K-means cluster analysis is an adequate method for reducing individual particle data, as long as extra clusters are used to allow for the non-spherical shape and natural variability of aerosol particles. The above method for choosing seedpoints does a particularly good job of detecting the types of low abundance particles that are interesting for urban atmospheric studies. The basic structure of the particle-type data increases the usefulness of factor rotation schemes. Application to the Phoenix aerosol suggests that the ability to discriminate between various types of crustal particles may yield valuable information in addition to that derived from particle types more commonly associated with anthropogenic activity.
|Original language||English (US)|
|Title of host publication||National Meeting - American Chemical Society, Division of Environmental Chemistry|
|Number of pages||4|
|State||Published - 1984|
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