A receptor model using a specific non-negative transformation technique for ambient aerosol

Abstract

Factor analysis receptor models attempt to estimate both the source composition and the source intensity from a series of observations. The factor analysis solution resulting from Principle Component Analysis (PCA) has no real physically interpretable meaning. Only an appropriate transformation enables a realistic interpretation. Any realistic transformation solution must obey certain natural and physical constraints, such as non-negative source elemental composition and non-negative source intensity, which are not explicitly examined in the existing receptor models. If these natural constraints are violated the results will be uninterpretable.

All observed data sets contain more or less information about the sources. This paper presents a receptor model, which extracts source information from the observed data set to deduce the source profiles, and respects the important natural constraints. This receptor model was tested with a simulated test data set, which was generated with the source profiles and intensities used in the Quail Roost II Workshop. It has also been applied to an ambient data set sampled in Berlin (West) during January and February 1984.