Toward aerosol/cloud condensation nuclei (CCN) closure during CRYSTAL‐FACE

VanReken, T. M.; Rissman, Tracey A.; Roberts, Grégory; Varutbangkul, Varuntida; Jonsson, Haflidi H.; Flagan, Richard C.; Seinfeld, John H.

doi:10.1029/2003jd003582

Cited by 108 publications

(118 citation statements)

References 40 publications

(66 reference statements)

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“…In a significant number of prior closure studies, modeled CCN concentrations were larger than measured, although generally within uncertainty limits (Martin et al 1994;Snider and Brenguier 2000;Chuang et al 2000;Covert et al 1998;Zhou et al 2001;Cantrell et al 2001;Snider et al 2003;Dusek et al 2003;Roberts et al 2002;VanReken et al 2003;Rissler et al 2004). The positive model bias also increased for moderate to highly polluted conditions.…”

Section: Introductionmentioning

confidence: 83%

“…Cantrell et al (2001) found good general agreement between the measured and predicted CCN for marine aerosol sampled during the Indian Ocean Experiment (INDOEX) field program; however, the modeled CCN overpredicted observed CCN number concentration for one specific period when organic carbon was greater than 25% of total aerosol mass. VanReken et al (2003) found that an idealized composition of pure (NH 4 ) 2 SO 4 yielded good aerosol-CCN closure during the Cirrus Regional Study of Tropical Anvils and Cirrus Layers: Florida Area Cirrus Experiment (CRYSTAL FACE) for all flights with the exception of one. For this particular flight, CCN was elevated in concentration and back trajectories originated from the polluted boundary layer over Georgia several days earlier.…”

Section: Introductionmentioning

confidence: 94%

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Cloud Activating Properties of Aerosol Observed during CELTIC

Stroud

Nenes

Jimenez³

et al. 2007

Journal of the Atmospheric Sciences

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Measurements of aerosol size distribution, chemical composition, and cloud condensation nuclei (CCN) concentration were performed during the Chemical Emission, Loss, Transformation, and Interactions with Canopies (CELTIC) field program at Duke Forest in North Carolina. A kinetic model of the cloud activation of ambient aerosol in the chamber of the CCN instrument was used to perform an aerosol-CCN closure study. This study advances prior investigations by employing a novel fitting algorithm that was used to integrate scanning mobility particle sizer (SMPS) measurements of aerosol number size distribution and aerosol mass spectrometer (AMS) measurements of the mass size distribution for sulfate, nitrate, ammonium, and organics into a single, coherent description of the ambient aerosol in the size range critical to aerosol activation (around 100-nm diameter). Three lognormal aerosol size modes, each with a unique internally mixed composition, were used as input into the kinetic model. For the two smaller size modes, which control CCN number concentration, organic aerosol mass fractions for the defined cases were between 58% and 77%. This study is also unique in that the water vapor accommodation coefficient was estimated based on comparing the initial timing for CCN activation in the instrument chamber with the activation predicted by the kinetic model. The kinetic model overestimated measured CCN concentrations, especially under polluted conditions. Prior studies have attributed a positive model bias to an incomplete understanding of the aerosol composition, especially the role of organics in the activation process. This study shows that including measured organic mass fractions with an assumed organic aerosol speciation profile (pinic acid, fulvic acid, and levoglucosan) and an assumed organic aerosol solubility of 0.02 kg kg Ϫ1 still resulted in a significant model positive bias for polluted case study periods. The slope and y intercept for the CCN predicted versus CCN observed regression was found to be 1.9 and Ϫ180 cm Ϫ3 , respectively. The overprediction generally does not exceed uncertainty limits but is indicative that a bias exists in the measurements or application of model. From this study, uncertainties in the particle number and mass size distributions as the cause for the model bias can be ruled out. The authors are also confident that the model is including the effects of growth kinetics on predicted activated number. However, one cannot rule out uncertainties associated with poorly characterized CCN measurement biases, uncertainties in assumed organic solubility, and uncertainties in aerosol mixing state. Sensitivity simulations suggest that assuming either an insoluble organic fraction or external aerosol mixing were both sufficient to reconcile the model bias.

