The plants emit different types of volatile organic compounds (Bio VOC’s) and can improve air quality: they effectively remove organic pollutions and reduce the number of microorganisms in the air by releasing phytoncides. The lack of negative ions in the air can cause deterioration of the health of humans breathing it. At the same time, an air saturated with negative ions can improve the state of health and provide a comfortable environment. In this article, the influence of the plants (Cupressus macrocarpa) on the number of ions is proved, based on a series of experiments performed with applying high-voltage pulses (air ionizer). This work is devoted to the elaboration of the mathematical relationship between the air ions concentration and the factors influencing it. For this purpose an experimental stand was made, consisting of two equal compartments: one contained the plants while another one was used as a control without plants. It was concluded that the plants, in general, are able to stabilize the ion concentration and to reduce its fluctuations. The plants help to increase the concentration of negative ions and to decrease the concentration of positive ones.

The growing economy with following industrialization and urbanization has led to environmental contamination with trace elements worldwide. In urban environment, the large inputs of anthropogenic contaminants in atmosphere are arising from mobile and stationary sources. The snow sample analysis is one of methods to monitor air contamination with heavy metals in urban areas. The aim of this research is to analyse heavy metal contamination and distribution in urban environment of Jelgava city. The samples were collected twice in January and February. Snow samples were collected in 20 urban area sampling plots and one natural area sampling plot with three repetitions taken from 1.0 to 1.5 kg of snow. The concentration of trace elements was estimated in 126 melted and filtrated snow water using inductively coupled plasma spectrometer (ICP-OES). The average heavy metals and nutrients concentrations were calculated for each sample. The concentrations data of trace elements were analysed using agglomerative hierarchical clustering method. The results show differences between results in January and February. The differences are related to anthropogenic impact intensity differences during the exposition periods of snow. The clustering results of snow samples taken in January show three clusters, but snow samples taken in February show four clusters.