Investigation of the correlation dependence between SO2 emission concentration and meteorological parameters: case study-Bor (Serbia).

This paper presents the investigation of the air-pollution management possibility in Bor (Serbia) using statistical analyses of the correlation dependence of SO(2) pollution concentration and meteorological parameters. This kind of approach allows data to determine the shape of time trends; models serial correlation and dependence on covariance; and provides statistical analyses of data. Air quality control in the area of Bor is measured at four monitoring stations: City park; Institute of Mining and Metallurgy; Jugopetrol oil logistic centre and Brezonik suburb. There is also a meteorological station near the aforementioned institute that measures temperature; air humidity; atmosphere pressure; wind speed and direction. The results received from all monitoring stations are processed by the Institute of Mining and Metallurgy in Bor. The data from the reported documents were used for statistical analyses, for determining the correlation between SO(2) emission concentration and meteorological parameters. The source of SO(2) emissions is the local copper smelter, built within the town of Bor from 1961-1963. However, the disposition of the pollutant concentration is influenced by meteorological parameters (air humidity, atmosphere pressure, speed and wind direction). The successful application of these statistical analyses in this paper points to a possibility of its usage in air pollution studies.

Optimizing the SO2 total emission control strategy: case study-Bor (Serbia).

A geographic information system (GIS)--based on spatial analysis--was developed for optimizing the SO(2) total emission cut scheme on air pollution in Bor (Serbia), combined with Models-3 modeling system and linear programming model. GIS is mainly used for establishing a multifactor assessment model to quantitatively divide environmental functional zone and also used for selecting control sites in linear programming model. A linear programming model was developed to optimize the emission determined by SO(2) control measures. According to the obtained results, some large emissions need to be cut for about 50%. The improvement of the ecological environment is urgently needed for controlling the background SO(2) pollution in Bor.