Activation capability of water soluble organic substances as CCN

Aerosol Science 34 (2003) 419 – 448 www.elsevier.com/locate/jaerosci

Activation capability of water soluble organic substances as CCN Masahiro Horia;∗ , Sachio Ohtab , Naoto Muraob , Sadamu Yamagatab a

Earth Observation Research Center, National Space Development Agency of Japan, 1-8-10, Harumi, Chuo-ku, Tokyo 104-6023, Japan b Division of Environment and Resources Engineering, Hokkaido University, Sapporo 060-8628, Japan Received 5 June 2002; accepted 7 November 2002

Abstract The activation capability of seven dicarboxylic acid compounds, ammonium oxalate, malonic acid, succinic acid, glutaric acid, adipic acid, malic acid and phthalic acid, was determined by laboratory experiments, and predictability by the K4ohler theory was discussed. Experimental results showed that ammonium oxalate had the highest capability comparable to that of ammonium sulfate, and malic acid and phthalic acid followed, whereas adipic acid exhibited the lowest capability close to that of an insoluble particle. Malonic acid and glutaric acid were considered to evaporate under normal experimental operations at 8–9% RH but exhibited high and moderate capability, respectively, under supplementary humid operations. The activation capability of succinic acid tended to depend on the laboratory temperatures but was possibly high, comparable to that of malic acid. Particulate drying, associated solute vaporization, morphology and hydrophobicity of particles could be key factors in the theoretical prediction and the interpretation of the experimental results. ? 2003 Elsevier Science Ltd. All rights reserved. Keywords: Aerosol; Polar organics; Dicarboxylic acid; Activation; CCN

1. Introduction Water soluble substances reduce the equilibrium water vapor pressure at the surface of aqueous solution droplets and grow into large droplets under supersaturated condition (Mason, 1971; Pruppacher & Klett, 1997). The particles that can be activated into cloud droplets preferentially at supersaturation below 1% are called cloud condensation nuclei (CCN), and the CCN concentrations ∗

Corresponding author. Tel.: +81-3-6221-9070; fax: +81-3-6221-9192. E-mail address: [email protected] (M. Hori).

0021-8502/03/$ - see front matter ? 2003 Elsevier Science Ltd. All rights reserved. doi:10.1016/S0021-8502(02)00190-8

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are strongly associated with the number density of cloud droplets in the atmosphere through aerosol– cloud interaction. Thus, perturbation of the CCN number can have a large impact on the optical properties of clouds and hence, on a climate change such as global warming (Twomey, 1991; IPCC, 1996). To assess the impact, identiFcation of the aerosol compounds eGectively acting as CCN is one of the most important and urgent subjects to be investigated. Some inorganic aerosols such as non-seasalt sulfate and seasalt have been known as ubiquitous compounds in the atmosphere and the most eGective CCN as well (Pruppacher & Klett, 1997). In particular, sulfate can be found as a major compound everywhere on the globe, and its CCN ability can be predicted by the K4ohler theory (H4anel, 1976). Past experimental studies have already veriFed the success of the theoretical prediction for those compounds (Gerber, Hoppel, & Wojciechowski, 1977). Soot particles generated from fossil fuel and biomass burning were also examined by experimental studies on their CCN ability (Lammel & Novakov, 1995; Weingartner, Burtscher, & Baltensperger, 1997). The results showed that the larger the sulfur contents in fuel were and the older the soot particles became, the more the CCN ability was enhanced. Recent studies on chemical characterization of atmospheric aerosols showed that organics were also among the major compounds in Fne particles comparable to sulfate all over the world (e.g., Heintzenberg, 1989; Ohta & Okita, 1990; Novakov et al., 1997), and about 50% of the total carbon was found to be water soluble polar organic compounds (Mueller, Fung, Heisler, Grosjean, & Hidy, 1982; Sempere & Kawamura, 1994). In particular, low molecular weight dicarboxylic acids were identiFed as one of the major water soluble organics in aerosols in both urban and rural areas (Rogge, Mazurek, Hildemann, Cass, & Simoneit, 1993; Kawamura & Ikushima, 1993; Kawamura & Usukura, 1993; Sempere & Kawamura, 1994; Hori, Ohta, Murao, & Yamagata, 1999). In addition, observational studies on the relationship between CCN number and mass size distribution of aerosol constituents suggested that water soluble organic substances could also contribute signiFcantly to the CCN number (Novakov & Penner, 1993; Matsumoto et al., 1998). Liu et al. (1996) revealed that CCN concentrations were signiFcantly associated with mass concentrations of oxalate which is often found to be a prevalent component among dicarboxylic acids. Recently, the current knowledge of the role of several organic acids in the formation of CCN was reviewed by Yu (2000), and their possible signiFcant contributions to CCN number were addressed again. That is why recently many studies have been focusing on laboratory veriFcations of the CCN capability of water soluble organic substances. Cruz and Pandis (1997) measured critical supersaturations of glutaric acid and adipic acid using diGerential mobility analyzers (DMA) to obtain monodisperse particles and showed that particles of around 0.055 –0:058 m in radius in both compounds were activated at a supersaturation of 0.3% whether or not the solute solubility is high. Cruz and Pandis (1998) revealed that the CCN ability of sulfate particles was enhanced when the particles were coated with glutaric acid. Corrigan and Novakov (1999) determined the activation diameters at which the CCN/CN ratio reached 0.50 for succinic acid, adipic acid and glucose particles at a supersaturation of 0.4%, 0.5% and 0.8% using DMA. Their results indicated that CCN ability correlated with solute solubility and that the resulting CCN ability of adipic acid was substantially lower than that of Cruz and Pandis (1997). The disagreement seen for adipic acid was attributed, as a possibility, to a possible diGerence in morphology of the particles generated in the two studies. They mentioned that the morphology of the slightly soluble particles generated by the atomization could deviate from a solid sphere, and thus the non-sphericity could be an important factor in determining the activation diameters when using DMA. Prenni et al. (2001) investigated the hygroscopic behavior of oxalic

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421

acid, malonic acid, succinic acid, glutaric acid and adipic acid using a DMA system and determined the critical supersaturations for 0:05 m radius particles. Their results for glutaric acid correlated well with those of Cruz and Pandis (1997). As for succinic acid and adipic acid, however, the three past experimental results do not correlate well. In particular, large disagreements can still be seen for adipic acid. Hegg et al. (2001) tested the CCN ability of pinonic acid and the oxidation products of cyclohexene and -pinene, and showed that CCN ability depended on solubility even in the case of the oxidation products. Several studies can also be found on a more speciFc topic of the surface tension reduction eGect by polar organic substances. Shulman, Jacobson, Carlson, Synovec, and Young (1996) measured the surface tensions of aqueous solutions for several dicarboxylic acids in the laboratory and simulated the condensation growth of sulfate solutions mixed with dicarboxylic acids. The results indicated that dicarboxylic acids reduced the surface tension of the solution droplets, and thus the dissolution of dicarboxylic acids into sulfate solutions promoted droplet growth through the suppression of the Kelvin eGect. Facchini, Mircea, Fuzzi, and Charlson (1999) also observed that a signiFcant surface tension reduction from pure water was caused in cloud water by surface-active organic compounds. Shulman, Carlson, and Davis (1997) investigated the eGect of surface-active organic compounds on the evaporation rate of their solution droplets and found that the surface-active solutes inLuenced the rate of water transport in a manner comparable to that of ammonium sulfate. The eGect of slowing evaporation could be accomplished with a lesser amount of material in the cases of the organic compounds than in the case of ammonium sulfate. To realize a more realistic simulation of the hygroscopic behavior of particles, Laaksonen, Korhone, Kumala, and Charlson (1998) reformulated the classical K4ohler theory to include the eGect of soluble gases and slightly soluble inorganic core substances and indicated the possibility of the occurrence of stable unactivated droplets with radii of up to 10 m, which was shown by the equilibrium curves with some local minima and maxima. The results suggest that growth and activation of slightly soluble substances could be more complicated than that predicted by the conventional K4ohler equation even in the cases of inorganic substances. In this way, the hygroscopic behavior of water soluble organic substances, particularly that of dicarboxylic acids, has been studied recently by experimental and theoretical approaches, focusing on the eGects of solute solubility and surface tension reduction. As stated above, however, there is still not complete agreement in the past experimental critical supersaturations for several organic compounds. No theoretical approaches can yet simulate the exact activation capability of surface active polar organic substances due to insuMcient availability of data on the surface tension properties (Laaksonen et al., 1998). Hence, there is a further need for laboratory studies with various approaches in order to increase the reliability of the past experimental results and accumulate knowledge on the CCN activation. Low molecular weight dicarboxylic acids have diGerent physicochemical properties such as solubilities, melting and boiling points alternately with the number of carbon atoms in the carbon chain, i.e., an odd–even eGect (Burrows, 1992). Whereas odd carbon number members such as malonic acid and glutaric acid can deliquesce below 100% RH and are suMciently water soluble comparable to ammonium sulfate, even members such as succinic acid and adipic acid are slightly soluble and cannot initiate apparent deliquescence below the saturated condition (Prenni et al., 2001). Rather, the even members exhibit a hydrophobic nature with a large contact angle for water, which can be observed with an optical microscope by placing the bulk materials under a highly humid condition.

