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A study of the ability of pure secondary organic aerosol to act as cloud condensation nuclei
Pergamon
Armosphrrrc
Enkwwnenr
PII: S1352-2310(97)00054-X
Vol. 31, No 15, pp. 2201-2214. 1997 .c\ 1997 Elsewer Saence Ltd All nghts reserved. Printed in Great Britain 13%2310!97 1617.M) + 000
A STUDY OF THE ABILITY OF PURE SECONDARY AEROSOL TO ACT AS CLOUD CONDENSATION CELIA N. CRUZ and SPYROS
ORGANIC NUCLEI
N. PANDIS
Department of Chemical Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, U.S.A. (First received 28 October 1996 and in_finalform 6 January 1997. Published May 1997)
Abstract-Submicron atmospheric particles that serve as cloud condensation nuclei (CCN) at low supersaturations are important for quantifying the effect of aerosols on cloud properties and global climate. In this study, we investigate experimentally the ability of model submicron aerosols consisting of pure organic species to become CCN at typical atmospheric supersaturations. The CCN activity of glutaric acid, adipic acid, and dyoctylphthalate (DOP) aerosols was determined by producing a nearly monodisperse distribution of submicron particles and comparing total CCN concentrations to total number concentrations. The measurements were performed using a Tandem Differential Mobility Analyzer in combination with a cloud condensation nuclei counter at supersaturations of 0.30 and 1.0%. The uncertainty in the measurements was determined by using NaCl and (NH&SO, aerosols; the results indicated that activation diameters could be measured within an error of f 16%. Adipic acid and glutaric acid aerosols served as CCN at both supersaturations and their behavior is in fair agreement with Kiihler theory. On the other hand, DOP aerosol as large as 0.15 pm in diameter, did not become activated, even at supersaturations as high as 1.2%. These results indicate that the CCN activity of hygroscopic organic aerosols may be comparable to that of some inorganic aerosols. 0 1997 Elsevier Science Ltd. Key word index: Cloud condensation nuclei, secondary organic aerosol (SOA), dicarboxylic acids, organic aerosol.
INTRODUCTION Submicron atmospheric particles can serve as nuclei on which water condenses to form cloud droplets at supersaturations lower than those required for homogeneous water nucleation. Understanding the cloud condensation nuclei (CCN) activity of atmospheric
aerosols is important in order to quantify their effect on the formation, lifetime, and radiative properties of clouds. The size distribution and chemical composition of the pre-cloud aerosols have been shown to be key factors in predicting the number density and size distributions of cloud droplets (Twomey, 1974). This aerosol-cloud interaction has been shown to be an indirect mechanism by which aerosols may affect the radiation balance of the Earth and global climate 1991). For instance, sulfates (e.g. (Twomey, (NH&S04, NH4HS04) are known to be a main component of CCN at low cloud supersaturations (< 0.3%) (Twomey, 1971; Kaufman and Tanre, 1994). It has been suggested that the high reflectivity of cloud droplets containing sulfate increases the Earth’s albedo resulting in a potential countereffect to global warming by greenhouse gases (Wigley, 1989, 1991; Jones et al., 1994). The process by which the inorganic fraction of atmospheric particles activates into CCN is well
understood (Kijhler, 1936; Pruppacher and Klett, 1980). For these particles, one can predict CCN activation based on chemical composition, solubility, surface tension, and dry particle size (Pruppacher and Klett, 1980). However, atmospheric aerosols have mixed chemical composition, with a variety of inorganic (e.g. sulfate, nitrate, ammonium, and sodium) and organic species often present in a single particle. Total organic carbon can represent lo-65% of the aerosol mass less than 2.5 pm (Wolff et al., 1991; Sloane et al., 1991; Chow et al., 1994; Lewis et al., 1986; Lewis and Dzumbay, 1986). while secondary organic carbon can contribute up to 25-50% of the fine aerosol mass in urban polluted areas (Gray et al., 1986; Larson et ul., 1989). Despite the considerable fraction of organic matter in atmospheric aerosol, relatively little is known about the ability of organic particles to act as CCN and about their contribution to ambient CCN concentrations. Studies on the size distribution and chemistry of CCN tend to ignore organic aerosols, because of lack of knowledge on the cloudnucleating properties of organic species (Hudson and Da, 1995). Therefore, it is key to determine the contribution of organic species to CCN activation and to cloud properties dependent on CCN size and chemistry.
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C. N. CRUZ and S. N. PANDIS
Recent studies on atmospheric aerosols by Novakov and Penner (1993) presented evidence that 37% of the CCN number concentrations measured at a remote site at 0.5% supersaturation were accounted for by sulfate and the remainder by organic material. However, due to lack of information about the mixing state of the atmospheric particles at the site, it was not clear whether the inorganic fraction of the mostly organic aerosol rendered these particles CCN active, or whether some organic compounds were intrinsically CCN active. This issue has not been resolved by previous investigations on the CCN activity of primary organic aerosol from wood burning and other combustion sources (Rogers et al., 1991; Lammel and Novakov, 1995). In these studies, the CCN activity of the organic aerosol was directly compared to the water-soluble fraction of the particles, which was assumed to be mostly inorganic and electrolytic. However, the water nucleation properties calculated under this assumption proved to be insufficient in predicting the CCN activity of the particles, thus indicating possible organic contribution to CCN. Saxena et al. (1995) showed that organic compounds alter the hygroscopicity of atmospheric particles. Their results indicated that in a nonurban location, the organic fraction of the atmospheric particles increased the water absorption by particles. Organics accounted for 25-40% of the aerosol liquid water content at relative humidities ranging from 80 to 88%. A possible explanation for this behavior was the presence of hydrophilic organics such as carboxylic and dicarboxylic acids, alcohols, and aldehydes, which are abundant in nonurban aerosols. The combination of these studies lead to the hypothesis that high wateraffinity organic compounds in atmospheric aerosols can present hygroscopic behavior comparable to inorganic species, and organic particles may therefore act as CCN. This study investigates the ability of some pure organic aerosols to act as CCN at conditions similar to those in the atmosphere. Organic compounds accumulate mainly in the submicrometer aerosol size regime (Finnlayson-Pitt, 1986; McMurry and Zhang, 1989), and their mass distribution is typically bimodal with the first peak at approximately 0.2 pm and the second around 1 pm (Pickle et al., 1990; Mylonas et nl., 1991). Dicarboxylic acids represent a major component of the water-soluble primary and secondary organic carbon mass in the atmosphere, therefore these species were chosen as representative organics for this investigation. In order to assess the CCN activity of these hydrophilic organic compounds, we study two dicarboxylic acids: adipic acid (CsHi004) and glutaric acid (C5H804). Specifically, adipic and glutaric acids are abundant secondary organic aerosol (SOA) species (Sempere and Kawamura, 1994; Saxena and Hildemann, 1996) formed from the oxidation reaction of olefins with ozone (Grosjean and Friedlander, 1979; Hatakeyama et al., 1985; O’Brien et al.,
1975). Additional organic acids measured in atmospheric aerosol include n-alkanoic acids (C66C34), n-alkenoic acids (C6-C8), benzoic acids, and other dicarboxylic acids (C3-C9) (Rogge et al., 1993). Thus, to a first approximation, the species selected for this study can be viewed as representative of a much larger group of compounds found in atmospheric aerosol. We compare these results to the CCN activity of dyoctylphthalate (DOP), which is an example of a hydrophobic organic compound with negligible solubility in water. Finally, we quantify the uncertainty in the CCN activity measurements for these pure organic aerosols by comparing them to CCN measurements for sodium chloride (NaCl) and ammonium sulfate ((NH&SO& two inorganic sahs modeled by Kiihler theory.
