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Abstract

Meteorological parameters which are most significant for ozone forecasting were chosen in the multiple regression analysis for the daily time series. Then correlations between the variables we~e investigated, both for the daily and temporary values. There was confirmed a strong relationship between atmospheric conditions and ozone concentrations as well as autocorrelations of the temporary time series of ozone from different monitoring stations. Diversification of autocorrelation values arises probably from different receptor locations which was confirmed by the principal component analysis. There were also shown dependences between the ozone time series from different monitoring stations. Strong space-time relationships of ozone concentrations and meteorological conditions in the Black Triangle region can be used in modeling and forecasting of ozone episodes.
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Authors and Affiliations

Artur Gzella
Jerzy Zwoździak
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Abstract

Time series analysis ofmonthly and daily SO2 data were considered for the detection of trends in SO2 due to possible effect of the emission abatement strategy in the Black Triangle region. Using a time series model, the main components were extracted from the original SO2 time series. Based on SO2 monitoring data from Czerniawa in Izery Mountains in Poland over the period 1993 -1998, our findings showed evidence of declining trends in SO2• A mean annual change of 14.1% was recorded in a 6-year record. It has also appeared that the exponential smoothing which considers a seasonal component and trends provided a reasonable fit to monthly mean SO2 values.
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Authors and Affiliations

Jerzy Zwoździak
Artur Gzella
Anna Zwoździak

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