Multivariate statistical modeling to estimate atmosferic environment and water quality in urban area.

The correct evaluation of various environmental events and pollution effects is mainly performed by the use of advanced multivariate statistical approaches united by the specific term environmetrics. The aim of the proposed project is create statistical models to estimate atmospheric environments (wet and dry precipitates), pot water quality, bioindicator plants ability and coastal sediments as pollution collector in urban areas. The models will be based on existing data sets. Advanced modelling methods, based on latent variables are needed, because the data sets often have three-or more-way structures, e.g. measurements x time x location. Therefore we want to study the application of three- and more-way principal components analysis.