Ambient air particles: the use of ion chromatography and multivariate techniques in analysis of water-soluble ions

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.