THEORY AND APPROACH
Kohler (1936) theory predicts the CCN activation of inorganic electrolytic salts such as NaCl and (NH&SO, based on the thermodynamic balance of two competing effects: the decrease in water vapor pressure due to the solvent (Raoult effect) and the increase in water vapor pressure due to the curvature of the droplet surface (Kelvin effect). In his derivation, Kohler assumed that the CCN consisted of a completely soluble substance that had negligible vapor pressure and that the mass of this solute remained constant during droplet growth. The Kohler equation describes the relationship between equilibrium saturation (S,,) of a water droplet and its radius (a) as 2ff”M, S,, = exp __ RTp,a
Wvm,M,/M, (4np”a3/3) - m,
1 (14
where 0” is the surface tension of the solution in air, M, and M, are the molecular weights of water and solute, respectively, m, is the solute mass, pw and p” are the densities of water and the solution, respectively, v is the average number of ions into which a solute molecule dissociates (e.g. vNaCl= 2 and V~Nu&so4= 3); and @”is the osmotic coefficient of the aqueous solution. This equation can be simplified by performing a Taylor series expansion on the exponential (S,, z 1) and applying the following assumptions: (i) the solution is dilute (m, < m,, where m, is the mass of water) and ideality applies (@”= 1); and (ii) the solution surface tension and bulk density are that of pure water (0” z 6, and p” z pw). The equilibrium supersaturation for a droplet is defined as, seq = &, - 1, or, WJ4,
scq = ~ RTp,u
-
3vm, M, 4zM,p,a3’
(lb)
For a given solute mass, the simplified Kohler equation (lb) describes an equilibrium curve with a
Pure secondary organic aerosol as CCN maximum at a critical supersaturation cal radius (a,):
(s,) and a criti-
(2) a, =
3B
J 2
where
&vMw
A=-.-----
RTP,
and
l3=$$$’
2207
Table 1. The theoretical values for Dp*were also calculated for glutaric and adipic acids species using the same assumptions outlined previously (Table 1). Given that the first-step dissociation constants (K,) for the diacids are less than 4.6 x lo--’ M, and the second-step dissociation constants are less than 3.9 x 10M5 M (CRC Handbook, 1986) a value of v = 1 was used in these calculations. The theoretical values calculated for D,*were used to determine the applicability of Kohler theory to these organic species.
s w EXPERIMENTAL
These critical values define a transition point from a stable to an unstable region in the supersaturation, s,~, vs droplet radius, a, equilibrium curve. For envir-
onmental supersaturations below s, and droplet radii less than a,, the solution droplet can achieve a diameter satisfying equation (lb), and it can attain stable equilibrium with the environment. When the environment achieves a supersaturation greater than s,, then the solution droplet is said to activate into a cloud droplet, because it will continue to grow limited only by diffusion of water vapor from the gas phase. A droplet is also activated when the environment supersaturation is greater than the equilibrium supersaturation predicted by Kiihler theory and the droplet radius is greater than a,. For the purposes of this study, a particle activates only when exposed to an environment supersaturation greater than or equal to its so and then grows into a cloud droplet. Thus, by selecting an experimental s, (e.g. 0.3%), it is possible to calculate from equation (2) the minimum theoretical solute mass necessary to activate the nucleus into a droplet. This mass can be converted into the corresponding dry particle diameter (0:) which, in theory, should activate into a cloud droplet at the chosen critical supersaturation. In this manner, CCN activity for any solute that satisfies Kohler theory, can be predicted for any given conditions. The theoretical values for the activation diameter (Dt), which is the dry particle diameter necessary for activation at the specified s,, are calculated in
The experimental apparatus is a combination of a Tandem Differential Mobility Analyzer (TDMA; Rader and McMurry, 1986) and a cloud condensation nuclei counter (CCNC) (Fig. 1). The primary components of the system are a monodisperse aerosol generation system, an aerosol classifier system, a single condensation particle counter (CPC), and the CCNC. This setup allows the control of particle size, particle chemical composition, and supersaturation for CCN measurements, while allowing independent measurements of particle size, total number concentration, and CCN concentration Monodisperse aerosol generation system
A collision atomizer (Constant Output Atomizer 3076, TSI) is used to produce an aerosol of the species to be investigated (e.g. C,H,,O,) from a 0.10 wt% doubledeionized water solution, or in the case of DOP, from a 0.10 ~01% methanol solution. Double deionized filtered water from a Milhpore system and EM Omnisolv grade methanol ( < 0.1 ppm residue after evaporation) are used as solvents to minimize impurities. The solvent is evaporated from the aerosol by passing it through a silica gel diffusion dryer. The polydisperse dry particles are then charged in a Kr-86 bipolar aerosol neutralizer (Aerosol Neutralizer 3077, TSI) and the aerosol reaches a nearly Boltzmann equilibrium distribution of charges. The aerosol then flows from the neutralizer into the first Differential Mobility Analyzer (DMAl), where particles of a chosen electrical mobility and diameter are selected (Liu and Pui, 1974; Knutson and Whitby, 1975). By changing the rod voltage in DMAl (Electrostatic Classifier 3071A, TSI), nearly monodisperse distributions of particles with different mean diameters are generated to enter both the DMA2-CPC system and the CCNC.
Table 1. Properties and theoretical activation diameters for investigated compounds
MW (g mot-‘) Sodium chloride Ammonium sulfate Glutaric acid Adipic acid
P (g cm-?
Solubihty (g per 100 cm3) Hz0
1’
0;: (pm) SC = 0.3%
D,* (pm) SC = 1.0%
58.44
2.165
36.0
2
0.052
0.023
132.14 132.11 146.14
1.769 1.424 1.360
75.4 116” 2.5”
3 1 1
0.063 0.098 0.103
0.028 0.044 0.046
Note: p, density, Y,average number of ions after dissociation, Dp*,activation diameter. All properties are taken from the CRC Handbook unless otherwise noted. All calculations assume T = 295.15 K, uw = 73 dyn cm-’ (0.073 J m-‘). ’Saxena and Hildemann (1996).
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C. N. CRUZ and S. N. PANDIS
Airzdion Neutralizer
]
DMAl t Compressed Air
Dilution
Air
DMA2 Syringe Exhaust
Pump
4 1 Air Ewi
1
CCNC
Compressed Air
Fig. 1. Schematic of experimental apparatus for cloud condensation nuclei measurements.
Aerosol classijer and total number concentration counter
The second DMA and the CPC (Condensation Particle Counter 3010, TSI) are part of the Scanning Mobility Particle Sizer system (SMPS 3934, TSI) used to classify particles by scanning voltages and measuring concentrations simultaneously. The CPC samples the total number concentration (CN) using a supersaturated environment of n-butanol where all particles are detected by a counting laser. The SMPS system can generate a full distribution in a few minutes, checking the consistency of the monodisperse generation system. During each experiment, a measurement of the full nearly monodisperse distribution and the total number concentration was acquired every 6-8 min. An intercalibration of both DMAs using NaCl aerosol indicated that the particles generated by DMAl and the particles measured by DMA2 agree in diameter within + 0.002 pm for D, < 0.090 pm and within + 0.006 pm for D, > 0.120 pm. Particle-sizing agreement between DMAl and DMA2 showed no dependence on chemical composition of the aerosol. Cloud condensation nuclei counter
The cloud condensation nuclei counter (CCNC) is a thermal diffusion chamber-type counter (Ml model, DH Associates) which operates by sampling a 6 mm3 volume approximately every 30 s. The upper and lower surfaces of the chamber are kept wet and at different temperatures, cooling the bottom one thermoelectrically. This way, a thermal and vapor density gradient is created within the chamber, with a maximum supersaturation near the center of the chamber. Particles with the correct size and chemistry for CCN activation grow into droplets and are counted by a laser. During
all experiments, the CCN concentration was kept lower than 1000 cme3. The supersaturation experienced by the particles can be adjusted by changing the temperature difference across the chamber. Experimental procedure
With this experimental setup (Fig. 1), the CCN activation curves can be reproduced in two ways: keeping the diameter of the sample aerosol constant and changing the supersaturation inside the CCNC (Kohler curves), or keeping the supersaturation constant and changing the size of the particles, i.e. mass of the species, entering the chamber. The latter procedure was used throughout these experiments, with a constant supersaturation of either 0.30 or 1.0%. For each diameter size, a measurement of the total number concentration of CCN was completed in an hour and was then compared to the average total number concentration (CN) measured by the SMPS during the sampling time. By calculating the ratio of CCN-activated particles to the total number of particles in the nearly monodisperse distribution, CCN/CN, it was possible to calculate the fraction of particles activated with increasing dry particle diameter. This procedure was repeated for different chemical species, yielding CCN activation curves for sodium chloride, ammonium sulfate, adipic acid and glutaric acid.
RESULTS AND DISCUSSION The first portion of this study was devoted to testing the accuracy of the experimental technique by
Pure secondary
d%oo-
J =,~ O.d20
organic
., ‘ O.d40
aerosol
as CCN
2209
L I
0.060
I 0.080
I
0.100
\ 0.120
Dry Particle Diameter (pm) Fig. 2. Experimental CCN activation curve for NaCl at s = 0.30 and 1.0%.
