Supporting Material
Airborne Single Particle Mass Spectrometers
(SPLAT II & miniSPLAT) and New Software for
Data Visualization and Analysis in a Geo-Spatial
Context
Alla Zelenyuk,*,† Dan Imre,‡ Jacqueline Wilson,† Zhiyuan Zhang,§ Jun Wang,§ Klaus
Mueller§
†
Pacific Northwest National Laboratory, Richland, WA 99354
‡
§
*
Imre Consulting, Richland, WA 99352
State University of New York, Stony Brook, NY 11790
Corresponding author. E-mail address: alla.zelenyuk@pnnl.gov
Figure S1. Three calibrations of miniSPLAT small particle detection probabilities, conducted on
three separate occasions. To determine the 50% cut-off point we follow the procedure described
in Vaden at al. [1]. We begin by measuring the mobility size distributions and high precision
densities of the particles to be used for the calibration. In Figure S1 we show two calibration runs
using sodium nitrate and one using ambient particles, which in this case were secondary organic
mixed with small amount of sulfate. While measuring the density of classified particles, the line
shape of the dva distribution is used to assure that particles are spherical and have a very narrow
distribution of densities. Once particles’ sphericity and density are established, the mobility and
dva distributions of the entire particle population are measured. Figure S1(a) shows the dva size
distributions of the polydisperse particle population for the three cases. The sharp drop-off on the
small particle size reflects the increase in particle beam divergence and rapid decrease in light
scattering signal [1-4]. Measured particle densities are used to convert the measured dva
distributions into the mobility size distributions, shown in Figure S1(b), which are used to
determine the 50% cut-off point, as illustrated in the figure.
The results show that while the precise 50% cut-off point of small particles detection can vary,
due instrument alignment and the optics quality, between 79 nm and 83 nm (~5%), it is nearly
identical to that of SPLAT II [1, 3].
Figure S2. Mass spectra of 14 particle classes characterized during the TCAP field campaign by
miniSPLAT, with the labeled characteristic peaks.
Figure S3. Data collected by miniSPLAT during one of the fight of the TCAP field campaign.
Figure S3a shows the temporal evolution of the aircraft altitude and the number concentrations of
particles larger than 100 nm, as measured by miniSPLAT. Figure S3(b) shows the temporal
evolution of the particle compositions indicated by the colors in the figure legend. The length of
each color bar represents the number fraction of particles with different compositions. The data
are displayed with temporal resolution of 2 minutes. The figure shows that the vast majority of
particles were composed of organics containing small amount of sulfate. Comparison of changes
in particle compositions with particle number concentrations shows that the plume probed at
~17:08 UTC contained larger fraction of sulfate-rich particles.
Overall the temporal evolution of particle compositions shows that particle compositions
varied only slightly with location, time, and altitude and would therefore not be a good example
to use to illustrate the capabilities of ND-Scope. It is for that reason that we used the ISDAC data
for that purpose.
Figure S4. Mass spectra of 10 particle classes characterized during ISDAC field campaign by
SPLAT II, with the labeled characteristic peaks.
References:
1.
Vaden T. D.; D. Imre; J. Beranek; A. Zelenyuk: Extending the Capabilities of Single
Particle Mass Spectrometry: II. Measurements of Aerosol Particle Density without DMA.
Aerosol Sci Tech 45, 125-135 (2011)
2.
Vaden T. D.; D. Imre; J. Beranek; A. Zelenyuk: Extending the Capabilities of Single
Particle Mass Spectrometry: I. Measurements of Aerosol Number Concentration, Size
Distribution, and Asphericity. Aerosol Sci Tech 45, 113-124 (2011)
3.
Zelenyuk A.; J. Yang; E. Choi; D. Imre: SPLAT II: An Aircraft Compatible, Ultra-
Sensitive, High Precision Instrument for In-Situ Characterization of the Size and Composition of
Fine and Ultrafine Particles. Aerosol Sci Tech 43, 411-424 (2009)
4.
Zelenyuk A.; J. Yang; D. Imre; E. Choi: Achieving Size Independent Hit-Rate in Single
Particle Mass Spectrometry. Aerosol Sci Tech 43, 305-310 (2009)