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Therefore, the hygroscopic behavior of even members, particularly at the early stages of condensation growth, is likely to diGer from that predicted by the conventional K4ohler theory which was derived on the assumption of the complete dissolution of the solute material into a spherical solution droplet from the beginning of the condensation (K4ohler, 1936). In this study, we investigated the activation capability of seven low molecular weight dicarboxylic acid compounds that have been identiFed frequently in the past aerosol samples: ammonium oxalate monohydrate ((COONH4 )2 · H2 O), malonic acid (HOOCCH2 COOH), succinic acid (HOOC(CH2 )2 COOH), glutaric acid (HOOC(CH2 )3 COOH), adipic acid (HOOC(CH2 )4 COOH), (DL-)malic acid (HOOCCH(OH)CH2 COOH) and phthalic acid (HOOCC6 H4 COOH). In addition, sodium chloride and ammonium sulfate were also examined in the same manner as dicarboxylic acids to validate the employed experimental system. Several physical and chemical properties of those compounds are listed in Table 1. Although oxalic acid ((COOH)2 ) is often found to be a preferential constituent of dicarboxylic acids in the atmosphere (Kawamura & Usukura, 1993; Sempere & Kawamura, 1994), ammonium oxalate is alternatively selected in this study. This is because the vapor pressure of oxalic acid is too high (8:26 × 10−5 mmHg; 25◦ C, Saxena & Hildemann, 1996) for the existence of a pure substance, and thus oxalic acid is expected to exist as a neutralized salt to become stable. Actually, oxalic acid particles generated in preliminary experiments exhibited signiFcant evaporation in the experiment system. DMA is frequently used in the past laboratory studies mentioned above to produce nearly monodisperse particles of a known size, which allows the operator to record the supersaturation activating the particles as the critical supersaturation without consideration of the original size distribution. However, as also stated above, there is a possibility that the employment of DMA could lead to incorrect size classiFcation of particles depending on particle morphology, mass and cross-sectional area which aGect the charging eMciency and electrical mobility in a static electric Feld. For comparison, therefore, a diGerent approach was employed in this study. Methodology involved Frst determining the cumulative number size distribution of the polydisperse particles as they are without using DMA. Next, the number concentrations of the droplets activated from the particles are measured as a function of supersaturation (CCN spectrum). The relation between critical supersaturations and dry particle sizes to be determined can then be obtained using the pairs that give the same number concentrations for the CCN spectrum and cumulative size distribution (Fig. 1). Although the methodology is a somewhat classical one (Katz & Kocmond, 1973) and it is not necessarily easy to obtain the exact cumulative distribution, the activation capability of particles can be measured without a problem related to the electrical mobility diGerence in DMA. Therefore, critical supersaturations obtained by this approach can be compared with those by the past studies to verify the past experimental results and to explore possible causes of the disagreements. Our experimental results are also compared with theoretical values to examine the predictability of activation capability of dicarboxylic acids. 2. Experimental approach To measure critical supersaturations, an experimental system consisting mainly of three subsystems was constructed as depicted in Fig. 2. The Frst subsystem generates polydisperse particles by atomizing a dilute solution. The second subsystem measures the CCN spectrum i.e., the number

HOOCCH2 COOH HOOC(CH2 )2 COOH HOOC(CH2 )3 COOH HOOC(CH2 )4 COOH HOOCCH(OH)CH2 COOH HOOCC6 H4 COOH 35.9 75.7

2.164 1.769

1.631 1.572 1.424 1.360 1.595 j 1.593 — —

0.0500 0.0409

0.0377 0.0363 0.0329 0.0314 0.0369 0.0368

1.0E-5f 7.9E-6g , 6.9E-7f 7.78E-6g , 4.1E-6f 1.11E-7g , 1.5E-7f 3.30E-08g; j No data

161 8.8 116 2.5 145 j 0.6

0.0365

—

5.1d 1.580

Mass conc. of atomizing solution g dry solute per 1-l solution

Solubilityb Densitye Vapor pressure g per (g cm−3 ) (mmHg) 100 g H2 0c

(0:25) (0:25) (0:25) (0:15) (0:25) (0:04) +0:42 (0:25) +0:55 (0:25)

−1:56 −2:91 −6:61 −7:26 −2:35 −2:03

+0:79 (0:25)

Surface tension of aqueous solutionh O; dyn cm−1 (at M, mol per kg water)i

b

Molecular weight is taken from Dean (1985). References for solubility: ammonium oxalate and ammonium sulfate: Washburn (1928b), malonic acid, succinic acid, glutaric acid, adipic acid and malic acid: Saxena and Hildemann (1996), sodium chloride: Deutsche Chemische Gesellschaft (1928), phthalic acid: the average of the values found in Stephen and Stephen (1963) and Deutsche Chemische Gesellschaft (1949). c Solubilities of ammonium oxalate, phthalic acid, sodium chloride and ammonium sulfate are the values at 20◦ C, and others at temperatures closest to 25◦ C (Saxena & Hildemann, 1996). d Converted from the value for anhydrous. e References for density: all dicarboxylic acid compounds except for malic acid: Deutsche Chemische Gesellschaft (1942), malic acid: Deutsche Chemische Gesellschaft (1921), inorganic compounds: Dean (1985). f The values at 30◦ C from Prenni et al. (2001). g The values at 25◦ C from Saxena and Hildemann (1996). h References for surface tension: ammonium oxalate (the value at 20◦ C): Morgan and McKirahan (1913), malonic acid, succinic acid and malic acid ◦ (20 C): King and Wampler (1922), glutaric acid, adipic acid and phthalic acid (room temperature): Shulman et al. (1996), sodium chloride (20◦ C) and ammonium sulfate (10 –20◦ C): Washburn (1928b). i Estimated as the diGerence from the surface tension of pure water (72:61 dyn cm−1 at 20◦ C) for all dicarboxylic acid compounds. Data unit from Shulman et al. (1996) is in mol per l. j As the value for L-malic acid.

a

58.45 132.14

104.06 118.09 132.12 146.14 134.09 166.13

(COONH4 )2 · H2 O

Ammonium oxalate monohydrate Malonic acid Succinic acid Glutaric acid Adipic acid (DL-)Malic acid Phthalic acid

Sodium chloride NaCl Ammonium sulfate (NH4 )2 SO4

142.11

Formula

Compound

Moleculara weight

Table 1 Formulas, molecular weights, solubilities, densities, vapor pressures, and mass concentrations of 1 liter/dilute aqueous solutions for atomization and surface tensions of aqueous solutions, listed for dicarboxylic acids, sodium chloride and ammonium sulfate

M. Hori et al. / Aerosol Science 34 (2003) 419 – 448 423

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M. Hori et al. / Aerosol Science 34 (2003) 419 – 448 Np

Nd

Sc s2

n2

s1

n1

s1

s2

S

CCN spectrum Subsystem for measuring number concentration of activated droplets

r2

r1

Rp

Cumulative number size distribution Subsystem for measuring number size distribution of generated aerosol particles

r2

r1

Rp

The relation between critical supersaturations and dry particle radii

Fig. 1. Schematic representation of the methodology for obtaining the relation between critical supersaturations (Sc ) and dry particulate radii (Rp ) for polydisperse particles. Nd denotes the number concentration of activated droplets as a function of supersaturation (CCN spectrum), and Np denotes the cumulative concentration of particles as a function of radius. The Sc -Rp relation can be obtained through the comparison of Nd and Np .

Fig. 2. Schematic diagram of the experimental system for the determination of critical supersaturations of polydisperse particles. M, F, V, R, TGDCC and OPC denote the mass Low meter, air Flter, valve, rotameter, conventional thermal gradient diGusion cloud chamber and optical particle counter, respectively. The system was composed mainly of three subsystems (1) for the generation of polydisperse particles, (2) for the measurement of the CCN spectrum and (3) for measuring the number size distribution of the polydisperse particles.

concentrations of droplets activated from the polydisperse particles in a unit volume as a function of supersaturation, using a conventional thermal gradient diGusion cloud chamber. The third subsystem measures the number size distribution of the polydisperse particles in a unit volume through the techniques of Flter sampling and image analysis with scanning electron microscope (SEM) observation.

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The experimental details of the individual subsystems are described in the following sections. However, here, we would like to note the restriction of our experimental system. In our system, dicarboxylic acid particles cannot be observed with SEM due to their evaporation losses under the high vacuum condition in the SEM, and thus their cumulative number size distributions cannot be obtained with the same techniques employed in the third subsystem. Instead, we measure the number size distribution only for sodium chloride particles to determine the number size distribution of aqueous solution droplets atomized by a constant output atomizer. Once the droplet size distribution is determined, the size distributions of dried solid particles for dicarboxylic acids and ammonium sulfate can be obtained from the droplet distribution taking into account the solute mass in individual solution droplets and solute densities. For the success of this procedure, all experimental conditions are maintained. This methodology is validated by comparing the experimental CCN spectra and critical supersaturations for ammonium sulfate with theoretical predictions. 2.1. Generation of polydisperse particles Aerosol particle generation was accomplished by the following procedure. Dilute aqueous solutions for individual dicarboxylic acids and inorganic compounds were prepared by the method described in the next section. Polydisperse solution droplets of individual compounds were then generated by atomizing the prepared solutions with a constant output atomizer (TSI, Model 3076) at a gas Low rate of 2:8 l min−1 . The atomized droplets were dried into solid state particles with a diGusion drier (TSI, Model 3062) and electrically neutralized with a bipolar neutralizer (TSI, Am-241). A partial Low (0:8 l min−1 ) out of the aerosol Low was mixed with Fltered pure dry air (20 l min−1 ) in a dilution glass tube to adjust the particle number concentrations. The diluted particles were then introduced into a sampling chamber with a volume of about 20 l. Relative humidity in the sampling chamber was always kept constant at around 8–9%. To ensure complete drying of the atomized droplets to the solid state, the polydisperse particles were passed through the chamber slowly with a residence time of about 1 min. Part of the particles in the chamber was then sampled at a Low rate of 0:53 l min−1 and utilized for subsequent measurements. Each generation of aerosol particles was performed for the duration of within 2:5 h, and the measurements of the CCN spectrum or number size distribution were performed during the last 1–2 h after the number size distribution of generated particles in the sampling chamber had become stable. Dea and Katz (1981) reported that atomization by the same model of the constant output atomizer sometimes became unstable due to gradual accumulation of solution between the nozzle and the impaction surface in the atomizer, and in the unstable cases, the number concentrations of atomized particles over the entire size range become 2–3 times those in a stable period over a long period of use. In this study, therefore, we frequently and carefully examined the performance of the atomizer by checking the circulation of the aqueous solution in the liquid feeding tubes and the closed reservoir in order to omit measurements in a terribly unstable mode. Dea and Katz (1981) indicated also that the variations in the number concentrations of particles in the unstable mode tended to become larger with increasing particle size. Thus, to evaluate the temporal stability of the performance of the atomizer, sodium chloride particles were generated during preliminary operations with all the experimental conditions being kept the same as those under the normal operations. The variations in the number concentrations of the particles larger than 0:15 m in radius (Np; r¿0:15 m ) were monitored by an optical particle counter (OPC; Lion, Model 237B) at a position downstream of the second