Dry Particle Diameter (pm) Fig. 3 Experimental CCN activation curves for (NH&SO4 at s = 0.30 and 1.0%
investigating the CCN activation of NaCl and (NH&S04. The results from this exercise were then used to assess the validity of the CCN measurements for adipic acid, glutaric acid, and DOP. NaCl and (NH&SO4 The experimental activation curves for NaCl and (NH&SO4 at the two supersaturations (s = 0.30 and 1.0%) are presented in Figs 2 and 3. The percentage activation is given as the ratio of CCN to the total
number concentration (CN) measured by the CPC. The dry particle diameters reported are the peaks of the nearly monodisperse distributions generated by DMAl, as measured by DMA2, and are thus, mobility-equivalent diameters. For spherical particles, these two diameters are equal, because density does not affect the diameters selected by the DMA. However, a shape factor of 1.08 was used to analyze data for NaCl (Kelly and McMurry, 1992). For each point on the curve, an average value for the peak dry diameter
C. N. CRUZ and S. N. PANDIS
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Table 2. Results for s = 0.3% and s = 1.0% Supersaturation
= 0.3%
Supersaturation
= 1.0%
Species
Da50 (pm)
Error’ (%)
Equationb (4) (pm)
Error’ (%)
NaCl (NH&S04 C&L@4 (glutaric) C,H,,O, (adipic)
0.060 0.074
+ 15.4 + 17.5
0.058 0.075
+ 11.5 + 19.0
0.014 0.029
- 15.5 + 3.6
0.019 0.029
- 15.5 + 3.6
0.111 0.115
+ 13.3 + 11.7
0.112 0.108
+ 14.3 + 4.9
0.060 0.052
+ 36.4 + 13.0
0.057 0.051
+ 29.5 + 10.9
Error (%)
Equation (4) (pm)
Error (%)
a Calculated from diameter at 50% activation (DsO) by curve fitting. bCalculated from equation (4) for all distributions with CCN activations between 20 and 80%. ‘The error for both methods was calculated as the difference between the experimental values and the theoretical value of 0: (Table 1) divided by the thoeretical Dp*.For example, (D,,, - Q/D,*.
and the total number CN concentration was used for the sampling time (x 80 min). This corresponds to the average of lo-14 sample distributions, whose peak diameters and total concentrations did not vary by more than 3 and lo%, respectively. The data from the CCN activation curves were analyzed using two methods. In the first method, an experimental value of D,* was derived by defining it as the diameter at 50% activation (D&. As seen in Figs 2 and 3, a sigmoidal function was fitted to the activation curves and a value for D5,_, was extracted for each supersaturation. The basis for this method is that at 50% activation, half the particles have a diameter greater than D50,which should correspond to Dz.The value for D5,,was then compared to the theoretical calculations in Table 1 to determine the accuracy of the Dp*measurements. The results from this analysis are shown in Table 2. In the second method for data analysis, an experimental value for Dp*was independently determined from each sample distribution. This method involved using the activation percentage (CCN/CN) to determine the fraction of particles in each distribution with a diameter larger than Dp*. That is, when analyzing the distributions measured by DMA2, the cumulative fraction of particles with diameter less than D;l*, Fp, is given by Fg = 1 - (CCN/CN).
(4)
This method was performed on CCN activation percentages between 20 and 80%, in order to avoid the error inherent in extreme values for activation. Figure 4 illustrates an example calculation of 0: using this method for a NaCl distribution at s = 0.30%. The results from both analyses for the NaCl and (NH&SO4 data are tabulated in Table 2. This calibration exercise indicates that a bias of approximately + 16% exists when measuring 0: at s = 0.30%. The bias is consistent for both salts and for both analysis methods. However, the calibration measurement at
6000
m d1oidDp) ( cme3)
80
F,p
N&l at s = 0.30% 1
/
(%I
Diameter (mn) Fig. 4. A sample calculation of Df using a measured distribution for NaCl at s = 0.30% where an activation percentage of CCN/CN = 62% was observed. The bottom graph is the calculated cumulative number distribution, where Fnp is the fraction of particles with diameters less than a grven diameter D,. The corresponding value from 0: is calculated from the relationship F,; = 1 - (CCN/CN).
s = 1.0% for (NH&SO4 indicates a greater accuracy in predicting Dg,at higher supersaturations. To understand the possible sources for error in the experimental technique, it is important to analyze the uncertainty in the individual measurements involved. ?? To estimate the sizing accuracy for the experiments, DMA2 was calibrated with certified PSL spheres (Duke Scientific NanospheresTM). The results indicated an average bias in DMA2 of + 5% for particle diameters of 0.083, 0.096 and 0.105 pm. This translates to an error in activation percentages of about - 2.5% and a negligible error in 0: (< 1%).
Pure secondary organic aerosol as CCN ?? Corrections for aerosol charging efficiencies were made based on the charge distribution approximations of Wiedensohler (1988), assuming that all particles in the nearly monodisperse distribution had a + 1 unit charge. Multiple charging was negligible for most of the experiments performed with particles smaller than 0.080 pm. However, the presence of doubly and triply charge particles becomes more important with increasing particle size. For example, in a nearly monodisperse distribution with a maximum diameter appearing at 0.150 pm, up to 19.6% of the particles can be doubly charged particles of a larger diameter. Assuming that all particles have a + 1 charge, overestimates the total number concentration of particles (CN), because it does not take into account the fraction of particles with multiple charges. The effect of this error is to overpredict Dt (CCN/CN ratios are lower), which is in agreement with the bias resulting from the measurements. However, this error becomes important only for Dp* > 0.080 pm, which would correspond to the diacids at s = 0.30%, thus not explaining the consistency of the bias. ?? Variability in the temperature difference (AT) between the two surfaces in the cloud chamber might explain some of the bias in the measurements. The temperature difference was adjusted manually, with a AT reading accuracy of + O.l”C. However, the corresponding variability in chamber supersaturation due to this temperature variance is not linear, and the error at lower supersaturations is magnified. Using Kohler theory for s = 0.30%, an accuracy of + O.l”C corresponds to an uncertainty in 0: of approximately + 0.004 pm, but for s = l.O%, this variance predicts an uncertainty of less than f 0.001 pm. This can be clearly observed in our results (Table 1). If the experi-
2211
mental value obtained for Dp* for both salts is used to calculate an experimental supersaturation inside the chamber, the result for the s = 0.30% experiments would yield a value of s, = 0.22%, while the s = 1.0% experiments yield a negligible error. ?? The error introduced by the infinite dilution assumption has been previously studied by Young and Warren (1991) for inorganic salts, Their results show that for an (NH&SO_, nuclei with mass greater than lo-‘g (D, > 0.022 pm) and within the size range used in this study, assuming that the salt dissociates completely and that the surface tension and density are kept constant, results in an error of + 6.6% when calculating n, (equation (3)). This is analogous to an error of + 4.4% in our theoretical calculations of Dp* which would increase the deviation to close to + 20%. Therefore. this analysis does not explain the deviation observed, but quantifies some of the error inherent in the simplified Kiihler equation. Overall, the results indicate that the technique allows the measurement of activation diameters for NaCl and (NH&SO4 within an error of + 15% at a specified supersaturation. In comparison with previous studies, this represents a substantial improvement in this type of measurement for pure inorganics and an increase in confidence on this type of CCNC (Lammel and Novakov, 1995; Fitzgerald, 1973; Katz and Kockmond, 1973). Dicarboxylic
acids
The CCN activation curves resulting from the glutaric acid and adipic acid experiments are presented in Figs 5 and 6. These curves indicate that pure adipic acid and glutaric acid aerosols do act as CCN
40 20
A00
od20
’ od40 ’ od60 ’ oh0
’ o.ioo
’ 0.120
’ o.i40
’ 0.160
Dry Particle Diameter (pm) Fig. 5. Experimental CCN activation curves for glutaric acid (C5H804) at s = 0.30 and 1.0%.
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C. N. CRUZ and S. N. PANDIS
Dry Particle Diameter (pm) Fig. 6. Experimental CCN activation curves for adipic acid (CsH,004) at s = 0.30 and 1.0%.
