Environmental information systems in Slovenia—the present and future state

Industrial air pollution is still one of the biggest environmental problems in Slovenia. To monitor air pollution, automated environmental information systems were built. These are complex computerized networks that couple automated measuring techniques and information technology. A typical environmental information system is described. Guidelines are given for the strategy of air pollution monitoring in complex terrain, attempting to find a balance between costs, the available funds and system performances desired. In the paper a strategy for achieving desired system performances is described. The most important parameters are measuring accuracy, reliability and maintenance simplicity. In complex terrain an environmental information system cannot cover the whole domain. Appropriate dispersion models should be added to the system to reconstruct the whole movement of the pollutant plume and to estimate its harmful effects in regions without measurements

Ozone prediction based on neural networks and Gaussian processes

The urban environment in Slovenia is confronted with the air pollution problem of harmfully high ozone concentrations. In the last two decades the automatic ozone measuring network was extended and now covers regions where the highest values are expected. Due to topographical and climatological conditions and the presence of extensive urban environments, the most critical locations are the ones in the western part of Slovenia. In the city of Nova Gorica a modern automatic urban air pollution measuring station was installed. Measurements at this station clearly showed that ozone is a considerable pollutant there, especially in the summer time. In this work a perceptron neural-network–based model and a Gaussian-process–based model for ozone concentration forecasting for the city of Nova Gorica was developed and evaluated. The methods of feature determination and pattern selection for the model training process are delineated. The shortcomings of the models and possibilities for improvements are discussed with respect to evaluation of the effectiveness of the methods

Re-evaluation of the Lagrangian particle modelling system on an experimental campaign in complex terrain

Slovenian legislation for industrial air pollution control requires efficient modelling systems for small domains over complex topography. To determine the performance and efficiency of the Lagrangian particle modelling system used for this purpose a study was made where a general purpose modelling system designed for local-scale areas was used. The main goal of the study was to evaluate a modelling system of this kind using an operational configuration of both input data and model parameters, choosing a testing period with very complex dispersion conditions. This severe check could help to better understand the general quality that a model can achieve in these conditions giving some idea on how to better evaluate and use some results that seem to be very negative simply looking at some statistical parameter. Data from a three-week experimental campaign performed around the ˇSoˇstanj thermal power plant during the spring of 1991 was used (analyzed) for evaluation. The database covers very high ambient concentrations (due to the absence of desulphurisation plants) over complex terrain. The simulation was performed for the full duration of the campaign and a particular situation during the 1st and the 2nd of April 1991 was used as an example to outline the model behaviour in complex conditions. During this selected sub-period measurements revealed that (measured) wind speeds were very low, wind changed course in all directions rapidly and consequently the plume spread in all directions. A comparison between measured and reconstructed SO2 concentrations was made at the positions of several automatic air quality measuring stations located around the thermal power plant. Standard statistical indexes to evaluate model performances are instead computed at the same positions for the entire period of the experimental campaign. Overall the reconstructed SO2 concentrations were underestimated relative to the measured ones, but all direct air pollution events were reconstructed. Some weaknesses of the model in the correct reconstruction of peak events are explained and a way to better describe them and to enhance statistical indexes is proposed