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| Titel |
Three-dimensional factorization of size-resolved organic aerosol mass spectra from Mexico City |
| VerfasserIn |
I. M. Ulbrich, M. R. Canagaratna, M. J. Cubison, Q. Zhang, N. L. Ng, A. C. Aiken, J. L. Jimenez |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1867-1381
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| Digitales Dokument |
URL |
| Erschienen |
In: Atmospheric Measurement Techniques ; 5, no. 1 ; Nr. 5, no. 1 (2012-01-25), S.195-224 |
| Datensatznummer |
250002317
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| Publikation (Nr.) |
 copernicus.org/amt-5-195-2012.pdf |
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| Zusammenfassung |
| A size-resolved submicron organic aerosol composition dataset from a
high-resolution time-of-flight mass spectrometer (HR-ToF-AMS) collected in
Mexico City during the MILAGRO campaign in March 2006 is analyzed using
3-dimensional (3-D) factorization models. A method for estimating the
precision of the size-resolved composition data for use with the
factorization models is presented here for the first time. Two 3-D models are
applied to the dataset. One model is a 3-vector decomposition (PARAFAC
model), which assumes that each chemical component has a constant size
distribution over all time steps. The second model is a vector-matrix
decomposition (Tucker 1 model) that allows a chemical component to have a
size distribution that varies in time. To our knowledge, this is the first
report of an application of 3-D factorization models to data from fast
aerosol instrumentation, and the first application of this vector-matrix
model to any ambient aerosol dataset. A larger number of degrees of freedom
in the vector-matrix model enable fitting real variations in factor size
distributions, but also make the model susceptible to fitting noise in the
dataset, giving some unphysical results. For this dataset and model, more
physically meaningful results were obtained by partially constraining the factor mass
spectra using a priori information and a new regularization method. We find
four factors with each model: hydrocarbon-like organic aerosol (HOA),
biomass-burning organic aerosol (BBOA), oxidized organic aerosol (OOA), and
a locally occurring organic aerosol (LOA). These four factors have
previously been reported from 2-dimensional factor analysis of the
high-resolution mass spectral dataset from this study. The size
distributions of these four factors are consistent with previous reports for
these particle types. Both 3-D models produce useful results, but the
vector-matrix model captures real variability in the size distributions that
cannot be captured by the 3-vector model. A tracer m/z-based method provides a
useful approximation for the component size distributions in this study.
Variation in the size distributions is demonstrated in a case study day with
a large secondary aerosol formation event, in which there is evidence for
the coating of HOA-containing particles with secondary species, shifting the
HOA size distribution to larger particle sizes. These 3-D factorizations
could be used to extract size-resolved aerosol composition data for
correlation with aerosol hygroscopicity, cloud condensation nuclei (CCN),
and other aerosol impacts. Furthermore, other fast and chemically complex 3-D
datasets, including those from thermal desorption or chromatographic
separation, could be analyzed with these 3-D factorization models.
Applications of these models to new datasets requires careful construction
of error estimates and appropriate choice of models that match the
underlying structure of those data. Factorization studies with these 3-D
datasets have the potential to provide further insights into organic aerosol
sources and processing. |
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