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Section: Introductionmentioning

confidence: 83%

Section: Introductionmentioning

confidence: 94%

Cloud Activating Properties of Aerosol Observed during CELTIC

Stroud

Nenes

Jimenez³

et al. 2007

Journal of the Atmospheric Sciences

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“…A higher concentration of CCN at a given supersaturation will lead to more droplets with a smaller mean droplet diameter. This may lead to a more reflective cloud and is termed the first indirect effect, or Twomey effect (Twomey, 1977). The second indirect effect is related to the inhibition of precipitation in clouds with small mean droplet diameters which affects the extent and lifetime of clouds (Albrecht, 1989).…”

Section: Introductionmentioning

confidence: 99%

Closure between measured and modeled cloud condensation nuclei (CCN) using size-resolved aerosol compositions in downtown Toronto

Broekhuizen

Chang

Leaitch³

et al. 2006

Atmos. Chem. Phys.

123

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Abstract. Measurements of cloud condensation nuclei (CCN) were made in downtown Toronto during August and September, 2003. CCN measurements were performed at 0.58% supersaturation using a thermal-gradient diffusion chamber, whereas the aerosol size distribution and composition were simultaneously measured with a TSI SMPS and APS system and an Aerodyne Aerosol Mass Spectrometer (AMS), respectively. Aerosol composition data shows that the particles were predominately organic in nature, in particular for those with a vacuum aerodynamic diameter of <0.25 µm. In this study, the largest contribution to CCN concentrations came from this size range, suggesting that the CCN are also organic-rich. Using the size and composition information, detailed CCN closure analyses were performed. In the first analysis, the particles were assumed to be internally mixed, the organic fraction was assumed to be insoluble, and the inorganic fraction was assumed to be ammonium sulfate. The AMS time-of-flight data were used for Köhler theory predictions for each particle size and composition to obtain the dry diameter required for activation. By so doing, this closure analysis yielded an average value of CCN predicted /CCN observed =1.12±0.05. However, several sample days showed distinct bimodal distributions, and a closure analysis was performed after decoupling the two particle modes. This analysis yielded an average value of CCN predicted /CCN observed =1.03±0.05. A sensitivity analysis was also performed to determine the aerosol/CCN closure if the organic solubility, droplet surface tension, or chamber supersaturation were varied.

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“…For example, different closure studies have relied on CCN concentrations determined through direct counting of the subset of an aerosol that activates at the peak supersaturation, S p , in the chamber (VanReken et al 2003), through measurement of the difference in concentration of a sampled aerosol before and after gravitational removal of all CCN (Cantrell et al 2001), through measurement of the droplet size distribution at equilibrium at 100% RH (Liu et al 1996), and through a calibration-based relationship between S c and droplet size in a CCN spectrometer (Gasparini et al 2006). Additionally, different investigators employ varied techniques to relate the aerosol data to CCN concentrations.…”

Section: Introductionmentioning

confidence: 99%

Isolation of Ambient Particles of Known Critical Supersaturation: The Differential Activation Separator (DAS)

Osborn

Taylor

Spencer

et al. 2008

Aerosol Science and Technology

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A field-deployable instrument has been developed that isolates from an ambient aerosol those particles that have critical supersaturations, S c , within a narrow, user-specified, range. This Differential Activation Separator (DAS) consists of two continuous flow diffusion chambers housed within a single enclosure. Particles are introduced into the upstream chamber referred to as the CCN remover (CCNR) near the centerline between a warm, water-soaked, plate and a cool, continuously circulated, water bath. Those particles that activate at the resulting peak supersaturation, S p , grow quickly and fall into the water bath. The remaining aerosol enters the second chamber referred to as the CCN separator (CCNS), which differs from the CCNR primarily in the use of a salt solution in the lower bath. The imposed temperature differential establishes an S p slightly higher than that maintained in the upstream chamber, while the presence of a salt solution at the lower boundary results in a subsaturated region in roughly the lower half of the chamber. Those particles having (S p ) CCNR < S c < (S p ) CCNS activate in this chamber and begin to fall due to gravitational settling. Before reaching the lower bath, the droplets evaporate in the subsaturated environment and continue to travel towards the chamber exit. The previously activated particles in the lower half of the chamber and the unactivated particles in the upper half are extracted in separate flows that are subsequently dried. Calibration of the DAS was achieved by measuring the size distribution of separated particles when a polydisperse ammonium sulfate aerosol was introduced.

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Toward aerosol/cloud condensation nuclei (CCN) closure during CRYSTAL‐FACE

Cited by 108 publications

References 40 publications

Cloud Activating Properties of Aerosol Observed during CELTIC

Cloud Activating Properties of Aerosol Observed during CELTIC

Closure between measured and modeled cloud condensation nuclei (CCN) using size-resolved aerosol compositions in downtown Toronto

Isolation of Ambient Particles of Known Critical Supersaturation: The Differential Activation Separator (DAS)

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