Initial application of the noise-sorted scanning clustering algorithm to the analysis of composition-dependent organic aerosol thermal desorption measurements

The FIGAERO-CIMS (Filter Inlet for Gases and AEROsols + chemical
ionization mass spectrometer) measures thermal desorption profiles for
individual ions evolved from evaporation of organic aerosol
components. Often, hundreds of individual thermograms are obtained,
reflecting the compositional complexity of organic aerosol. We
have developed a novel clustering algorithm, Noise-Sorted
Scanning Clustering (NSSC), that provides a robust, reproducible analysis
of the FIGAERO temperature-dependent mass spectral data. The NSSC allows
for determination of thermal profiles for compositionally distinct
clusters, increasing the accessibility and enhancing the interpretation of
FIGAERO data. The potential of NSSC for analysis of FIGAERO-CIMS data is
demonstrated via application to a suite of distinct experiments. A static
version of the NSSC algorithm is archived here, and an evolving version at
GitHub (doi: 10.5281/zenodo.3361796). The data used to test and
develop the NSSC, and reported on in Li et al. (submitted to Atmospheric
Measurement Techniques) and in Ziyue Li's dissertation at UC Davis,
are archived here. The experiments took place at the Pacific Northwest
National Laboratory.