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M. Hori et al. / Aerosol Science 34 (2003) 419 – 448

and third subsystems during the last 2 h of the atomization. During the normal operations for the measurements of CCN spectra, we also monitored the occurrence of the unstable atomization by measuring Np; r¿0:15 m discontinuously in rotation with a measurement of the CCN spectrum and excluded the data in the unstable mode. 2.2. Preparation of dilute solutions for atomization To simplify the comparison of the size distributions for individual compounds, and also to minimize the diGerences in aerodynamic losses (deposition and impaction) of particles between the compounds, we prepared dilute aqueous solutions for all compounds with a Fxed common volume concentration of 0:0231 cm3 dry solute per liter of solution. Each solute was Frst dried for 24 h in a room at ¡ 30% RH, and its volume of 0:0231 cm3 was then weighed with an electrical balance, taking into account the bulk solute density, and the material was dissolved in pure water (MILLIPORE, mill-Q Jr.) in a plastic Lask (Nalgen, PMP Lask). The bulk solute densities and weighed masses employed for preparing the 1 l solutions are also listed in Table 1. Mass concentrations of the prepared solutions were less than 0:0004 mol l−1 which are suMciently dilute not to alter the surface tensions of the solutions from that of pure water (Shulman et al., 1996). By this preparation method, an atomized solution droplet of a speciFc size always produces a dried solute particle of a common volume (equivalent radius) for all compounds. Therefore, the size distribution measured for sodium chloride particles can be directly substituted for those of dicarboxylic acids and ammonium sulfate, as far as the size distribution of atomized droplets does not vary. In principle, the accuracy of the bulk solute densities employed for individual reagents could be of importance when the common number size distribution was substituted for the distributions of individual compounds. In the case where a 5% overestimation of solute density occurred, the possible error would be roughly estimated to be a +1:64% overestimation of particle size. This error is relatively small compared with the size determination error (about ±10% for a 0:05 m particle) estimated from the uncertainties in cumulative number size distribution (see Section 4.1). Thus, the errors originating from the inaccuracy in solute densities are not likely to alter the interpretation of experimental results. 2.3. Measurement of CCN spectrum Number concentrations of the droplets activated from the polydisperse particles were measured with a thermal gradient diGusion cloud chamber (USUI KOGYO KENKYUJO, the same chamber system used by Naruse, 1978, hereafter TGDCC) as a function of supersaturation. For all experiments, the room temperature in the laboratory ranged around 20 ± 5◦ C, and the temperature of the upper plate in the TGDCC was kept at around 15◦ C. The temperature of only the bottom plate was adjusted in the range of 8.5 –12:5◦ C to set an arbitrary supersaturation of 0.1–2% in the TGDCC. The plate temperatures were measured with a thermistor within an accuracy of ±0:1◦ C. Aerosol particles in the sampling chamber were introduced into the TGDCC at an air Low rate of 0:53 l min−1 to measure the CCN spectra discontinuously in rotation with the OPC measurements as described above. For the detection of activated droplets in the TGDCC, a CCD camera (Elmo, ME-411, lens: T3425MB) was used which could detect a droplet larger than 1–2 m in diameter within a volume of 25 mm3 (dimensions: 1 mm width×5 mm length×5 mm height) at the central part in the TGDCC illuminated

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427

by a mercury lamp (USIO electric corp. USH-250D, 250 W). Droplet images detected with the CCD camera were recorded as movies on 8 mm tapes until no activation events were seen to occur. The number of droplets falling down toward the bottom plate in the movies was then counted manually by playing back the video tape. When counting the droplet number we took into account only the droplets that initiated activation within the illuminated volume and then fell down toward the bottom plate; we excluded the droplets that activated outside of the illuminated volume and fell down into the interior. 2.4. Measurement of number size distribution of sodium chloride particles The number size distribution of polydisperse sodium chloride particles in the sampling chamber was measured with a Flter-sampling method and an image analysis technique. First, the particles in the chamber were collected on a Nuclepore Flter (47 mm in diameter, pore size: 0:1 m) set in a detachable Flter holder at a Low rate of 0:53 l min−1 for 30 min. The particles collected on the Flter were then observed with a SEM (HITACHI, S-3200). The observed SEM images (35 000 magniFcations) were analyzed with image analysis software (Leica, Q500MC) to count the number of particles in all size intervals on the axis of volume equivalent radius. One particle size interval was a one hundredth width of the logarithmic scale between 0.01 and 1 m. Thirty-six points on the Nuclepore Flter were observed to produce the average for each radius interval. In this study, the size distribution in the range larger than 0:02 m in radius was utilized for the determination of critical supersaturations because the resolution of SEM images was not high enough to discriminate between the particles smaller than 0:02 m in radius. 3. Theoretical prediction 3.1. K8ohler theory and assumptions To examine the applicability of the K4ohler theory to the hygroscopic behavior of dicarboxylic acid compounds, we compared the experimental critical supersaturations with the calculated values based on the modiFed K4ohler equation derived by Mason (1971), er
= exp(2  MW =L R∗ Tr)[1 + (imS MW =MS ((4r 3 =3)L − mS ))]−L =L ; e∞

(1)

where er is the equilibrium vapor pressure at the surface of a solution droplet of radius r; e∞ the equilibrium vapor pressure over the plane water surface,  the surface tension of the solution, L the density of pure water, L the density of the solution, R∗ the universal gas constant, T temperature, i the van’t HoG factor, mS the mass of solute, MS the molecular weight of the solute and MW is the molecular weight of water. In the above equations, the exponential part on the right-hand side expresses the extent to which the equilibrium vapor pressure at the droplet surface is elevated from that over the plane surface, depending on the curvature (i.e., the Kelvin eGect). The bracket part with the exponent (−L =L ) expresses the depression of the equilibrium vapor pressure due to the presence of the dissolved solute material in water (Raoult’s eGect, hereafter the R part). Moreover, i is calculated only for ammonium oxalate using Eq. (8) of Low (1969).

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Necessary parameters for the computation of i such as the densities, surface tensions and boiling point elevations for ammonium oxalate solution were obtained from the International Critical Tables of Numerical Data, Physics, Chemistry and Technology (Washburn, 1928a, b) and Gmelins Handbuch der Anorganischen Chemie (Deutsche Chemische Gesellschaft, 1936). For other dicarboxylic acid solutions, however, as the past studies did (Corrigan & Novakov, 1999; Prenni et al., 2001), the values of i were assumed to be 1.0 and the density and surface tension of pure water (20◦ C) were employed because the physical properties for those compounds are not fully available in the literature. In this calculation, we assumed that the droplet shape always remained spherical from the beginning of condensation growth, whether the solute solubility was high or low. In the case where a less soluble solute could not dissolve entirely into an aqueous solution, an embryo formed on the solute at the initial stages, and the droplet was assumed to be formed with an inhomogeneous structure, i.e., a spherical solute core with a perfect wettable surface covered with a spherical saturated solution shell, until the whole solute dissolved into the shell. In such a case, the equilibrium vapor pressure at the droplet surface was still assumed to be expressed by Eq. (1). As stated before, the even members among dicarboxylic acids exhibit a hydrophobic nature, which is inconsistent with the above assumption of a perfect wettable surface. In addition, several substances studied can be considered to exhibit surface tension reduction early in the droplet growth due to their surface activity (Shulman et al., 1996), which is not taken into account in the theoretical prediction. For simplicity, however, we made those assumptions for the simulation of the hygroscopic behavior of dicarboxylic acid compounds and examined the extent to which actual behavior deviated from the theoretical prediction, depending on the factors characterizing the physicochemical properties of the organic substances such as solubility, surface activity, hydrophobicity and morphology and so on. When the theoretical relation between critical supersaturations and dry particle radii is obtained from the maximum peaks of the equilibrium curves, the dry particle radii are calculated from the solute masses Fxed for each equilibrium curve by taking into account the solute density. Thus, as in the case of the experimental approach, the inaccuracy of an employed bulk solute density could cause an error in the estimation of particle radii also in the theoretical prediction. In this case, the 5% overestimation of bulk solute density could cause a −1:61% underestimation of the particle radius. Hence, if a 5% overestimation of solute density occurred, total uncertainties in particle radii would be summed to be −1:61%–+1:64% when comparing the experimental results with the theoretical prediction. However, the uncertainties are still smaller than those from the cumulative size distribution. Hence, again, the inaccuracy of solute density would not alter the interpretation of the results obtained in this study. 3.2. Expected hygroscopic behavior of dicarboxylic acids Simulated hygroscopic behavior for the seven dicarboxylic acid compounds can be typically divided into three classes. Figs. 3a–c show the three diGerent types of hygroscopic behavior shown for ammonium oxalate, adipic acid and malic acid, respectively. Basically, the classiFcation depends on the degree of solute solubility, i.e., Raoult’s eGect. The Frst type shown in Fig. 3a (we call this type A) results from moderate solubility of the solute material. Ammonium oxalate (5:1 g 100 g H2 O−1 ) and succinic acid (8:8 g 100 g H2 O−1 ) belong to this type. The calculated results indicate that the equilibrium vapor pressure of type A is

M. Hori et al. / Aerosol Science 34 (2003) 419 – 448 1.025

1.025 10-16g

(a) Ammonium oxalate

10-16g 1.020

(b) Adipic acid

1.020

Pure water droplet (20°C)

Pure water droplet (20°C) Saturation ratio

1.015 Saturation ratio

429

IP 1.010 10-15g

NP

1.005

10-15g

1.015 1.010

10-14g

1.005

10-13g

1.000

1.000 10-14g

0.995

0.995 10-13g 0.990 0.01

0.1 1 Droplet radius (micrometer)

10

0.990 0.010

0.10 1.0 Droplet radius (micrometer)

10

1.025 10-17g

(c) Malic acid

1.020 Saturation ratio

Pure water droplet (20°C) 1.015 1.010 1.005

10-16g

10-14g

10-15g

1.000 10-13g 0.995 0.990 0.01

0.1 1 Droplet radius (micrometer)

10

Fig. 3. Variations with droplet size of the equilibrium vapor pressure (saturation ratio er =e∞ ) over pure and aqueous solution droplets at 20◦ C formed from (a) ammonium oxalate, (b) adipic acid and (c) malic acid, calculated for various solute masses. In the Figs. 3a, b, the open circle at the left end of each curve indicates the initiation peak of the deliquescence (IP). NP denotes the normal peak of the conventional K4ohler curve.

