, 2009;Snider et al., 2010).Alternatively, we could also first keep S constant and vary D d as the "D d scan" mode (Petters et al., 2009;Wiedensohler et al., 2009;Rose et al., 2011).
The scan of S can be achieved by scanning the temperature gradient between the saturator and growth tube (by changing the saturator or growth tube temperature; Mordas et al., 2008;Kupc et al., 2013) or scanning the aerosol flow rate of the CPC (Gallar et al., 2006;Wimmer et al., 2013).The former approach, however, has not been actively pursued partly due to the relatively slow thermal response, limiting the time resolution of measurement to tens of minutes with current CPCs (McDermott et al., 1991).However, if we are only interested in a narrow size ranges, i.e., sub-10 nm or even a single size, it is still a feasible option, because relatively small number of sizes needs to be scanned.The scanning flow approach has better time resolution.In the work of Gallar et al. (2006), the flow scan is achieved by varying the mixing ratio of saturator and dilution air and their main purpose is to obtain particle size spectrum.After using fast-response flow controllers, time response of CPC (with a perfluorinated organic compound as the working fluid) could reach ∼ 1 s to the change of supersaturation.

Measurement procedure and data analysis
Concerning the application of nano-CCNC, we proposed the following procedure as shown in Fig. 4b.The first step is to characterize the calibration curve, i.e., the cumulative supersaturation distribution that aerosol particles experienced in the CPCs, which Introduction

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Full will then be used to determine the characteristic activation supersaturation of aerosol samples for inferring chemical composition.

Determination of supersaturation distribution
For particles of the same composition, their ideal activation curves would be a step function according to the Köhler theory.However, the observed activation curves in Fig. 3 turn out to be a rather broad distribution.The broadening of the activation curves can be attributed to (1) the non-uniform S that particles have been exposed to in the CPC, (2) the transfer function of DMA, especially for smaller nanoparticles due to diffusional effects (Stolzenburg, 1988), and (3) the doubly/multiply charged particles.The influence of doubly/multiply charged particles can be minimized by carefully adjusting the size distribution of calibration aerosols (so that the investigated diameter lies on the right side of the mode diameter of calibration aerosols).The diffusion of nanoparticles in the CPC causes the non-uniformity of exposed S, which results in a broadening effect much larger than that from the DMA transfer function.For example, at particle diameter of ∼ 2-3 nm, the DMA transfer function (TSI nano-DMA model 3085) only contributes to ∼ 36 % of the overall broadened width while the rest can be attributed to the non-uniformity of S. The value of 36 % is calculated from a ∼ 18 % NFWHM (normalized full-width at half-maximum) of the DMA transfer function (Chen et al., 1998;Stolzenburg and McMurry, 2008;Jiang et al., 2011b) and a ∼ 50 % NFWHM for the observed activation curves (Kupc et al., 2013).
Figure 5 explains the origin of non-uniformity of exposed S in the CPC.In the aerosol activation unit (growth tube, Fig. 5a), S is not evenly distributed and the maximum S appears in the centerline (Fig. 5b).Though a sheath flow is used to focus the aerosol samples, the paths of nanoparticles could still deviate from the centerline due to dispersions (Stolzenburg and McMurry, 1991).Thus particles of the same properties can either be activated or not depending on its exposed S (only the portion of particles that experienced S higher than its critical supersaturation (S cri ) can be activated, Fig. 5d).That is why a broadened activation curve was observed instead of a step function as 11142 Introduction

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Full shown in Fig. 3.The S distribution that particles experience depends on the spatial distribution of S in the CPC and the path taken by the particles.By assuming a dominant role of S non-uniformity in the broadening effect, we have the following a mathematical expression for the observed activated fraction F act (D d ): where H(S) can be regarded as the a cumulative distribution function (CDF) of effective S inside the CPC (i.e., the fraction of particles experiencing a supersaturation lower than or equal to the value of S); n N (S) is the aerosol number distribution as functions of its critical activation supersaturation; Then we have the value of the cumulative distribution function at By changing S cri of aerosol samples, we could scan through the S space and get the whole distribution of H(S).In practice, the scanning of supersaturation can be achieved by scanning D d .Equation ( 2) is actually suggesting that the supersaturation distribution H(S) that aerosol particles experience in the CPC can be determined from counting efficiency spectra of compounds whose activation function is known (so that S cri can be directly calculated from D d based on the Köhler equation).Introduction

