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Environmental informatics can be briefly characterized as an interdisciplinary field concerned with the solution of the environmental problems using modern informatics approaches which include methods of mathematical modelling, mathematical statistics, high performance computing, machine learning techniques etc. This field has been changing dramatically in recent years, particularly thanks to the boom of available data which come from both conventional observations and by exploitation of non-traditional measurements, such as sensor networks, cell phones, floating car data, new satellite data etc. This change, as well as the advancements in technologies in other fields, brings number of new interesting problems and challenges. These problems and challenges are the subject of our research.
Some examples of our research activities are the following:
- Modelling of the meteorological and air quality quantities, where we have used various data assimilation techniques and we have utilized many observations from different sources (conventional, satellite and aircraft observations, surface remote sensing). The main goal of the research is to improve the modelling and prediction skills of the models.
- Inversion modelling techniques have been used in connection with air quality models for improvements of the emission inventories and diurnal profiles of the emission as well as for attribution of the air pollution abatement health benefit to individual emission sources.
- In modelling of the urban heat island and other meteorological and air quality aspects of the urbanized areas we utilize the urban canopy and building energy models inside the regional models in the very fine space resolution or inside the large eddy simulation of microscale models.
- We have developed several natural gas consumption models for statistical estimation of consumption behavior of individual natural gas consumers. We have developed also the standardized load profiles for natural gas consumption in the Czech Republic.
- We have developed forecasting methods for renewable energies based on global solar radiation, cloud cover variables , wind speed and wind direction predictions using specifically parametrized numerical weather prediction models and sophisticated statistical and machine learning methods.
- We realized radon source magnitude assessment based on online processing of tracer gas measurements.
- We have studied dynamical modeling of longitudinal sample of asthmatic children in Ostrava including description of the dynamical effect of selected pollutants upon the asthma status.
Responsible: Emil Pelikán