and their behavior is analogous to that of inorganic salts, as observed in the shape of the activation curves. It is important to assess the applicability of Kiihler theory to these results, in order to relate the behavior of organic compounds to more studied species. Both methods described previously for analysis of the CCN measurements were applied to the dicarboxylic acid data. The discrepancy between predicted and measured 0: for these species is also shown in Table 1. According to these results, the measurements for adipic acid are in agreement with Kohler theory at both supersaturations, after considering the experimental error observed in the inorganic salt measurements. However, glutaric acid shows a larger deviation from theory for measurements at s = 1.0% ( + 30%). The reason for this added deviation is not random experimental error, because the CCN activation curve shows a very smooth behavior with increasing diameter (Fig. 5). However, we can examine certain assumptions in the theory to explore possible sources of this additional error. ?? Even though glutaric acid and adipic acid have similar chemical structure, their thermodynamic properties are different. The vapor pressure of glutaric acid at 295.15 K(6.82 x 10e4 f 15% Pa) is approximately 75 times greater than that of adipic acid (Tao and McMurry, 1989). The possibility of partial evaporation of the glutaric acid nuclei was investigated using the experimental flow rates and conditions. The maximum change in diameter due to evaporation between DMAl and the CCNC was - 0.002 pm for a 0.046 pm particle and - 0.005 pm for a 0.025 /*m particle. This could result in an added + 3 to + 4%
error in the 0: measurements, but is still comparable to the DMA sizing errors. In addition, no diameter changes were detected indicating evaporation between DMAl and DMA2, once taking into account sizing discrepancies determined from the TDMA intercalibration. ?? The solution behavior of glutaric acid and adipic acid, when compared to the salts, may play an important role in determining additional sources of error. Organic species, for which thermodynamic data may not be available (e.g. activity coefficients of diacids in solution), could present certain non-idealities not included in this analysis. For example, the ideal solution assumption that CD”= 1, may not be valid for diacid-water solutions at high concentrations, such as those found at activation. Thus, the effects of solution properties on the CCN activation theory for pure organic species must be quantified further with the appropriate thermodynamic data as was done by Young and Warren (1991) for the inorganic salts. ?? The effect of the dicarboxylic acids on the surface tension of the solution is another aspect to consider when looking at the applicability of Kohler theory to these data. According to the results in Shulman et al. (1996), at diacid concentrations of less than 0.3 M, which is the highest aqueous-phase concentration in the activated CCN in this study, the reduction of water surface tension is less than 10%. Lowering the surface tension by this percentage decreases the critical supersaturation, and increases the theoretical value for 0: by 7.3%. Therefore, an error in the specified surface tension cannot fully explain the discrepancy between theory and our data, but it would tend to decrease the deviation observed.
Pure secondary Dyoctylphthalate
organic
(DOP)
Even though DOP is not a compound commonly found in the atmosphere, it has been traditionally used in aerosol experiments as a model aerosol. Its non-hygroscopic properties make it a good representative of water-insoluble organics than could serve as CCN. No CCN activity was observed for DOP at supersaturations as high as s = 1.2% and for dry particle diameters as large as 0.150 ,um. These results are encouraging, in that the classification of organics according to their hygroscopicity and water solubility, might lead to a better sense of which organics affect the CCN activity of atmospheric aerosols. Our data show that some hydrophilic organic compounds can become CCN active at typical atmospheric supersaturations, as observed in the results for the dicarboxylic acids. Further consideration of solubility effects, surface tension effects, and solution properties would lead to a more quantitative understanding of the applicability of Kohler theory to pure organic CCN. However, the fact that common SOA species such as adipic acid and glutaric acid act as CCN, establishes the necessity for further consideration of organic aerosol as CCN during cloud formation studies. Implications
for theoretical
studies of cloud formation
Traditionally, organic aerosol components are either neglected, or treated as inert mass in theoretical studies of cloud and fog microphysics (Flossmann et al., 1985; Pandis et al., 1990). Our results suggest that at least a fraction of these organics could assist in the activation of aerosol particles into cloud droplets, if the organic and inorganic fractions had an additive behavior following Kohler theory. This would effectively decrease the activation diameter of the aerosol population and increase the fraction of particles that get activated. Overall, our results indicate that the question of how the inorganic and organic fractions interact during CCN activation becomes more important once the activity of organics has been established. In general, the organic compounds studied are less CCN active by mass and volume than the inorganic salts, due to their high molecular weight, low density, and low equivalence, which are all important parameters in Kohler theory. However, this study suggests that a range of CCN activities may be present in the numerous hydrophilic organic compounds present in the atmosphere, some of which may be comparable to that of inorganic salts.
CONCLUSIONS
Until now, only circumstantial evidence that some pure organic aerosols serve as CCN existed. In this study, we have presented an experimental technique for determining the CCN activity of pure organic
aerosol
as CCN
2213
aerosols. Error estimates based on NaCl and (NH&SO4 activation indicated that uncertainty in the experimental activation diameter measurements were within f 16%, when compared to Kohler theory. Using this technique we have determined that adipic acid and glutaric acid, two hydrophilic organic compounds, act as CCN in supersaturations similar to those in the atmosphere (s = 0.30 and 1.0%). The two compounds presented cloud-nucleating properties comparable to that of the two inorganic salts within experimental uncertainty. The same measurements were performed with DOP, but CCN activation was shown to be negligible within the limits of the instrumentation. This demonstrated that hydrophobic organics with similar characteristics as DOP may not serve as good CCN at atmospheric conditions. The applicability of Kohler theory to organic species has been shown to be successful within experimental error. Experiments indicated a better correlation with theory for adipic acid, than for glutaric acid, which might indicate the necessity for more compound-specific assumptions in the theory. However, this behavior is analogous to the deviations of certain complex salts such as (NH&SO4 when compared to simpler ones, e.g. NaCl, when applying CCN activation theory. Deviations are expected to arise due to lack of thermodynamic data that predicts the ideality limits for the organic compounds in solution and their application to Kohler theory. Acknowledgements-We thank W. Richard Leaitch and Peter Liu from Atmospheric Environment Service, Canada, for supplying the cloud condensation nuclei counter and for their continuous input. This work is funded by the National Science Foundation grant ATM 9508051 and by the U.S. Environmental Protection Agency (R-823514-01-0). Acknowledgement is made to the donors of The Petroleum Research Fund, administered by the ACS for partial support of this research.
REFERENCES Chow, J. C., Watson, J. G., Fujita, E. M., Lu, Z. Q., Lawson, D. R. and Ashbaugh, L. L. (1994) Temporal and spatial variations of PM25 and PM10 aerosol in Southern California Air Quality. Atmospheric Enoironment 28, 2061-2080. Fitzgerald, J. W. (1973) Dependence of the supersaturation spectrum of CCN on aerosol size distribution and composition. J. atmos. Sci. 30, 628-634. Flossmann, A. I., Hall, W. D. and Pruppacher, H. R. (1985) A theoretical study of the wet removal of atmospheric pollutants-I. The redistribution of aerosol particles captured through nucleation and impaction scavenging by cloud drops. J. atmos. Sci. 42, 583-606. Gray, H. A., Cass, G. R., Huntzicker, J. J., Heyerdahl. E. K. and Rau, J. A. (1986) Characteristics of atmospheric organic and elemental carbon particle concentrations in Los Angeles. Enuir. Sci. Technol. 20, 580-589. Grosjean, D. and Friedlander, S. K. (1979) Formation of organic aerosols from cyclic olefins and diolefins. In The Character and Origins of Smog Aerosols, ed. G. M. Hidy, P. K. Mueller, D. Grosjean, B. R. Appel and J. J. Wesolowski. Wiley, New York.
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Hatakeyama, S., Tanonaka, T., Weng, J., Bandow, H., Takagi, H. and Akimoto, H. (1985) Ozone-cyclohexene reaction in air: quantitative analysis of particulate products and the reaction mechanism. Envir. Sci. Technol. 19, 935-941. Hudson, J. G. and Da, X. (1995) Volatility and size of cloud condensation nuclei. 1. geophys. Res. 101,4435-4442. Jones, A., Roberts, D. L. and Slingo, A. (1994) A climate model study of indirect radiative forcing by anthropogenic sulphate aerosol. Nature 370, 450-453. Katz, U. and Kockmond, W. C. (1973) An investigation of the size-supersaturation relationship of soluble condensation nuclei. J. atmos. Sci. 30, 160-165. Kaufman, Y. J. and Tanre, D. (1994) Effect of variations in supersaturation on the formation of cloud condensation nuclei. Nature 369, 45-48. Kelly, W.P. and McMurry, P. H. (1992) Measurements of particle density by inertial classification of differential mobility analyzer-generated monodisperse aerosols. Aerosol Sci. Technol. 17, 199-212. Knutson, E. 0. and Whitby, K. T. (1975) Aerosol classification by electrical mobility: apparatus, theory, and applications. J. Aerosol Sci. 6, 4434.51. KGhler, H. (1936) The nucleus in the growth of hygroscopic droplets. Trans. Faraday Sot. 32, 1152-l 161. Lammel, G. and Novakov, T. (1995) Water nucleation properties of carbon black and diesel soot particles. Atmospheric Environment 29, 813-823. Larson, S. M., Cass, G. R. and Gray, H. A. (1989) Characteristics of summer midday low-visibility events and the Los Angeles basin. Envir. Sci. Technol. 10. 118-130. Lewis: C. W. and Dzumbay, T. G. (1986) Measurement of light absorption and extinction in Denver. Aerosol Sci. Technol. 5, 325-336.
Lewis, C. W., Baumgardner, R. E., Stevens, R. K. and Russwurm, G. M. (1986) Receptor modeling study of Denver winter haze. Envir. Sci. Technol. 20, 1126-I lj6. Liu. B. Y. H. and Pui. D. Y. H. 11974)A submicron aerosol siandard and the primary, absolite calibration of the condensation nuclei counter. J. Colloid Interface Sci. 47, 155-171. McMurry, P. H. and Zhang, X. Q. (1989) Size distributions of ambient organic and elemental carbon. Aerosol Sci. Technol. 10,430-437.
