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Chemical Composition of Ambient Nanoparticles on a Particle-by-Particle Basis

Klems, Joseph P., Zordan, Christopher A., Pennington, M. Ross, Johnston, Murray V.
Analytical chemistry 2012 v.84 no.5 pp. 2253-2259
aerosols, algorithms, carbon, data collection, elemental composition, factor analysis, mixing, nanoparticles, nitrogen, oxidation, oxygen, spectrometers, sulfur
The nano aerosol mass spectrometer provides a quantitative measure of the elemental composition of individual, ambient nanoparticles in the 10–30 nm size range. In this work, carbon mole fraction plots are introduced as an efficient means of visualizing the full range of particle compositions in an ambient data set. These plots are constructed by plotting the composition of each particle in the data set, beginning with the particle having the highest carbon mole fraction and ending with the particle having the lowest carbon mole fraction. The method relies on the observation that the carbon content of an ambient particle is generally anticorrelated with oxygen, nitrogen, and sulfur. Carbon mole fraction plots allow internal vs external mixing of particle compositions to be assessed, and they provide a means of exploring the relationship between the oxidation of carbonaceous matter and the presence of inorganic species in a particle. It is shown that unoxidized carbonaceous matter exists primarily as externally mixed particles, whereas oxidized carbonaceous matter is found only in particles that also contain a significant amount of inorganic species. Particles containing oxidized carbonaceous matter are generally neutralized, whereas particles containing unoxidized carbonaceous matter or no carbon at all are acidic. Carbon mole fraction plots show how factor analysis methods such as the Adaptive Resonance Theory – 2a algorithm (ART-2a) and positive matrix factorization partition a continuum of particle compositions into a few fixed composition profiles, and they provide a simple way to characterize how ambient particle compositions change with season and/or location.