not depressed as in the case of ammonium sulfate at the beginning of condensation, because Raoult’s eGect of the solute material is weaker than that of ammonium sulfate. Thus the equilibrium curves of type A can have two local maxima as depicted in Fig. 3a. One is the left peak at the end of each curve at which the solute particle initiates deliquescence (hereafter IP (initiation peak of the deliquescence)). Thus, the droplet radius at the IP corresponds to the volume equivalent radius of the initial dry solute particle. The other local maximum is the second peak on the right side of the IP in each curve, for example, at a droplet radius of around 0:3 m for a 10−15 g solute mass in Fig. 3a. The second peak corresponds to the maximum peak of the conventional K4ohler curve usually computed for strong electrolytes such as ammonium sulfate where only one local maximum can be seen deFned as the critical supersaturation (hereafter, NP (normal peak of the K4ohler curve)). The peak heights of IP and NP depend on the solute masses contained in individual droplets. The IP heights themselves decrease steeply with the increase in the solute mass (i.e., the size of the initial

430

M. Hori et al. / Aerosol Science 34 (2003) 419 – 448

droplet) due to the reduction of the Kelvin eGect, whereas the NP heights gradually decrease with increasing solute mass. As a result, IP can be higher than NP when the solute mass is less than 10−14 g in the Fgure, and vice versa. This means that critical supersaturations of type A material are determined not only by NP heights but also by those of IP depending on the solute masses. In the latter case, even the deliquescence cannot be initiated until the saturation ratio (er =e∞ ) exceeds the IP heights. Fig. 3b shows the second type (type B) of hygroscopic behavior resulting from poor solute solubility in water. Adipic acid (2:5 g 100 g H2 O−1 ) and phthalic acid (0:6 g 100 g H2 O−1 ) are members of this type. Their equilibrium curves have essentially only one local maximum, i.e., the higher left maxima (IP) and very small inconspicuous right peaks (NP) due to their poor solubilities as shown in Fig. 3b for the adipic acid case. In the case of phthalic acid, even higher IP peaks can be seen in its K4ohler curves, nearly comparable to the curve of pure water. Hence, critical supersaturations of type B are expected to be determined in most cases by the IP heights and to be higher than those of type A. There are several dicarboxylic acid compounds that have a solubility even higher than those of the typical CCN substances such as ammonium sulfate (75:7 g 100 g H2 O−1 ). Malonic acid (161 g 100 g H2 O−1 ), glutaric acid (116 g 100 g H2 O−1 ) and malic acid (145 g 100 g H2 O−1 ) meet this condition. Due to the high solubilities, their hygroscopic behavior becomes very similar to that of ammonium sulfate as shown in Fig. 3c for malic acid (type C). The equilibrium curves are equivalent to the conventional K4ohler curves and have just one local maximum. Thus, the type C material is expected to have lower critical supersaturations than the other two types of dicarboxylic acid compounds considered above. 4. Results and discussion 4.1. Number size distribution, and temporal stability of atomization The number size distribution and cumulative number size distribution of generated polydisperse particles obtained for sodium chloride are shown in Fig. 4. In the image analysis process, the radii of more than 3000 particles were measured in the range from 0.02 to around 0:15 m. The resulting number concentrations in individual size intervals ranged between 3:6×104 and 6:0×106 particles l−1 , and the converted cumulative number concentrations ranged from about 6:3 × 104 particles l−1 at a radius of 0:15 m to 7:4 × 107 particles l−1 at 0:02 m. Uncertainties in the number concentrations of particles are also indicated for the cumulative distribution in the Fgure by dashed lines below and above the distribution as “expected ranges of the maximum variation” which were estimated from the OPC measurements of the Luctuations in number concentrations of the particles larger than 0:15 m in radius (Np; r¿0:15 m ) in the preliminary operations as described below. The preliminary operations for sodium chloride particle generation were performed seven times in order to estimate the temporal variations in Np; r¿0:15 m . Fig. 5a shows the observed temporal variations in Np; r¿0:15 m for the duration of 2:5 h operation. The average concentration during the last 2 h is 72 710 particles l−1 (STD = 6160), which is almost consistent with the cumulative number concentration at a radius of 0:15 m in Fig. 4. Maximum Luctuations in Np; r¿0:15 m ranged within ±18% of the average concentration. According to the results of Dea and Katz (1981), variations

Number size distribution (particles L-1)

108

108 Expected ranges of the maximum variation (-30.5%~+43.9%)

107

107

106

106

105

105

0.02

0.04 0.06 0.08 0.1 Radius of dry particle (micrometer)

431

Cumulative number size distribution (particles L-1)

M. Hori et al. / Aerosol Science 34 (2003) 419 – 448

0.15

Fig. 4. Number size distribution (solid circles) and cumulative number size distribution (solid line) of sodium chloride particles obtained with Flter sampling and SEM image analysis techniques. The expected ranges of the maximum variation (−30:5– 43.9%) shown for the cumulative distribution (dashed lines) were estimated from temporal variations in the concentrations of the particles larger than 0:15 m in radius (Np; r¿0:15 m ).

(a)

140000 the average + 18%

80000

60000

40000

20000

the average - 18% the line of the average concentration of the seven operations Time period for measuring CCN spectrums or number size distribution

0 0:00:00 0:30:00 1:00:00 1:30:00 2:00:00 2:30:00 Time from the start of atomization (H:MM:SS)

N (r > 0.15 micrometer, particles L-1)

N (r > 0.15 micrometer, particles L-1)

100000

(b)

Phthalic acid 120000 100000 80000

Succinic acid (NH4)2SO4 NaCl

60000 40000 20000

Malic acid Adipic acid Ammonium oxalate Glutaric acid Malonic acid

0 0:00:00 0:30:00 1:00:00 1:30:00 2:00:00 2:30:00 Time from the start of atomization (H:MM:SS)

Fig. 5. Temporal variations in the concentrations of particles larger than 0:15 m in radius (Np; r¿0:15 m ) measured with an optical particle counter during (a) seven preliminary operations for sodium chloride and (b) typical normal operations for all compounds studied.

in particle number concentrations in the size range smaller than 0:15 m in radius are expected to fall within the maximum variation in Np; r¿0:15 m . We then assumed that the number concentrations of dried solid particles that can reach the second and third subsystems in all size intervals could Luctuate with time to the same extent within ±18%. Based on this consideration, the introductions of particles into the second and third subsystems at arbitrary timing can be expected to cause a bias in the number concentrations to be measured by both subsystems. For example, it is possible that the data in Fig. 4 themselves were obtained at the timing with the positive maximum deviation

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M. Hori et al. / Aerosol Science 34 (2003) 419 – 448

Table 2 Statistical summary of the OPC measurements during normal and humid operations Compounds

Np; r¿0:15

m

(particles l−1 )

Np; humid; r¿0:15

m

(particles l−1 )

Np; humid; r¿0:15 Np; r¿0:15 m

Average

STD

Average

STD

Ammonium oxalate Malonic acid Succinic acid Glutaric acid Adipic acid Malic acid Phthalic acid

35800 7134 59512 13540 58306 62458 114366

1043 1541 3623 1705 2506 2668 6157

38674 43112 62326 21826 65241 90144 149425

936 2128 297 2378 1457 874 5809

1.08 6.04 1.05 1.61 1.12 1.44 1.31

Sodium chloride Ammonium sulfate

72710 61287

6160 4999

— 104822

— 935

— 1.71

m =

+18% from the average, although a CCN spectrum might be obtained with a negative −18%, and vice versa (e.g., Np = Nave × 1:18; Nd = Nave × 0:82). Therefore, when we compare the cumulative distribution obtained by the third subsystem with the CCN spectra by the second subsystem for the Fnal determination of the critical supersaturations, the vertical axis of the cumulative number distribution (Np ) can have a bias of +43:9% (1:18=0:82) to −30:5% (0:82=1:18) at the maximum from that of the CCN spectrum (Nd ). Although the expected ranges of the maximum variation are not small, the change rate of the cumulative number size distribution with particle size is extremely large as shown in Fig. 4 with the logarithmic scale as the right ordinate, which enables us to compare with the CCN spectra to obtain critical supersaturations with substantial accuracy with which we can discuss the diGerences in CCN ability between the examined compounds. As for the temporal stability of droplet atomization under normal operations, typical temporal variations in Np; r¿0:15 m for all compounds obtained with OPC are shown in Fig. 5b. Average and standard deviations of the OPC measurements are summarized in Table 2. Although the absolute number concentrations cannot necessarily be compared between the compounds because of possible diGerences in their optical refractive indices and morphology on which the OPC counts are sensitively dependent, the number concentrations for all compounds distributed well within the ±18% of the average for individual compounds. Therefore, the temporal variation estimated for sodium chloride under the preliminary operations is also expected to hold for all compounds under the normal operations. From Fig. 4, the concentration of particles larger than 0:15 m in radius can be estimated to be around 63 000 particles l−1 with which Np; r¿0:15 m values for NaCl, (NH4 )2 SO4 , succinic acid, adipic acid and malic acid were almost consistent (Fig. 5b). Therefore, if the particles are non-volatile and have a nearly spherical shape and if the complete evaporation of atomized droplets is accomplished, the particles can be expected to retain the common size distribution exhibiting the same OPC counts around 63 000 particles l−1 . However, absolute Np; r¿0:15 m counts for malonic acid and glutaric acid are substantially lower than that of sodium chloride, which can be expected to result due to the vaporization of solute substances in the experimental system as described in Section 4.3. On the other hand, the counts for phthalic acid and ammonium oxalate are 1.6 times as much

M. Hori et al. / Aerosol Science 34 (2003) 419 – 448

433

Fig. 6. Morphology of (a) ammonium oxalate and (b) phthalic acid crystallized by evaporating aqueous solution droplets (mass concentration: 0:037 g l−1 , initial volume: 50 l) on a TeLon Flter under 30% RH for 6 h, observed with an optical microscope.

as and about half that of sodium chloride, respectively. The former can be expected to result due to insuMcient evaporation of the atomized droplets to solid crystals, whereas the latter might be due to morphological deviation of the solute crystals from a sphere because the CCN spectra obtained for ammonium oxalate exhibited no apparent feature of solute vaporization as will be described in Section 4.3. In order to gain insight into the morphology of the particles generated in our experimental system, using an optical microscope we observed solute crystals reproduced for several dicarboxylic acid compounds from a small amount (50 l) of the dilute solution for the atomization. It is of interest that, among the seven dicarboxylic acid compounds, ammonium oxalate and phthalic acid exhibited quite characteristic crystal shapes. Ammonium oxalate had a very Fne needle shape, and their aggregation (Fig. 6a) may imply that the thinner part of the needle-shaped particle might determine the signal strength of the OPC, and thus low Np; r¿0:15 m counts might result. On the other hand, phthalic acid tended to form long pillars and thin plates retaining a round structure as a whole (Fig. 6b), which might indicate traces of the preferential absorption of solute molecules at the surface of concentrated solution droplets, by which the rate of droplet evaporation may slow down. 4.2. Correction of CCN spectrum and validation of experimental system Fig. 7a shows the CCN spectrum obtained for sodium chloride particles (solid squares). Horizontal error bars for individual experimental data were estimated from the Luctuations in the plate temperatures in the TGDCC. The theoretical line (solid line) and the expected ranges of the maximum variation (dashed lines) were estimated from the cumulative number size distribution in Fig. 4 by utilizing the theoretical relation between critical supersaturations and dry particle radii for sodium chloride by H4anel (1976). Also shown in the upper horizontal axis are the threshold radii of dry solid particles that give the same cumulative number concentrations in Fig. 4. The experimental data increase with the increase in supersaturation along the theoretical line in Fig. 7a. However, some data deviate from the theory particularly in the range of lower supersaturation