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Pandis, S. N., Seinfeld, J. H. and Pillinis, P. (1990) Chemical composition differences in fog and cloud droplets of different sizes. Atmospheric Environment 24, 1957-1969. Pickle, T., Allen, D. T. and Pratsinis, S. E. (1990) The source and size distribution of aliphatic and carbonyl carbon in Los Angeles aerosol. Atmospheric Environment 24A, 2221-2228.
Pruppacher, H. R. and Klett, J. D. (1980) Microphysics of Clouds and Precipitation. Reidel, Dordrecht. Rader, D. J. and McMurry, P. H. (1986) Application of the tandem differential mobility analyzer to studies of droplet growth or evaporation. J. Aerosol Sci. 17, 771-787. Rogge, W. F., Mazurek, M. A., Hildemann, L. M., Cass, G. R. and Somoneit, B. R. T. (1993) Quantification of urban organic aerosols at a molecular level. Identification, abundance, and seasonal variation. Atmospheric Environment 27, 1309-1330.
Rogers, C. F., Hudson, J. G., Hallet, J., and Penner, J. E. (1991) Cloud droplet nucleation by crude oil smoke and coagulated crude oilwood smoke particles. Atmospheric Environment 25A, 2571-2580.
Saxena, P. and Hildemann, L. (1996) Water-soluble organics in atmospheric particles: a critical review of the literature and application of thermodynamics to identify candidate compounds. J. atmos. Chem. 24, 57-109. Saxena, P., Hildemann, L. M., McMurry, P. H. and Seinfeld, J. H. (1995) Organics alter the hygroscopic behavior of atmospheric particles. J. geophys. Res. 100,18,755-18,770. Sempere, R. and 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., Jacobson, M. C., Carlson, R. J., Synovec, R. E. and Young, T. E. (1996) Dissolution behavior and surface tension effects of organic compounds in nucleating cloud droplets. Geophys. Res. Lett. 23, 277-280. Sloane, C. S., Watson, J., Chow, J., Pritchett, L. and Richards, L. W. (1991) Size-segregated fine particle measurements by chemical species and their impact on visibility impairment in Denver. Atmospheric Environment 25A, 1013-1024.
Tao, Y. and McMurry, P. H. (1989) Vapor pressures and surface free energies of C14-Cl8 monocarboxylic acids and CS and C6 dicarboxylic acids. Envir. Sci. Technol. 23, 1519-1523.
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Twomey, S. A. (1974) Pollution and the planetary albedo. Atmospheric Environment 8, 1251-1256.
Twomey, S. A. (1991) Aerosols, clouds, and radiation. Atmospheric Environment 25A, 2435-2442.
Weast. R. C. (Ed.) (1986) CRC Handbook of Chemistrv and Physics. CdC I&s, Coca Raton, FL. ’ Wiedensohler, A. (1988) An approximation of the bipolar charge distribution for particles in the submicron size range. J. Aerosol Sci. 19, 387-389. Wigley, T. M. L. (1989) Possible climate change due to SO,-derived cloud condensation nuclei. Nature 339, 365-367.
Wigley, T. M. L. (1991) Could reducing fossil-fuel emissions cause global warming? Nature 349, 505-506. Wolff, G. T., Ruthosky, M. S., Stroup, D. P. and Korsog, P. E. (1991) A characterization of the principal PM-10 Species in Claremont (summer) and Long Beach (Fall) during SCAQS. Atmospheric Environment 25A, 2173-2186.
Young, K. C. and Warren, A. J. (1992) A reexamination of the derivation of the equilibrium supersaturation curve for soluble particles. J. atmos. Sci. 49, 1138-l 143.
Armosphrrrc
Enkwwnenr
PII: S1352-2310(97)00054-X
Vol. 31, No 15, pp. 2201-2214. 1997 .c\ 1997 Elsewer Saence Ltd All nghts reserved. Printed in Great Britain 13%2310!97 1617.M) + 000
A STUDY OF THE ABILITY OF PURE SECONDARY AEROSOL TO ACT AS CLOUD CONDENSATION CELIA N. CRUZ and SPYROS
ORGANIC NUCLEI
N. PANDIS
Department of Chemical Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, U.S.A. (First received 28 October 1996 and in_finalform 6 January 1997. Published May 1997)
Abstract-Submicron atmospheric particles that serve as cloud condensation nuclei (CCN) at low supersaturations are important for quantifying the effect of aerosols on cloud properties and global climate. In this study, we investigate experimentally the ability of model submicron aerosols consisting of pure organic species to become CCN at typical atmospheric supersaturations. The CCN activity of glutaric acid, adipic acid, and dyoctylphthalate (DOP) aerosols was determined by producing a nearly monodisperse distribution of submicron particles and comparing total CCN concentrations to total number concentrations. The measurements were performed using a Tandem Differential Mobility Analyzer in combination with a cloud condensation nuclei counter at supersaturations of 0.30 and 1.0%. The uncertainty in the measurements was determined by using NaCl and (NH&SO, aerosols; the results indicated that activation diameters could be measured within an error of f 16%. Adipic acid and glutaric acid aerosols served as CCN at both supersaturations and their behavior is in fair agreement with Kiihler theory. On the other hand, DOP aerosol as large as 0.15 pm in diameter, did not become activated, even at supersaturations as high as 1.2%. These results indicate that the CCN activity of hygroscopic organic aerosols may be comparable to that of some inorganic aerosols. 0 1997 Elsevier Science Ltd. Key word index: Cloud condensation nuclei, secondary organic aerosol (SOA), dicarboxylic acids, organic aerosol.
INTRODUCTION Submicron atmospheric particles can serve as nuclei on which water condenses to form cloud droplets at supersaturations lower than those required for homogeneous water nucleation. Understanding the cloud condensation nuclei (CCN) activity of atmospheric
aerosols is important in order to quantify their effect on the formation, lifetime, and radiative properties of clouds. The size distribution and chemical composition of the pre-cloud aerosols have been shown to be key factors in predicting the number density and size distributions of cloud droplets (Twomey, 1974). This aerosol-cloud interaction has been shown to be an indirect mechanism by which aerosols may affect the radiation balance of the Earth and global climate 1991). For instance, sulfates (e.g. (Twomey, (NH&S04, NH4HS04) are known to be a main component of CCN at low cloud supersaturations (< 0.3%) (Twomey, 1971; Kaufman and Tanre, 1994). It has been suggested that the high reflectivity of cloud droplets containing sulfate increases the Earth’s albedo resulting in a potential countereffect to global warming by greenhouse gases (Wigley, 1989, 1991; Jones et al., 1994). The process by which the inorganic fraction of atmospheric particles activates into CCN is well
understood (Kijhler, 1936; Pruppacher and Klett, 1980). For these particles, one can predict CCN activation based on chemical composition, solubility, surface tension, and dry particle size (Pruppacher and Klett, 1980). However, atmospheric aerosols have mixed chemical composition, with a variety of inorganic (e.g. sulfate, nitrate, ammonium, and sodium) and organic species often present in a single particle. Total organic carbon can represent lo-65% of the aerosol mass less than 2.5 pm (Wolff et al., 1991; Sloane et al., 1991; Chow et al., 1994; Lewis et al., 1986; Lewis and Dzumbay, 1986). while secondary organic carbon can contribute up to 25-50% of the fine aerosol mass in urban polluted areas (Gray et al., 1986; Larson et ul., 1989). Despite the considerable fraction of organic matter in atmospheric aerosol, relatively little is known about the ability of organic particles to act as CCN and about their contribution to ambient CCN concentrations. Studies on the size distribution and chemistry of CCN tend to ignore organic aerosols, because of lack of knowledge on the cloudnucleating properties of organic species (Hudson and Da, 1995). Therefore, it is key to determine the contribution of organic species to CCN activation and to cloud properties dependent on CCN size and chemistry.