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Determination of characteristic supersaturations
Once the whole distribution H(S) = f (S) is determined, the characteristic activation S for a monodisperse unknown compounds can be directly calculated from its inverse function: Equation ( 3) refers to monodisperse particles of a single activation S. It becomes more complicated when monodisperse particles with multiple activation supersaturations are considered (externally mixed aerosol particles).The mathematical solution to this problem is explained as follows.By discretizing the right hand side of Eq. ( 1) into J bins, we have F act as a linear combination of n * N where j denotes the bin number of S; i denotes the i th H(S) distribution (because we can measure the same kind of aerosol particles with CPCs of different H).The a i ,j and x j are introduced here for simple illustration, in which a i ,j is a known parameter, a i ,j = (1 − H i (S j ))∆S and x j = n * N is an unknown.Finally, n N * can be solved by constructing a series of independent equations, i.e. total number of i , I, should meet the equation with: I ≥ J.A complete data retrieval method will be presented in a following paper, in which the DMA transfer function, size dependence of H(S), particle shape factors and mixing states will be considered along with the S distribution.

Ambient measurement
With a given activation fraction F act , we can infer the S cri from the supersaturation distribution H(S).However, in most cases, the low concentration/count of sub-10 nm particles challenges our instrument because the electrometer can only be operated reliably 11144 Introduction

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Full at high concentration level (> 1000 cm −3 ; Wiedensohler et al., 1994), which is basically never the case for size-resolved measurement at ambient condition.To overcome this problem, we propose the use of relative activation ratio R H/H 0 , which is defined as the ratio of activation fraction at one H(S) distribution to that of the other H 0 (S) distribution: in which T and T 0 correspond to the different saturator temperature T s , N act,T and N act,T 0 are CPC counts at T and T 0 , respectively.On the other hand, R H/H 0 can be determined from two H(S) characterized by calibration aerosols: Then the same as Eq. ( 2), once R H/H 0 is measured, we can determine: According to Eq. ( 5), R H/H 0 can be measured by two CPCs with different saturator temperature.Electrometer is not needed in this case and the corresponding detection limit problem no longer exists.

Results and discussion
In the following sections, we will demonstrate the proposed methods with laboratory experimental data for different aerosol particles.We first used tungsten oxide (WO x ) particles for the determination of H(S), and then calculated the characteristic S cri for different kinds of 2.5 nm particles.Introduction

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Supersaturation distribution
In this study, WO x particles, produced by a WO x generator (Grimm Aerosol Technik, Nano WO x -generator, model 7.860; Wimmer et al., 2013), was used to determine the H(S) under different saturator temperatures.As demonstrated in Fig. 4a, a water-based CPC (TSI model 3788) was used as a SS-CPC to measure N act and a Faraday Cup Electrometer (Grimm Aerosol Technik, model 5.705) was used to measure N tot .The S distribution that particles experienced inside the water-based CPC, H(S), was achieved by measuring the counting efficiency spectra from 2 to 10 nm.Seven H(S) distributions were measured with saturator temperature (T s ) varying from 284 to 296 K, while the growth tube temperature (T gt ) was fixed at 348 K.Each temperature adjustment takes 150 s for stabilization.Following Eq. ( 2), we retrieve H(S) from the counting efficiency spectra for WO x particles (Fig. 6).As expected, H(S) was changed considerably by tuning the saturator temperature.Increasing the saturator temperature will reduce the temperature gradient and the supersaturation inside the growth tube.During the data retrieval process, we found that the activation curves for WO x particles represent a bimodal distribution.The following expression of a bimodal lognomal CDF was used to fit the activation curves: Here, "erf" is the Gauss error function, a is the number fraction for one mode, D 1 and D 2 are the geometric mean values of particle diameter, and σ 1 and σ 2 are the standard deviations of the cumulative Gaussian distribution function.
For the conversion of D d to S cri , we adopt the multilayer adsorption theory accounting for the very low solubility and hygroscopicity for WO x particles.The basic idea is to include an adsorption isotherm (FHH (Frenkel, Halsey and Hill) isotherm in this study) Introduction

