Identification of Source Nature and Seasonal Variations of Arctic Aerosol byPositive Matrix Factorization

Abstract

Abstract Week-long samples of airborne particulate matter were obtained at Alert, Northwest Territories, Canada, between 1980 and 1991. The concentrations of 24 particulate constituents have some strong, persistent seasonal variations that depend on the transport from their sources. In order to explore the nature of the cyclical variation of the different processes that give rise to the measured concentrations, the observations were arranged into both a two-way matrix and a three-way data array. For the latter, the three modes consist of chemical constituents, weeks within a year, and years. The two-way bilinear model and a three-way trilinear model were used to fit the data and a new data analysis technique, positive matrix factorization (PMF), has been used to obtain the solutions. PMF utilizes the error estimates of the observations to provide an optimal pointwise scaling data array for weighting, which enables it to handle missing data, a common occurrence in environmental measurements. It can also ap...