2205
2206
C. N. CRUZ and S. N. PANDIS
Recent studies on atmospheric aerosols by Novakov and Penner (1993) presented evidence that 37% of the CCN number concentrations measured at a remote site at 0.5% supersaturation were accounted for by sulfate and the remainder by organic material. However, due to lack of information about the mixing state of the atmospheric particles at the site, it was not clear whether the inorganic fraction of the mostly organic aerosol rendered these particles CCN active, or whether some organic compounds were intrinsically CCN active. This issue has not been resolved by previous investigations on the CCN activity of primary organic aerosol from wood burning and other combustion sources (Rogers et al., 1991; Lammel and Novakov, 1995). In these studies, the CCN activity of the organic aerosol was directly compared to the water-soluble fraction of the particles, which was assumed to be mostly inorganic and electrolytic. However, the water nucleation properties calculated under this assumption proved to be insufficient in predicting the CCN activity of the particles, thus indicating possible organic contribution to CCN. Saxena et al. (1995) showed that organic compounds alter the hygroscopicity of atmospheric particles. Their results indicated that in a nonurban location, the organic fraction of the atmospheric particles increased the water absorption by particles. Organics accounted for 25-40% of the aerosol liquid water content at relative humidities ranging from 80 to 88%. A possible explanation for this behavior was the presence of hydrophilic organics such as carboxylic and dicarboxylic acids, alcohols, and aldehydes, which are abundant in nonurban aerosols. The combination of these studies lead to the hypothesis that high wateraffinity organic compounds in atmospheric aerosols can present hygroscopic behavior comparable to inorganic species, and organic particles may therefore act as CCN. This study investigates the ability of some pure organic aerosols to act as CCN at conditions similar to those in the atmosphere. Organic compounds accumulate mainly in the submicrometer aerosol size regime (Finnlayson-Pitt, 1986; McMurry and Zhang, 1989), and their mass distribution is typically bimodal with the first peak at approximately 0.2 pm and the second around 1 pm (Pickle et al., 1990; Mylonas et nl., 1991). Dicarboxylic acids represent a major component of the water-soluble primary and secondary organic carbon mass in the atmosphere, therefore these species were chosen as representative organics for this investigation. In order to assess the CCN activity of these hydrophilic organic compounds, we study two dicarboxylic acids: adipic acid (CsHi004) and glutaric acid (C5H804). Specifically, adipic and glutaric acids are abundant secondary organic aerosol (SOA) species (Sempere and Kawamura, 1994; Saxena and Hildemann, 1996) formed from the oxidation reaction of olefins with ozone (Grosjean and Friedlander, 1979; Hatakeyama et al., 1985; O’Brien et al.,
1975). Additional organic acids measured in atmospheric aerosol include n-alkanoic acids (C66C34), n-alkenoic acids (C6-C8), benzoic acids, and other dicarboxylic acids (C3-C9) (Rogge et al., 1993). Thus, to a first approximation, the species selected for this study can be viewed as representative of a much larger group of compounds found in atmospheric aerosol. We compare these results to the CCN activity of dyoctylphthalate (DOP), which is an example of a hydrophobic organic compound with negligible solubility in water. Finally, we quantify the uncertainty in the CCN activity measurements for these pure organic aerosols by comparing them to CCN measurements for sodium chloride (NaCl) and ammonium sulfate ((NH&SO& two inorganic sahs modeled by Kiihler theory.
THEORY AND APPROACH
Kohler (1936) theory predicts the CCN activation of inorganic electrolytic salts such as NaCl and (NH&SO, based on the thermodynamic balance of two competing effects: the decrease in water vapor pressure due to the solvent (Raoult effect) and the increase in water vapor pressure due to the curvature of the droplet surface (Kelvin effect). In his derivation, Kohler assumed that the CCN consisted of a completely soluble substance that had negligible vapor pressure and that the mass of this solute remained constant during droplet growth. The Kohler equation describes the relationship between equilibrium saturation (S,,) of a water droplet and its radius (a) as 2ff”M, S,, = exp __ RTp,a
Wvm,M,/M, (4np”a3/3) - m,
1 (14
where 0” is the surface tension of the solution in air, M, and M, are the molecular weights of water and solute, respectively, m, is the solute mass, pw and p” are the densities of water and the solution, respectively, v is the average number of ions into which a solute molecule dissociates (e.g. vNaCl= 2 and V~Nu&so4= 3); and @”is the osmotic coefficient of the aqueous solution. This equation can be simplified by performing a Taylor series expansion on the exponential (S,, z 1) and applying the following assumptions: (i) the solution is dilute (m, < m,, where m, is the mass of water) and ideality applies (@”= 1); and (ii) the solution surface tension and bulk density are that of pure water (0” z 6, and p” z pw). The equilibrium supersaturation for a droplet is defined as, seq = &, - 1, or, WJ4,
scq = ~ RTp,u
-
3vm, M, 4zM,p,a3’
(lb)
For a given solute mass, the simplified Kohler equation (lb) describes an equilibrium curve with a
Pure secondary organic aerosol as CCN maximum at a critical supersaturation cal radius (a,):
(s,) and a criti-
(2) a, =
3B
J 2
where
&vMw
A=-.-----
RTP,
and
l3=$$$’
2207
Table 1. The theoretical values for Dp*were also calculated for glutaric and adipic acids species using the same assumptions outlined previously (Table 1). Given that the first-step dissociation constants (K,) for the diacids are less than 4.6 x lo--’ M, and the second-step dissociation constants are less than 3.9 x 10M5 M (CRC Handbook, 1986) a value of v = 1 was used in these calculations. The theoretical values calculated for D,*were used to determine the applicability of Kohler theory to these organic species.
s w EXPERIMENTAL
These critical values define a transition point from a stable to an unstable region in the supersaturation, s,~, vs droplet radius, a, equilibrium curve. For envir-
onmental supersaturations below s, and droplet radii less than a,, the solution droplet can achieve a diameter satisfying equation (lb), and it can attain stable equilibrium with the environment. When the environment achieves a supersaturation greater than s,, then the solution droplet is said to activate into a cloud droplet, because it will continue to grow limited only by diffusion of water vapor from the gas phase. A droplet is also activated when the environment supersaturation is greater than the equilibrium supersaturation predicted by Kiihler theory and the droplet radius is greater than a,. For the purposes of this study, a particle activates only when exposed to an environment supersaturation greater than or equal to its so and then grows into a cloud droplet. Thus, by selecting an experimental s, (e.g. 0.3%), it is possible to calculate from equation (2) the minimum theoretical solute mass necessary to activate the nucleus into a droplet. This mass can be converted into the corresponding dry particle diameter (0:) which, in theory, should activate into a cloud droplet at the chosen critical supersaturation. In this manner, CCN activity for any solute that satisfies Kohler theory, can be predicted for any given conditions. The theoretical values for the activation diameter (Dt), which is the dry particle diameter necessary for activation at the specified s,, are calculated in
The experimental apparatus is a combination of a Tandem Differential Mobility Analyzer (TDMA; Rader and McMurry, 1986) and a cloud condensation nuclei counter (CCNC) (Fig. 1). The primary components of the system are a monodisperse aerosol generation system, an aerosol classifier system, a single condensation particle counter (CPC), and the CCNC. This setup allows the control of particle size, particle chemical composition, and supersaturation for CCN measurements, while allowing independent measurements of particle size, total number concentration, and CCN concentration Monodisperse aerosol generation system
A collision atomizer (Constant Output Atomizer 3076, TSI) is used to produce an aerosol of the species to be investigated (e.g. C,H,,O,) from a 0.10 wt% doubledeionized water solution, or in the case of DOP, from a 0.10 ~01% methanol solution. Double deionized filtered water from a Milhpore system and EM Omnisolv grade methanol ( < 0.1 ppm residue after evaporation) are used as solvents to minimize impurities. The solvent is evaporated from the aerosol by passing it through a silica gel diffusion dryer. The polydisperse dry particles are then charged in a Kr-86 bipolar aerosol neutralizer (Aerosol Neutralizer 3077, TSI) and the aerosol reaches a nearly Boltzmann equilibrium distribution of charges. The aerosol then flows from the neutralizer into the first Differential Mobility Analyzer (DMAl), where particles of a chosen electrical mobility and diameter are selected (Liu and Pui, 1974; Knutson and Whitby, 1975). By changing the rod voltage in DMAl (Electrostatic Classifier 3071A, TSI), nearly monodisperse distributions of particles with different mean diameters are generated to enter both the DMA2-CPC system and the CCNC.
Table 1. Properties and theoretical activation diameters for investigated compounds
MW (g mot-‘) Sodium chloride Ammonium sulfate Glutaric acid Adipic acid
P (g cm-?
Solubihty (g per 100 cm3) Hz0
1’
0;: (pm) SC = 0.3%
D,* (pm) SC = 1.0%
58.44
2.165
36.0
2
0.052
0.023
132.14 132.11 146.14
1.769 1.424 1.360
75.4 116” 2.5”
3 1 1
0.063 0.098 0.103
0.028 0.044 0.046
Note: p, density, Y,average number of ions after dissociation, Dp*,activation diameter. All properties are taken from the CRC Handbook unless otherwise noted. All calculations assume T = 295.15 K, uw = 73 dyn cm-’ (0.073 J m-‘). ’Saxena and Hildemann (1996).
2208
C. N. CRUZ and S. N. PANDIS
Airzdion Neutralizer
]
DMAl t Compressed Air
Dilution
Air
DMA2 Syringe Exhaust
Pump
4 1 Air Ewi
1
CCNC
Compressed Air
Fig. 1. Schematic of experimental apparatus for cloud condensation nuclei measurements.
