Cloud Condensation Nuclei (CCN) Analysis of
Biogenic Secondary Organic Aerosol
Rachel L. Atlas1, Celia L. Faiola2, Timothy VanReken2
1University
of Chicago, Dept. of Physics and Geophysical Sciences, 2Washington State University, Dept. of Civil and Environmental Engineering
CCN
Motivation
Figure 1. CCNc with cover removed and
labVIEW data collection program.
Cloud condensation nuclei (CCN) are particles which water vapor condenses onto to form cloud droplets at sufficient
supersaturations. CCN can include anthropogenic or biogenic material, the latter often produced from the atmospheric
oxidation of biogenic volatile organic compounds (BVOCs) to form secondary organic aerosol (SOA). Trees' BVOC
emissions change in response to stress, which may affect how much SOA they form and how effective it is as CCN.
Emissions producing more CCN would be expected to have a net cooling effect on climate and those producing fewer
CCN, a net warming effect. The relationship is more complex, as stressors, such as increased ozone concentration,
temperature and herbivory are linked to climate change. Tree emissions and climate change form a challenging
feedback loop, which must be better understood in order to reduce uncertainties in climate models.
The CCNc exposes aerosols to a known temperature
gradient, in a wetted column, to promote droplet formation.
The purpose of the calibration is to find the relationship
between the temperature gradient within the CCNc and the
effective supersaturation. Four different temperature
gradients are used. The scanning mobility particle sizer
(SMPS) is used to select ammonium sulfate particles of
twenty known sizes. For each temperature gradient, the
efficiency spectrum (#CCN/# particles) is plotted against the
size of the particles. A sigmoid function is fit to the data and
the x-value corresponding to the half max of the fit function
is taken as the critical diameter.
The raw data must be corrected because the differential
mobility analyzer (DMA) does not produce completely
monodisperse particles, which causes a discrepancy
between the desired particle diameter and the actual mean
particle diameter. The mean diameter is calculated from the
efficiency spectrum and electrical mobility of the particles.
A linear relationship is observed between the CCNc
temperature gradients and the effective supersaturations.
The supersaturations used to calculate kappa for the
chamber experiments were calculated using this linear
relationship.
HEPA
Filter
Flow
Controller
Atomizer
Compressor
BVOC
Stressors
(increased ozone,
herbivory)
CCN
Counter
Figure 3. Raw calibration data with sigmoid fit curves
and corrected activation curves, with the calculated
critical diameters.
Dryer
Sheath Flow
Calibration data is consistent with earlier
calibrations and literature.
Kappa values are low because the CCN analysis
program was written for moderate relative CCN
concentrations, as are observed in the field, and
breaks down at high relative concentrations, as are
produced in the laboratory.
HR-ToF-AMS
(Organic Aerosol
Characterization)
GC-MS
(Organic
Speciation)
PTR-MS (Gas
Phase
Organics)
Figure 6. Laboratory setup for chamber experiments
Cloud
Condensation
Nuclei Counter
(CCNc)
Differential
Mobility
Analyzer
(DMA)
Figure 5.
Laboratory
setup for
the CCNc
calibration
Condensation
Particle Counter
(CPC)
Mixing
Tube
Further Work
Modify CCN analysis program for laboratory
measurements, to account for high relative CCN
concentrations and seed particles, which are 50 nm
ammonium sulfate particles.
Produce size-resolved CCN data, by directing the
chamber air through the SMPS before the CCNc.
Figure 7. CCN concentration for five supersaturations.
Each point shows six minutes of one-second data. Four
minutes have been removed from every supersaturation
cycle, to account for the time it takes for the CCNc
temperatures to stabilize after switching supersaturations.
Figure 9. Total
Particle
Concentration
for
comparison
with the CCN
concentration
(above)
Figure 4. Linear relationship between the measured
CCNc temperature gradients and the calculated
effective supersaturations.
Flow Meter
Conclusions
SMPS
Biogenic
Plant
Chamber
Zero Air Generator
Vacuum
Pump
Neutralizer
Aerosol
Growth
Chamber
CPC (Total
Particle Count)
Laboratory
HEPA
Filter
Ozone
Concentration
Ozone Source
Laboratory
Ammonium
Sulfate
Solution
OH, O3,
NO3, hn
In this study, trees are kept in a laboratory chamber and their emissions are directed into a separate
chamber, where they react with ozone, the oxidizing agent, to form SOA. The experiment is run twice:
before and after the trees are stressed by the introduction of ozone or methyl jasmonate (to simulate
herbivory) into the plant chamber. Several instruments are used to analyze the plants’ gas-phase
emissions and the aerosols they form (figure 6), including a cloud condensation nuclei counter (CCNc)
and scanning mobility particle sizer (SMPS). The kohler equation is modified for organic aerosols,
using a hygroscopicity parameter, k. Using the data from the SMPS and the CCNc, k is calculated to
quantify the relationship between CCN activity and particle size.
Kohler Equation: S is the saturation ratio, aw
 2vw sol  is the activity of water, v is the partial
w
S  aw exp 

 RTr  molar volume of water, sol is the solution
surface tension, R is the gas constant, T is
the temperature and r is the particle radius.
Sample Flow
Global
Climate
Change
BVOC
Chamber Experiments
An aerosol’s ability to act as a CCN is described by the
Kohler Equation (below), which relates the particle’s critical
supersaturation, above which the particle will act as a CCN,
to its composition and size. This equation is a good
approximation for inorganic particles and is used in the
calibration of the cloud condensation nuclei counter (CCNc).
Dilution Flow
Oxidized
Figure 2. Feedback loop between climate
change and biogenic aerosol.
Calibration
Indicates
Particles
SOA
Figure 8. Image plot of the evolution of particles. A
nucleation event is observed at 1:00 PM. The delay
between the nucleation event and the spike in CCN
concentration is due to the particles’ growth time.
Modified Kohler Equation
 A 
D D

S 3
exp
3
Dw  Dd (1  k )
 Dw 
3
w
3
d
8.69251*10 6  sol
A
T
Dw and Dd are wet and
dry particle diameters,
sol is the surface
tension of the solution, T
is the temperature, and
k is the hygroscopicity
parameter.
Figure 10. Kappa values for bristlecone pine
biogenic SOA at .38% supersaturation.
References
Rose, D., Gunthe, S. S., Mikhailov, E., Frank, G. P., Dusek, U., Andreae, M. O., and Pöschl, U.: Calibration and measurement uncertainties of a
continuous-flow cloud condensation nuclei counter (DMT-CCNC): CCN activation of ammonium sulfate and sodium chloride aerosol particles in
theory and experiment, Atmos. Chem. Phys., 8, 1153-1179, doi:10.5194/acp-8-1153-2008, 2008.
Petters, M. D. and Kreidenweis, S. M.: A single parameter representation of hygroscopic growth and cloud condensation nucleus activity – Part 2:
Including solubility, Atmos. Chem. Phys., 8, 6273-6279, doi:10.5194/acp-8-6273-2008, 2008.
Seinfeld, John H. ; Pandis, Spyros N. (2006). Atmospheric Chemistry and Physics - From Air Pollution to Climate Change (2nd Edition).. John Wiley
& Sons.
Baron, Paul A.; Willeke, Klaus (2001). Aerosol Measurement - Principles, Techniques, and Applications (2nd Edition).. John Wiley & Sons.
Jacob Oberman, LAR REU student, 2010
Logan Callen, student researcher, 2008
This work was supported by the National Science
Foundation’s REU program under grant number AGS1157095