Seventeen water-soluble substances (sodium, ammonium, potassium, magnesium,
calcium, formate, methanesulfonate, glyoxylate, chloride, nitrite, nitrate,
glutarate, succinate, malate, malonate, sulfate, and oxalate) in 94 samples
of particle matter in the ambient air, collected for ten months, in a suburb
of Belgrade (Serbia), were determined by ion chromatography. To apportion
the sources of the air pollution, the log-transformed data were processed by
applying multivariate techniques. Principal component and factor analysis
identified three main factors controlling the data variability: stationary
combustion processes with the highest loadings of oxalate, malonate, and
malate; landfill emission and secondary inorganic aerosol characterized by
high levels of ammonium, nitrate, and sulfate; and a contribution of mineral
dust composed of magnesium, calcium, and chloride. The hierarchical cluster
analysis pointed out a differentiation of the samples into five groups
belonging to different variables inputs. For the classification of ambient
air samples using nine selected ions, the recognition ability of linear
discriminant analysis, k-nearest neighbors, and soft independent modeling of
class analogy were 87.0, 94.6, and 97.8 %, respectively. Time-series
analysis showed that the traffic emission is more pronounced in winter in
contrast to the mineral dust influence, while the effect of waste combustion
exhibits no trend.