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Fine particulate matter in the atmosphere, especially the fraction less than 2.5 µm in diameter (PM2.5), arises from several sources. Assessing the relative contributions from each source may be modeled through a mixing method, where the chemical signatures of known sources are mixed in a variety of proportions to provide the best explanation of the measured data. Alternatively, unmixing models determine what the chemical composition of the end members must have been in order to produce the observations. This study uses three different unmixing models with both a synthetic and a real-life (environmentally measured) alkane dataset from PM2.5 collected in five locations in Chile. Polytopic vector analysis (PVA), positive matrix factorization (PMF), and UNMIX modeling were used with ∼300 samples collected across 18 months. Using the synthetic data, both PVA and PMF were able to satisfactorily reconstruct the initial sources and their contribution to the samples, with PMF marginally more accurate than...

Airborne particulate matter (PM2.5) are known environmental cotaminants. Nevertheless, it is not only the size of particulate matter that influences human health, but also its chemical composition. The chemical composition of the PAH suite in PM2.5 may be indicative of the source materials, typically combustion products. In this study, particulate matter (PM2.5) was collected using portable air samplers during all of 2013 and 2014 at five locations of the Los Rios Region, Valdivia, Chile. The quantity of PM2.5 collected was measured using gravimetric methods. Solvent extracts were analyzed for associated PAHs by means of GC-MS techniques. The concentrations of PM2.5 for all locations ranged from 2.8 to 386 µg/m3 for the autumn/winter periods and from 1.1 to 315 µg/m3 for the spring/summer periods. The mean concentrations of PM2.5 ranged from 11.9 to 112 µg/m3 in summer for all sites. The concentrations of PAHs for all locations ranged from 2.8 to 115 ng/m3 for the autumn/winter periods and from 0....