Aerosol classijer and total number concentration counter
The second DMA and the CPC (Condensation Particle Counter 3010, TSI) are part of the Scanning Mobility Particle Sizer system (SMPS 3934, TSI) used to classify particles by scanning voltages and measuring concentrations simultaneously. The CPC samples the total number concentration (CN) using a supersaturated environment of n-butanol where all particles are detected by a counting laser. The SMPS system can generate a full distribution in a few minutes, checking the consistency of the monodisperse generation system. During each experiment, a measurement of the full nearly monodisperse distribution and the total number concentration was acquired every 6-8 min. An intercalibration of both DMAs using NaCl aerosol indicated that the particles generated by DMAl and the particles measured by DMA2 agree in diameter within + 0.002 pm for D, < 0.090 pm and within + 0.006 pm for D, > 0.120 pm. Particle-sizing agreement between DMAl and DMA2 showed no dependence on chemical composition of the aerosol. Cloud condensation nuclei counter
The cloud condensation nuclei counter (CCNC) is a thermal diffusion chamber-type counter (Ml model, DH Associates) which operates by sampling a 6 mm3 volume approximately every 30 s. The upper and lower surfaces of the chamber are kept wet and at different temperatures, cooling the bottom one thermoelectrically. This way, a thermal and vapor density gradient is created within the chamber, with a maximum supersaturation near the center of the chamber. Particles with the correct size and chemistry for CCN activation grow into droplets and are counted by a laser. During
all experiments, the CCN concentration was kept lower than 1000 cme3. The supersaturation experienced by the particles can be adjusted by changing the temperature difference across the chamber. Experimental procedure
With this experimental setup (Fig. 1), the CCN activation curves can be reproduced in two ways: keeping the diameter of the sample aerosol constant and changing the supersaturation inside the CCNC (Kohler curves), or keeping the supersaturation constant and changing the size of the particles, i.e. mass of the species, entering the chamber. The latter procedure was used throughout these experiments, with a constant supersaturation of either 0.30 or 1.0%. For each diameter size, a measurement of the total number concentration of CCN was completed in an hour and was then compared to the average total number concentration (CN) measured by the SMPS during the sampling time. By calculating the ratio of CCN-activated particles to the total number of particles in the nearly monodisperse distribution, CCN/CN, it was possible to calculate the fraction of particles activated with increasing dry particle diameter. This procedure was repeated for different chemical species, yielding CCN activation curves for sodium chloride, ammonium sulfate, adipic acid and glutaric acid.
RESULTS AND DISCUSSION The first portion of this study was devoted to testing the accuracy of the experimental technique by
Pure secondary
d%oo-
J =,~ O.d20
organic
., ‘ O.d40
aerosol
as CCN
2209
L I
0.060
I 0.080
I
0.100
\ 0.120
Dry Particle Diameter (pm) Fig. 2. Experimental CCN activation curve for NaCl at s = 0.30 and 1.0%.
Dry Particle Diameter (pm) Fig. 3 Experimental CCN activation curves for (NH&SO4 at s = 0.30 and 1.0%
investigating the CCN activation of NaCl and (NH&S04. The results from this exercise were then used to assess the validity of the CCN measurements for adipic acid, glutaric acid, and DOP. NaCl and (NH&SO4 The experimental activation curves for NaCl and (NH&SO4 at the two supersaturations (s = 0.30 and 1.0%) are presented in Figs 2 and 3. The percentage activation is given as the ratio of CCN to the total
number concentration (CN) measured by the CPC. The dry particle diameters reported are the peaks of the nearly monodisperse distributions generated by DMAl, as measured by DMA2, and are thus, mobility-equivalent diameters. For spherical particles, these two diameters are equal, because density does not affect the diameters selected by the DMA. However, a shape factor of 1.08 was used to analyze data for NaCl (Kelly and McMurry, 1992). For each point on the curve, an average value for the peak dry diameter
C. N. CRUZ and S. N. PANDIS
2210
Table 2. Results for s = 0.3% and s = 1.0% Supersaturation
= 0.3%
Supersaturation
= 1.0%
Species
Da50 (pm)
Error’ (%)
Equationb (4) (pm)
Error’ (%)
NaCl (NH&S04 C&L@4 (glutaric) C,H,,O, (adipic)
0.060 0.074
+ 15.4 + 17.5
0.058 0.075
+ 11.5 + 19.0
0.014 0.029
- 15.5 + 3.6
0.019 0.029
- 15.5 + 3.6
0.111 0.115
+ 13.3 + 11.7
0.112 0.108
+ 14.3 + 4.9
0.060 0.052
+ 36.4 + 13.0
0.057 0.051
+ 29.5 + 10.9
Error (%)
Equation (4) (pm)
Error (%)
a Calculated from diameter at 50% activation (DsO) by curve fitting. bCalculated from equation (4) for all distributions with CCN activations between 20 and 80%. ‘The error for both methods was calculated as the difference between the experimental values and the theoretical value of 0: (Table 1) divided by the thoeretical Dp*.For example, (D,,, - Q/D,*.
and the total number CN concentration was used for the sampling time (x 80 min). This corresponds to the average of lo-14 sample distributions, whose peak diameters and total concentrations did not vary by more than 3 and lo%, respectively. The data from the CCN activation curves were analyzed using two methods. In the first method, an experimental value of D,* was derived by defining it as the diameter at 50% activation (D&. As seen in Figs 2 and 3, a sigmoidal function was fitted to the activation curves and a value for D5,_, was extracted for each supersaturation. The basis for this method is that at 50% activation, half the particles have a diameter greater than D50,which should correspond to Dz.The value for D5,,was then compared to the theoretical calculations in Table 1 to determine the accuracy of the Dp*measurements. The results from this analysis are shown in Table 2. In the second method for data analysis, an experimental value for Dp*was independently determined from each sample distribution. This method involved using the activation percentage (CCN/CN) to determine the fraction of particles in each distribution with a diameter larger than Dp*. That is, when analyzing the distributions measured by DMA2, the cumulative fraction of particles with diameter less than D;l*, Fp, is given by Fg = 1 - (CCN/CN).
(4)
This method was performed on CCN activation percentages between 20 and 80%, in order to avoid the error inherent in extreme values for activation. Figure 4 illustrates an example calculation of 0: using this method for a NaCl distribution at s = 0.30%. The results from both analyses for the NaCl and (NH&SO4 data are tabulated in Table 2. This calibration exercise indicates that a bias of approximately + 16% exists when measuring 0: at s = 0.30%. The bias is consistent for both salts and for both analysis methods. However, the calibration measurement at
6000
m d1oidDp) ( cme3)
80
F,p
N&l at s = 0.30% 1
/
(%I
Diameter (mn) Fig. 4. A sample calculation of Df using a measured distribution for NaCl at s = 0.30% where an activation percentage of CCN/CN = 62% was observed. The bottom graph is the calculated cumulative number distribution, where Fnp is the fraction of particles with diameters less than a grven diameter D,. The corresponding value from 0: is calculated from the relationship F,; = 1 - (CCN/CN).
s = 1.0% for (NH&SO4 indicates a greater accuracy in predicting Dg,at higher supersaturations. To understand the possible sources for error in the experimental technique, it is important to analyze the uncertainty in the individual measurements involved. ?? To estimate the sizing accuracy for the experiments, DMA2 was calibrated with certified PSL spheres (Duke Scientific NanospheresTM). The results indicated an average bias in DMA2 of + 5% for particle diameters of 0.083, 0.096 and 0.105 pm. This translates to an error in activation percentages of about - 2.5% and a negligible error in 0: (< 1%).