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Full in the traditional Köhler theory instead of the solute term: where σ is the surface tension; D is the diameter of solution droplet; M w and ρ w are the molar mass and density of water; R is the universal gas constant and T is absolute temperature.The parameter A characterizes interactions between adsorbed molecules and between the surface and adjacent adsorbate molecules and B characterizes the attraction between the solid surface and the adsorbate in subsequent layers.For further details concerning the derivation and explanation of Eq. ( 9), we refer the reader to Sorjamaa and Laaksonen (2007).The evaluation of parameters A and B in Eq. ( 9) are determined by the best fitting between measured and calculated activated fractions F act for ammonium sulfate (AS) particles at 2.5 nm (Fig. 7), with values of 0.1 and 2.1, respectively.These values are located in the range of previous literature reports (0.1 < A < 3, 0.5 < B < 3; Sorjamaa and Laaksonen, 2007, and references therein).Our calculations suggest that with the appropriate parameter values, the activated fractions can be well predicted by the modified Köhler equation with FHH isotherm for the insoluble particles.For sodium chloride (NaCl) particles, it is difficult to predict F act due to its uncertain shape factor.However, if we assume the volume equivalent diameter of ∼ 2.1 nm, we will get similar results as shown in Fig. 7.

Characteristic S for 2.5 nm particles
For the determination of S cri , we choose 2.5 nm as the target diameter and select monodisperse NaCl, AS and sucrose particles as examples.An electrospray aerosol generator (TSI model 3480) was used to produce their nanoparticles.All solutions were prepared in a standard 20 mM ammonium acetate buffer solution with a conductivity of 0.2 S m −1 (siemens per meter; Chen et al., 1995;Kupc et al., 2013).The activation Introduction

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Full fractions were determined from results of the electrometer and SS-CPC.Seven saturator temperatures from 284 to 296 K were tested in our experiments.Figure 8a shows distinct activation curves of various chemical compounds at 2.5 nm.For the same T s (or H(S)), NaCl shows the highest activation fraction F act while WO x shows the lowest, which is consistent with their hygroscopicities.To reach the same F act as NaCl, AS would require a ∼ 4 K lower T s , i.e., a larger temperature gradient and S while a further lower T s (∼ 10 K) is needed for sucrose.Such difference in the temperature gradient is significant enough in discriminating the investigated nanoparticles, much higher than the instrument noise ∼ 0.1 K.The Hygroscopic Tandem Differential Mobility Analyzer (HTDMA) has been applied with D d down to ∼ 6 nm (Biskos et al., 2006a, b;Swietlicki et al., 2008), while size-resolved measurements by traditional CCN counters are limited to D d > 30 nm as aforementioned.We now push this limit down to 2.5 nm.
Figure 8b shows the calculated S cri for various chemical compounds at 2.5 nm.Good agreement between the estimated and theoretical supersaturation has been achieved for AS particles, as indicated in Fig. 7.In summary, our results demonstrate that based on the determined H(S) distributions, the chemical compounds with different hygroscopicity can be separated distinctly, especially between representative inorganic (AS, S = 55 % ± 5 %) and organic (sucrose, S = 67 % ± 1 %) compounds.
As aforementioned, the detection sensitivity of the electrometer precludes its application in ambient measurement.We suggest using the relative activation ratio R H/H 0 as an alternative parameter.As shown in Fig. 9, different compounds (NaCl, AS, sucrose and WO x ) exhibit distinct R H/H 0 distributions (the ratio of F act,T to F act,11 • C ). Their characteristic S cri can also be determined from R H/H 0 by Eq. ( 5).It has been suggested that the major compositions of newly formed particles are sulfate and organics (Zhang et al., 2012;Almeida et al., 2013;Ehn et al., 2014), which corresponds to the envelope between the AS and WO x profiles in Fig. 9. Introduction