434

M. Hori et al. / Aerosol Science 34 (2003) 419 – 448

0.050

0.032

0.025 0.0210.018

Expected ranges of the maximum variation (-30.5% ~ +43.9%)

107 NaCl (Theory with the size distribution of Figure 4)

106 0.08 0.1

0.3

0.5

Supersaturation (%) Number conc. of activated droplets (droplets L-1)

(a)

108

(c)

Number conc. of activated droplets (droplets L-1)

Number conc. of activated droplets (droplets L-1)

Threshold radius for sodium chloride (micrometer) 108 Expected ranges of the maximum variation (-30.5% ~ +43.9%)

107 NaCl (Theory with the size distribution of Figure 4)

106 0.08 0.1

0.3

0.5

Supersaturation (%)

(b)

108 Expected ranges of the maximum variation (-30.5% ~ +43.9%)

107

(NH4)2SO4 (Theory with the size distribution of Figure 4)

106 0.08 0.1

0.3

0.5

Supersaturation (%)

Fig. 7. CCN spectra for (a) sodium chloride (uncorrected), (b) sodium chloride (corrected) and (c) ammonium sulfate (corrected); the last ones were obtained at two diGerent times of atomization (open and solid squares). The data corrections were made based on the equation shown in Fig. 8b (see text). Theoretical lines with the expected ranges of the maximum variation were estimated from the cumulative distribution in Fig. 4, and horizontal error bars were from the variation in plate temperatures in TGDCC.

beyond the expected ranges of the maximum variation in number concentration and also beyond the estimated errors in supersaturation, which suggests that detection losses of the generated polydisperse particles occurred in the second subsystem to a much greater extent than in the third subsystem. Fig. 8a shows the ratio of the CCN number concentrations detected in the second subsystem to the cumulative concentrations of the solid particles obtained by the third subsystem as a function of the threshold particle radius (i.e., data with a ratio of 100% can reach the theoretical lines in Fig. 7a. Hereafter, we call the ratio “detection eMciency” of the second subsystem). A systematic bias can be seen in the detection eMciency as a function of the threshold particle size, which is considered due

M. Hori et al. / Aerosol Science 34 (2003) 419 – 448

435

Fig. 8. (a) The ratio of cumulative concentrations of the particles detected as activated droplets in the second subsystem to those of the solid particles obtained by the third subsystem (i.e., “the detection eMciency” of particles in the second subsystem) as a function of the threshold radius for sodium chloride particles. (b) Same as (a) but as a function of the number concentration of activated droplets detected in the second subsystem.

to the fact that the deposition losses of larger solid particles occurred within the second subsystem to a much greater extent than in the third subsystem. To correct the systematic bias in the CCN spectra obtained not only for sodium chloride but also for other compounds, we then estimated the relation between the detection eMciencies and the number concentrations of activated droplets as shown in Fig. 8b, based on the assumption that a systematic bias occurred equally in the CCN spectra for all compounds only as a function of droplet number concentration (i.e., as a function of the threshold particle size). With the equation in Fig. 8b, the spectrum data for sodium chloride were corrected to have a detection eMciency of 75% equally within the expected ranges of the maximum variation without the threshold size dependence. Fig. 7b is the corrected CCN spectrum for sodium chloride particles indicating that all the data can distribute within the variation ranges. With the same procedure, CCN spectra obtained for ammonium sulfate at two diGerent times of atomization were corrected as shown in Fig. 7c. The theoretical line in the Fgure was derived in the same manner as in the sodium chloride case with the results of H4anel (1976). Again, all the data ranged within the variation ranges along the theoretical line, in spite of the fact that the cumulative number size distribution obtained for sodium chloride had been utilized for deriving the theoretical line. Therefore, it can be concluded that the employed experimental system does not cause uncertainties in the vertical axes of both the CCN spectrum and the cumulative number size distribution beyond the expected ranges of the maximum variation, except for the systematic bias seen in Fig. 8b and also for substance-inherent uncertainties such as evaporation losses. 4.3. Corrected CCN spectra and solute evaporation losses Fig. 9a shows the corrected CCN spectra for ammonium oxalate, adipic acid, malic acid and phthalic acid, and Fig. 9b shows those for malonic acid, succinic acid and glutaric acid. In both

NaCl (Theory) (NH4)2SO4 (Theory)

107

106

105

Wettable but water-insoluble particle (Theory)

0.1

1 Supersaturation (%) Number conc. of activated droplets (droplets L-1)

(a)

108

(c)

Number conc. of activated droplets (droplets L-1)

M. Hori et al. / Aerosol Science 34 (2003) 419 – 448 Number conc. of activated droplets (droplets L-1)

436

108

107

106

105 0.1

1

(b)

Supersaturation (%)

108

107

106

105 0.1

1 Supersaturation (%)

Fig. 9. CCN spectra for (a) ammonium oxalate (open triangles), adipic acid (crosses), malic acid (solid diamonds) and phthalic acid (open squares), (b) malonic acid (open circles), succinic acid (solid circles) and glutaric acid (solid triangles), both obtained under the normal operation with the particle drying process at 8–9% RH, and (c) ammonium sulfate (open diamond), ammonium oxalate, malonic acid, succinic acid, glutaric acid and adipic acid (the same symbols as (a) and (b)) under the humid operation at around 30 –50% RH.

Fgures, theoretical lines for sodium chloride, ammonium sulfate and wettable but water insoluble particle are also indicated by thick solid, dashed and dotted lines, respectively; the last one was estimated with the theoretical relations taken from Mason (1971). Spectral data for the four dicarboxylic acid compounds in Fig. 9a ranged between the theoretical lines of ammonium sulfate and insoluble particles parallel to them, which suggests that no additional systematic bias due to deposition losses or solute vaporization occurred beyond the expected ranges of the variation. The spectra of ammonium oxalate, malic acid and phthalic acid are very high, comparable to that of ammonium sulfate, whereas adipic acid has the lowest spectrum, close to that of an insoluble particle. On the other hand, malonic acid, succinic acid and glutaric acid in Fig. 9b have diGerent spectral features. Number concentrations of activated droplets do not increase with the increase in

M. Hori et al. / Aerosol Science 34 (2003) 419 – 448

Cumulative volume dist. (micrometer3 L-1)

105

104

glutaric acid (10.2ppb, g)

437

malonic acid (13.1ppb, f)

succinic acid (10.4ppb, g) glutaric acid (5.4ppb, f) succinic acid (0.9ppb, f) adipic acid (0.2ppb, f)

103

adipic acid (0.15ppb, g)

malic acid (0.04ppb, g)

102

101 0.01

0.1

0.2

Radius of dry particle (micrometer)

Fig. 10. Cumulative volume (under) size distribution of the generated polydisperse particles, estimated from the size distribution in Fig. 4. Particulate volume concentrations necessary to establish the saturated vapor pressure in the sampling chamber through the particle evaporation are indicated for individual substances (horizontal dashed and dotted lines) with the vapor concentrations and the reference codes (g and f) listed in the note of Table 1.

supersaturation as much as those of four other dicarboxylic acid compounds do in Fig. 9a. Rather, the data for malonic acid and glutaric acid reach the ceiling at supersaturation around 0.4%. The slope of the CCN spectrum can reLect the cumulative size distribution of solute particles as shown in Fig. 1. Thus, when a spectrum does not become parallel to the spectra of non-volatile compounds, the spectral feature can be considered as a sign of particle evaporation. Hence, the ceiling feature suggests that vaporization losses of the particles, particularly small particles, occurred. As for succinic acid, the spectral data exhibit a more complex feature; the data seem to follow two branches. As listed in Table 1, the vapor pressures of malonic acid, succinic acid and glutaric acid are higher than those of other dicarboxylic acids studied. In general, the saturated vapor pressure for a pure substance can be considered to increase with decreasing particle size due to the increase in curvature, i.e., the Kelvin eGect. Thus it is likely that smaller particles evaporate in preference to larger particles. Fig. 10 shows the cumulative volume size distribution (under size distribution) of the generated particles converted from the number size distribution in Fig. 4. To assess possible maximum vaporization losses of particles and to identify the compounds for which the evaporation losses can inLuence the CCN spectra, total particle volumes necessary to establish the saturated vapor pressures in the experiment system were estimated for individual compounds and are indicated in Fig. 10 by horizontal dashed and dotted lines. The saturated conditions for adipic acid and malic acid can be established by the evaporation of only the particles smaller than 0:02 m in radius that is small enough to have no inLuence on the experimental results. On the other hand, in the cases of malonic acid and glutaric acid, the saturated vapor pressure cannot be established even though all the particles in the whole range of 0.01–0:2 m in radius evaporate. Therefore, the abnormal spectral features seen in the CCN spectra for malonic acid and glutaric acid can be explained successfully by the