Pure secondary organic aerosol as CCN ?? Corrections for aerosol charging efficiencies were made based on the charge distribution approximations of Wiedensohler (1988), assuming that all particles in the nearly monodisperse distribution had a + 1 unit charge. Multiple charging was negligible for most of the experiments performed with particles smaller than 0.080 pm. However, the presence of doubly and triply charge particles becomes more important with increasing particle size. For example, in a nearly monodisperse distribution with a maximum diameter appearing at 0.150 pm, up to 19.6% of the particles can be doubly charged particles of a larger diameter. Assuming that all particles have a + 1 charge, overestimates the total number concentration of particles (CN), because it does not take into account the fraction of particles with multiple charges. The effect of this error is to overpredict Dt (CCN/CN ratios are lower), which is in agreement with the bias resulting from the measurements. However, this error becomes important only for Dp* > 0.080 pm, which would correspond to the diacids at s = 0.30%, thus not explaining the consistency of the bias. ?? Variability in the temperature difference (AT) between the two surfaces in the cloud chamber might explain some of the bias in the measurements. The temperature difference was adjusted manually, with a AT reading accuracy of + O.l”C. However, the corresponding variability in chamber supersaturation due to this temperature variance is not linear, and the error at lower supersaturations is magnified. Using Kohler theory for s = 0.30%, an accuracy of + O.l”C corresponds to an uncertainty in 0: of approximately + 0.004 pm, but for s = l.O%, this variance predicts an uncertainty of less than f 0.001 pm. This can be clearly observed in our results (Table 1). If the experi-
2211
mental value obtained for Dp* for both salts is used to calculate an experimental supersaturation inside the chamber, the result for the s = 0.30% experiments would yield a value of s, = 0.22%, while the s = 1.0% experiments yield a negligible error. ?? The error introduced by the infinite dilution assumption has been previously studied by Young and Warren (1991) for inorganic salts, Their results show that for an (NH&SO_, nuclei with mass greater than lo-‘g (D, > 0.022 pm) and within the size range used in this study, assuming that the salt dissociates completely and that the surface tension and density are kept constant, results in an error of + 6.6% when calculating n, (equation (3)). This is analogous to an error of + 4.4% in our theoretical calculations of Dp* which would increase the deviation to close to + 20%. Therefore. this analysis does not explain the deviation observed, but quantifies some of the error inherent in the simplified Kiihler equation. Overall, the results indicate that the technique allows the measurement of activation diameters for NaCl and (NH&SO4 within an error of + 15% at a specified supersaturation. In comparison with previous studies, this represents a substantial improvement in this type of measurement for pure inorganics and an increase in confidence on this type of CCNC (Lammel and Novakov, 1995; Fitzgerald, 1973; Katz and Kockmond, 1973). Dicarboxylic
acids
The CCN activation curves resulting from the glutaric acid and adipic acid experiments are presented in Figs 5 and 6. These curves indicate that pure adipic acid and glutaric acid aerosols do act as CCN
40 20
A00
od20
’ od40 ’ od60 ’ oh0
’ o.ioo
’ 0.120
’ o.i40
’ 0.160
Dry Particle Diameter (pm) Fig. 5. Experimental CCN activation curves for glutaric acid (C5H804) at s = 0.30 and 1.0%.
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C. N. CRUZ and S. N. PANDIS
Dry Particle Diameter (pm) Fig. 6. Experimental CCN activation curves for adipic acid (CsH,004) at s = 0.30 and 1.0%.
and their behavior is analogous to that of inorganic salts, as observed in the shape of the activation curves. It is important to assess the applicability of Kiihler theory to these results, in order to relate the behavior of organic compounds to more studied species. Both methods described previously for analysis of the CCN measurements were applied to the dicarboxylic acid data. The discrepancy between predicted and measured 0: for these species is also shown in Table 1. According to these results, the measurements for adipic acid are in agreement with Kohler theory at both supersaturations, after considering the experimental error observed in the inorganic salt measurements. However, glutaric acid shows a larger deviation from theory for measurements at s = 1.0% ( + 30%). The reason for this added deviation is not random experimental error, because the CCN activation curve shows a very smooth behavior with increasing diameter (Fig. 5). However, we can examine certain assumptions in the theory to explore possible sources of this additional error. ?? Even though glutaric acid and adipic acid have similar chemical structure, their thermodynamic properties are different. The vapor pressure of glutaric acid at 295.15 K(6.82 x 10e4 f 15% Pa) is approximately 75 times greater than that of adipic acid (Tao and McMurry, 1989). The possibility of partial evaporation of the glutaric acid nuclei was investigated using the experimental flow rates and conditions. The maximum change in diameter due to evaporation between DMAl and the CCNC was - 0.002 pm for a 0.046 pm particle and - 0.005 pm for a 0.025 /*m particle. This could result in an added + 3 to + 4%
error in the 0: measurements, but is still comparable to the DMA sizing errors. In addition, no diameter changes were detected indicating evaporation between DMAl and DMA2, once taking into account sizing discrepancies determined from the TDMA intercalibration. ?? The solution behavior of glutaric acid and adipic acid, when compared to the salts, may play an important role in determining additional sources of error. Organic species, for which thermodynamic data may not be available (e.g. activity coefficients of diacids in solution), could present certain non-idealities not included in this analysis. For example, the ideal solution assumption that CD”= 1, may not be valid for diacid-water solutions at high concentrations, such as those found at activation. Thus, the effects of solution properties on the CCN activation theory for pure organic species must be quantified further with the appropriate thermodynamic data as was done by Young and Warren (1991) for the inorganic salts. ?? The effect of the dicarboxylic acids on the surface tension of the solution is another aspect to consider when looking at the applicability of Kohler theory to these data. According to the results in Shulman et al. (1996), at diacid concentrations of less than 0.3 M, which is the highest aqueous-phase concentration in the activated CCN in this study, the reduction of water surface tension is less than 10%. Lowering the surface tension by this percentage decreases the critical supersaturation, and increases the theoretical value for 0: by 7.3%. Therefore, an error in the specified surface tension cannot fully explain the discrepancy between theory and our data, but it would tend to decrease the deviation observed.
Pure secondary Dyoctylphthalate
organic
(DOP)
Even though DOP is not a compound commonly found in the atmosphere, it has been traditionally used in aerosol experiments as a model aerosol. Its non-hygroscopic properties make it a good representative of water-insoluble organics than could serve as CCN. No CCN activity was observed for DOP at supersaturations as high as s = 1.2% and for dry particle diameters as large as 0.150 ,um. These results are encouraging, in that the classification of organics according to their hygroscopicity and water solubility, might lead to a better sense of which organics affect the CCN activity of atmospheric aerosols. Our data show that some hydrophilic organic compounds can become CCN active at typical atmospheric supersaturations, as observed in the results for the dicarboxylic acids. Further consideration of solubility effects, surface tension effects, and solution properties would lead to a more quantitative understanding of the applicability of Kohler theory to pure organic CCN. However, the fact that common SOA species such as adipic acid and glutaric acid act as CCN, establishes the necessity for further consideration of organic aerosol as CCN during cloud formation studies. Implications
for theoretical
studies of cloud formation
Traditionally, organic aerosol components are either neglected, or treated as inert mass in theoretical studies of cloud and fog microphysics (Flossmann et al., 1985; Pandis et al., 1990). Our results suggest that at least a fraction of these organics could assist in the activation of aerosol particles into cloud droplets, if the organic and inorganic fractions had an additive behavior following Kohler theory. This would effectively decrease the activation diameter of the aerosol population and increase the fraction of particles that get activated. Overall, our results indicate that the question of how the inorganic and organic fractions interact during CCN activation becomes more important once the activity of organics has been established. In general, the organic compounds studied are less CCN active by mass and volume than the inorganic salts, due to their high molecular weight, low density, and low equivalence, which are all important parameters in Kohler theory. However, this study suggests that a range of CCN activities may be present in the numerous hydrophilic organic compounds present in the atmosphere, some of which may be comparable to that of inorganic salts.
CONCLUSIONS
Until now, only circumstantial evidence that some pure organic aerosols serve as CCN existed. In this study, we have presented an experimental technique for determining the CCN activity of pure organic
aerosol
as CCN
2213
aerosols. Error estimates based on NaCl and (NH&SO4 activation indicated that uncertainty in the experimental activation diameter measurements were within f 16%, when compared to Kohler theory. Using this technique we have determined that adipic acid and glutaric acid, two hydrophilic organic compounds, act as CCN in supersaturations similar to those in the atmosphere (s = 0.30 and 1.0%). The two compounds presented cloud-nucleating properties comparable to that of the two inorganic salts within experimental uncertainty. The same measurements were performed with DOP, but CCN activation was shown to be negligible within the limits of the instrumentation. This demonstrated that hydrophobic organics with similar characteristics as DOP may not serve as good CCN at atmospheric conditions. The applicability of Kohler theory to organic species has been shown to be successful within experimental error. Experiments indicated a better correlation with theory for adipic acid, than for glutaric acid, which might indicate the necessity for more compound-specific assumptions in the theory. However, this behavior is analogous to the deviations of certain complex salts such as (NH&SO4 when compared to simpler ones, e.g. NaCl, when applying CCN activation theory. Deviations are expected to arise due to lack of thermodynamic data that predicts the ideality limits for the organic compounds in solution and their application to Kohler theory. Acknowledgements-We thank W. Richard Leaitch and Peter Liu from Atmospheric Environment Service, Canada, for supplying the cloud condensation nuclei counter and for their continuous input. This work is funded by the National Science Foundation grant ATM 9508051 and by the U.S. Environmental Protection Agency (R-823514-01-0). Acknowledgement is made to the donors of The Petroleum Research Fund, administered by the ACS for partial support of this research.
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