Using Geoinformation Services to Make Operational Decisions to Minimize Health Risks to Populations in Areas of Wildfires

The purpose of this study is to develop and test geoinformation services for making operational decisions aimed at reducing the health risk to the population when smoke from wildfires is exposed near populated areas and at a considerable distance. Processing services implement spatial analysis methods. The computational models are implemented on the JupyterHub interactive computing platform provided by the infrastructure. That technology was tested on the example of areas the Baikal region in the Republic of Buryatia during periods of significant smoke contamination of the territory associated with local mass fires and remote at 1000–2500 km. The assessment modeling results are presented in the form of thematic interactive maps that change depending on the filtering of results by various criteria, graphs, and tables. A digital environment has been developed that allows one to quickly upload primary data, present it in various schemes, carry out calculations, and obtain information about harmful substances in the air. The calculation methodology is presented as a set of services and Jupyter documents. Visualization of the results of assessing the potential and realized risk in the form of multilayer maps makes it possible to quickly identify the areas of greatest danger. In the Baikal region, the probability of respiratory symptoms associated with air pollution was CO 27.4% and total matter particles 6.7% of the number of exposed.