438

M. Hori et al. / Aerosol Science 34 (2003) 419 – 448

solute evaporation. As for succinic acid, a nonnegligible diGerence can be seen in the two saturated vapor pressures taken from the literature. In the case of a higher vapor pressure, the particles in the whole size range can evaporate. The lower one, however, allows a substantial volume of succinic acid to survive in the experimental system in particulate form in the size range larger than 0:03 m in radius which is enough to cover the whole CCN spectrum in Fig. 9b. Hence, the moderately high vapor pressure of succinic acid might inLuence the extent to which the evaporation of particles occurred, depending sensitively on the variation in the laboratory temperature (20 ± 5◦ C). To reduce the eGect of solute vaporization losses, several CCN spectra were obtained without drying the air introduced for the dilution of particle number density, which was expected to result in an increase in the relative humidity in the sampling chamber to around 30 –50% or more depending on the relative humidity in the laboratory (we call this operation “humid operation” in contrast to the “normal operation”). The average OPC counts under the humid operations and the ratio to Np; r¿0:15 m (Rhumid=normal ) are also listed in Table 2. It is of interest that Rhumid=normal values for ammonium oxalate, succinic acid and adipic acid are small (1.05 –1.12) which might suggest that not only evaporation losses under the normal operations but also deliquescence under the humid condition did not occur as reported for succinic acid and adipic acid by Prenni et al. (2001). On the other hand, the OPC counts for malonic acid and glutaric acid signiFcantly increased up to 43 000 particles l−1 (Rhumid=normal = 6:04) and 21 800 particles l−1 (1:61), respectively, under the humid operation. Fig. 9c shows the CCN spectra under the humid operation for malonic acid, succinic acid and glutaric acid; spectra for ammonium sulfate, ammonium oxalate and adipic acid were also obtained for comparison. Although ammonium sulfate, ammonium oxalate and adipic acid exhibited no discernible diGerences from that under the normal operation, the data for malonic and glutaric acid apparently exhibited signiFcant increases in the CCN number concentrations from that in the normal operation. The raised spectrum for malonic acid becomes exactly parallel to those of other non-volatile compounds, whereas that of glutaric acid still tends to reach the ceiling. This implies that the humid condition suppressed the vaporization of solute particles substantially for malonic and considerably for glutaric acids by slowing down the evaporation rate of the droplets. Finally, the humid operation did not alter the CCN spectrum of succinic acid from the higher branch seen in the normal operation (Fig. 9b). This fact may imply that evaporation losses have not occurred in the higher branch case. 4.4. Activation capability of dicarboxylic acids Fig. 11 shows the critical supersaturations of sodium chloride (solid squares) and ammonium sulfate (solid circles) retrieved through the comparison between the corrected CCN spectra and the cumulative number size distribution. For comparison, the past experimental results by Gerber et al. (1977) are shown with the same but open symbols. Also shown are the theoretical lines for sodium chloride, ammonium sulfate and wettable but insoluble particles by thick solid, dashed and dotted lines, respectively. The horizontal error bars shown for individual data were estimated from the expected ranges of the maximum variation in the cumulative size distribution (Fig. 4), and the vertical error bars were the same as the horizontal error bars shown in Figs. 7b–c. As inferred also from the CCN spectra, the experimental data in Fig. 11 are quite consistent with the theoretical lines and also with the results by Gerber et al. (1977) within the expected error bars, indicating the well-known high ability as CCN.

M. Hori et al. / Aerosol Science 34 (2003) 419 – 448

Critical supersaturation (%)

1.0

439

Wettable but insoluble particle (Theory) (NH4)2SO4 (Theory)

NaCl (Theory) 0.1 0.02 0.04

0.06

0.08 0.1

0.15

Radius of dry particle (micrometer)

Fig. 11. The experimentally obtained relations between critical supersaturations and dry particle radii for sodium chloride (solid squares) and ammonium sulfate (solid circles). The past results by Gerber et al. (1977) are also shown (the same but open symbols). The error bars indicate uncertainties in the radius (horizontal) and supersaturation (vertical) estimated from the variations in the cumulative distribution of particles and those in the plate temperatures in TGDCC, respectively. Theoretical lines for inorganic compounds are taken from H4anel (1976) and that of wettable but insoluble particles is from Mason (1971).

Figs. 12a–g show the experimental critical supersaturations derived for (a) ammonium oxalate, (b) malonic acid, (c) succinic acid, (d) glutaric acid, (e) adipic acid, (f) malic acid and (g) phthalic acid (for each Fgure, the open circles show the results in the normal operation, the solid circles in the humid operation), and the past experimental results (solid triangles: Cruz & Pandis, 1997; solid diamonds: Corrigan & Novakov, 1999; solid squares: Prenni et al., 2001). Also shown are the theoretical lines estimated for individual dicarboxylic acid compounds. In particular, for the type A and B materials (ammonium oxalate, succinic acid, adipic acid and phthalic acid), the two types of theoretical relations estimated from the IP (dotted line) and NP (dashed and single-dotted line) in the equilibrium curves are illustrated, while for the type C (malonic acid, glutaric acid and malic acid) only the NP line is shown. For individual compounds, the activation capability and its theoretical predictability are discussed below, compared with the past experimental studies. 4.4.1. Ammonium oxalate (C2) Ammonium oxalate is a moderately soluble material. However, the experimental critical supersaturations for ammonium oxalate shown in Fig. 12a are quite low, exhibiting the highest CCN ability among the seven dicarboxylic acid compounds comparable to ammonium sulfate. The experimental values are consistent not with the theoretical IP line but with the NP line under both normal and humid operations. This strongly suggests that the whole solute can dissolve into a solution droplet even in the early stages of condensation far beyond the moderate solubility of the bulk material to depress the highest IP peaks down to below the NP heights. This may be accounted for by the Ostwald–Freundlich equation (Dundon, 1923; Dundon & Mack, 1923) which describes the

440

M. Hori et al. / Aerosol Science 34 (2003) 419 – 448 Wettable but insoluble particle (Theory)

(b) Malonic acid

1.0 NP Oxalic acid

Critical supersaturation (%)

Critical supersaturation (%)

(a) Ammonium oxalate

IP

(NH4)2SO4 (Theory) NaCl (Theory) 0.1 0.02 0.04 0.06 0.08 0.1 Radius of dry particle (micrometer)

1.0 NP

0.1 0.02

0.15

(d) Glutaric acid

1.0 NP

0.1 0.02

Critical supersaturation (%)

Critical supersaturation (%)

(c) Succinic acid

IP

1.0 NP

0.1 0.02

0.04 0.06 0.08 0.1 0.15 Radius of dry particle (micrometer)

0.04 0.06 0.08 0.1 0.15 Radius of dry particle (micrometer)

(f) Malic acid

(e) Adipic acid 1.0

Critical supersaturation (%)

Critical supersaturation (%)

0.15 0.04 0.06 0.08 0.1 Radius of dry particle (micrometer)

NP IP

0.1 0.02 0.04 0.06 0.08 0.1 Radius of dry particle (micrometer)

0.15

1.0

NP

0.1 0.02

0.04

0.06 0.08 0.1

0.15

Radius of dry particle (micrometer)

Fig. 12. Same as Fig. 11 but for (a) ammonium oxalate, (b) malonic acid, (c) succinic acid, (d) glutaric acid, (e) adipic acid, (f) malic acid and (g) phthalic acid obtained under the normal (open circles) and humid (solid circles) operations. The past experimental results are also shown by Cruz and Pandis (1997, solid triangles for glutaric acid and adipic acid), Corrigan and Novakov (1999, solid diamonds for succinic acid and adipic acid) and Prenni et al. (2001, solid squares for oxalic acid, malonic acid, succinic acid, glutaric acid and adipic acid). Theoretical lines for the individual dicarboxylic acid compounds (IP and/or NP lines) are derived from the computed equilibrium curves (e.g., Figs. 3a–c).

M. Hori et al. / Aerosol Science 34 (2003) 419 – 448

441

(g) Phthalic acid IP Critical supersaturation (%)

1.0

NP

0.1 0.02

0.04 0.06 0.08 0.1 Radius of dry particle (micrometer)

0.15

Fig. 12. (continued).

theoretical solubility enhancement of a solute particle as a function of particle size (i.e., the Kelvin equation for a solid–liquid interface). In addition, if the morphology of ammonium oxalate particle deviates from a sphere, for example, in the case of the Fne needle shape as inferred from Fig. 6a, the solubility enhancement eGect can be further enhanced due to the large curvature on the local particle surface, although the actual morphology of the submicron-order particles and the associated solubility enhancement eGect will have to be validated in other experiments. As a possibility, there might be another cause for the consistency of the experimental results with the NP line. That is, the particles might not crystallize completely when dried under 8–9% RH in the experimental system due to, for example, slowing down of the evaporation rate of water by the nature of the solute material. Peng and Chan (2001) observed that while ammonium oxalate could not initiate deliquescence until the RH became close to 100%, the substance could sustain water down to 60% RH in the evaporation loop and remain highly supersaturated until the size of the supersaturated droplet became nearly close to (only 1.03 times as large as) that of the dried particle. Because the possible concentrated droplet is too close in size to the dried crystal size, the OPC measurements might not have detected the occurrence explicitly. Therefore, this possibility cannot be excluded. As for the surface tension reduction eGect by the solute material, as summarized in Table 1, an aqueous solution of ammonium oxalate exhibits a slight surface tension enhancement similar to those of inorganic electrolytes such as ammonium sulfate and sodium chloride in contrast to the surface tension reduction by the other dicarboxylic acids (e.g., oxalic acid: −0:38 dyn cm−1 (King & Wampler, 1922), for others, see Table 1). Therefore, the surface tension eGect cannot explain the reduction of critical supersaturations from the IP line to NP. Prenni et al. (2001) measured the critical supersaturation of oxalic acid which is also shown in Fig. 12a (solid square) indicating higher critical supersaturation than our results for ammonium oxalate. As they mentioned, their experimental value also diGers from the theoretical value (Sc = 0:20%) calculated by them. Although the compounds are diGerent and the experimental conditions