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Solvoscopicity and SS-CPCB
The concept of scanning supersaturation (SS) is not limited to water-based CPCs, and may also work for CPCs with other working fluids.In analogy to aerosol "hygroscopcity" describing the affinity for water, we introduce the term "solvoscopicty", which from a broad sense, is the ability of a substance to attract and hold solvent molecules.
Substances showing higher solvoscopicity for one working liquid may have lower solvoscopicity for another working liquid (Kangasluoma et al., 2014).For example, Fig. 10a  and b show that NaCl is more hygroscopic (higher S cri and lower D cri ) than Ag but become less "solvoscopic" in butanol vapor.
The solvoscopic parameter can be used as "footprint" to estimate/distinguish the aerosol composition.However, it does not work once different substances show similar solvoscopicities, e.g., as sucrose and emery oil in butanol (Fig. 10c).This problem can be solved by performing additional measurements with water-based CPC, in which sucrose and emery oil show distinct hygroscopicities.Therefore, we suggest running multiple CPCs with different working fluids in a SS mode, which gives a SS-CPCB (SS-CPC battery) system.Compared to a single SS-CPC, SS-CPCB results in a multiple dimension of S cri enabling better inference of chemical composition.As shown in Fig. 10c, different inorganic and organic substances as well as metal can be easily distinguished in the 2-D solvoscopiciy matrix.Compared to earlier applications of (nano-)CPCB (Kulmala et al., 2007;Riipinen et al., 2009;Kangasluoma et al., 2014), the SS-CPCB system could provide size-resolved solvoscopicity information for each working fluid, while CPCB present integrated information over certain size ranges.

Conclusion and outlook
In this study, we present the theoretical basis and design of a nano-CCN counter for the purpose of hygroscopicity measurement in the nano size range (sub-10 nm).The basic concept is to operate a water-based CPC in a scanning supersaturation mode Introduction

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Full as a CCNC, recording a composition-dependent activated spectrum and retrieving the solvoscopicity parameter/distribution.The proof-of-principle experiments were carried out with 2.5 nm sodium chloride, ammonium sulfate, sucrose and tungsten oxide particles, which show a clear composition dependency and reproducibility of the activation spectra.By using calibration aerosols (WO x ), we show the importance of using activation fraction F act (D d ) of aerosol samples to calibrate H(S) inside CPC at different saturator temperatures and its use in further retrieval of aerosol hygroscopicities.
Though termed as nano-CCNC, the design is not limited to the water-based CPC, but also applies to CPCs with other working fluids.We introduce the term "solvoscopicty" to describe the ability of a substance to attract and hold solvent molecules.Substance solvoscopicity might vary in different working fluids.Compared with single SS-CPC, the SS-CPCB, a combination of CPCs with multiple working fluids in a SS mode, might hence provide further insight into the chemical composition of nanoparticles.
In addition, pulse-height spectral analysis has been used to investigate the chemical composition of newly formed particles (Marti et al., 1996;Saros et al., 1996;Weber et al., 1998;O'Dowd et al., 2004;Gallar et al., 2006).The combination of activation fraction and pulse-height spectra will be explored in our future study.Introduction

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Full Thermal desorption chemical ionization mass spectrometer (TDCIMS;Smith et al., 2004) and nano aerosol mass spectrometer (NAMS; Wang and Johnston, 2006) are commonly used at 10-30 nm particles.Analysis of molecular clusters with diameter up to ∼ 1 nm has been achieved by cluster chemical ionization mass spectrometry (Cluster-CIMS; Zhao et al., 2010;Jiang et al., 2011a) and chemical ionization with the atmospheric pressure interface time-offlight mass spectrometer (CI-APi-TOF; Jokinen et al., 2012).The use of scanning supersaturation CPC as nano-CCNC introduced in this study shall help to close the gap of 1-10 nm.Introduction

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Full     .The green and blue circles represent the results for sodium chloride (NaCl) and ammonium sulfate (AS) particles, respectively.The CPC was operated with a growth tube temperature and a saturator temperature of 78 and 8 • C, respectively (Mordas et al., 2008).The CCNC was operated with a temperature difference of 4.5 K across the growth chamber (Moore et al., 2010).Introduction

