The sources of dust on the territory of Ruse region, Bulgaria are industry, transport and domestic heating by solid fuel. PM10 (particulate matter with a diameter between 2.5 and 10 μm) levels for Ruse mark a significant increase during the autumn-winter period compared to the levels during the spring-summer period [1]. Obviously there is a relationship between PM10 contamination levels and ambient air temperature. The lower the temperatures are, the higher the PM10 levels are. The biggest peak of PM10 levels for the autumn-winter period is usually observed in January months. It is in January that the number of days in which there is exceedance of the limit values of the PM10 levels is maximum observed. Also in January months the day and night temperatures are the lowest and usually they do not pass 0°C for many days of the month. To understand better this relationship we provide a statistical analysis of ambient air PM10 contamination during winter periods. Correlations between the measured PM10 values and the respective temperatures measured for January months for different years are presented. Descriptive statistics of PM10 and some atmospheric characteristics as well as linear regression analysis are calculated and commented in the paper.

Mathematical modeling of the heat transfer during the pyrolysis process used for the treatment of the End-of-Lifetires (EOLT) is presented in this paper. The pyrolysis process is 3D and non-stationary and because of this it is very complicated for modeling and studying. To simplify the modeling here a hierarchy of 2D models for the temperature which describe the non-stationary heat transfer in such a pyrolysis station is created. An algorithm for solving the model equations, based on MATLAB software is developed. The results for the temperature for some characteristic periods of operation of pyrolysis station are presented and commented in the paper. The results from this modeling can be used in the real pyrolysis station for more precise displacement of measurement devices and for designing of automated management of the process.

Temperature, air humidity and atmospheric pressure measurements in Ruse region for 40 years period are statistically studied in this paper. Descriptive statistics, Pearson correlation coefficients and linear regression models for these characteristics are presented and commented. The most variable atmospheric parameter is air humidity during the spring seasons. The hardest change of temperature and atmospheric pressure is during January. Temperature has biggest change in January and smallest - in July. Humidity has biggest change in April and smallest - in October. Atmospheric pressure has biggest change in January and smallest - in July. Characteristics temperature and atmospheric pressure of spring (April) and autumn (October) are very similar. Summer temperatures and atmospheric pressure (July) have smallest change. The atmospheric temperature data for Ruse region are also compared with the official basic data for Bulgaria. It is shown that mean values of the temperature in Ruse region are bigger than the mean temperature for Bulgaria. It is shown that the winter and spring temperatures for Ruse region are slightly going up lately which could be connected with the typical for Ruse region air pollution especially by particle matter.

The presented study of the PM10 concentrations in the atmosphere ground layer emitted from industrial sources in the Industrial zone in the city of Ruse in the days with exceedances for this pollutant is aimed to determining the possibility of cross-border BG-RO PM10 contamination. Climatic conditions measured in these days with PM10 exceedances in January 2017 are also taken into account in Jet Gauss model and in the Langrageo-statistical approach for describing the turbulent diffusion. The results show that the PM10 pollutant from the investigated sources in industrial zone in Ruse is reaching the territory of Republic of Romania with low concentrations and have no potential for impact on air quality in the cross-border area.