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(residence time and relative humidity) are not necessarily the same between their system and ours, there might be a possibility of evaporation losses of solid particles in their system, as also occurred for oxalic acid in our system. As a result, the assumption of the inhomogeneous droplet structure with the employment of the bulk solute solubility, which gives the prediction of the IP line, could not simulate the experimental results probably due to the solubility enhancement associated with non-spherical morphology or due to incomplete crystallization. Rather, the hygroscopic behavior of ammonium oxalate can be predicted by the K4ohler equation with the original assumption that the solute core has dissolved entirely into the droplet in the early stages of the condensation. 4.4.2. Malonic acid (C3) Malonic acid is expected to have high CCN activity because of its high solubility as a type C material. Because of the evaporation losses which occurred during the normal operation, we will discuss the activation capability of malonic acid only with the results obtained under the humid operations in which the vaporization losses were expected to be substantially suppressed. The humid operations lower the critical supersaturations down to the theoretical line with which the results of Prenni et al. (2001) are also consistent (solid square). Hence, when the solute evaporation is suppressed due to a moderately humid condition, malonic acid can be considered to act as the second most eGective CCN following ammonium oxalate as shown in Fig. 12b, which can be successfully predicted by the conventional K4ohler curves. 4.4.3. Succinic acid (C4) Succinic acid is moderately soluble in water (type A) similar to ammonium oxalate, so that both IP and NP lines are illustrated in Fig. 12c. In contrast to the lower experimental values of the past studies that are consistent with the NP line, the experimental values of this study at a glance exhibit complex features. That is, the data tend to follow two branches on the Fgure. Although the higher branches (six open circles in the Fgure) seem to follow the IP line, the possibility of vaporization losses cannot be eliminated for the higher branch case from the discussion on the vapor pressure in Section 4.3. On the other hand, the lower one (lower 3 open circles and 2 solid circles) close to the NP line resulted during both the normal and humid operations and thus can be expected to result without the evaporation losses. From the view point of Raoult’s eGect, however, the solubility of the bulk material is too low to depress the high equilibrium water vapor pressure at the deliquescent (IP) points in the modiFed K4ohler curves down to the NP line. Thus, to follow the NP line, the particles have to dissolve into the solution droplets far beyond the bulk solubility due to solubility enhancement. The surface activity of a slightly dissolved solute can also have the same eGect of the depression of the equilibrium vapor pressure at the initial stages of condensation. However, the surface activity eGect estimated with the bulk solubility is insuMcient to diminish the IP (only 0.15% depression of the saturation ratio can occur for a 0.05-m radius particle). Another possibility is that the atomized droplets remained concentrated solutions from the beginning of the condensation due to imperfect drying. However, Prenni et al. (2001) seem to accomplish the crystallization of succinic acid particles and obtain the critical supersaturation close to the NP line (solid square in Fig. 12c). Thus the lower branch data can be considered to result without incomplete drying. Therefore, the combined eGect of the solubility enhancement and the surface tension reduction may have occurred in

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443

the lower branch case, although the occurrence of the solubility enhancement seems to be inconsistent with the hydrophobic nature of succinic acid. More delicate control of the experimental conditions might be necessary to obtain more explicit results regarding its CCN capability. As a result, a possible explanation for the noncommittal hygroscopic behavior is that solute solubility enhancement, surface tension reduction, evaporation losses and the hydrophobic nature of solute, several or all of these eGects were sensitively associated and aGected by variable experimental conditions such as the laboratory temperature. The consistency of the past studies and our low branch data with the NP line might suggest that the NP line is more practical for predicting the activation of succinic acid in the atmosphere in which moderately humid air is expected to reduce the evaporation losses of solute particles. 4.4.4. Glutaric acid (C5) The solubility of glutaric acid is quite high, comparable to that of ammonium sulfate (type C). However, the vaporization losses of particles were signiFcant under the normal operation due to its high vapor pressure. Thus, only the critical supersaturations obtained under the humid operation are shown in Fig. 12d. The experimental values still exhibit an unstable tendency with a steep increase with decreasing particle size, which suggests that the evaporation losses of smaller particles were not suppressed completely even in the humid operation. Even the lowest experimental results among the past studies cannot reach the theoretical line. The remaining inconsistency between the experiments and the theory might be due to the further evaporation losses of particles as mentioned by Prenni et al. (2001). Given that the evaporation losses are suppressed, the actual activation capability is expected to be at least around the lower boundary of the experimental values close to the NP line exhibiting a relatively lower CCN capability among the seven dicarboxylic acid compounds. 4.4.5. Adipic acid (C6) The CCN activity of adipic acid has been frequently investigated (Cruz & Pandis, 1997; Corrigan & Novakov, 1999; Prenni et al., 2001). Nonetheless, the experimental critical supersaturations obtained by the past and the present studies are signiFcantly dispersed between the theoretical IP and NP lines as shown in Fig. 12e. From the discussion of the poor solute solubility and surface hydrophobicity, it is reasonable that adipic acid has a low CCN ability as a type B material as indicated by the IP line, with which our experimental values are quite consistent. The resulting CCN ability is the lowest among the past and our experimental results for adipic acid and also the lowest among the seven compounds studied. One possible reason for the dispersion and the deviation from the IP line seen for the past results, particularly for Cruz and Pandis (1997) and Corrigan and Novakov (1999), may be incomplete drying of the atomized droplets. The relative humidity and temperature in the particle drying stages in the experimental systems employed by the present and the past studies range as follows: 8–9% RH at 20 ± 5◦ C (this study), ¡ 5% at 30◦ C (Prenni et al., 2001) and ¡ 20% (Corrigan & Novakov, 1999) (not shown in Cruz & Pandis, 1997), although the residence time of particles from the atomizer to the cloud chamber is not described clearly in those studies except for ours (over 1 min). If the relative humidity or residence time was insuMcient for the complete evaporation of droplets, the atomized droplets could remain a highly concentrated solution as a whole or partially, which has the same eGect as the solubility enhancement and may cause a large surface tension

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reduction beyond the measured values by Shulman et al. (1996) in the early stages of condensation growth. The consistency of our experimental results with the IP line for adipic acid indicates that the assumption of the inhomogeneous droplet structure succeeded in the simulation of the hygroscopic behavior of adipic acid particles generated in this experimental system. 4.4.6. Malic acid (C4) In Fig. 12f, the theoretical line (NP) is quite consistent with the experiment values, which demonstrates the high CCN ability of malic acid comparable to that of malonic acid. Malic acid has an extremely high solubility (type C) and can also reduce the surface tension of its aqueous solution from that of pure water as much as succinic acid does (Table 1), which leads to a large reduction in the surface tension of solution droplets at the early growth stages with the help of the extremely high solubility. As a result, the hygroscopic behavior of malic acid can be considered to follow the conventional K4ohler curves. 4.4.7. Phthalic acid (C8) Phthalic acid has the lowest solubility among the examined compounds. Thus the highest critical supersaturations determined by the IP heights in the modiFed K4ohler curves were expected as a type B material. However, as shown in Fig. 12g, contrary to this expectation, the experimental values were not close to the IP line but to the NP line exhibiting high CCN ability just comparable to that of malic acid! The most probable cause for the resulting high CCN ability were the incomplete drying of atomized droplets as explained earlier for the large OPC counts of phthalic acid particles, which was expected to result in apparent enhancement of solute solubility and the associated surface tension reduction. Although the surface tension of phthalic acid solution measured by Shulman et al. (1996) does not exhibit a large reduction from that of pure water due to the poor solubility, the incomplete drying may promote the preferential absorption of solute molecules at the concentrated droplet surface (Shulman et al., 1997) and thus lead to a large surface tension reduction at the droplet surface. Although it is still diMcult to specify the actual particulate form of phthalic acid in the atmosphere and also diMcult to determine whether the particles crystallize, the experimental results at least demonstrate that the high activation capability of the pure aqueous solution droplets of phthalic acid can be expected and that the observed hygroscopic behavior can be successfully predicted by the K4ohler theory with the conventional assumption. 5. Summary and conclusions The activation capability of seven low molecular weight dicarboxylic acid compounds was determined by laboratory experiments. Among the seven compounds, ammonium oxalate had the highest capability, comparable to ammonium sulfate. Malic acid and phthalic acid had the second highest ability. Adipic acid, on the other hand, had the lowest capability nearly close to that of an insoluble particle. Malonic acid and glutaric acid exhibited particle evaporation in the experimental system under normal experimental operations, but had high (close to malic acid) and moderate capability, respectively, under supplementary humid operation. Finally, succinic acid exhibited noncommittal

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Table 3 Summary of the experimental critical supersaturations (%) of low molecular weight dicarboxylic acids at a radius of 0:05 m obtained by this study in normal and humid operations and by past laboratory studies Compounds

This study

Past studies

Normal operation

Humid operation

Prenni et al. (2001)

Corrigan and Novakov (1999)

Cruz and Pandis (1997)

Ammonium oxalate Oxalic acid Malonic acid Succinic acid Glutaric acid Adipic acid Malic acid Phthalic acid

0.19 — ND 1.22 ND 1.65 0.25 0.25

0.18 — 0.23 (0.27) ND (1.65) — —

— 0.44 0.24 0.21 0.32 1.00 — —

— — — (0.32) — (0.58) — —

— — — — 0.37 0.37 — —

Ammonium sulfate

(0.16)

—

—

(0.16)

(0.20)

Note. ND: not determinable due to the evaporation of solid particles. Values in parentheses are obtained by extrapolation of the experimental data.

behavior of high or low capability, which might be due to the dependence of the physicochemical properties of the solute on the laboratory temperature. The resulting experimental critical supersaturations for 0.05-m radius particles are summarized with the past results in Table 3. In the atmosphere, supersaturation of 0.1– 0.4% occurs naturally in the usual cloud processes. Thus, the dicarboxylic acid compounds with a critical supersaturation lower than 0.4% can be expected to activate into cloud droplets preferentially, even if the particles are distributed in a size range smaller than 0:1 m in radius. However, it should be noted that, as appeared from the comparisons with the past studies for adipic acid, the experimentally derived critical supersaturations for slightly water-soluble compounds could depend signiFcantly on the particle phase (solid or liquid) exhibited in the initial condensation stages. Theoretical predictability of the experimental results with the K4ohler theory was also signiFcantly inLuenced by the initial phase of the particles. These suggest that the control of the initial particle phase in the experimental system is of critical importance for the experiments on the hygroscopic behavior of less soluble particles. In the real atmosphere, also, the initial particle phase can be considered a key factor to be determined in order to evaluate the actual CCN ability for such less soluble compounds. In addition, morphology of the solid particles might be another important factor to be taken into account when the particles exhibit crystallization and also a highly non-spherical shape, because a solubility enhancement eGect might occur. Further studies on this eGect for various less soluble compounds will have to be done to determine the necessity of the consideration. Even if the particles are volatile and are distributed partially in the gas phase as seen for oxalic acid, recondensation of organic acid vapors on existing droplets could promote droplet growth as shown for nitric acid by Laaksonen et al. (1998). Thus, the condensation eGect of volatile compounds will also have to be taken into account.