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Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | different substances.Finally, we discuss potential applications of the nano-CCNC in field and laboratory experiments in combination with other techniques.
Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | n N (S)dS equals number concentration of particles in the critical supersaturation range of S to S + dS and n * N (S) = n N (S)/N tot is the normalized distribution.According to the Köhler theory, particles of identical size and composition have the same critical supersaturation S cri and the corresponding n * N (S) becomes a Dirac delta function, or δ function.Substituting n * N (S) = δ(S − S cri ) into Eq.(1) gives Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Dusek, U., Frank, G. P., Hildebrandt, L., Curtius, J., Schneider, J., Walter, S., Chand, D., Drewnick, F., Hings, S., Jung, D., Borrmann, S., and Andreae, M. O.: Size matters more than chemistry for cloud-nucleating ability of aerosol particles, Science Discussion Paper | Discussion Paper | Discussion Paper | (CPCB): a new tool to investigate the activation properties of nanoparticles, J

Figure 1 :Figure 1 .
Figure 1: Size ranges of different measurement instruments in atmospheric aerosol 694 research.The year when each technique was first reported is indicated on the 695 left-hand side.Aerosol mass spectrometer (AMS) can measure particles with 696 diameters down to ~40 nm (Jayne et al., 2000 and updated references on 697 http://cires.colorado.edu/jimenez/ams-papers.html).Thermal desorption chemical 698 ionization mass spectrometer (TDCIMS; Smith et al., 2004) and nano aerosol mass 699 spectrometer (NAMS; Wang and Johnston, 2006) are commonly used at 10-30 nm 700 particles.Analysis of molecular clusters with diameter up to ~1 nm has been achieved 701 by cluster chemical ionization mass spectrometry (Cluster-CIMS; Zhao et al., 702 Discussion Paper | Discussion Paper | Discussion Paper |

Figure 2 :
Figure 2: Critical water vapor supersaturation for the activation of particles with different dry diameter and chemical composition.The color bar indicates the κ values.The open circles are reference of water droplet.

Figure 2 .
Figure 2. Critical water vapor supersaturation for the activation of particles with different dry diameter and chemical composition.The color bar indicates the κ values.The open circles are reference of water droplet.

Figure 3 :
Figure 3: The symmetry between counting efficiency of a CPC (condensation particle counter, TSI model 3786) and the activation curve of a CCNC (cloud condensation nuclei counter, DMT CCNC).The green and blue circles represent the results for sodium chloride (NaCl) and ammonium sulfate (AS) particles, respectively.The CPC

Figure 3 .
Figure3.The symmetry between counting efficiency of a CPC (condensation particle counter, TSI model 3786) and the activation curve of a CCNC (cloud condensation nuclei counter, DMT CCNC).The green and blue circles represent the results for sodium chloride (NaCl) and ammonium sulfate (AS) particles, respectively.The CPC was operated with a growth tube temperature and a saturator temperature of 78 and 8 • C, respectively(Mordas et al., 2008).The CCNC was operated with a temperature difference of 4.5 K across the growth chamber(Moore et al., 2010).
Discussion Paper | Discussion Paper | Discussion Paper |

Figure 4 :
Figure 4: Schematics of the (a) laboratory calibration and (b) data analysis procedure for a SS-CPC used as nano-CCNC (section 2.3 in the text).

Figure 4 .Figure 6 :
Figure 4. Schematics of the (a) laboratory calibration and (b) data analysis procedure for a SS-CPC used as nano-CCNC (Sect.2.3 in the text).

Figure 6 .
Figure 6.(a) Detection efficiencies of the SS-CPC (filled symbols) for WO x particles.The waterbased CPC 3788 was operated with a constant temperature of growth tube (T gt ) and the varied temperatures of the saturator (T s ).The different colored lines are fits of a bimodal lognomal cumulative Gaussian distribution function (Eq.8) to the experimental points, corresponding to the different saturator temperatures.(b) Cumulative supersaturation distribution H(S) inside CPC retrieved from the activation curve F act (D d ) based on Eq. (2).The colored solid lines indicate the different saturator temperatures, which are in line with (a).

Figure 9 .Figure 10 .
Figure 9. Profiles of relative activation ratio as a function of saturator temperature.The critical supersaturations for NaCl, AS, sucrose and WO x are average values at seven saturator temperatures.The dash dot lines represent the compounds with critical supersaturation in the range of 57 to 75 %, during which is indicative of ambient nanoparticles.