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Finally, the mass concentrations of dicarboxylic acid compounds in the atmosphere can be estimated to be on the order of a tenth of those of non-seasalt sulfate from the past studies (Sempere & Kawamura, 1994; Kawamura & Usukura, 1993; Husain & Dutkiewicz, 1990; Savoie, Prospero, Arimoto, & Duce, 1994; Hori et al., 1999). The present study provides experimental data on the activation capability for the pure dicarboxylic acid compounds as the Frst step. Because actual particles in the atmosphere could be mixed with various inorganic and organic compounds, the particles may exhibit more complex properties such as solubility, surface activity, hydrophobicity and morphology and so on. Therefore, the eGect of those complicated features on the hygroscopic behavior of particles will have to be investigated. References Burrows, H. D. (1992). Studying odd-even eGects and solubility behavior using ; !-dicarboxylic acids. Journal of Chemical Education, 69, 69–73. Corrigan, C. E., & Novakov, T. (1999). Cloud condensation nucleus activity of organic compounds: a laboratory study. Atmospheric Environment, 33, 2661–2668. Cruz, C. N., & Pandis, S. N. (1997). A study of the ability of pure secondary organic aerosol to act as cloud condensation nuclei. Atmospheric Environment, 31, 2205–2214. Cruz, C. N., & Pandis, S. N. (1998). The eGect of organic coatings on the cloud condensation nuclei activation of inorganic atmospheric aerosol. Journal of Geophysical Research, 103, 13111–13123. Dea, J. Y., & Katz, U. (1981). Steady generation of aerosols with an improved constant output atomizer. Journal de Recherches Atmospheriques, 15, 285–290. Dean, J. A. (1985). Lange’s handbook of chemistry (pp. 7–596). New York: McGraw-Hill. Deutsche Chemische Gesellschaft (1921). Beilsteins Handbuch der Organischen Chemie, Vol. 4. AuL., Bd. 3. Berlin: Springer. Deutsche Chemische Gesellschaft (1928). Gmelins Handbuch der Anorganischen Chemie, System-Nr. 21, Natrium. Berlin: Verlag Chemie. Deutsche Chemische Gesellschaft (1936). Gmelins Handbuch der Anorganischen Chemie, System-Nr. 23, Ammonium. Berlin: Verlag Chemie. Deutsche Chemische Gesellschaft (1942). Beilsteins Handbuch der Organischen Chemie, 4. AuL., 2. Erg., Bd. 2. Berlin: Springer. Deutsche Chemische Gesellschaft (1949). Beilsteins Handbuch der Organischen Chemie, 4. AuL., 2. Erg., Bd. 9. Berlin: Springer. Dundon, M. L. (1923). Surface energy of several salts. Journal of American Chemical Society, 45, 2658–2667. Dundon, M. L., & Mack, E. Jr. (1923). The solubility and surface energy of calcium sulfate. Journal of American Chemical Society, 45, 2479–2485. Facchini, M. C., Mircea, M., Fuzzi, S., & Charlson, R. J. (1999). Cloud albedo enhancement by surface-active organic solutes in growing droplets. Nature, 401, 257–259. Gerber, H. E., Hoppel, W. A., & Wojciechowski, T. A. (1977). Experimental veriFcation of the theoretical relationship between size and critical supersaturation of salt nuclei. Journal of Atmospheric Science, 34, 1836–1841. H4anel, G. (1976). The properties of atmospheric aerosol particles as functions of the relative humidity at thermodynamic equilibrium with the surrounding moist air. Advances in Geophysics, 19, 73–188. Hegg, D. A., Gao, S., Hoppel, W., Frick, G., CaGrey, P., Leaitch, W. R., Shantz, N., Ambrusko, J., & Albrechcinski, T. (2001). Laboratory studies of the eMciency of selected organic aerosols as CCN. Atmospheric Research, 58, 155–166. Heintzenberg, J. (1989). Fine particles in the global troposphere: a review. Tellus, 41B, 149–160. Hori, M., Ohta, S., Murao, N., & Yamagata, S. (1999). Concentrations of water soluble organic aerosols at Mt. Lemmon in Arizona. Journal of Global Environment Engineering, 5, 11–25. Husain, L., & Dutkiewicz, V. A. (1990). A long-term (1975 –1988) study of atmospheric SO2− 4 : Regional contributions and concentration trends. Atmospheric Environment, 24A, 1175–1187.

M. Hori et al. / Aerosol Science 34 (2003) 419 – 448

447

Intergovernmental Panel on Climate Change (IPCC) (1996). In J. T. Houghton et al. (Eds.), Climate Change 1995: The Science of Climate Change, Contribution of WG1 to the Second Assessment Report of the Intergovernmental Panel on Climate Change. New York: Cambridge University Press. Katz, U., & Kocmond, W. C. (1973). An investigation of the size supersaturation relationship of soluble condensation nuclei. Journal of Atmospheric Science, 30, 160–165. Kawamura, K., & Ikushima, K. (1993). Seasonal change in the distribution of dicarboxylic acids in the urban atmosphere. Environmental Science and Technology, 27, 2227–2235. Kawamura, K., & Usukura, K. (1993). Distributions of low molecular weight dicarboxylic acids in the north paciFc aerosol samples. Journal of Oceanography, 49, 271–283. King, H. H., & Wampler, R. W. (1922). The adsorption and orientation of the molecules of dibasic organic acids and their ethereal salts in liquid–vapor interfaces. Journal of American Chemical Society, 44, 1894–1902. K4ohler, H. (1936). The nucleus in and the growth of hygroscopic droplets. Transactions of the Faraday Society 1152–1161. Laaksonen, A., Korhone, P., Kumala, M., & Charlson, R. J. (1998). ModiFcation of the K4ohler equation to include soluble trace gases and slightly soluble substances. Journal of Atmospheric Science, 55, 853–862. Lammel, G., & Novakov, T. (1995). Water nucleation properties of carbon black and diesel soot particles. Atmospheric Environment, 29, 813–823. Liu, P. S., Leaitch, W. R., Banic, C. M., Li, S. -M., Ngo, D., & Megaw, W. J. (1996). Aerosol observations at Chebogue Point during the 1993 North Atlantic Regional Experiment: Relationships among cloud condensation nuclei, size distribution, and chemistry. Journal of Geophysical Research, 101, 28971–28990. Low, R. D. H. (1969). A generalized equation for the solution eGect in droplet growth. Journal of Atmospheric Science, 26, 608–611. Mason, B. J. (1971). The physics of clouds (671pp). London: Oxford University Press. Matsumoto, K., Nagao, I., Tanaka, H., Miyaji, H., Iida, T., & Ikebe, Y. (1998). Seasonal characteristics of organic and inorganic species and their size distributions in atmospheric aerosols over the northwest paciFc ocean. Atmospheric Environment, 32, 1931–1946. Morgan, J. L. R., & McKirahan, W. W. (1913). The weight of a falling drop and the laws of tate; XIV. The drop weights of aqueous solutions of the salts of organic acids. Journal of American Chemical Society, 35, 1759–1767. Mueller, P. K., Fung, K. K., Heisler, S. L., Grosjean, D., & Hidy, G. M. (1982). Atmospheric particulate carbon observations in urban and rural areas of the United States (pp. 343–370). In G. T. WolG & R. L. Klimisch (Eds.), Particulate carbon-atmospheric life cycle. New York: Plenum Press. Naruse, H. (1978). On an improvement of the thermal diGusion chamber for cloud nuclei measurement and some measurements around the paper mills (in Japanese with English abstract). Meteorology and Geophysics, 29, 141–150. Novakov, T., Corrigan, C. E., Penner, J. E., Chuang, C. C., Rosario, O., & Mayol-Bracero, O. L. (1997). Organic aerosol in the Caribbean trade winds: A natural source? Journal of Geophysical Research, 102, 21307–21313. Novakov, T., & Penner, J. E. (1993). Large contribution of organic aerosols to cloud-condensation nuclei concentrations. Nature, 365, 323–365. Ohta, S., & Okita, T. (1990). A chemical characterization of atmospheric aerosol in Sapporo. Atmospheric Environment, 24A, 815–822. Peng, C., & Chan, C. K. (2001). The water cycles of water-soluble organic salts of atmospheric importance. Atmospheric Environment, 35, 1183–1192. Prenni, A. J., DeMott, P. J., Kreidenweis, S. M., Sherman, D. E., Russell, L. M., & Ming, Y. (2001). The eGects of low molecular weight dicarboxylic acids on cloud formation. Journal of Physical Chemistry, 105, 11240–11248. Pruppacher, H. R., & Klett, J. D. (1997). Microphysics of clouds and precipitation (954pp). Dordrecht: Kluwer Academic Publishers. Rogge, W. F., Mazurek, M. A., Hildemann, L. M., Cass, C. R., & Simoneit, B. R. T. (1993). QuantiFcation of urban organic aerosols at a molecular level: IdentiFcation, abundance and seasonal variation. Atmospheric Environment, 27A, 1309–13330. Savoie, D. L., Prospero, J. M., Arimoto, R., & Duce, R. A. (1994). Non-sea-salt sulfate and methanesulfonate at American Samoa. Journal of Geophysical Research, 99, 3587–3596.

448

M. Hori et al. / Aerosol Science 34 (2003) 419 – 448

Saxena, P., & Hildemann, L. M. (1996). Water-soluble organics in atmospheric particles: A critical review of the literature and application of thermodynamics to identify candidate compounds. Journal of Atmospheric Chemistry, 24, 57–109. Sempere, R., & Kawamura, K. (1994). Comparative distributions of dicarboxylic acids and related polar compounds in snow, rain and aerosols from urban atmosphere. Atmospheric Environment, 28, 449–459. Shulman, M. L., Carlson, R. J., & Davis, E. J. (1997). The eGects of atmospheric organics on aqueous droplet evaporation. Journal of Aerosol Science, 28, 737–752. Shulman, M. L., Jacobson, M. C., Carlson, R. J., Synovec, R. E., & Young, T. E. (1996). Dissolution behavior and surface tension eGects of organic compounds in nucleating cloud droplets. Geophysical Research Letters, 23, 277–280. Stephen, H., & Stephen, T. (1963). Solubilities of inorganic and organic compounds, Vol. 1. Oxford: Pergamon Press. Twomey, S. (1991). Aerosols, clouds and radiation. Atmospheric Environment, 25A, 2435–2442. Washburn, E. W. (1928a). International critical tables of numerical data, physics, chemistry and technology, Vol. 3. New York: McGraw-Hill. Washburn, E. W. (1928b). International critical tables of numerical data, physics, chemistry and technology, Vol. 4. New York: McGraw-Hill. Weingartner, E., Burtscher, H., & Baltensperger, U. (1997). Hygroscopic properties of carbon and diesel soot particles. Atmospheric Environment, 31, 2311–2327. Yu, S. (2000). Role of organic acids (formic, acetic, pyruvic and oxalic) in the formation of cloud condensation nuclei (CCN): A review. Atmospheric Research, 53, 185–217.